Paul F. Collins
University of Oregon
Department of Psychology
Eugene, Oregon 97403
pcollins@oregon.uoregon.edu
personality, extraversion, dopamine, incentive motivation, neurobiology, behavioral sensitization, heterosynaptic plasticity
Individual differences in the functioning of this network arise from functional variation in the properties of the ventral tegmental area dopamine projections, which are directly involved in coding the intensity of incentive motivation. Animal evidence suggests that there are three neurodevelopmental sources of individual differences in dopamine: genetic, "experience-expectant", and "experience-dependent processes". Individual differences promote variation in the heterosynaptic plasticity that enhances the connection between incentive context and incentive motivation and behavior. Our psychobiological threshold model explains the effects of individual differences in dopamine transmission on behavior and their relation to personality traits.
Twenty-five years ago, Gray (1973) revolutionized thinking about the nature of personality traits. He argued that they reflect motivational systems that evolved to increase adaptation to classes of stimulus associated with positive and negative reinforcement. Individual differences in personality thereby reflect variation in the sensitivity to such stimuli, and overall personality represents the relative strength of sensitivities to various stimulus classes. For instance, impulsive people can be described as more sensitive to reward than punishment, approaching rewarding situations even when punishers make restraint more appropriate. Sensitivity ultimately means reactivity of the neurobiology associated with a motivational system. Gray (1973, 1992) accordingly outlined neurobehavioral models of several traits, and others have extended Gray's work (e.g., Cloninger, Svrakic & Przybeck 1993; Netter, Hennig & Roed 1996; Zuckerman 1991). Nevertheless, a comprehensive neurobehavioral model of a personality trait has yet to be proposed. Such a model must specify at least five points: (a) the behavioral and emotional characteristics of a trait, particularly those that are central to its definition, (b) the motivation inferred to underlie those central characteristics, (c) the network of brain structures that integrates the motivation, (d) the neurobiological variables that account for individual differences in the functioning of the network, and (e) the sources of those individual differences. This target article specifies all five points in a model of one personality trait - extraversion, and evaluates the human evidence related to the model.
In developing the model, we followed the strategy outlined in Figure 1. Personality psychology was used to define extraversion's behavioral, emotional, and motivational characteristics. Next, we identified a mammalian behavior pattern with corresponding characteristics, as described in the psychological and ethological literatures. Once an analogous motivation was identified, animal neurobiological research provided empirical links to its neural organization and neurochemical modulation. These hypotheses were then extended to humans, and subjected to empirical tests.
Variation in emphasis on the characteristics of extraversion has resulted in the use of terms for the higher-order trait other than Extraversion (e.g., Costa & McCrae 1992; Eysenck & Eysenck 1985; Gray 1973, 1989), including Social Activity or Sociability (Buss & Plomin 1984; Guilford, Zimmerman & Guilford 1976; Zuckerman 1994; Zuckerman et al. 1988, 1991), Surgency (Goldberg 1990), Novelty Seeking (Cloninger et al. 1991, 1993), and Positive Emotionality (Tellegen 1985; Tellegen & Waller 1997). Despite this terminological variation, a higher-order trait resembling extraversion is identified in virtually every taxonomy of personality (Buss & Plomin 1984; Cattell, Eber & Tatsuoka 1980; Cloninger et al. 1993; Comrey 1970; Costa & McCrae 1985, 1992; Digman 1990; Eysenck & Eysenck 1975, 1985; Goldberg 1981; Guilford & Zimmerman 1949; Jackson 1984; Tellegen & Waller 1997; Zuckerman et al. 1991), and in many psychometric tests of psychopathology (Gough 1987; Hathaway & McKinley 1943). Because of the long history of the term extraversion, first introduced by Jung (1921) to describe variation in orientation toward the world, and because the term already has recognized meaning to trait psychologists, we adopt it here.
TABLE 1. CHARACTERISTICS OF
EXTRAVERSION INCLUDED IN THE THEORIES OR MULTIDIMENSIONAL PERSONALITY
QUESTIONNAIRES OF TRAIT PSYCHOLOGISTS
| Author1 | Sociability/
Affiliation |
Agency | Activation | Impulsivity-
Sensation Seeking |
Positive Emotions | Optimism |
| Buss-Plomin | X | |||||
| Cattell | X | |||||
| Cloninger | X | X | X | |||
| Costa-McCrae | X | X | X | X | X | |
| Eysenck | ||||||
|
|
X | X | X | X | ||
|
|
X | X | X | ? | X | |
| Goldberg | X | X | X | X | X | |
| Guilford | X | |||||
| Hogan | X | X | ||||
| Jackson | X | X | X | |||
| Jung | X | X | X | |||
| Tellegen | X | X | X | X | X | |
| Zuckerman | X |
2Sociability/Affiliation (agreeableness, affiliation,
social recognition, gregariousness, warmth, social closeness)
Agency
(surgency, assertion, endurance, persistance, achievement, social
dominance, exhibitionism, ascendancy, ambitious)
Activation
(lively, talkativeness, energy level, activity level, active)
Impulsivity-
Sensation Seeking (impulsivity, sensation
seeking, excitement seeking, novelty seeking, bold, risk-taking,
unreliable, unorderly, adventurous, thrill and adventure seeking,
monotony avoidance, boredom susceptibility)
Positive Emotions (positive
emotions, positive affect, elated, enthusiastic, exuberant, cheerful,
merry, jovial)
Optimism
(optimistic)
Two of the characteristics in Table 1 are most frequently cited as central to extraversion, though they are differentially weighted by trait psychologists: interpersonal engagement and impulsivity. We analyze these two for the purpose of defining the type of motivation underlying extraversion, which we propose is incentive motivation. Extraversion needs to be clarified in this way as a prelude to identifying in animals an analogous motivation and its neurobiology.
1.1 The Interpersonal Engagement Characteristic of Extraversion
Every trait psychologist except Guilford and Cloninger has identified interpersonal engagement as one of the central characteristics of extraversion. Even Guilford identified a higher-order trait termed Social Activity (composed of Sociability, Ascendance-Dominance, and Activity-Energy), but he believed that extraverted behavior was more closely related to the distinct, higher-order trait of impulsivity (Rhathymia; Guilford & Zimmerman 1949). As shown in Table 1, interpersonal engagement is not a unitary characteristic, but rather has two components. One component, sociability or affiliation, reflects enjoying and valuing close interpersonal bonds, and being warm and affectionate; the other component, agency, reflects social dominance and the enjoyment of leadership roles, assertiveness, exhibitionism, and a subjective sense of potency in accomplishing goals. These two components are represented, respectively, in lower-order traits of extraversion, such as Warmth-Gregariousness vs Assertiveness (Costa and McCrae's 1992), Social Closeness vs Social Potency (Tellegen & Waller 1997), Sociability vs Ascendance-Dominance (in Social Activity; Guilford & Zimmerman 1949), Warmth (in Agreeableness) vs Assertion (in Surgency) (Goldberg & Rosolack 1994), Warmhearted-Socially Enmeshed vs Dominant-Ascendant (Cattell et al. 1980), and Sociability vs Ambition (in Surgency) (Hogan 1983). These two components are also consistent with the two major traits identified in the theory of interpersonal behavior: Warm-Agreeable vs Assured-Dominant (Wiggins 1991; Wiggins et al. 1988). These traits form the two major orthogonal dimensions in Figure 2, and they are accompanied by two additional dimensions identified by Wiggins that further characterize interpersonal behavior (Gregarious, Extraverted - Aloof, Arrogant - Unassuming). Within this multidimensional structure (referred to as a circumplex), all interpersonal behavior can be represented as a combination of the two major traits.
Several trait psychologists proposed that affiliation and agency extend beyond interpersonal behavior, and represent distinct dispositions that emerge as two separate lower-order traits of extraversion (Hogan 1983; Tellegen & Waller 1997). Whereas affiliation is clearly interpersonal in nature, agency represents a more general disposition encompassing dominance, ambition, mastery, efficacy, and achievement. The nature of this disposition is reflected in trait terms like Agency (Wiggins 1991; Wiggins et al. 1988), Social Dominance (Cattell et al. 1980; Costa & McCrae 1992; Guilford & Zimmerman 1949; Tellegen 1982), Ambition (Watson & Clark 1996), Surgency (Goldberg & Rosolack 1994; Hogan 1983), Achievement (Tellegen & Waller 1996), and Ascendancy (Cattell et al. 1980; Guilford & Zimmerman 1949). Thus, agency is a disposition that is manifest in a range of achievement-related, as well as interpersonal, contexts.
Church and Burke (1994) supported a two-component structure of extraversion by demonstrating that the lower-order traits of extraversion measured by Costa and McCrae's (1992) questionnaire factored into agency (assertiveness, activity) and affiliation (warmth, positive emotions, agreeableness). Furthermore, when general affiliation and agency traits were derived in joint factor analyses of several multidimensional personality questionnaires (Cattell et al. 1980; Jackson 1984; Tellegen 1982), the lower-order trait of achievement loaded strongly (0.71) on agency but weakly (-0.08) on affiliation, whereas lower-order traits related to affiliation showed a strong reverse pattern (Tellegen & Waller 1997).
Several studies found a similar pattern in joint factor analyses of multidimensional personality questionnaires (Church 1994; Costa & McCrae 1989; Tellegen & Waller 1997); two general traits were identified in each case as affiliation and agency. This made it possible to plot the loadings of lower-order traits from several studies in relation to the general agency and affiliation traits (see Appendix A). When trait loadings are plotted from different studies, the interrelations among traits will only be approximations in a quantitative sense, but the pattern with respect to the general affiliation and agency traits is instructive. For purposes of comparison, the lower-order traits are plotted within the interpersonal trait structure of Wiggins in Figure 2. Lower-order traits of achievement, persistence, social dominance, and activity all load much more strongly on agency than on affiliation, whereas traits of sociability and agreeableness show a reverse pattern. Lower-order traits of well being and positive emotions are associated with both agency and affiliation about equally.
1.2 Clarifying the Motivational Nature of Extraversion
Results described so far raise the possibility that the lower-order traits associated with the agency factor (social dominance, achievement, endurance, efficacy, activity, energy) represent different manifestations of a single underlying process. All these traits suggest a form of behavior that is activated or motivated to achieve goals, including both social (e.g., social dominance) and work-related (e.g., achievement) goals. Several trait psychologists include activation as either a specific component of extraversion or one that is moderately correlated with it (see Table 1), as reflected in the traits of activity (Buss & Plomin 1984; Costa & McCrae 1992; Eysenck & Eysenck 1985; Zuckerman et al. 1991), energy and talkativeness (Goldberg & Rosolack 1994), and lively (Eysenck & Eysenck 1985).
It would be incorrect to assume that the activation accompanying extraversion is only a nonspecific form of arousal (although such arousal may be a part of extraversion; Fowles 1980). Tellegen argues convincingly that the type of activation linked with extraversion is positive affect, where affect means a joint experience of emotional feelings and motivation (Tellegen 1985; Tellegen et al. 1988; Tellegen & Waller 1996). Tellegen's (1982) higher-order trait of extraversion includes the lower-order trait of well being, reflecting the extent to which an individual generally feels positive affect. Positive affect has also been associated with extraversion in studies by Costa and McCrae (1980, 1984), who later included it as a lower-order trait of extraversion in their personality questionnaire (Costa & McCrae 1985, 1992). Positive affect is also incorporated in extraversion in the questionnaires of Cattell et al. (1980) and Goldberg (& Rosolack 1994), and is part of Eysenck and Eysenck's (1975) early description of extraversion (cheerful, optimistic, and enthusiastic). When various measures of positive affect were factor analysed jointly with several multidimensional personality questionnaires (Eysenck & Eysenck 1985; Guilford & Zimmerman 1949; Goldberg & Rosolack 1994), positive affect loaded as highly and specifically on a general extraversion trait as traits of social activity (Guilford), surgency (Goldberg), and extraversion (Eysenck) (Watson & Clark 1997). This is consistent with reports of strong, specific correlations between measures of positive affect and extraversion (e.g., 0.66 with Eysenck's extraversion and 0.61 with Goldberg's surgency trait; Watson & Clark 1997). Moreover, Watson and Clark (1997) have shown in two independent samples that, consistent with previous studies (Hogan 1983; Wiggins 1979, 1982; Wiggins et al. 1988), independent measures of positive affect correlate more strongly with both agency and affiliation components of extraversion (both 0.42) than agency and affiliation correlate with each other (0.14).
In contrast to an individual's typical level of positive affect, which represents trait measurement, it is also possible to measure current level of self-reported mood, which represents state measurement. Watson and Tellegen's (1985) integration of the literature on the structure of state mood indicates that it is composed of two orthogonal affective dimensions, positive and negative affect. In agreement with the results on trait positive affect, the subjective experience of state positive affect is a combination of positive emotional feelings and motivation, which is reflected by the adjectives most strongly associated with a state of high positive affect (elated, enthusiastic, excited, peppy, strong, energetic, active). This suggests that both trait and state positive affect reflect the same motivation, which facilitates pleasurable engagement with the environment (Watson & Tellegen 1985). Indeed, the mean level of state positive affect, based on 90 days of current mood ratings, is specifically and significantly correlated with trait measures of positive affect (0.65 - 0.67, Watson & Clark 1996; Zevon & Tellegen 1982) and is moderately related to extraversion itself (0.20 - 0.50; Costa & McCrae 1980, 1984; Emmons & Diener 1985, 1986; Tellegen 1985; Warr et al. 1983; Watson & Clark 1984, 1997).
Our interpretation of this pattern of evidence is that extraversion is closely associated with strong positive affect, which in turn reflects an underlying motivational system. This interpretation is grounded in Gray's (1973, 1987, 1992) proposal that higher-order traits of personality are based on underlying motivational systems, with extraversion arising from what Gray (1973, 1992) and Fowles (1980, 1987) call the Behavioral Activation or Approach System. The latter is a motivational system activated by signals of reward. Extraversion can accordingly be interpreted as sensitivity to signals of reward, as supported by the work of Newman (Newman, Widom, & Nathan 1985; Newman 1987; Wallace & Newman 1990) and Ball and Zuckerman (1990). In the animal neurobehavioral literature, signals of reward are called positive incentive stimuli, and the motivation activated by those stimuli is called positive incentive motivation. Our concept of extraversion is therefore based on incentive motivation rather than on a nonspecific behavioral activation system.
Incentive motivational theory is meant to explain how goal-directed behavior is elicited and guided by incentive stimuli (or their central representations) in interaction with central drive states (Bindra 1978; Panksepp 1986; Toates 1986). Although incentive motivation may be either positive or aversive, only the former is relevant to extraversion. Robinson and Berridge (1993) suggest that positive incentive motivation involves three distinct processes that typically cooccur. First, engagement with unconditioned positive incentive stimuli activates the neural substrates for pleasure, which normally serves as a trigger for the following two processes. Second, through classical associative learning, the experience of pleasure is associated with the neutral stimulus context (objects, acts, events, places) in which pleasure occurred. The previously neurtral stimuli thereby become conditioned incentive stimuli, which upon reoccurring have the capacity to elicit anticipatory pleasure and incentive motivation. Because of the predominance of symbolic (conditioned) processes in guiding human behavior in the absence of unconditioned stimuli, conditioned incentives are particularly important elicitors of a positive incentive motivational disposition (Fowles 1987; Gray 1973).
The third process encodes incentive stimuli (or their central representation) for their intensity or salience, thereby attributing a motivational value to the stimuli. In this way, the incentive motivational influence on emotional and behavioral responses is scaled. Subsequent exposure to the incentive stimuli (or activation of their central representation) elicits an incentive motivational state that facilitates and guides approach behavior to a goal. In humans, incentive motivational states are associated with strong positive affect characterized by feelings of desire, wanting, excitement, enthusiasm, energy, potency, and self-efficacy. These feelings are distinct from, but typically cooccur with, feelings of pleasure and liking (MacLean 1986; Robinson & Berridge 1993; Watson & Tellegen 1985). We propose that variation in this process of encoding incentive salience is the basis of individual differences in the frequency and intensity of incentive motivation and, by extension, is the main source of individual differences in extraversion.
