Neural substrates associated with evaluative processing during co-activation of positivity and negativity: A PET investigation

Biological Psychology 73 (2006) 253–261 www.elsevier.com/locate/biopsycho

Neural substrates associated with evaluative processing during co-activation of positivity and negativity: A PET investigation Young Chul Jung a, Suk Kyoon An a, Jeong Ho Seok b, Jae Seung Kim c, Seung Jun Oh c, Dae Hyuk Moon c, Jae-Jin Kim a,* a

Institute of Behavioral Science in Medicine, Severance Mental Health Hospital, Yonsei University College of Medicine, 696-6 Tanbul-dong Gwangju-si, Gyeonggi-do 464-100, Republic of Korea b Department of Psychiatry, Hallym University Sacred Heart Hospital, 896 Pyongchondong Anyang-si, Gyeonggi-do 431-070, Republic of Korea c Department of Nuclear Medicine, Asan Medical Center, 388-1 Pungnap-2dong, Songpa-gu, Seoul 138-736, Republic of Korea Received 10 August 2005; accepted 25 April 2006 Available online 12 July 2006

Abstract Affective symmetries, such as the positivity offset and negativity bias, have been postulated to be attributable to distinct activation functions of the positive and negative affect systems. We investigated the neural substrates that are engaged when the positive and negative affect systems undergo parallel and integrative processing. Eleven subjects were scanned using H215O PET during choosing the subjective feeling produced by a stimulation pair of pictures or words. Four different conditions were designed for contrast: pure positivity, pure negativity, positivity offset, and negativity bias. The dorsolateral prefrontal activation was associated with positivity offset and negativity bias condition, whereas the ventromedial prefrontal activation, together with limbic and subcortical activations, was associated with pure positivity and pure negativity condition. The results indicated that positivity offset and negativity bias are not merely due to asymmetric activations of the positive and negative systems, but integrative processing of higher neocortical levels is involved. # 2006 Elsevier B.V. All rights reserved. Keywords: Positivity offset; Negativity bias; Dorsolateral prefrontal cortex; PET

1. Introduction Previous researchers have suggested that the affect system derives input from at least two specialized evaluative channels: one in which positive (appetitive) information is processed and a second in which negative (aversive) information is processed (Lang et al., 1990; Gilbert, 1993; Gray, 1994; Marcus et al., 1995; LeDoux, 1996; Zautra et al., 1997; Watson et al., 1999). Functional brain imaging studies have investigated the neural correlates of these two evaluative systems and substantial evidence supports distinct activation patterns during positive and negative affective processing (George et al., 1995; Imaizumi et al., 1997; Irwin et al., 1996; Lane et al., 1997; Paradiso et al., 1999; Phillips et al., 1997; Lang et al., 1998a; Morris et al., 1998; Northoff et al., 2000; Aalto et al., 2002; Hamann et al., 2002; Lee et al., 2004). However, there have

* Corresponding author. Tel.: +82 31 760 9402; fax: +82 31 761 7582. E-mail address: [email protected] (J.-J. Kim). 0301-0511/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.biopsycho.2006.04.006

been few studies to explore how the positive and negative systems are organized when these two systems are co-activated for parallel and integrative processing. To address this issue, Cacioppo and his colleagues advanced a model of affective processing, named the Evaluative Space Model, which proposes that the positive and negative systems are governed by different underlying substrates and that these separable systems are assumed to posses distinct activation functions (Cacioppo and Bemston, 1994; Cacioppo et al., 1999; Cacioppo and Gardner, 1999). These differences in activation functions manifest two affective asymmetries: the positivity offset and negativity bias. The positivity offset refers to a tendency for the positive system to respond more than the negative system when the evaluative input is weak or absent (Kaplan, 1973; Matlin and Stang, 1978; Peeters and Czapinski, 1990; Cacioppo et al., 1999). The negativity bias refers to a tendency for the negative system to respond more intensely than the positive system when evaluative input increases (Kanouse and Hansen, 1971; Kaneman and Tvershy, 1984; Peeters and Czapinski, 1990; Taylor et al., 2003; Cacioppo