1.3 The Impulsivity Characteristic of Extraversion
The association of impulsivity to extraversion remains an unresolved issue. Impulsivity comprises a heterogeneous cluster of lower-order traits that includes terms such as impulsivity, sensation seeking, risk-taking, novelty seeking, boldness, adventuresomeness, boredom susceptibility, unreliability, and unorderliness. On the basis of Jung's concept of extraversion, Eysenck and Eysenck (1975) included impulsivity in their measure of extraversion, only to remove much of it later because evidence indicated that impulsivity and extraversion were separate traits (Guilford 1975, 1977; Rocklin & Revelle 1981). Currently, most trait models of personality also separate impulsivity and extraversion into distinct traits (Costa & McCrae 1985, 1992; Goldberg & Rosolack 1994; Tellegen 1982, 1985; Tellegen & Waller 1996; Zuckerman 1994; Zuckerman et al. 1991).
Several trait psychologists, however, continue to associate impulsivity and extraversion. Gray (1973; 1987, 1992) proposes that impulsivity represents the interaction of the higher-order traits of extraversion, neuroticism, and psychoticism. Eysenck (Eysenck 1981; Eysenck & Eysenck 1985) defines nine lower-order traits of extraversion that include sensation seeking, venturesomeness, carefree, and lively, whereas impulsivity itself is included in the higher-order trait of psychoticism. Similarly, Cloninger's personality questionnaire replaces extraversion with a higher-order trait of novelty seeking which, according to several lines of evidence, is aligned much more closely with impulsivity and sensation seeking than with extraversion (Cloninger et al. 1991, 1993; Heath et al. 1994; Stallings et al. 1996; Waller, Lilienfeld, Tellegen & Lykken 1991; Zuckerman et al. 1991; Zuckerman, personal communication).
This issue is complex, because the content of the measures of impulsivity is heterogeneous, ranging from purely motor and cognitive impulsivity to novelty- and sensation-seeking, boldness, thrill and adventure seeking, and risk-taking. Not all of these measures are highly interrelated, nor are they consistent in their correlation with extraversion (see below). Furthermore, some measures of impulsivity lack affective content [Conscientiousness (Costa & McCrae 1992; Goldberg & Rosolack 1994) and Constraint (Tellegen & Waller 1997)], and these measures in particular are not, or only weakly, related to extraversion. In contrast, other measures of impulsivity have positive affective content [e.g., Novelty Seeking (Cloninger et al. 1993), several Sensation Seeking measures (Zuckerman 1994), and venturesomeness, boldness, and risk-taking measures in several questionnaires]. To illustrate this point (see Figure 3), we plotted the trait loadings derived in 11 studies (see Appendix B) in which two or more multidimensional personality questionnaires were jointly factor analyzed in order to derive general, higher-order traits of personality. All studies identified a higher-order trait of impulsivity that lacks affective content, which in Figure 3) is labelled constraint following Tellegen (1982, 1985; Tellegen & Waller 1996), who introduced the term to emphasize its independence from affective traits such as extraversion and neuroticism. All studies also found constraint to be orthogonal to a general, higher-order extraversion trait.
Figure 3 shows a continuous distribution of traits within the two intersecting orthogonal dimensions of extraversion and constraint. Nevertheless, three relatively homogeneous clusterings of traits can nevertheless be delineated on the basis of the position and content of traits, relative to extraversion and constraint. First, lower-order traits associated with extraversion (sociability, dominance, achievement, positive emotions, activity, energy) or extraversion itself cluster at the high end of the extraversion dimension without substantial association with constraint. A tight clustering of most traits to extraversion is evident, although several lower-order traits of extraversion are "pulled" toward the high end of constraint in a few studies, which may be due to differences in definitions of trait content or in measurement. Second, various traits of impulsivity that do not incorporate strong positive affect (e.g., Conscientiousness) cluster tightly around the high end of the constraint dimension without substantial association with extraversion; Eysenck's Psychoticism trait and various aggression measures are located at the low end of constraint and show little association with extraversion. The anchoring of the two extreme ends of constraint by Conscientiousness and Psychoticism was also observed by Zuckerman (1991). Third, all but one trait measure of impulsivity that incorporate positive affect (sensation seeking, novelty seeking, risk-taking) are located within the dashed lines in Figure 3, and are moderately associated with both extraversion and constraint.
1.4 Lines of Causal Neurobiological Influence in the Structure of Personality
Although the clustering of traits in Figure 3 is instructive with respect to the structure of personality, Gray's (1973, 1987, 1992) challenge concerning where the lines of causal influence lie within that structure remains cogent. Both Cloninger (1986, 1987; Cloninger et al. 1991) and Zuckerman (1991) have argued that a major line of neurobiological influence lies with the cluster of impulsivity and sensation seeking traits rather than along the extraversion dimension. Similarly, Gray (1973, 1987, 1992) proposed that impulsivity rather than extraversion is associated with a line of causal influence. His impulsivity trait would lie with the impulsivity cluster in Figure 3 if (a) neuroticism (defined as an overall amplifier of emotion) is aligned with the constraint dimension in Figure 3, (b) high psychoticism is positioned at the low end of the constraint dimension (as occurs in Figure 3), and (c) extraversion is interpreted as the relative sensitivity to signals of reward vs punishment.
At the level of behavior, we also suggest that impulsivity arises from an interaction of traits, but specifically between extaversion and constraint as in Figure 3. We differ from others in our interpretation of the nature of this interaction. Extraversion, when interpreted as reflecting incentive motivation, consists of positive affect and action-readiness; therefore, high levels of extraversion can be associated with action-proneness that shades toward impulsivity under conditions of strong positive affect. This behavioral disposition interacts with constraint. For us, constraint lacks ties to a specific motivational system, which is supported by the traits that cluster around the constraint dimension in Figure 3. We suggest that constraint functions as a threshold variable that modulates stimulus elicitation of motor behavior, both positive and negative affect, and cognition, all of which may be associated with serotonin functioning (Depue 1995, 1996; Depue & Spoont 1986; Depue & Zald 1993) as was also proposed by others (Panksepp 1982; Soubrie 1986; Spoont 1992; Zuckerman 1991). This formulation is consistent with findings that low constraint is associated with both reduced serotonin functioning and with a generalized motor-cognitive-affective impulsivity, but not preferentially with any specific motivational system (Coccaro & Siever 1992; Depue 1995, 1996; Depue & Spoont 1986; Spoont 1992). Gray's (1973, 1987, 1992) theoretical treatment of neuroticism as a general amplifier of reactivity to both signals of reward and punishment, hence influencing the magnitude of both impulsivity and anxiety, is more consistent with our concept of constraint. Similarly, Eysenck's psychoticism trait and Zuckerman's (1989, 1991) impulsivity trait overlap our concept, whereas Cloninger's personality model does not include a trait analogous to constraint.
We nevertheless are in basic disagreement with the positions of Gray, Cloninger, and Zuckerman concerning the lines of causal neurobiological influence, which we propose lie along the two orthogonal dimensions of extraversion and constraint rather than along an impulsivity diagonal resulting from their interaction. The main reason for our disagreement is that we believe the impulsivity-sensation seeking traits in Figure 3 represent emergent traits that result from the interaction of extraversion, constraint, and possibly harm-avoidance in the case of sensation seeking (Depue 1995, 1996). If extraversion and constraint have coherent neurobiological influences, such an emergent trait would be expected to have heterogeneous neurobiological sources of influence. Accordingly, research attempting to detect a neurobiological variable strongly and specifically associated with that trait would likely produce weak and inconsistent results. For instance, in Gray's (1973, 1992) model, impulsivity emerges from two levels of complex interactions between the higher-order traits of extraversion and neuroticism. First, extraversion represents the interaction of the relative strength of sensitivities to two distinct classes of stimulus - signals of reward (more the extravert) and punishment (more the introvert). The model is affectively bipolar, with high and low extremes of extraversion being associated with different predominant affective states - positive vs negative. Sensitivities to these two stimulus classes undoubtedly have distinct neurobiological foundations. Second, the intrinsically interactive trait of extraversion interacts with neuroticism, entailing the further influence of at least one more neurobiological variable, to form the emergent trait of impulsivity. At the level of behavior, it is plausible that impulsivity represents the interaction of several higher-order traits, even if those traits are based on distinct motivations. At the level of neurobiology, however, we doubt that coherent lines of causal influence are associated with traits of such complexity.
We propose that causal neurobiological influence can be identified
most clearly by disecting higher-order traits into more homogeneous
components (if they are initially heterogeneous). In the case of
affective higher-order traits, more homogeneous components would
reflect single motivational systems, which naturally are affectively
unipolar. Positive incentive motivation, for instance, is associated
with a unipolar dimension of positive affect, ranging from strong
presence to complete absence at the extremes (Tellegen & Waller
1997; Watson & Tellegen 1985). Accordingly, we prefer to disect
extraversion into separate components of agency and affiliation, as
they are more likely to be associated with separable motivations and
neurobiological influences (e.g., Dichiara, Acquas & Carboni 1992).
Our model of extraversion, which focuses on the agency component, is
based on a single neurobiological network that integrates incentive
motivation. Consequently, we assume that individual differences in the
neurobiology of the agency component of extraversion are not
linked causally to the neurobiology associated with other higher-order
traits. Theoretical arguments far exceed data in the debate over where
to place the lines of causal influence within the relational structure
of personality. Nevertheless, we believe that our theoretical position
is important, because it directs the search in the animal literature to
the neurobiological foundations of incentive motivation and ultimately
of extraversion itself.
2.1 Personality Trait Structure
Higher-order personality traits can be modeled in a hierarchical
structure shown in Figure 4-A for
extraversion. This structure illustrates the interrelations among the
characteristics and underlying processes of extraversion discussed
above. In the figure, lower-order traits are each associated with
extraversion, because each trait reflects the influence of the same
underlying processes (energy, incentive motivation, positive affect,
cognition). Some of the lower-order traits, such as positive affect and
activation, represent underlying processes directly, whereas others
reflect their influence as manifested in different environmental
contexts, e.g., competitive (Social Potency), long-term goal
acquisition (Achievement), and social (Affiliation). We attribute to
extraversion a central mechanism that provides a facilitatory
modulation of all underlying processes. This modulatory influence
binds the processes together and scales their intensity, leading to
varying degrees of facilitation of behavioral approach. The final
specific forms of behavior associated with different contexts (e.g.,
social, achievement-related) are manifested in the lower-order traits,
and are presumably mediated by specific behavioral systems (see
below).
2.2 Behavioral System Structure
From an evolutionary biology perspective, behavioral systems may be understood as behavior patterns that evolved to adapt to stimuli critical for survival and species preservation (Gray 1973; MacLean 1986; Panksepp 1986; Schneirla 1959). Linkage of behavioral systems to critical stimulus conditions suggests that their neurobiology is integrated with brain networks responsible for both the recognition of stimulus significance and the activation of effector systems (locomotor, facial, vocal, autonomic, hormonal). Collectively, this group of interrelated brain functions is referred to as emotion (LeDoux 1987, 1996). Thus, behavioral systems are fundamentally emotional systems. This distinction is important because the term emotion, derived from the latin verb emovere (to move, to push), not only implies activation of behavior, but also of a motivational state and emotional experience that is concordant with the reinforcement properties of critical stimuli (Gray 1973; Rolls 1986).
Behavioral systems vary along a dimension of increasing generality (Blackburn, Phillips, Jakerbovic, & Fibiger 1989; Gray 1973; MacLean 1986; McNaughton 1989; Panksepp 1986). At lower levels of the dimension, specific interoceptive and exteroceptive stimuli related to primary biological aims elicit behavior and emotions that are relatively specific to those conditions (e.g., sexual, social, food). At the highest level of the dimension, there are a limited number of general behavioral systems that are more flexible, and have less immediate objectives and more variable topographies (Blackburn et al. 1989; MacLean 1986; McNaughton 1989). These systems are activated by broad classes of stimulus (Depue, in press-a; Gray 1973; Rolls 1986), and regulate general emotional-behavioral dispositions, such as desire-approach or anxiety-inhibition, that modulate goal-directed activity. It is the relatively small number of general systems that directly influences the structure of mammalian behavior at higher-order levels of organization, because, like extraversion, their modulatory effects on behavior derive from frequent activation by broad stimulus classes.
There is one general behavioral system that is based on underlying processes and behavior that correspond to extraversion. This system is activated by, and serves to bring an animal in contact with, unconditioned and conditioned positive incentive stimuli (Benninger 1983; Depue in press; Gray 1973; Hebb 1949; Koob, Robledo, Markou, & Caine 1993; Panksepp 1986; Schneirla 1959; Stewart, de Wit, & Eikelboom 1984). As outlined by Gray (1973), incentive stimulus conditions also include signals of safety that may lead to termination of aversive stimuli (as in active avoidance of punishment), and signals of frustrative nonreward, where affective aggression may lead to removal of obstacles to reward. This system is consistently described in all animals across phylogeny (Hebb 1949; Schneirla 1959), but has been defined at two conceptual levels: (a) behavioral, as a search (MacLean 1986), foraging (Panksepp 1986), and approach system (Gray 1973; Schneirla 1959); and (b) underlying process, as an incentive (Beninger, 1983), expectancy (Panksepp 1986), preparatory (Blackburn et al. 1989), and activation system (Fowles 1987; Gray 1973). We define this system as behavioral approach based on incentive motivation.
To illustrate the correspondence with extraversion, we structured the behavioral system hierachically in Figure 4-B. In the figure, approach behavior (the output) is jointly supported by several underlying processes (locomotor initiation, incentive motivation, positive affect, cognitive) that direct behavior to a rewarding goal. As in the structure of extraversion, a higher-order central mechanism is proposed that underlies the joint activation of these supporting processes. For reasons that will become clear in discussion of neurobiology below, this mechanism is termed facilitation, which corresponds to the modulatory mechanism embodied in extraversion in Figure 4-A.
2.3 Conclusion
We propose that at higher-order levels of personality and behavior (extraversion and facilitation in Figure 4), there is a common neurobiology. Animal research demonstrates that behavioral facilitation is associated with the functional properties of the ventral tegmental area (VTA) dopamine (DA) projection system. Just as extraversion and facilitation emerge as higher-order constructs that incorporate a modulatory mechanism that operates across lower-order traits and supporting processes, the VTA DA projection system might also be considered a higher-order modulator of a neurobiological network that integrates behavioral functions associated with extraversion. If correct, the general form of this three-part parallelism suggests that the higher-order relational structure of personality may be associated with a few, not many, neuromodulator systems that have sufficently widespread brain distributions to modulate the variety of supporting processes associated with higher-order traits.
In the following discussion, we define the neurobiology of
behavioral facilitation. This neurobiology is extended to the essence
of personality - individual differences - by assessing the role of DA
in various personality traits, as well as in three neurodevelopmental
processes that represent fundamental sources of individual differences
in general. The effects of individual differences in DA functioning on
behavioral factilitation are then organized within a psychobiological
threshold model, which yields implications for conceptualizing
individual differences in extraversion. We conclude by discussing other
variables to be considered in a multifactorial neurobehavioral model of
extraversion.
3.1 A General Functional Role for VTA DA Ascending Projections
Because VTA and substantia nigra DA ascending projections innervate between 20-30 structures, it is unlikely that DA mediates any specific behavioral functions (Le Moal & Simon 1991; Oades & Halliday 1987). Rather, the functional effects of DA are largely dependent on the types of process integrated within terminal structures and their associated networks. Behavioral deficits resulting from DA inactivation can be reinstated, not just by DA agonists (Kelley & Stinus 1985), but also by changes in the internal environment (e.g., hunger) and by stress or strong emotional stimuli (Koob et al. 1993; Le Moal & Simon 1991; Oades 1985; Taghzouti, Simon & Le Moal 1986). Also, selective DA lesions in various projection areas create behavioral deficits that are similar to deficits produced by electrolytic lesions of those same areas (Le Moal & Simon 1991; Louilot et al. 1987). Thus, behavioral processes seem in tact but latent in the absence of DA.
Independent of brain region, DA has the general function of facilitating neural processes subserving goal-directed behavior (Bozarth 1987; Depue in press; Deutch, Bourdelais & Zahm 1993; Fibiger & Phillips 1987; Le Moal & Simon 1991; Louilot et al. 1987; Oades 1985; Oades & Halliday 1987; Robbins & Everitt 1992). DA agonists or antagonists in the VTA or nucleus accumbens (NAS), which is a major terminal area of VTA DA projections, in rats and monkeys facilitate or markedly impair, respectively, locomotor activity to novelty and food; exploratory, aggressive, social, and sexual behavior; the number of attempted behavioral strategies; acquisition and maintenance of approach and active avoidance behavior; response reversal; spontaneous alternation; food-hoarding; and maternal nursing behavior. These deficits are not motor, per se, because diurnal locomotor patterns remain unchanged, and animals can perform tasks normally once they are moved or pushed by the experimenter to do so (Oades 1985). Neither are these deficits evident in nonvolitional motor behavior, such as escape, nor in consummatory behavior (Blackburn et al. 1989; Le Moal & Simon, 1991). It is precisely incentive motivation that is lost, such that volitional behavior elicited by incentive stimuli cannot be initiated or facilitated (Beninger 1983; Bozarth 1987; Everitt & Robbins 1992; Koob et al. 1993; Le Moal & Simon 1991). We emphasize that DA mediation of incentive motivation is not proposed here; rather, DA is seen as providing a strong modulatory influence - facilitation - on incentive motivation. Put generally, incentive motivation is neurobiologically organized in regions of integration, whereas DA serves to neuromodulate those regions (Le Moal & Simon 1991; Mesulam 1990).
3.2 Dopamine and Incentive Motivation
DA agonists injected in the NAS reduce, while both DA D1 and D2 antagonists increase, the threshold for electrical intracranial self-stimulation reward, a response model of incentive motivation (Bozarth 1987; Everitt & Robbins 1992; Fibiger & Phillips 1987; Knapp & Kornetsky 1994; Koob et al. 1993; Le Moal & Simon 1991; Mogenson, Grudzynski, Wu, Yang & Yim 1993). Increased DA metabolism during intracranial self-stimulation in the VTA is confined to structures of the ventral striatum, especially the NAS (Fibiger & Phillips 1987), and studies using both self-administration of electrical stimulation and of stimulant drugs revealed a converging activation of VTA mesolimbic DA pathways (Porrino 1987). Furthermore, dose-dependent DA D1, D2, and D3 receptor activation in the VTA-NAS pathway facilitates the acute rewarding effects of stimulants, and the NAS is a particularly strong site for intracranial self-administration of DA and DA agonists (Hoebel, Monaco, Hernandez, Aulise, Stanley & Lenard 1983; Le Moal & Simon 1991; Pich et al. 1997). D1 and D2 agonists injected in the NAS also modulate behavioral responses to conditioned incentive stimuli in a dose-dependent fashion (Cador, Taylor & Robbins 1991; Robbins, Cador, Taylor & Everitt 1989; Wolterink, Cador, Wolterink, Robbins & Everitt 1989). Conversely, decreases in DA metabolism induced by uncontrollable stress are associated with marked and long-lasting reductions in self-stimulation in the NAS and dorsal VTA, suggesting reduced incentive motivation (Anisman, Zalcman & Zacharko 1993; Zacharko & Anisman 1991). In addition, DA lesions (using 6-OHDA, with terminal field ablations of 95% or more) in the NAS or VTA create a reduction in motivation to work for reward, extinction-like responding, and long-lasting reductions in self-administration of stimulants (Caine & Koob 1993; Fibiger & Phillips 1987; Koob 1992; Koob et al. 1993; Phillips & Fibiger 1978; Pich, Pagliusi, Tessari, Talabot-Ayer, Huijsduijnen, & Chiamulera 1997; Robledo, Maldonado-Lopez & Koob 1992), whereas lesions of other DA terminal fields affect stimulant self-administration very little, if at all (Roberts & Zito 1987).
The initiation phase of locomotor activity is closely tied to incentive motivational input to the motor system. DA D1 and D2 agonists, particularly when injected in the NAS compared to the dorsal striatum, facilitate the initiation, speed, and vigor of locomotion (Clarke & White 1987; Fishman, Feigenbaum, Yanaiz & Klawans, 1983; Le Moal & Simon 1991; Oades 1985), and markedly increase the frequency and duration of spontaneous exploratory activity (Fink & Smith 1980). In inbred mouse strains, both the quantity of spontaneous exploratory locomotion and amphetamine-induced locomotion are both positively related to the number of VTA DA neurons, as well as to the relative density of innervation of DA terminals and to DA content in the NAS; accordingly, these behavioral effects may be related to the proportionately greater synthesis and release of DA in high-DA neuron strains (Fink & Reiss 1981; Oades 1985; Sved, Baker & Reis 1984; 1985). In contrast, VTA DA projections to the amygdala and olfactory tubercle do not significantly influence initiation of locomotor activity or stimulant self-administration, although projections to the ventral pallidum can be moderately facilitative (Oades 1985; Oades, Taghzouti, Rivet, Simon & Le Moal 1986; Pich et al. 1997).
In single-unit recording studies, VTA DA neurons are activated preferentially by appetitive incentive stimuli, whereas responses to signals of punishment occur in only a few cells (Mirenowicz & Schultz 1996; Schultz et al. 1995b; Schultz, Dayan & Montague 1997). DA cells, most numerously in the VTA, respond vigorously to, and in proportion to the magnitude of, both conditioned and unconditioned incentive stimuli, and in anticipation of reward (Bowman, Aigner & Richmond 1996; Henriksen & Giacchino 1993; Houk, Adams & Barto 1995; Koob et al. 1993; Le Moal & Simon 1991; Mark, Blander & Hoebel 1991; Mitchell & Gratton 1992; Mirenowicz & Schultz 1996; Nishino et al. 1987; Pfaus, Damsma, Nomidos, Wekstren, Blaha, Phillips & Fibiger 1990; Schultz, Apicella & Ljungberg 1993; Schultz et al. 1995b; Shultz et al. 1997; Weiss, Hurd, Ungerstedt, Markou, Plotsky & Koob 1992).
VTA DA neuron responses to incentive stimuli may play a role in facilitating the association between stimuli that predict reward and behavioral responses that obtain reward (Schultz et al. 1997). The optimal stimuli for activating DA neurons are phasically occuring unpredicted food and liquid rewards, whereas fully predicted stimuli are ineffective (Schultz et al. 1995b). During an experiment's progression, DA neurons show increased activity in the presence of neutral stimuli that consistently predict reward, and a concurrent decrease in activity to the unconditioned rewards, until DA responding has transferred completely to the conditioned incentive stimuli (Schultz et al. 1995b, 1997). The same process is observed when control of behavioral responding is transferred to earlier occurring stimuli that are predictive of the primary incentive stimulus (Schultz et al. 1997). Thus, "DA discharge ratchets backward in time, in a sequence of familiar events, so as to respond to earlier and earlier predictors of reinforcement" (Houk et al. 1995, p. 250). DA activity is not necessary, however, to the development of associations between stimuli, per se, even associations involving reward (Beninger 1983; Everitt & Robbins 1992; Le Moal & Simon 1991). Instead, DA activity is critical to the control of appetitive behavior by conditioned incentive stimuli - specifically, to link stimuli predicting reward to the response-facilitation mechanism in the NAS (Beninger 1983; LeMoal & Simon, 1991; Schultz et al. 1997).
3.3 Neuroanatomical Integration of Incentive Information
The critical role of the VTA-NAS DA pathway in the facilitation of incentive motivation suggests that the NAS is a site of integration of incentive information. The caudomedial shell region of the NAS (NASshell) is a major point of convergence of motivational information from many limbic structures (Heimer, Alheid & Zahm 1993; Kalivas et al. 1993; Wright, Beijer, & Groenewegen 1996). Particularly high rates of intracranial self-stimulation and energy use (2-deoxyglucose uptake) during self-stimulation are found mainly in the NASshell (Deutch et al. 1993). Whereas NAS cells decrease firing during periods of focused attention and consummatory events, they increase firing to primary and conditioned signals of reward and novelty, and during intervals when reward is expected and during engagement in rewarding social and aggressive acitivity (Apicella, Ljungberg, Scarnati & Schultz 1991; Henriksen & Giacchino 1993; Le Moal & Simon 1991; Schultz, Apicella, Scarnati & Ljungberg 1992; Schultz et al. 1995a). In contrast, pharmacologic impairment of NASshell functioning leads to extinction-like responding on established reinforcement schedules, long-lasting decreases in the self-administration of reinforcing drugs, and reduced effort in working for drug reward (Lyness, Friedle & Moore 1979; Lyness & Smith 1992; Roberts, Koob, Klonoff & Fibiger 1980).
Responses of NAS neurons to conditioned incentives are due to afferent excitatory stimulation arising from several sources: (a) the basolateral complex of the amygdala (i.e., the basal, accessory basal, and lateral nuclei; Kalivas et al. 1993; Wright et al. 1996), (b) regions comprising the extended amygdala (Everitt & Robbins 1992; Mogenson et al., 1993; Nishijo, Ono & Nishino 1988; Pert, Post & Weiss 1992), (c) the hippocampus (Everitt & Robbins 1992; Gaffan 1992), and (d) the prefrontal medial orbital cortex (Thorpe, Rolls & Maddison 1983; Watanabe 1990). All of these structures are strongly interconnected (Kalivas et al. 1993), but each provides different, specific information about the salient incentive context to the NAS as follows:
3.3.1 The basolateral amygdala of the rat (Wright et al. 1996) and monkey (Heimer et al. 1993) provides massive, topographically organized, compartmentally bounded innervation of the NASshell. With simultaneous stimulation of both the amygdala and VTA (Boldry, Willins, Wallace & Uretsky 1991; Willins, Wallace, Miller & Uretsky 1992), NAS stimulation more readily produces initiation of forward locomotion (Deutch et al. 1993) and exploratory activity to novelty (Kelley, Cador & Stinus 1989). In both monkey and human, the basolateral amygdala plays a critical role in classical stimulus-reinforcement conditioning (Aggleton 1992; Bechara, Tranel, Damascio, Adolphs, Rockland & Damascio 1995; Cahill & McGaugh 1990; Everitt & Robbins 1992; Gaffan 1992; LeDoux 1996; LeDoux, Cicchetti, Xagoraris & Romanski 1990; Selden, Everitt, Jarrad & Robbins 1991). Bilateral basolateral amygdala lesions specifically impair the association of discrete stimuli with reinforcement, whereas the motivational efficacy of food rewards or of DA injections in the NAS remains in tact (Aggleton 1992; Everitt & Robbins 1992; Gaffan 1992). This indicates that the basolateral amygdala performs stimulus-reinforcement associative functions, whereas DA release in the NAS modulates an incentive motivational influence. Nevertheless, lesions of either the basolateral amygdala or NAS impair responding for reward, suggesting that these two structures are serially connected (Everitt & Robbins 1992; Mogenson et al. 1993).
3.3.2 Basolateral and olfactory amygdala complexes send massive projections to a group of structures collectively referred to as the extended amygdala, which represents a macrostructure that is characterized by two divisions, central and medial (Heimer et al. 1993; Martin, Hadfield, Dellovade & Price 1991). Stretching from the central and medial nuclei of the amygdala, the cental and medial divisions merge specifically with the caudomedial region of the NASshell. Many intrinsic connections occur along these divisions, particularly the central division (Heimer et al. 1993), suggesting that high level integration occurs within the extended amygdala (Koob & LeMoal 1997; LeDoux 1996). Although the manner in which behavioral functions are organized within the extended amygdala is not understood, these structures appear to be integrate information related to reinforcement, stimulus-reward associations, and motivation (Koob et al. 1993). Pharmacological and lesion manipulations of all central extended amygdala structures modify incentive motivation to work for rewards and initiation of locomotor activity as a means of obtaining rewards (Heimer et al. 1993; Kalivas et al. 1993; Koob 1992; Koob et al. 1993). Most structures of the extended amygdala can transmit this motivationally-relevant information to some or all hypothalamic and brainstem structures related to emotional expression (Heimer et al. 1993), leading Holstege (1991, 1992) to consider the extended amygdala as a third or emotional motor system.
3.3.3 The hippocampus topographically innervates the NASshell (Groenewegen, Berendse, Meredith, Haber, Voorn, Wolters & Lohman 1991), but lesions of the fimbria-fornix or ventral hippocampus do not impair the association of discrete stimuli with reinforcement (Bechara et al. 1995; Gaffan 1992). Rather, hippocampal, but not basolateral amygdala, lesions disrupt Pavlovian associations formed between the spatial and contextual interrelations of environmental stimuli and reinforcement (Annett, McGregor & Robins 1989; Selden et al. 1991; Sutherland & McDonald 1990). NAS lesions, on the other hand, can produce behavioral deficits closely related to those following impairment of hippocampal functions (Annett et al. 1989). Thus, doubly dissociable limbic-striatal functions (amygdala-NAS vs hippocampal-NAS) may correspond to the compartmentalization of the NAS (Everitt & Robbins 1992; Gaffan 1992; LeDoux 1992, 1996).
3.3.4 The orbital frontal cortex, particularly Brodmann's posterior medial orbital prefrontal cortical area 13 (MOC 13), integrates the most complex level of associations of reinforcement with both stimuli and responses (Rolls, 1986; Thorpe et al. 1983). MOC 13 has strong connectivity with regions that process all sensory modalities of contemporaneous and stored information, as well as topographically organized efferents that densely innervate the NASshell (Deutch et al. 1993; Goldman-Rakic 1987; Kalivas et al. 1993). Through its dense reciprocal connections with the basolateral, central, and extended amygdala regions, MOC 13 has access to emotional and reinforcement associations of contemporaneous and recalled sensory events (Goldman-Rakic, 1987; Porrino, Crane & Goldman-Rakic 1981). MOC 13 forms higher-level conditional representations of sensory events by associating them with existing or newly developing response- reinforcement contingencies; or more simply, MOC 13 may abstract an integrated structure of appetitive and aversive behavioral contingencies from the environment (Thorpe et al. 1983). When behavioral responses evoke unexpected reinforcement outcomes, MOC 13, in collaboration with the basolateral amygdala (Everitt & Robbins 1992) and hippocampus (Gray, Feldon, Rawlins, Hemsley & Smith 1991), encodes the new contingencies that are relevant to the modification of response programs (Thorpe et al. 1983). MOC 13 may be capable of holding such representations of behavioral-reinforcement contingencies in working memory as motor strategies are selected over time (Goldman-Rakic 1987; Scalaidhe, Wilson & Goldman-Rakic 1997). This capacity would allow a comparison of the valence and magnitude of outcome expectancies associated with several possible response strategies, and then an updating of contingencies as circumstances unfold during the temporal duration of the selected response strategy (Houk et al. 1995).
3.3.5 The above discussion is integrated in Figure 5, where the information transferred by MOC 13, the basolateral amygdala, and hippocampus to the NASshell represents the salient context of incentive stimuli (Houk et al. 1995; Pierce et al. 1996; Schultz et al. 1995b; Schultz et al. 1997). Context includes distinctive attributes of incentive stimuli (modality, size, color, scent, texture, etc.) as well as their immediate sensory surround (position, location of targets of action, etc.), both of which are integrated with respect to internal drive states, desirability of action, and intended actions in the near future. Contextual information arrives from these areas via 5,000 - 20,000 glutamatergic efferents that interdigitate on the heads of dendritic spines of single medium spiny neurons in the NASshell (Christie et al. 1987; Davis 1992; Dudai 1989; Fuller et al. 1987; Goldman-Rakic 1988; Gronewegen et al. 1990; Groves et al. 1995; Houk et al. 1995; Kalivas et al. 1995; Kapp et al. 1992; Mishkin & Appenzeller 1987; Schultz et al. 1995b; Takagishi & Chiba 1991; Wickens et al. 1995). Most of these efferents are excitatory to NAS function and are reciprocated (Kalivas et al. 1993; Pierce et al. 1996). Between 4500 - 8000 VTA DA efferents synapsing on spinal shafts of single NAS neurons interdigitate with the contextual glutamatergic inputs (Groves et al. 1995; Grace 1991; Schultz et al. 1995b; Meredith et al. 1993; Sesack & Pickel 1990, 1992). As discussed in more detail above (Section 4.3.1), neuroanatomic association between cortical and limbic glutamate and VTA DA efferents on NAS dendrites allows DA to facilitate the synaptic strength of the glutamatergic inputs to the NAS. This DA facilitation would promote the activation of incentive motivation by, and approach behavior toward, the most salient context (Houk et al. 1995; Kalivas 1995; Pierce et al. 1996; Schultz et al. 1995b; Schultz et al. 1997; Toshibiko, Graybiel & Kimura 1994; Wickens et al. 1995).
3.4 Generation of An Incentive Motivational State Within A Motive Circuit
Kalivas et al. (1993) proposed that incentive context and reinforcement associations, which are integrated in the amygdala and MOC, are translated into an incentive motivational state within a motive circuit (Kalivas et al. 1993). The circuit includes the NASshell, ventromedial subterritory of the ventral pallidum (VPm), and VTA DA ascending projections (see lower half of Figure 6). All three regions are strongly, reciprocally, and preferentially connected with each other, as compared to other subregions of the striatum and pallidum (Deutch et al. 1993; Heimer et al. 1993). Functionally, these regions are interdependent in that the rewarding self-administration of electrical stimulation and stimulant drugs, as well as the initiation of locomotor activity, can be elicited from all three regions (Kalivas et al. 1993; Klitenick, Deutch, Churchill & Kalivas 1992; Koob et al. 1993). Also, impairment of any one of these regions blocks the initiation of locomotor activity normally elicited by stimulation of either of the two remaining regions (Austin & Kalivas 1991; Kalivas et al. 1993).
One major function of the integration of information in the NASshell is to encode the motivational intensity or salience of incentive stimuli (Kalivas et al., 1993). The NASshell can transmit this code back to the extended amygdala as a means of influencing extended amygdala output to brainstem autonomic and somatomotor regions (Heimer et al. 1993), and to the VPm for further integration. Because the VPm can transmit the information back to the VTA (Zahm 1989), the NASshell - VPm - VTA loop can be closed, setting up a reverberatory capacity within the circuit that permits temporal maintenance of an incentive motivational state (Kalivas et al. 1993). With a reverberatory mode engaged, the intensity of an incentive motivational state could be modulated, in accord with variation in reward value of stimuli encountered, via afferent feedback to the motive circuit from the MOC, amygdala regions, and hippocampus.
The current motivational code established in the motive circuit can be transmitted from VPm to MOC 13 via the mediodorsal (MD) nucleus of the thalamus (Deutch et al. 1993; Groenewegern 1988; Kalivas et al. 1993). Presumably, this code is merged with the most current representation of behavioral-reinforcement contingencies held in working memory by MOC 13, perhaps invoking a reintegration that reflects a change in motivational state (Houk et al. 1995). MOC 13 may then transmit the updated contingency structure back to the motive circuit via efferents to the NASshell and VTA (Deutch et al. 1993; Groenewegen et al. 1990; 1991; Kalivas et al. 1993). The result would be a continual iterative updating, not only of incentive motivational intensity as integrated in the motive circuit, but also of reinforcement priorities and behavioral outcome expectations as constructed in MOC 13.
3.5 Neural Organization of Incentive-Facilitated Behavior In A Medial Orbital Network
Whereas the motive circuit encodes the intensity of incentive motivation, a broader network of distributed neural structures is implicated in the modulatory influence of incentive motivation on appetitive behavior. Extending the ideas of others (Deutch et al. 1993; Groenewegen et al. 1990; 1991; Heimer et al. 1993; Kalivas et al. 1993), we propose an MOC network illustrated in Figure 6. In keeping with the structure of other network models (Alexander, Crutcher & Delong 1990; Groenewegen et al. 1990; 1991; Mesulam 1990; Goldman-Rakic 1987), the origin and termination site of this network lies within the prefrontal cortex, specifically MOC 13. Connections between all components of the network are topograpically organized (Groenewegen et al. 1990; 1991), indicating that the basal ganglia-thalamocortical circuits of the ventral forebrain are congruent with the structure of more dorsally located cortical circuits outlined by Alexander et al. (1990).
The MOC network incorporates three basic components: (1) a motive circuit that integrates, maintains, and updates information to form an intensity encoded incentive motivational state, (2) the VTA DA projection system that facilitates the neural integration occurring in the motive circuit, as well as within network interactions more generally, and (3) MOC 13, which performs higher-order regulation of network processes, which is consistent with similar proposals regarding the rat ventral prefrontal cortex (Deutch et al. 1993; Kalivas et al. 1993; Thorpe et al. 1983; Watanabe 1990). Only MOC 13 has the requisite features to exert such high level regulation, including cellular properties that can maintain a current reinforcement expectation in working memory while it is updated within the network; and extensive patterns of connectivity with other MOC network structures, with cortical and subcortical structures that integrate contemporaneous and stored information within and across all sensory modalities, and with brainstem somatomotor regions (Scalaidhe et al. 1997). Moreover, since a portion of ventral prefrontal efferents appear to be highly collateralized (Beckstead, 1979a), the MOC may provide a coordinated modulation of network regions. For instance, the MOC could vary the level of facilitation of motor, autonomic, and neurohormonal components of appetitive behavior according to contextual circumstances (Rolls 1986; Thorpe et al. 1983).
Topographically organized efferents from the MOC to the NASshell (which overlap amygdala input to the shell; Beckstead 1979a,b; Oades & Halliday 1987) and VTA create fine-point modulation of the VTA-NAS DA pathway (Deutch et al. 1993; Groenewegen et al. 1990;1991; Kalivas et al. 1993; Takagishi & Chiba 1991). These efferents use excitatory amino acids (such as glutamate) that have excitatory effects on both NASshell and VTA neurons (Deutch et al. 1993; Grace 1991; Imperato, Honore & Jensen 1990; Kalivas, Duffy & Barrow 1989; Youngren, Daly & Moghaddam 1993). In addition to direct MOC-NASshell efferents that exert a modulatory influence on DA release in the NASshell (Grace 1991; Le Moal & Simon 1991), MOC-VTA efferents increase the activity of VTA DA cells that project to the NASshell, central and basolateral amygdala, and VPm (Groenewegen et al. 1990; 1991). MOC input strongly regulates burst firing of VTA DA cells, which is associated with a doubling of DA release per action potential in the NAS (Gonon 1988; Johnson, Seutin & North 1992; Suaud-Chagny, Dhergui, Chouvet & Gonon 1992). Incentive stimuli also elicit increased DA release in the NASshell (Deutch et al. 1993), and since DA release in the NASshell gates motivational information arriving from the amygdala and hippocampus (Mogenson et al. 1993), MOC regulation of VTA-NASshell DA projections may have a significant indirect impact on the transfer of motivational information to the VPm and hence around the entire motive circuit.
Besides regulating the intensity and temporal maintenance parameters of the motive circuit, MOC 13 could influence whether the incentive motivational state is eventually transmitted to the voluntary motor system. The MOC network likely interacts with a parallel motor network that is involved in translating motivational state to motor areas (Joel & Weiner 1994). Deutch et al. (1993) concluded that such a motor network is associated with the core region of the NAS, and is involved in attaching the motivational codes of the shell region to voluntary motor activity. Hence, the NAScore may represent the interface between motivation and voluntary movement. The threshold for eliciting DA utilization is lower for MOC network structures than for structures associated with the NAScore (Deutch et al., 1993). Thus, as suggested by others (Deutch et al., 1993; LeMoal & Simon, 1991), behavioral responses to incentive stimuli may be facilitated by DA in a graded manner as follows. First, DA facilitates the generation of an incentive motivational state in the NASshell, which is associated with behavioral outcome expectations in the MOC network. Next, if reward acquisition is expected, DA facilitates attachment of an incentive motivational intensity code to motor acts, and initiation of locomotor activity, via the NAScore network. Finally, DA facilitates sensory-motor integration in the dorsal striatopallidal system to provide coordinated motor responses that lead to reward.
3.6 Conclusions on the Neural Organization of Behavioral Facilitation
Figure 4-C illustrates that VTA DA projections to structures of the MOC network provide the neural substrate for extraversion and behavioral facilitation, as diagrammed in Figure 4-A and 4-B, respectively. The VTA is a site of massive convergence of motivational information from many limbic and MOC network structures, including the MOC and NASshell (Oades & Halliday 1987). Both the NAS and MOC provide a converging point-to-point activation of VTA DA neurons which, in turn, project widely to facilitate processes integrated within MOC network structures (Kalivas et al. 1993; Oades & Halliday 1987; Phillipson & Griffiths 1985).
As outlined in Figure 4-C, behavioral facilitation involves various patterns of VTA DA innervation. First, reciprocal innervation between VTA DA neurons and the NASshell (Phillipson & Griffiths 1985) facilitates incentive motivation and, in collaboration with the NAScore, initiation of locomotion, as reviewed above. Second, VTA DA efferents to the VPm, which modulate VP cell firing rates (Napier 1992), may facilitate the intiation of appetitive motor activity (Klitenick et al. 1992), as well as the backprojection of information via VPm-VTA efferents, thus promoting temporal maintenance of an incentive motivational state within the motive circuit.
Third, there is dense VTA DA innervation of the basolateral and central amygdaloid nuclei (Oades & Halliday 1987), both of which innervate the NASshell (Kelley, Domesick & Nauta 1982). DA effects in the amygdala are complex due to the different functions of the various amygdala nuclei, other routes by which the amygdala can influence the NAS (e.g., via efferents to the MOC and VTA), and to the influence of the amygdala itself on DA transmission in the NAS (Aggleton 1992; Kalivas et al. 1993). Kalivas et al. (1993) proposed that VTA DA efferents to the amygdala facilitate the flow of motivational information from the amygdala to the NASshell, VP, and the VTA itself. VTA DA projections to the central and medial nuclei of the amygdala may be particularly relevant to facilitation of emotional expression, since these nuclei serve as important output centers of the amygdala to brainstem and hypothalamic areas involved in activation of vocal, gross motor, facial, hormonal, and autonomic components of emotional behavior (Aggleton 1992; Depue & Spoont 1986; Kalivas et al. 1993; Pert et al. 1992; Spoont 1992).
Finally, incentive motivation is associated in humans with both positive emotional feelings such as elation and euphoria, and motivational feelings of desire, wanting, craving, potency, and self-efficacy. Robinson and Berridge (1993) argued that motivational feelings are related most directly to the process of attributing incentive salience to stimuli, as discussed above. Both sets of subjective experiences may be facilitated by VTA DA projections to the NASshell and amygdala in order to generate a broader and more enduring state that encourages engagement with the environment. In humans, DA-activating psychostimulant drugs induce both sets of feelings (Koob et al. 1993; Stewart et al. 1984). Also, neuroimaging studies of cocaine addicts found that, during acute administration, the intensity of a subject's subjective euphoria increased in a dose-dependent manner in proportion to cocaine binding to the DA uptake transporter (and hence DA levels) in the striatum (Volkow et al. 1997). Moreover, cocaine-induced activity in the NAS was linked equally strongly (if not more strongly) to motivational feelings of desire, wanting, and craving, as to the emotional experience of euphoric rush (Breitner, Rosen, & Hyman 1997).
The emotional and motivational feelings associated with DA facilitation of incentive motivation raises the possibility that abnormal DA transmission underlies certain forms of affective disorders (Willner & Scheel-Kruger 1991; Wise & Bozarth 1987). We have considered both qualitative and quantitative alterations in DA-induced behavioral facilitation as both causal and moderating factors in bipolar, unipolar, and seasonal affective conditions (Depue 1995; Depue, Arbisi, Spoont, & Leon 1989, 1990; Depue & Iacono 1989; Depue, Krauss, & Spoont 1987; Depue & Zald 1993). Space does not permit adequate treatment of this literature; hence, readers are referred to these references.
3.7 DA Reactivity to Aversive Stimuli
Although the role of MOC network structures in positive incentive motivation and behavioral facilitation has been our focus, these structures do not function exclusively in a hedonically pleasurable context, just as incentive motivation itself may be appetitive or aversive. The basolateral and extended amygdala are involved in associative processes related to negative reinforcement and punishment, as well as the expression of negative emotions of fear or anxiety, and of aversive behaviors such as defensive or affective aggression (Aggleton 1992; LeDoux 1992, 1996; LeDoux et al. 1990). Specific MOC 13 neurons respond to aversive and nonrewarding stimuli (Thorpe et al. 1983), while the hippocampus may play a role in conveying information concerning unexpected and aversive behavioral outcomes to the NAS (Gray et al. 1991). Also, stressors or their conditioned cues that are not uncontrollable and enduring can enhance behaviors typically associated with incentive motivation, such as novelty- and stimulant-induced locomotor activity, self-administration of stimulants, the reinstatement of stimulant self-administration after extinction, and VTA-NAS DA transmission itself (Abercrombie, Keefe, DiFrischia & Zigmond 1989; Anisman, Zalcman & Zacharko 1993; Herman, Guillonneau, Dantzer, Scatton, Semerdjian-Rouquier & Le Moal 1982; Mantz, Thierry & Glowinski 1989; Piazza & Le Moal 1996; Roth, Tam, Ida, Yang & Deutch 1988; Young, Joseph & Gray 1993). The capacity of both stressors and incentive stimuli to enhance NAS DA activity may be due to one or more of the following factors:
3.7.1 Anatomical heterogeneity within the VTA and NAS raises the possibility that they may integrate several distinct behavioral functions, not simply those associated with positive incentive motivation. For example, the NAS is composed of three major areas (shell, core, and rostral pole) that have different patterns of histochemistry, cytoarchitecture, and extrastriatal connectivity (Wright et al. 1996; Zahm & Heimer 1993). The NASshell alone has different zones (Wright & Groenewegen 1995), projects to the VTA, substantia nigra, and periacquiductal gray (Berendse, Groenewegen, & Lohman 1992), and can be divided into at least three subterritories that may have different functional affiliations (Wright et al. 1996): rostral, ventral caudomedial (which has been the focus of our discussion), and dorsal caudomedial, also referred to as the "septal" pole or "cone" (Deutch et al. 1993; Heimer et al. 1993; Zahm & Brog 1992). Similarly, VTA cell groups are heterogeneous in structure, projection targets, and stimulus reactivity (Deutch et al. 1993; Oades & Halliday, 1987). Although most VTA DA neurons respond preferentially to unconditioned and conditioned incentive stimuli, those responding to unconditioned and conditioned aversive stimuli and anxiogenic agents appear to be localized more in the caudal midline aspects of the VTA; project mainly to the ventromedial prefrontal cortex (infralimbic cortex in the rat) rather than the NAS or other cortical areas (e.g., cingulate, piriform, and entorhinal); and specifically innervate the deep layers of infralimbic cortex (Anisman et al. 1993; Bannon, Wolf & Roth 1983; Deutch & Roth 1990; Deutch et al. 1991; 1993; Roth et al. 1988; Young et al. 1992; Zacharko & Anisman 1991). Also, the threshold for stress-induced DA reactivity is not homogeneous across or within structures: it is lowest of all regions in infralimbic cortex, while, in the NAS, it is lowest in the cone region, followed by other areas of the shell, and finally by the core (Deutch & Cameron 1992). Because most VTA DA neurons projecting to NAS regions do not appear to be directly responsive to aversive stimuli (Mirenowicz & Schultz 1996), the increased DA utilization in the NAS may result from at least two sources. First, VTA DA innervation of efferents from infralimbic regions to the NAS, and perhaps from the amygdala to the NAS, may transynaptically regulate NAS DA release (Barbieto et al. 1990; Lindefors 1993); and second, neurons in infralimbic, limbic, and autonomic regions that register aversive stimuli may activate specific DA neurons at the level of the VTA, which then enhance DA transmission in selected NAS terminal fields.
Anatomical and connectional heterogeneity in brain regions may be associated with integrative activities of separate parallel-but-interacting circuits (Joel & Weiner 1994). For instance, basolateral amygdala subregions project to specific compartments of the NASshell and NAScore, suggesting that these subregions differentially influence particular NAS outputs subserving separate functions (Wright et al. 1996). Wright et al. (1996) suggested that the accessory basal amygdala nuclei project via the NAScore, substantia nigra (pars reticulata), and medial thalamus to the prelimbic cortex, whose projections reach autonomic centers in brainstem and spinal cord. Similarly, the infralimbic cortex and the cone of the NASshell have dense reciprocal connections with areas linked to autonomic functions (Brog et al. 1993; Deutch & Cameron 1992; Goldman-Rakic 1987; Thorpe et al. 1983; Zahm & Brog 1992), and have the lowest thresholds for stress-induced DA release from distinct VTA DA afferents (Deutch et al. 1993). Anxiogenic agents activate, while anxiolytics prevent, stressor-induced increases in DA synthesis and utilization in the infralimbic cortex but not the NAS (Anisman et al. 1993; Knorr, Deutch & Roth 1989; Roth et al. 1988). These various findings suggest that DA may facilitate the integration of autonomic arousal within a VTA DA-infralimbic-NAScone circuit informed by basolateral amygdala input. Such a circuit may operate in parallel to, but interact with (Deutch et al. 1993; Joel & Weiner 1994), other cortico-striatal circuits, such as the MOC 13 network. In this way, alterations of DA transmission in the NAS induced by different stimulus contexts (e.g., stressful vs rewarding) may arise from activation of separable but overlapping neurobiological networks.
3.7.2 Goal-directed behavior is often required to adapt to stressors, such as in incentive-motivated avoidance (approach to the reward of safety) or affective aggression aimed at removing an object blocking acquisition of reward (Anisman et al. 1993; Depue & Iacono 1989; Gray 1973). Moreover, mesocortical DA appears to facilitate higher-order cognitive processes that guide behavior through both rewarding and aversive environments (Luciana, Depue, Arbisi, & Leon 1992; Luciana & Collins 1997; Luciana, Collins & Depue in press). Thus, joint activation of VTA-NAS DA and VTA-prefrontal DA projections could be required in many circumstances associated with stress.
When no successful adaptive behavior is possible, as in uncontrollable stress, the resulting behavioral sequence of preparation for, then withdrawal from, goal-directed action has been associated with a pattern of NAS DA transmission that is distinguishable from that elicited by psychostimulants (Cabib & Puglisi-Allegra 1996). Although results may vary across brain regions, inbred strains, and types of stressor (Anisman et al. 1993), stress-induced extracellular DA in the NAS follows a time-dependent biphasic pattern of a short-lasting increase that typically endures less than five days of repeated stress (Cabib & Puglisi-Allegra 1994, 1996; Imperato, Cabib & Puglisi-Allegra 1993; Rouge-Pont et al. 1993), followed by a subsequent decrease to sub-basal levels that lasts as long as the stressful circumstances persist (Cabib & Puglisi-Allegra 1994; Pothos, Creese & Hoebel 1995; Rossetti, Lai, Hmadan & Gessa 1993). Approximately 20 minutes after termination of the stressor, DA release returns to levels found during the initial exposure to the stressor, indicating that the decrease in DA release is inhibited actively when responding is not adaptive (Anisman et al. 1993).
3.7.3 VTA-NAS DA projections may have an over-arching role of facilitating heterosynaptic plasticity, thereby strengthening the connections of all salient incentive stimuli, both positive and negative, in the NAS (Bindra 1978; Horvitz et al. 1997; Puglisi-Allegra & Cabib 1990; Robinson & Berridge 1993). When integrated with the discussion in 3.7.1 above, this possibility is consistent with our proposal: DA facilitation of connections of positive and aversive stimulus contexts in the NAS may occur within separable VTA-NAS circuitries that are associated with different motivational-behavioral patterns.
3.7.4 Finally, stress-induced enhancement of NAS DA transmission may
facilitate a positive emotional state to diminish the aversive effects
of stress, thereby serving a protective function under prolonged
stressful conditions (Anisman et al. 1993; Piazza & Le Moal 1996;
Sapolsky 1992).
4.1. Genotype-Driven Processes
Genotype-driven processes operate most extensively prenatally, and influence the basic structure and function of neuron populations (Greenough & Black 1992). Much evidence relating DA to behavioral expression relies on the use of inbred strains, which provide a well-defined and stable genotype for analysis (Crabbe, Belknap & Buck 1994; Plomin, McClearn, Gora-Maslak & Neiderhiser 1991). One problem with this strategy is that behavioral differences between strains of disparate origins could reflect many genetic and neurochemical differences between strains, and cosegregation of traits could be due to the occurrence of genetic differences at the same or different loci (Phillips 1997; Robinson 1988). These complexities are increased with behavioral traits, which tend to be polygenic in nature (Bouchard, 1994; Plomin 1990), because behavioral contrasts between strains may reflect disparate components of polygenic complexes (Phillips 1997). For instance, C57 and DBA mice are among the most studied inbred strains in the behavioral pharmacology of DA, and they differ in several parameters of the DA system that relate directly to behavioral differences (Puglisi-Allegra & Cabib 1997). These strains also exhibit several qualitatively different behavior patterns that rely on separate DA networks (e.g., mesoaccumbens vs nigrostriatal) and on different modes of inheritance. Therefore, we discuss behavioral differences that rely on the VTA-NAS DA pathway in an effort to focus on genetic influences on DA facilitation of incentive motivation.
An example of genotype-driven processes is variation in the number of DA neurons produced during prenatal development. Inbred mouse strains with variation in the number of neurons in the VTA DA cell group show marked differences in behaviors dependent on DA transmission in the VTA-NAS pathway, including levels of spontaneous exploratory activity and DA agonist-induced locomotor activity (Fink & Reis 1981; Oades 1985; Ross, Judd, Pickel, Joh & Reis 1976; Segal & Kuczenski 1987; Shuster, Yu & Bates 1977; Sved, Baker & Reis 1984; 1985). That this increased behavioral facilitation in high- vs low-DA neuron strains is due to DA transmission is suggested by their greater density of DA terminals in target fields, greater synthesis and release of DA, greater DA agonist-induced inhibition of prolactin secretion, and, importantly in terms of incentive motivation, increased DA content in the NAS.
There is a similar relation between behavior and DA transmission in C57BL/6 (C57) and DBA/2 (DBA) inbred mouse strains (Cabib & Puglisi-Allegra 1996; Phillips 1997; Puglisi-Allegra & Cabib 1997). C57 mice show greater novelty-induced locomotor activity than DBA mice (Anisman & Cygan 1975; Anisman, Wahlsteing & Kokkinidis 1975; Wenger 1979), which is particularly relevant because novelty-induced locomotion is strongly modulated by the number of DA neurons in the VTA region (Fink & Reis 1981), and by natural and stimulant-induced variation in DA transmission (Fink & Smith 1980; Joyce, Stinus & Iversen 1983; Kelley, Seviour & Iversen 1975; Koob, Stinus & Le Moal 1981). Moreover, novel conditions have been found to enhance DA transmission in the NAS (Piazza, Rouge-Pont, Deminiere, Kharoubi, Le Moal & Simon 1991). Not surprisingly, then, C57 mice exhibit a shift to the left of the dose-effect curve of amphetamine on locomotor activity relative to DBA mice (Cabib 1993; Phillips, Dickinson & Burkhart-Kasch 1994; Stevens, Mikley & McDermott 1986; Zocchi, Orsini, Cabib & Puglisi-Allegra 1996). C57 mice are also characterized by a greater propensity to acquire self-administration of psychostimulants than the DBA strain, suggesting an enhanced incentive motivational effect in C57 mice (Belknap & O'Toole 1991; Belknap, Crabbe, Riggan & O'Toole 1993; Carney, Landrum, Cheng & Seale 1991; Crabbe et al. 1994).
The increased effects of psychostimulants in C57 mice are associated with several indicators of enhanced DA transmission in the VTA-NAS pathway. Enhanced amphetamine-induced locomotor effects in C57 mice were accompanied by increased release of DA in the NAS compared to DBA mice (Zocchi et al. 1996). Variation in NAS DA release may be the result of strain-dependent differences in DA D2, but not D1, receptor densities. Increased density of D2 autoreceptors located on VTA neurons, and lower D2 postsynaptic receptors in the NAS, were observed in DBA relative to C57 mice (Erwin, Womer, Campbell & Jones 1993; Kanes, Hitzeman & Hitzeman 1993; Ng, O'Dowd & George 1994; Puglisi-Allegra & Cabib 1997; Puglisi-Allegra, Cabib, Calza & Giardino 1994). Activation of D2 autoreceptors inhibits impluse flow, synthesis, and release rates of DA neurons (White & Wang 1984), and D2 autoreceptors have higher affinity relative to postsynatic DA receptors for DA and DA agonists (Bannon, Grace, Bunney & Roth 1980; Skirboll, Grace & Bunney 1978). Therefore, low-dose DA agonists activate D2 autoreceptors, thereby inhibiting DA transmission, and decrease the behavioral facilitation that accompanies postsynaptic DA activation (Depue, Luciana, Arbisi, Collins & Leon 1994). As would be predicted from their higher D2 autoreceptor: D2 postsynaptic receptor density ratio, DBA compared to C57 mice have shown data indicative of reduced DA synthesis that is largely independent of DA release (Cabib & Puglisi-Allegra 1991; Kuczenski & Segal 1989; Zetterstrom, Sharp, Collin & Ungerstedt 1988; Zocchi et al. 1996), greater inhibitory effects of low-dose DA agonists on mesoaccumbens DA metabolism and on locomotor activity (Cabib & Puglisi-Allegra 1991; Zocchi et al. 1996), and weaker effects of higher DA-agonist doses on locomotor activation. Finally, the DA differences between these strains may relate to the finding that DBA mice are more vulnerable to loss of incentive motivation (anhedonia) induced by uncontrollable shock, as indexed by a marked and persistent reduction of intracranial self-stimulation in the NAS and anteromedial prefrontal cortex (Zacharko, Gilmore, MacNeil, Kasian & Anisman 1990; Zacharko, Lalonde, Kasian & Anisman 1987).
A similar pattern of associations between behavioral and DA indicators was demonstrated in two inbred rat strains - Lewis and Fisher 344. Lewis rats exhibit increased novelty- (Camp, Browman & Robinson 1994) and stimulant-induced (Camp et al. 1994; George & Goldberg 1988; George, Porrino, Ritz & Goldberg 1991) locomotor activity, a greater propensity to acquire self-administration of a variety of psychostimulants as well as a conditioned place preference to cocaine and morphine (George 1990; Suzuki, Otani, Koike & Misawa 1988; Suzuki, George & Meisch 1988, 1992), and a shift to the left in the dose-effect curve of methamphetamine on locomotor activity (Camp et al. 1994). No Lewis-Fischer strain-dependent differences in basal DA concentrations in the NAS (Camp et al. 1994) or in D1 or D2 receptor binding or function (George et al. 1991; Luedtke, Artymyshyn, Monks & Molinoff 1992) were identified. Lewis compared to Fisher rats did show larger and more prolonged elevations of extracellular concentrations of DA in the NAS in response to acute systemic injection of DA agonists (Camp et al. 1994; Chen, Paredes, Lowinson & Gardner 1991; but see conflicting results where absolute rather than baseline-corrected DA elevation values were used: Strecker, Eberle & Ashby 1993; Terwilliger et al. 1991). Also, there is evidence indicating higher rates of DA synthesis and postsynaptic D1 receptor activation in Lewis vs Fisher rats (Beitner-Johnson, Guitart & Nestler 1991, 1992).
Thus, several inbred mouse and rat strains exhibit consistent relations between greater VTA DA neuron number and/or heightened DA transmission in the VTA-NAS DA pathway and enhanced incentive-motivated behavior patterns, such as novelty- and stimulant-induced locomotor activity and an increased propensity to acquire self-administration of stimulants. This suggests that influences from genetic variation in VTA-NAS DA projections are expressed in terms of significant individual differences in the threshold to elicit incentive motivation.
4.2. Experience-Expectant Processes
Experience-expectant processes involve widespread cortical synapse overproduction during sensitive periods in brain development (Greenough & Black 1992; Rakic, Bourgeois, Eckenhoff, Zecevic & Goldman-Rakic 1986). Following overproduction, excess cortical synapses are "pruned back" in response to environmental stimulation. The basic implication of experience-expectant processes for the development of individual differences is that the degree of stimulation-rich environment will be encoded in the number of functional synaptic connections within neural pathways. Moreover, during expectant periods, individual differences in both genotype-driven processes (e.g., VTA DA neuron number) and environmental experience (e.g., time spent exploring novel environments) would be expected to collaborate. The outcomes of such periods, therefore, might establish different trajectories in the functional development of the VTA DA system across individuals, and thus partially specify eventual trait levels of behavioral facilitation. It is unknown whether experience-expectant processes are a significant source of individual differences in DA transmission, although the effects of drug-induced DA activation on behavior during periods of rapid developmental change can be persistent (Feigenbaum & Yanai 1984; Middaugh & Zemp 1985; Spear & Brake 1983; Spear, Shalaby & Brick 1980). An initial task is to identify sensitive periods in the postnatal development of the VTA DA system, e.g., as marked behaviorally around one year of age in humans by a relatively abrupt increase in locomotor exploration of novel environments.
4.3. Experience-Dependent Processes
Experience-dependent processes encode experience unique to the individual through interactions of neurotransmitter systems that modulate dendritic outgrowth, synaptogenesis, and synaptic regression (Colman, Nabekura & Lichtman 1997; Magee & Johnston 1997; Mattson 1988). Through these mechanisms, neurotransmitter activity may regulate synaptic connectivity within the distributed structures of a particular neural network. For example, the activity of VTA DA neurons may influence synaptic relations within pathways of the MOC network. Indeed, VTA DA release in terminal regions facilitates dendritic branching in the NAS, hippocampus, and neocortex in rats (Lindefors 1993; Shankaranarayana-Rao, Desirajo & Raju 1993). Because most DA synaptogenesis occurs postnatally and continues into adulthood (Le Moal & Simon 1991), experience-dependent effects may be an important ontogenetic mechanism in the formation, and even stability, of individual differences in DA system reactivity. In that sense, experience-dependent processes are central to understanding personality as a dynamic developmental construct that involves the collaboration of genetic and environmental influences across the lifespan.
Behavioral sensitization is a form of experience-dependent heterosynaptic plasticity that involves DA neurotransmission in both the NAS and VTA (Browman et al. 1996; Groves & Thompson 1970; Kalivas 1995; Koob & Le Moal 1997; Robinson & Becker 1986; Robinson & Berridge 1993; Robinson et al. 1988; Stewart 1992). It is produced by intermittent noncontingent administration of a variety of psychostimulants or stressors, and is demonstrated by a progressive and enduring enhancement of behavior elicited by a noncontingent psychostimulant test challenge administered days to weeks after the initial exposure phase (Badiani et al. 1995a,b,c; Kalivas 1995; Kalivas & Stewart 1991; Prasad et al. 1995; Robinson & Becker 1986; Sorg et al. 1994; Stewart 1992). Behavioral sensitization can also be induced through repeated self-administration of cocaine (Hooks et al. 1994), may be expressed by use of natural incentives (Mitchell & Gratton 1992; Mitchell & Stewart 1990), and repeated administration of stress or psychostimulants can enhance the acquisition of amphetamine and cocaine self-administration (Horger et al. 1990, 1992; Piazza et al. 1989, 1990; Piazza & Le Moal 1996; Woolverton, Cervo & Johanson 1984). It is likely, therefore, that enhanced incentive motivation is central to behavioral sensitization (Koob & Le Moal 1997; Robinson & Berridge 1993). We focus on behavioral sensitization, because it serves as a starting point for understanding experience-dependent variation in DA facilitation of incentive motivation within the MOC network and, theoretically, in the development of extraversion trait levels.
Behavioral sensitization encompasses two temporally and spatially distinct occurrences of heterosynaptic plasticity. The development of behavioral sensitization involves an early sequence of molecular and cellular events within the VTA region, whereas its enduring expression is associated with subsequent changes in the release of and postsynaptic response to neurotransmitters in the NAS (Kalivas 1995; Kalivas & Stewart 1991; Miserendino & Nestler 1995; Paulson & Robinson 1991; Robinson & Becker 1986; Robinson et al. 1988). Although sensitization can develop in a context-independent manner as a nonassociative process (Anagnostaras & Robinson 1996; Castaneda et al. 1988; Henry & White 1991; Vezina & Stewart 1990), the expression of behavioral sensitization is largely context-specific (Anagnostaras & Robinson 1996; Bell & Kalivas 1996; Stewart 1992). That is, the behavioral expression of an existing sensitized neural substrate is dependent on the similarity of the context extant during the development of sensitization and the context of the subsequent test challenge environment. Anagnostaras and Robinson (1996) argued persuasively that context acts more as an occasion-setter for behavior than as an excitatory or inhibitory conditioned stimulus, and thereby determines whether sensitization is expressed at any particular time or place. As occasion-setter, context modulates (facilitates or inhibits) the pharmacological elicitation of a sensitized unconditioned response. Thus, expression of a sensitized behavioral response appears to involve the interaction of converging efferents representing salient context and sensitized neural processes (Post et al. 1992; Wolf et al. 1995).
4.3.1 HETEROSYNAPTIC PLASTICITY IN THE NAS AND VTA
Although enhancing NAS DA transmission is not sufficient to establish behavioral sensitization, its expression is temporally associated with a psychostimulant-, mu-opioid-, or stress-induced enduring increase in DA release, particularly in the NASshell (Kalivas 1995; Kalivas & Duffy 1990, 1993a; Kalivas & Stewart 1991; Paulson & Robinson 1991; Pierce & Kalivas 1995; Robinson & Becker 1986; Sorg et al. 1994), where D1 rather than D2 receptors appear to mediate these effects (Kalivas 1995; Kalivas & Stewart 1991; Martin-Iverson & Burger 1995; Miserendino & Nestler 1995; Nestler & Aghajanian 1997; Pierce & Kalivas 1995). A glutamate-DA interaction is an important dynamic in the expression of behavioral sensitization in the NAS. Glutamate increases the release of DA in the NAS (Kalivas 1995; Kalivas & Stewart 1991), and motor activity elicited by injection of either DA or glutamate agonists into the NAS is diminished by coadministration of antagonists to the other neurotransmitter (Bell & Kalivas 1996; Kalivas 1995; Karler et al. 1991, 1994; Pierce et al. 1995, 1996). NAS neurons also show enhanced responsiveness to glutamate in sensitized states that may be related to glutamate receptor adaptations observed in the NAS (Lu et al. 1997; Nestler & Aghajanian 1997; Pierce et al. 1996; Zhang et al. 1997). Lesions of the glutamatergic efferents from prefrontal cortex, amygdala, and hippocampus (representing contextual inputs, see Figure 5) to the NAS prevent a sensitized behavioral response (Dahlin et al. 1994; Kalivas 1995; Kalivas & Stewart 1991; Pert et al. 1992; Yoshikawa et al. 1991), suggesting that these efferents serve as contextual occasion-setters.
The manner in which DA facilitates heterosynaptic plasticity in interaction with glutamate in the NAS was recently modeled. The effect of DA release on dendritic spines of NAS neurons is proposed to be dependent on the strength of glutamate-induced activity of the NAS neuron arising from cortical and limbic contextual inputs (Houk et al. 1995; Wickens et al. 1995). As shown at the top of Figure 7, these inputs vary naturally in strength as a function of their relation to the salient incentive context. In the middle of the figure, DA release causes long-term depression of weakly-afferented, low activity NAS neurons, whereas it simultaneously facilitates strongly-afferented, high activity NAS neurons, which are in the minority during an episode of environmental stimulation (Chiodo & Berger 1986; Houk et al. 1995; Schultz et al. 1995b; Wickens et al. 1995). Thus, the effect of DA release on NAS neurons is to increase the contrast gradient between weak and strong glutamatergic inputs in relation to the salient incentive context. With repeated strong glutamatergic and DA efferent input to NAS neurons (bottom of Figure 7), DA release increases this contrast gradient via induction of long-term potentiation (Begg et al. 1993; Wickens et al. 1995). Because the learning capabilities of the isolated striatum are limited, in this way DA plays an important role in selective strengthening of glutamatergic efferents to the NAS, thereby enhancing the association of salient contexts (conveyed by corticolimbic efferents) with previously successful responses (Schultz et al. 1997).
  Progressive, differential effects of dopamine release on weak (depressing) and strong (facilitating) cortical and limbic inputs to NAS spiny neurons. In the bottom of the figure, the salient inputs to the NAS have been enduringly strengthened by dopamine release via a process thought to be similar to long-term potentiation. From Schultz et al. 1995b.
Heterosynaptic plasticity in the development of behavioral sensitization occurs in part through the interaction of DA and glutamate in the VTA region. Although increased firing of VTA DA neurons, in itself, is not a prerequisite for the development of behavioral sensitization, enhanced VTA somatodendritic DA release onto D1 (but not D2) receptors is a common factor in such development (Kalivas 1995; Kalivas & Stewart 1991; Pierce et al. 1996). D1 receptors are not expressed on VTA neurons (Mansour et al. 1992), but are found in large quantity in the ventral midbrain mainly on terminals of forebrain efferents to VTA cells. Thus, VTA somatodendritic DA release appears to activate glutamate release via D1 receptors located on glutamatergic forebrain efferents to VTA neurons (Carlezon et 1997; Criswell et al. 1990; Kalivas 1995; Kalivas & Alesdatter 1993; Kalivas & Duffy 1995; Kalivas & Stewart 1991; Karler et al. 1989; Nestler & Aghajanian 1997; Pierce et al. 1996; Zhang et al. 1997).
A proposed sequence of events that induce heterosynaptic plasticity in the VTA and NAS has been outlined (Kalivas 1995; Koob & Le Moal 1997; Nestler & Aghajanian 1997; Piazza & Le Moal 1996; Pierce et al. 1996; Sorg et al. 1997). Repeated administration of psychostimulants or stress produces increased VTA somatodendritic DA release, which results in D1-mediated enhanced glutamatergic release from prefrontal, amygdala, hippocampal, and other forebrain efferents to VTA DA neurons. Stimulation of glutamate receptors on VTA DA soma and/or dendrites further increases somatodendritic DA release (Kalivas 1995; Nestler & Aghajanian 1997) which, reciprocally, strengthens the heterosynaptic connections between glutamate efferents conveying contextual information and VTA DA neurons (Johnston 1997; Kalivas 1995; Murphy & Glanzman 1997; Nestler & Aghajanian 1997). Prefrontal glutamatergic efferents to VTA DA neurons may be particularly influential in this sequence. Although prefrontal glutamatergic efferents to the NAS can influence NAS DA release directly, the primary pathway for prefrontal regulation of NAS DA release is via projections directly to the VTA (Taber et al. 1995). Sensitization-induced strengthening of prefrontal regulation of VTA DA neurons could enhance NAS DA release, and hence the expression of behavioral sensitization, in three ways: (a) by inhibition of VTA DA neurons projecting to prefrontal areas, which in turn would disinhibit prefrontal-NAS glutamate efferents that enhance DA release in the NAS (Sorg et al. 1997), and (b) by direct activation of VTA DA neurons projecting to the NAS; when prefrontal input to these neurons is particularly strong, glutamate-mediated burst firing of VTA DA neurons may occur, which is associated with markedly enhanced DA release in the NAS (Gonon 1988; Johnson et al. 1992; Suaud-Chagny et al. 1992).
4.3.2 INDIVIDUAL DIFFERENCES IN DA FUNCTIONING AND BEHAVIORAL SENSITIZATION
A preponderance of studies suggests a strong relation between individual differences in novelty-induced locomotion, other DA-modulated behaviors, and behavioral sensitization, although variation of results exists as a function of type of behavior (e.g., mesoaccumbens- vs nigrostriatally-mediated motor patterns), sensitization criteria (e.g., increased locomotor activity vs a hyperactivity-stereotypy multiphasic pattern), dose level, and subject population (e.g., outbred vs inbred strains) (Deminiere, Piazza, Le Moal & Simon 1989; Hooks et al. 1991a, 1992c; Piazza & Le Moal 1996; Piazza et al. 1989; Robinson 1988). In these studies, subjects (typically rats) are selected on the basis of degree of locomotor reactivity to a novel environment, where high and low responders are defined by a median split in locomotor scores. Across a wide range of doses, high responders exceed low responders in the rate of responding, and in the amount of drug administered, during the acquisition of psychostimulant self-administration (Piazza & Le Moal 1996; Piazza et al. 1989, 1991a), and in levels of intra-VTA self-stimulation (Eisler, Swanny, Justice & Neil 1994). These differences appear to be influenced by genetic variation (Ambrosio, Goldberg & Elmer 1995; Elmer, Pieper, Goldberg & George 1995), and by the number of DA neurons in the VTA region (Fink & Reis 1981). In many studies, pretreatment novelty-induced locomotion is positively correlated across animals with locomotor reactivity to psychostimulants administered systemically (Deroche, Piazza, Le Moal & Simon 1993; Exner & Clark 1993; Hooks, Colvin, Juncos & Justice 1992a; Hooks, Jones, Liem & Justice 1992b; Hooks, Jones, Neill & Justice 1992c; Hooks, Jones, Smith, Neill & Justice 1991a,b; Piazza, Deminiere, Le Moal & Simon 1989; Piazza, Maccari, Deminiere, Le Moal, Mormede & Simon 1991a) or into the NAS or VTA (Hooks, Jones, Hembly & Justice 1993; Hooks & Kalivas 1994; Piazza & Le Moal 1996).
Behavioral differences between high and low responders are related to variation in DA transmission. A direct relation exists between DA utilization in the NAS and level of spontaneous exploratory activity to novelty (Ahlenius, Hillegaart, Thorell, Magnusson & Fowler 1987; Barnes, Costall, Domeney & Naylor 1987; Brose, O'Neill, Boutelle, Anderson & Fillenz 1987). In addition, extracellular concentration and release of DA in the NAS is greater and more prolonged in high vs low responders in both basal levels (Bradberry, Grugen, Berridge & Roth 1991; Hooks et al. 1992a; Piazza et al. 1991b), and and levels induced by novelty (Piazza et al. 1991b), stimulants (Bradberry et al. 1991; Hooks et al. 1991b, 1992a), and stressors (Rouge-Pont et al. 1993). The correlations across aimals between novelty-induced locomotor scores and basal and stress-induced NAS DA concentrations appear to be substantial (0.54, 0.86, respectively; Rouge-Pont et al. 1993). Sensitivity to the postsynaptic effects of DA also appears to be increased in high vs low responders, where the former showed an enhanced locomotor response to intra-NAS infusion of DA, as well as a combination of a 20% increase in D1, but a 50% decrease in D2, receptor binding (Hooks et al. 1994). Furthermore, lower DA concentrations in prefrontal cortex were found in high vs low responders, correlating -0.56 (p<0.01) with locomotor scores across animals (Piazza et al. 1991b). The importance of this last finding is that DA levels in prefrontal cortex are reduced in behaviorally sensitized rats (Kalivas 1995; Sorg et al. 1997), and are inversely related to basal and stress-induced concentrations of DA in the NAS, as well as to locomotor reactivity to, and propensity to self-administration of, psychostimulants (Deutch, Clark & Roth 1990; Louilot et al. 1989; Simon & Le Moal 1988; Schenk, Horger, Peltier & Shelton 1991;Vezina, Blanc, Glowinski & Tassin 1991). Finally, novelty-induced locomotion is positively correlated with basal and stress- and novelty-induced corticosterone secretion, which in turn is related to the amount of drug administered during the acquisition of self-administration of amphetamine and cocaine (Goeders & Guerin 1994; Piazza & Le Moal 1996; Piazza et al. 1991a). Functionally, corticosterone enhances firing of VTA DA neurons projecting to the NAS, sensitivity of D1 and D2 receptors, DA release in the NAS, and DA release to stressors (Piazza et al. 1991a; Piazza & Le Moal 1996).
In the study by Piazza et al. (1989), high responders acquired self-administration of amphetamine, whereas low responders did not, which may reflect the latter group's reduced DA transmission and, hence, lower incentive motivation during opportunities for psychostimulant reward. However, when low responders were provided DA-enhancement via sensitization to amphetamine, subsequent acquisition of self-administration of amphetamine was equivalent to high responders. Similarly, when a high dose of amphetamine was employed, Hooks et al. (1992c) observed robust sensitization in low responders who had failed to sensitize at lower doses. Thus, individual differences in DA functioning, even if influenced by fixed characteristics in DA systems, may be modifiable by strong experiences acting through experience-dependent processes.
The role of DA in both behavioral sensitization and individual differences in novelty-induced locomotion leads to the prediction that high locomotor responders will more readily sensitize to DA-active psychostimulants. At low to moderate doses of stimulants, a correlation between pretreatment novelty-induced locomotion and degree of subsequent sensitization was observed in several studies (Hooks et al. 1991a, 1992b,c; Piazza et al. 1989, 1990). In some cases the relation was substantial (0.84; Hooks et al. 1992c), and may be influenced by genetic variation in DA concentrations in the NAS (Cabib 1993; Camp et al. 1994; Fink & Reis 1981). On the basis of this relation, we propose that the capacity of the VTA-NAS DA pathway for experience-dependent plasticity, indexed by behavioral sensitization, is modulated by stable individual differences in DA transmission in the VTA-NAS pathway, indexed by novelty-induced locomotion. If true, this hypothesis implies that individual differences in VTA-NAS DA pathway transmission modulate the strength of afferent connections carrying the salient incentive context to NAS neurons and, hence, the extent to which that context facilitates approach behavior.
Concordant with this proposal, the inbred strain of C57 mice, which shows enhanced DA transmission, developed robust behavioral sensitization when repeated amphetamine treatments occurred in the same environment in which the test challenge of amphetamine was administered. In other words, strong context-dependent behavioral sensitization was exhibited (Cabib 1993). The inbred strain of DBA mice, which shows lower DA transmission, failed to exhibit significant context-dependent sensitization. When saline was administered in the same drug-paired environment, C57 but not DBA mice exhibited hyperactivity, indicating that the occasion-setting context exerted a much stronger facilitating effect on the locomotor activity of C57 mice even in the absence of stimulant drugs. In contrast, when amphetamine administration was not paired with the test environment (context-independent sensitization), the two strains showed comparable sensitization 6-7 days after withdrawal from amphetamine pretreatment (Robinson 1988). Thus, the generally enhanced DA transmission of C57 mice appears to interact with the plastic process of strengthening the facilitatory influence of salient context on sensitized responding, not with the basic development of behavioral sensitization. Similar findings favoring context-dependent sensitization in a selected line of rats with enhanced responses to novelty have been reported (Ahmed, Stinus, Le Moal & Cador 1993).
4.4 Conclusion
The regulation of neuroarchitecture by DA may be one avenue for collaboration among genotype-driven, experience-expectant, and experience-dependent processes (Collins & Depue 1992). As an illustration, individual differences in the number of VTA DA neurons represent an outcome of genotype-driven processes. This variable markedly influences the sensitivity to incentive stimuli and DA agonists and, thereby, can be thought of as a temperament trait underlying behavioral facilitation and extraversion (Depue in press a, b). If the number of DA neurons is relatively large, an individual will possess the structural capacity to release high levels of DA at terminal sites of VTA projections during experience-expectant sensitive periods. Such an individual would be predisposed to stabilize a large number of synaptic contacts within MOC network structures. Although an enhanced functional outcome in high-DA neuron individuals would not occur if environmental experience were reward-impoverished, findings in animal behavior genetics suggest that an individual with a rich genetic endowment of DA neurons actively explores the environment in search of rewarding stimulation (Fink & Reis 1981; Sved, Baker & Reis 1984; 1985). Thus, the likely (but not inevitable) outcome of the sensitive period would be a strong functional capacity in the VTA DA system to facilitate responses to incentive stimuli.
Experience-dependent processes would likely maintain this capacity, since an enduring predisposition to engage incentive stimuli established during experience-expectant development would entail frequent activation of synapses in the terminal fields of VTA DA projections. The notion that early experience has prolonged effects on VTA DA functional properties is supported by findings that uncontrollable prenatal stress produced permanent alterations in NAS and prefrontal DA transmission in adulthood (Deminiere et al. 1992; Fride & Weinstock 1988). Similarly, persistent changes in DA metabolism and behavior have been observed with the administration of psychostimulants during periods of rapid developmental change (Feigenbaum & Yanai 1984; Middaugh & Zemp 1985; Spear & Brake 1983; Spear et al. 1980).
Thus, early experiential processes may lay the foundation for
trends in positive incentive motivated behavior by moderating
the strength of later experience-dependent processes involving the
functional capacities of the VTA DA projection system (Collins &
Depue 1992). Stable individual differences in VTA DA transmission, for
instance, appear to affect the expression of behavioral sensitization
by modifying the strength of synaptic connections of contextual
efferents in the NAS. Therefore, across the lifespan, extensive
synaptic arborization within MOC network circuitry of an individual
with high VTA DA transmission would consistently enhance responsivity
to incentive stimuli, which would be manifested in a high, stable level
of behavioral facilitation. This provides one means of understanding
the high interindividual stability of psychometric measures of
extraversion over as many as 20 years (Costa & McRae 1994; McGue,
Bacon & Lykken 1993).
5.1 A Psychobiological Threshold Model of Behavioral Facilitation
Models of DA-induced behavioral facilitation often employ a minimum threshold that represents a central nervous system weighting of the external and internal factors that contribute to response facilitation (Stricker & Zigmond 1986; White 1986). The threshold is weighted most strongly by the joint function of two main variables: magnitude of incentive stimulation, and level of DA postsynaptic receptor activation (Blackburn et al. 1989; Cools, 1980; Mogenson et al. 1993; Oades, 1985; Scatton, D'Angio, Driscoll & Serrano 1988; White 1986). The relation between these two variables is represented in Figure 8 as a trade-off function (Grill & Coons 1976; White 1986), where pairs of values (of incentive magnitude and DA activation) specify a diagonal representing the minimum threshold value for response facilitation. Because the two input variables are interactive, independent variation in either one not only modifies the probability of response facilitation, but it also simultaneously modifies the value of the other variable that is required to reach a minimum threshold for facilitation.
The main determinant of facilitatory efficacy of incentive stimuli is the magnitude of reward. Response facilitation in sated animals is strongly related to sucrose or saccharine concentration in water and food (Grill & Coons 1976; Stellar, Brooks & Mills 1979), to the numeric quantity and quality of reward (Koob 1992; Koob et al. 1993; Nishino et al. 1987; Schultz 1986), and to the level of enhancement (vs degradation) of conditioned incentive stimuli (Schultz 1986). Other stimulus-reward variables that influence DA neuronal activity are less well researched, but the availability of reward and effort required to obtain it are important factors (Nishino et al. 1987; Schultz 1986; Tombaugh, Grandmaison & Zito 1982). The magnitude of both unconditioned and conditioned incentive stimuli is strongly associated with the quantity of DA release in the NAS and with a graded increase in the frequency and duration of VTA DA neuronal activity, an activity that is well correlated with behavioral effort and velocity (Nishino et al. 1987). Thus, magnitude of incentive reward is stongly related to the induced level of DA transmission and to the probability of response facilitation (Blackburn et al. 1989; Nishino et al. 1987; Schultz 1986; Schultz et al. 1995b; White 1986).
Findings reviewed above show that state changes in DA transmission in the VTA-NASshell pathway activation influence the threshold for response facilitation. State alterations in DA transmission also modify the salience and response-facilitatory effectiveness of incentive stimuli. Increased DA transmission markedly enhances responding to conditioned reinforcers (Beninger 1983; Blackburn et al. 1989; Robbins 1975; Robbins, Watson, Gaskin & Ennis 1983), an effect that is due selectively to a dose-dependent DA release in the NAS (Le Moal & Simon 1991). Conversely, acute administration of DA receptor antagonists reduces the facilitatory effectiveness of conditioned incentive stimuli at doses that do not decrease subsequent consummatory motor patterns (Blackburn et al. 1989; Koob et al. 1993; Le Moal & Simon 1991), suggesting that facilitation under such conditions is achieved by only strong incentive stimuli.
As discussed in Section 4, the threshold of response facilitation is associated with genetic variation that affects stable levels of VTA DA transmission, as well as with induced long-term or permanent changes, particularly those involving DA release in the NAS, that alter previous threshold values. Sensitization-induced increased NAS DA release was associated with enhancement of the salience of incentive stimuli and of locomotor activity to subsequent DA agonist challenge. Figure 8 illustrates a sensitization effect as a reducion in the threshold for response facilitation across the entire range of effective incentive stimuli, as suggested by Robinson (1988; Robinson & Berridge 1993).
5.2 Implications for Extraversion
This model permits behavioral predictions that have implications for conceptualizing extraversion. A trait dimension of VTA DA postsynaptic receptor activation is represented on the horizontal axis of Figure 8, where two individuals with divergent trait levels are demarcated: A (low trait level) and B (high trait level). First, for any given incentive stimulus, the degree of state DA response will, on average, be larger in individual B vs A. This is the neurobiological equivalent of what Gray (1973) refers to as individual differences in sensitivity to signals of incentive reward, and is our hypothetical basis of variation in behavioral facilitation and extraversion. Because degree of state DA activity affects the salience of incentive stimuli, the subjective emotional and motivational experiences that are naturally elicited by incentive stimuli and that are part of extraversion - elation-euphoria, desire, incentive motivation, sense of potency or self-efficacy - will also be more enhanced in B vs A (Koob 1992; Koob et al. 1993; Stewart et al. 1984).
Second, the difference between individuals A and B in magnitude of subjective experience may contribute to variation in the contemporaneous encoding of a stimulus' incentive intensity or salience. In this regard, DA modulation of the encoding of incentive salience may represent one form of state-dependent learning. Furthermore, variation in contemporaneous salience encoding may affect the incentive salience encoded during subsequent memory consolidation (Robinson & Berridge 1993). Accordingly, individuals A and B may develop differences in their long-term encoding of incentive stimuli, due primarily to consistent differences in the intensity of positive affective representations of these stimuli (Mishkin 1982). Differences in stored affective representations of stimuli could have marked effects on behavior, because central representations may be retrieved via prefrontal cortical projections as a means of motivating behavior when explicit goal cues are not present in the immediate environment (Goldman-Rakic 1987; 1995). Thus, individuals A and B may develop differences in their capacity to facilitate behavior by central incentive representations of abstract or temporally-delayed goals, such as, for example, a college degree four years hence. Put differently, individuals A and B may differ in activation and sustainment of achievement motivation by central representations of delayed rewards, which represents one lower-order trait defining extraversion (see Table 1).
Third, trait differences in DA transmission may have marked effects on the range of effective (i.e., facilitating) incentive stimuli. This is illustrated in Figure 8, where the right vertical axis represents the range of effective incentive stimuli. Increasing trait levels of DA postsynaptic receptor activation (horizontal axis) are associated with an increasing efficacy of weaker incentive stimuli and, thus, with an increasing range of effective stimuli. In Figure 8, individuals A and B are shown to have a narrow (A) vs broad (B) range of effective incentive stimuli, respectively.
Fourth, the broader range of effective incentives for individual B suggests that, on average, B will experience more frequent elicitation of approach behavior, and more pervasive positive emotional and motivational feelings associated with extraversion. This means that the probability, at any point in time, of being in a DA-facilitated state for individual B is higher, on average, than for A. Therefore, when incentive stimuli are encountered, their subjectively evaluated salience will show a stronger positive bias for B than A. Thus, extraversion trait differences reflecting variation in DA transmission may proactively influence the salience evaluation of incentive stimuli, and may not be restricted to reactive motivational and motoric processes of behavioral facilitation (Bindra 1978; Robinson & Berridge 1993).
Fifth, trait differences in both incentive encoding and range of effective incentive stimuli may interact to produce individual variation in the dynamics of behavioral engagement with the environment. The positive relation between state DA transmission and incentive stimulus efficacy suggests that, as an initial incentive stimulus enhances DA release in the NAS, the facilitatory efficacy of subsequently encountered incentive stimuli may be increased proportional to the degree of the initial DA enhancement. Under conditions of strong DA enhancement, perhaps even previously subthreshold incentives may come to facilitate behavior for a period of time. This dynamic process of gradually rising incentive motivation might affect the degree of facilitation of behavior throughout the temporal course of the behavioral engagement (degree of effort, vigor, and vigilance, all of which are affected by DA transmission in the motive circuit; Kalivas et al., 1993), and hence the aggregate incentive salience encoded for the eventual goal. This may relate to the positive relation between DA transmission and resistance to extinction (Le Moal & Simon 1991). In our example, individual A is predicted to exhibit reduced effort and less resistance to extinction relative to B in situations where reward is relatively weak, intermittent, or based on delayed gratification. As the latter "obstacles" to reward increase, individual A is predicted to show reduced perseverance or earlier extintion of reward acquisition behavior (i.e., less enduring behavioral facilitation) than individual B due to less DA reactivity to the incentive stimuli. Perhaps the failure of low novelty-induced locomotion groups to acquire self-administration of amphetamine represents the interactive effects of the above factors (Piazza et al. 1989).
Sixth, variation in DA facilitation is associated with behavioral
flexibility when changes in motor, affective, and cognitive response
patterns are required by environmental circumstances (Oades 1985). DA
lesions (6-OHDA) of the VTA, dorsolateral prefrontal cortex (Brozoski
et al., 1979), and the NAS (Louilot et al. 1987) reduce or completely
abolish spontaneous alternation, reversal, resistance to extinction,
and the number of cognitive strategies used in response to
environmental modifications (Cools, 1980; Le Moal & Simon 1991;
Oades, 1985), while DA agonists produce the opposite effects. When DA
transmission is very low, a problem in exceeding the facilitation
threshold of any response may occur. At abnormally high DA transmission
levels, an extremely high rate of facilitated switching between
response alternatives may occur (as perhaps in mania; Depue &
Iacono 1989), which can evolve into a low variety of responses (e.g.,
stereotypy) as if the currently initiated response is locked on and
other response alternatives cannot enter the circuit (Oades 1985;
Spoont 1992). Thus, returning to our example, individual B vs A is
predicted to manifest more flexibility in changing motor, affective,
and cognitive response strategies, and thus more flexible (or
facilitated) adaptation to environmental contingencies as they
fluctuate over time.
Several personality theorists have suggested that the VTA DA projection system may be associated with human personality traits, but there is a lack of clarity as to which traits are thought to be of greatest relevance (Cloninger et al. 1993; Gray 1987, 1992; Netter, Hennig & Roed 1996; Netter & Rammsayer 1991; Rammsayer, Netter & Vogel 1993; Zuckerman 1991). Zuckerman (1991) suggested that "Dopamine seems to mediate a general behavioral approach system that might be identified with extraversion or sensation seeking, but it could also involve impulsivity or other P(sychoticism) type tendencies" (p. 186). Although most theorists posit a relation of DA to behavioral approach and extraverted-like behavior, Gray, Cloninger, Netter, and Zuckerman have aligned DA's predominant association not directly with extraversion, but rather with aggression and/or the cluster of impulsivity-sensation seeking traits illustrated in Figure 3.
Empirically, the situation is not much clearer, probably because the number of relevant studies is small and the neurobiological methodologies are relatively crude. No significant differences were found between normal introverts and extraverts in urinary levels of DA or of a major DA metabolite in response to two DA antagonists (Rammsayer, Netter & Vogel 1993). The relation of urinary to central estimates of DA functioning, however, is questionable (Depue & Iacono 1989). Additionally, no significant relation of DA agonist- or antagonist-induced prolactin decreases or increases, respectively, were associated with aggression or the Zuckerman sensation seeking scales of Disinhibition, Experience Seeking, and Boredom Susceptibility (Netter, Hennig & Roed 1996).
DA pharmacological manipulations in relation to both extraversion and sensation seeking scales indicated that the relation of DA activity to reaction-time performance is an inverted U-shaped function (Netter & Rammsayer 1991; Rammsayer et al. 1993). Subjects high on these traits showed impaired or improved task performance depending on whether a DA agonist or antagonist, respectively, was applied; the reverse pattern was found in subjects low in these traits. Zuckerman (1984) suggested a similar relationship between catecholamine (including DA) activity and sensation seeking, sociability, and anxiety. Our interpretation is that a positive correlation exists between three variables: DA functioning, extraversion and sensation-seeking trait levels, and position on the inverted U-shaped performance curve. Thus, DA agonism worsens the performance of high DA-high trait subjects by "pushing" them into the upper, descending limb of the performance curve where performance is deteriorating, but improves the performance of low DA-low trait subjects by "pushing" them up the ascending limb of the curve where performance is improving. DA antagonists would have the opposite effects on high and low personality trait subjects, as was found in the above studies.
Recent work raises the possibility that genetic variation in the DA D4 receptor is a source of individual differences in behaviors relevant to extraversion, including addiction to DA-agonists (Comings et al. 1991) and novelty- and reward-seeking (Benjamin et al. 1996; Ebstein et al. 1996). Even here, however, results are not completely clear: while certain genotypes were related to Extraversion, Positive Emotions, Excitement Seeking, and Novelty Seeking, the same genotypes were not related to the impulsivity subscale of Cloninger's Novelty Seeking scale (Benjamin et al. 1996), suggesting a stronger relation with extraversion than impulsivity, per se. Also, on the basis of Cloninger's (1987) prediction that early onset alcoholics are high on Novelty Seeking, and thus should have greater DA reactivity to alcohol (a DA agonist), Heinz et al. (1996) assessed DA agonist-induced growth hormone responses in detoxified, early onset alcoholics, but found no significant association with Cloninger's Novelty Seeking scale.
We assessed the association of individual differences in DA D2 reactivity and extraversion (Depue et al. 1994), as measured by Tellegen's Multidimensional Personality Questionnaire (Tellegen & Waller 1996). Two indices of DA response, inhibition of prolactin secretion and activation of spontaneous eye blinking, served as a within-study replication of a DA-extraversion association, since they are innervated by separate DA projection systems. Several prolactin and blink indices of D2 receptor effects were strongly, significantly, and specifically related to extraversion (e.g., r = 0.75, p<0.003), but not to two other personality factors, i.e., Constraint and Negative Emotionality (Neuroticism) (Depue et al. 1994). In addition, the degree of D2 agonist-activated blink and prolactin values were strongly and significantly related to each other as well as to extraversion, indicating that the effects of D2 activation are similar, and are similarly related to extraversion, across two variables that are influenced by separate DA systems. These findings were replicated using the same methods on a larger sample. The relation of extraversion to D2 agonist-induced prolactin values was 0.60 (p < 0.01), but was not significantly different from zero for other factors [e.g., Constraint (r = 0.05), the Impulsivity subscale of Constraint (r = 0.11), and Negative Emotionality (r = 0.08) (p's > 0.25) (Depue 1995, 1996). In a separate analysis, D2 agonist-induced prolactin was not correlated significantly with Zuckerman's Sensation Seeking Scales of Disinhibition (r = -0.10) and Boredom Susceptibility (r = -0.12), nor with Tellegen's Aggression factor (r = -0.02) or the Buss-Durkee Hostility Inventory (r = -0.22). These nonsignificant associations were also found by others (Netter et al. 1996). D2 agonist-induced prolactin was, however, significantly but moderately correlated with Eysenck's impulsivity scales associated with strong positve affect (Venturesomeness, r = 0.40; Risk Taking, r = 0.33, p's<0.05).
Overall, this set of findings of (a) a high significant relation
between DA indicators and extraversion; (b) near-zero correlations of
DA indicators with Constraint, aggression, and sensation seeking scales
lacking strong positive affect; but (c) a moderate correlation with
impulsivity scales incorporating positive affect supports (i) our
placement of a DA dimension directly in line with the extraversion
dimension, and (ii) an indirect DA influence on impulsivity
traits incorporating positive affect (see Figure 3). Of interest is that
prolactin, reflecting the action of DA in the hypothalamus, was
strongly related to extraversion, whose behaviors reflect the function
of VTA DA cells. DA cell groups, including those in the VTA and
hypothalamus, manifest a common genetic influence on cell number that
is reflected in their functional properties. For instance, DA agonist
effects are correlated across prolactin secretion, exploratory
behavior, and locomotor activity in inbred strains of mice that differ
in both VTA and hypothalamic DA cell number (Fink & Reis 1981;
Oades 1985; Sved et al. 1984; 1985). It is possible, therefore, that
the high heritability of extraversion (Bouchard, 1994; Tellegen et al.
1988) is related to genetic influences on DA cell groups, and that
unmeasured genetic variance in our subjects contributed substantially
to the observed correlations between extraversion and drug response
indices controlled by separate DA projection systems. In any case, the
consistently strong and specific DA-extraversion associations found in
our studies indicate that the emotional-motivational functions of DA
derived from animal research may hold for humans as well.
State or trait variation in the functional properties of biological variables that influence the functioning of MOC network structures could influence DA neurotransmission in the NASshell. For example, genetic variation in retinoic acid and retinoid receptors modifies the expression of D1 and D2 receptors preferentially in the ventral striatum, and influences incentive-related locomotor and cocaine responsivity (Kreczel, Ghyselinck, Samad, Dupe, Kastner, Borrelli & Chambon 1998). Also, DA functioning in the amygdala and ventral prefrontal cortex modulates DA utilization in the NAS, as well as the sensitivity to self-administration of DA agonists (Le Moal & Simon 1991; Piazza et al. 1991b). State (due, for instance, to a history of stressors) and trait differences in the secretion of, or sensitivity to, glucocorticoids significantly modulate DA functioning in the VTA and NAS, and influence incentive-facilitated behaviors (Piazza & Le Moal 1996), such as the amount of stimulants self-administered and the magnitude of behavioral sensitization (but see Badiani, Morano, Akil & Robinson 1995c). Furthermore, both neurotensin and substance P, which influence DA neurotransmission in the NAS (Kalivas et al. 1993) and basal and psychostimulant-induced locomotor activity, differ in the VTA and NAS of high and low locomotor responders to novelty (Hooks, Sorg & Kalivas 1994; Kalivas, Bush & Hanson 1995).
Functional levels of neurotransmitters that provide a strong, relatively tonic inhibitory influence on DA are particularly significant modifying factors because of persistent effects on the threshold of behavioral facilitation. Serotonin is such a factor. It is an inhibitory modulator of a host of DA-facilitated behaviors, including the reinforcing properties of psychostimulants, novelty-induced locomotor activity, the acquisition of self-administration of cocaine, and DA utilization in the NAS (Depue & Spoont 1986; Herve, Simon, Blanc, Le Moal, Glowinski & Tassin 1981; Kelland & Chiodo 1996; Loh & Roberts 1990; Lucki 1992; Piazza et al. 1991b; Ritz, Lamb, Goldeberg & Kuhar 1987; Spoont 1992). Moreover, low trait levels of serotonin activity in animals and humans result in exaggerated expression of, or reduced threshold for, a broad range of DA-facilitated behaviors (Coccaro & Siever 1992; Depue & Spoont 1986; Spoont, 1992). This modulatory influence arises in large part from the dense dorsal raphe efferents to the VTA and NASshell, connections that are known to modulate DA activity (Deutch et al., 1993; Kalivas et al. 1993; Schultz 1986). A proposed serotonin influence on the threshold of behavioral facilitation is illustrated in Figure 8. For similar reasons, functional levels of GABA activity may also influence the threshold of behavioral facilitation. Because of its structural similarity to GABA, baclofen may have a GABA-mimetic action as an inhibitor of substance P, a neuromodulator having excitatory effects on VTA DA neurons (Kalivas et al. 1993; Le Moal & Simon 1991). Baclofen withdrawal is associated with supersensitivity of postsynaptic receptors of the mesolimbic DA system and with extreme facilitation of behavior (i.e., mania; Depue & Iacono 1989).
Finally, the mitochondrial enzyme monoamine oxidase (MAO) is responsible for presynaptic degradation of biogenic amines and, therefore, modifies DA functioning, particularly human MAO-B that has DA as its major substrate (Mitra, Mohanakumar & Ganguly 1994). MAO activity is stable over time and is under genetic control (Haier, Buchsbaum, Murphy, Gottesman & Coursey 1980). Pharmacological inhibition of MAO in bipolar affective disorder is associated with the onset of extremely facilitated affective behavior (i.e., mania), which is often interpreted as being due to increased DA neurotransmission (Depue & Iacono 1989). From a trait perspective, reduced MAO acitivity levels in the general population are associated with an increased probability of impulsivity, sensation-seeking behavior, and affective lability (Haier et al. 1980; Zuckerman 1991). Thus, in the general population, MAO-B activity appears to be inversely related to the magnitude of DA-induced facilitation of behavior. Although studies of the relation of extraversion and MAO (often unspecified as to type) have been inconsistent (Zuckerman 1991), we found MAO-B activity to be inversely related to Tellegen's measure of extraversion (-.50, p<.01) in the general population, suggesting that DA functioning and MAO-B activity interact to influence levels of extraversion (Depue 1995, 1996).
Despite the complexity inherent in the neurobiology of personality,
there is good reason to start with one neurotransmitter, explore the
details of its relation to personality traits, and gradually build
complexity by adding additional factors one at a time. This is
particularly true when biogenic amines (DA, serotonin, norepinephrine)
are involved. Amines are phylogenetically old, and modulate brain
structures associated with behavioral processes relevant to
personality, including emotions, motivation, motor propensity, and
cognition (Luciana & Collins 1996; Luciana et al. 1992, in press).
Moreover, none of the amines appear to serve primarily a mediating role
in the central nervous system, as we have seen for DA. Rather, each may
have a specific modulatory role in influencing neural processes (Depue
in press; Depue et al. 1994; Depue & Spoont 1986; LeMoal &
Simon 1991; Mesulam 1990; Oades 1985; Spoont 1992). This fact, taken
together with their broad distribution patterns in the brain (Oades
1985; Oades & Halliday 1987; Tork 1990), indicate that variation in
a single amine can have widespread effects on behavior and on the
functioning of multifocal neural networks (Mesulam 1990). Animal
research on the behavioral effects of both DA and serotonin clearly
supports this. Thus, variation in the biogenic amines may provide a
powerful predictor of human behavioral variation, as has been
demonstrated robustly for serotonin functioning (Coccaro & Siever
1991; Depue & Spoont 1986; Spoont 1992). Therefore, single amine
models of behavior may serve as important building blocks for more
complex models of personality traits. If so, LeMoal and Simon's (1991)
suggestion, in their extensive review of DA and behavior, is an
appropriate closing to our discussion: "...we predict that individual
differences in adaptation will be in the near future an important field
of research and that investigations on the dopaminergic network will
provide insights on these psychological typologies (p. 185)."
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| Study | Numbered Trait Abbreviation (in numerical order) | Corresponding Personality Questionnaire Trait b |
|---|---|---|
| Tellegen & Waller 1996 | ||
| WB1 | Tellegen Multidimensional Pers. Q., Well
Being | |
| Dom2 | Tellegen Multidimensional Pers. Q.,
Social Potency | |
| Ach3 | Tellegen Multidimensional Pers. Q.,
Achievement | |
| Affil4 | Tellegen Multidimensional Pers. Q.,
Social Closeness | |
| Ach5 | Personality Research Form,
Achievement | |
| Affil6 | Personality Research Form,
Affiliation | |
| Dom7 | Personality Research Form, Dominance | |
| Persis8 | Personality Research Form,
Endurance | |
| Affil9 | Personality Research Form,
Exhibition | |
| Nurtur10 | Personality Research Form,
Nurturance | |
| Play11 | Personality Research Form, Play | |
| Affil12 | Personality Research Form, Social
Recognition | |
| Succor13 | Personality Research Form,
Succorance | |
| Church 1994 | ||
| Affil14 | Costa & McCrae NEO, E1- Warmth | |
| Affil15 | Costa & McCrae NEO, E2 -
Gregariousness | |
| Dom16 | Costa & McCrae NEO, E3 -
Assertiveness | |
| Act17 | Costa & McCrae NEO, E4 -
Activity | |
| Excit18 | Costa & McCrae NEO, E5 -
Excitement Seeking | |
| PE19 | Costa & McCrae NEO, E6 - Positive
Emotions | |
| Affil20 | Costa & McCrae NEO,
Agreeableness | |
| WB21 | Tellegen Multidimensional Pers. Q., Well
Being | |
| Dom22 | Tellegen Multidimensional Pers. Q.,
Social Potency | |
| Ach23 | Tellegen Multidimensional Pers. Q.,
Achievement | |
| Affil24 | Tellegen Multidimensional Pers. Q.,
Social Closeness |
| Study | Numbered Trait Abbreviationd (in numerical order) | Corresponding Personality Questionnaire Trait e |
|---|---|---|
| Zuckerman et al. 1989 |
||
| Imp1 | Buss-Plomin EASI, Inhibitory
Control |
|
| Ag2 | Buss-Plomin EASI Anger |
|
| P3 | Eysenck Personality
Questionnaire, Psychoticism |
|
| SS4 | Sensation Seeking Scales,
Boredom Susceptibility |
|
| SS5 | Sensation Seeking Scales,
Experience Seeking |
|
| Risk6 | Jackson Personality Inventory,
Risk Taking |
|
| SS7 | Buss-Plomin, EASI Sensation
Seeking |
|
| SS8 | Sensation Seeking Scales,
Disinhibition |
|
| SS9 | Karolinska Scale of
Personality, Monotony Avoidance |
|
| Imp10 | Karolinska Scale of
Personality, Impulsivity |
|
| SS11 | Sensation Seeking Scales,
Thrill-Adventure Seeking |
|
| E12 | Eysenck Personality
Questionnaire, Extraversion |
|
| Soc13 | California Personality
Inventory, Sociability |
|
| Act14 | Buss-Plomin EASI
Activity |
|
| En15 | Jackson Personality Inventory,
Energy Level |
|
| Ag16 | Buss-Durkee Hostility
Inventory |
|
| Ag17 | Personality Research Form,
Aggression |
|
| C18 | Strelau Temperament Inventory,
Restraint |
|
| C19 | Jackson Personality Inventory,
Responsibility |
|
| Conform20 | Jackson Personality
Inventory, Conformity |
|
| Soc21 | California Personality
Inventory, Socialization |
|
| Ag-22 | Karolinska Scale Personaltiy,
Inhibition of Aggression |
|
| Soc-23 | Karolinska Scale of
Personality, Detachment |
|
| Sco24 | Buss-Plomin EASI,
Sociability |
|
| Soc25 | Jackson Personality Inventory,
Social Participation |
|
| Soc26 | Personality Research Form,
Affiliation |
|
| Imp27 | Buss-Plomin EASI, Decision
Time |
|
| Goldberg & Rosolack 1994 |
||
| E28 | Eysenck Personality
Questionnaire, Extraversion (with factors I and III) |
|
| P29 | Esysenck Personality
Questionnaire, Psychoticism (with factors I and III) |
|
| P30 | Eysenck Personality
Questionnaire, Psychoticism (with factors I and II) |
|
| Zuckerman et al. 1993 (four factor solution with entire scales) | ||
| E31 | Costa & McCrae NEO
Extraversion |
|
| E32 | Eysenck Personality
Questionnaire,Extraversion |
|
| Soc33 | Zuckerman-Kuhlman Personality Quest., Sociability | |
| Act34 | Zuckerman-Kuhlman Personality
Quest., Activity |
|
| C35 | Costa & McCrae NEO,
Conscientiousness |
|
| P36 | Eysenck Personality
Questionnaire, Psychoticism |
|
| Imp37 | Zuckerman-Kuhlman Personality
Quest., Impulsive Sensation Seeking |
|
| Ag38 | Zuckerman-Kuhlman Personality
Quest., Aggression |
|
| Agree39 | Costa & McCrae NEO,
Agreeableness |
|
| Zuckerman et al. 1993 (five factor solution | with primary scales included) | |
| Soc40 | Costa & McCrae NEO, E2 -
Gregariousness |
|
| Soc41 | Costa & McCrae NEO, E1 -
Warmth |
|
| Act42 | Costa & McCrae NEO, E4 -
Activity |
|
| SS43 | Costa & McCrae NEO, E5 -
Excitement Seeking |
|
| PE44 | Costa & McCrae NEO, E6 -
Positive Emotions |
|
| Dom45 | Costa & McCrae NEO, E3 -
Assertiveness |
|
| C46 | Costa & McCrae NEO, C4 -
Achievement |
|
| C47 | Costa & McCrae NEO, C5 -
Self-Discipline |
|
| C48 | Costa & McCrae NEO, C6 -
Deliberation |
|
| C49 | Costa & McCrae NEO, C3 -
Dutiful |
|
| C50 | Costa & McCrae NEO, C1 -
Competence |
|
| C51 | Costa & McCrae NEO, C2 -
Order |
|
| Angleitner & Ostendorf 1994f |
||
| Soc52 | Buss-Plomin EASI III,
Sociability I |
|
| E53 | Costa & McCrae NEO,
Extraversion |
|
| C54 | Costa & McCrae NEO,
Conscientiousness |
|
| Imp55 | Buss-Plomin EASI III, Non
Inhibition Control |
|
| Imp56 | Buss-Plomin EASI III, Short
Decision Time |
|
| SS57 | Buss-Plomin EASI III, Sensation
Seeking |
|
| Persis-58 | Buss-Plomin EASI III, Non
Persistence |
|
| Act 59 | Buss-Plomin EASI III,
Activity - Tempo |
|
| Act60 | Buss-Plomin EASI III, Activity
- Vigor |
|
| Panter, Tanaka & Hoyle 1994 |
||
| E61 | Goldberg Surgency |
|
| E62 | Costa & McCrae NEO,
Extraversion |
|
| C63 | Goldberg
Conscientiousness |
|
| C64 | Costa & McCrae NEO,
Conscientiousness |
|
| Church 1994 |
||
| WB65 | Tellegen Multidimension
Personality Q., Well-Being |
|
| Dom66 | Tellegen Multidimensional
Pers. Q., Social Potency |
|
| Soc68 | Costa & McCrae NEO, E1 -
Warmth |
|
| Soc69 | Costa & McCrae NEO, E2 -
Gregariousness |
|
| Dom70 | Costa & McCrae NEO, E3 -
Assertiveness |
|
| Act71 | Costa & McCrae NEO, E4 -
Activity |
|
| SS72 | Costa & McCrae NEO, E5 -
Excitement Seeking |
|
| PE73 | Costa & McCrae NEO, E6 -
Positive Emotions |
|
| C74 | Costa & McCrae NEO,
Conscientiousness |
|
| Tellegen & Waller 1996 |
||
| E75 | Tellegen Mulitidimen. Pers. Q.,
Positive Emotionality |
|
| Soc76 | California Personality
Inventory, Personal Orientation |
|
| E77 | Eysenck Personality
Questionnaire, Extraversion |
|
| C78 | Tellegen Multidimensional Pers.
Q., Constraint |
|
| C79 | California Personality
Inventory, Rigidity |
|
| P80 | Eysenck Personality
Questionnaire, Psychoticism |
|
| Zuckerman 1996 |
||
| ImpSS81 | Zuckerman-Kuhlman
Personality Quest., ImpSS |
|
| P82 | Eysenck Personality
Questionnaire, Psychoticism |
|
| E83 | Eysenck Personality
Questionnaire, Extraversion |
|
| Act84 | Zuckerman-Kuhlman Personality
Quest., Activity |
|
| Soc85 | Zuckerman-Kuhlman Personality
Quest., Sociability |
|
| Waller et al. 1991 (interscale correlations, not factor loadings) | ||
| NS86 | Cloninger Tridimensional Pers. Q., Novelty Seeking [average of NS subscale correlations X Tellegen MPQ | |
| Well-Being (best E estimate)
& Control (best Constraint estimate)] |
||
| Stallings et al. 1996 (interscale correlations, not factor loadings) | ||
| NS87 | Cloninger Tridimensional
Pers.Q., Novelty Seeking (NS correlated x EPQ E &
P) |
|
| NS88 | Cloninger Tridimensional Pers.
Q., Novelty Seeking (NS correlated x EPQ E & KSP
Impulsivity) |
|
| NS89 | Cloninger Tridimensional Pers.
Q., Novelty Seeking (NS correlated x EPQ E & KSP Monotany
Avoidance |