254

Y.C. Jung et al. / Biological Psychology 73 (2006) 253–261

et al., 1999). The positivity offset and negativity bias have been demonstrated in the attitude judgments of color photographs (Ito et al., 1998a) and was replicated in evaluative reactions to words (Ito et al., 1998b). In addition, these affective asymmetries were observed not only in self-reports, but also at electrophysiological level in recent studies using the eventrelated potential (Ito and Cacioppo, 2000; Smith et al., 2002). Our study explores the neural substrates associated with evaluative processing, when the positive and negative systems are co-activated with asymmetric manifestations. We expect that the neural substrates associated with affective asymmetries will be different from the substrates of univalent positive or negative affective processing. Our hypothesis is that affective asymmetries are not merely due to asymmetric activation of the positive and negative systems, but additional integrative processing of higher neocortical level is engaged. We previously developed an emotional discrimination task in order to induce affective asymmetries in our experimental setting for positron emission tomography (PET) activation study. Considering the issue of whether the behavioral measure is appropriate for reflecting affective asymmetries, our behavioral task was preliminarily examined in a relatively large sample.

2. Methods 2.1. Subjects The subjects for PET activation study were eleven healthy right-handed volunteers (six men and five women). Their mean age and mean educational achievement were 23.7 (S.D. = 2.3) years and 14.6 (S.D. = 1.1) years, respectively. Previously, 16 healthy right-handed volunteers, 7 men and 9 women, participated in the pilot study to verify that the behavioral task produced the desired responses. Consequently, 27 volunteers, 13 men and 14 women, were the subjects for the behavioral measures. The mean age of all subjects was 25.1 (S.D. = 3.2) years and their mean educational achievement was 14.8 (S.D. = 1.5) years. Exclusion criteria for all subjects were any past or present history of neurological, general medical or psychiatric illnesses, which were screened for during an interview session including the Structured Clinical Interview for DSM IV (SCID-IV; First et al., 1996). After a complete description of the study was provided to the subjects, written informed consent was obtained. Our study was carried out under the guidelines for the use of human subjects established by the institutional review board at Severance Mental Health Hospital.

2.2. Stimulus materials and behavioral tasks Emotional stimulation was performed with pairs of words or pictures. The picture stimuli were developed by modifying pictures from the International Affective Picture System (IAPS) (Lang et al., 1998b). Forty different pictures (neutral, 20; negative, 10; and positive, 10) were used to form stimulation pairs for the behavioral tasks. The word stimuli were chosen from the 100 emotional words frequently used in Korea (Lee, 1998) whereas 42 different disyllables (neutral, 22; negative, 10; and positive, 10) were used for the behavioral tasks. The visual stimuli were sequentially presented as a juxtaposed pair of pictures or words in a vertical array on an LCD monitor. The picture stimuli were displayed in the form of a pair of black and white quadrangles (7.0 cm high  3.5 cm long) on a black background. The word stimuli were longitudinally presented in the form of white disyllables (3.5 cm high  1.4 cm long) on a black background, within a pair of boxes with the same size as the picture stimuli. Our emotional discrimination task consisted of four different conditions according to the nature of the stimuli: (i) positive–positive pair; (ii) negative– negative pair; (iii) neutral–neutral pair; (iv) positive–negative (or negative– positive) pair. Each condition had a word set and a picture set, therefore the

behavioral task was composed of eight different sets. Each set consisted of 60 pairs and the stimuli were projected for 2.5 s at 500 ms intervals with a total duration of 180 s for each set. The sequence of the sets was randomized. The subjects were instructed to press 1 of 3 buttons depending upon the subjective feeling produced by the stimuli. The subjects were encouraged to select between positive (right button) and negative (left button), but in case neither affect was produced, the subject could choose the middle button. By these instructions, the subjects were likely to make a choice between positive and negative, even though the evaluative input was weak (neutral–neutral pair) or conflicting (positive–negative pair). The positive–positive pair and negative–negative pair were designed to elicit conditions in which only the positive or negative system is activated. In contrast, the neutral–neutral pair and positive–negative (or negative– positive) pair were intended to co-activate the positive and negative system. All responses were automatically transferred to a computer file, which was then utilized for the calculation of the response percentage and reaction time. After completing the behavioral task (and PET investigations in the case of the subjects for the activation study), the valences of all of the stimuli were evaluated by asking the subjects to rate the p1easantness of each stimulus. We used the valence dimension of the self-assessment manikin (SAM) affective rating system (Lang, 1980), in which a graphic figure from frowning (corresponding to 1) to smiling (corresponding to 9) depicted the valence on a continuously varying nine-point scale.

2.3. PET activation study Scans were obtained using an ECAT EXACT HR + scanner (Siemens-CTI, Knoxville, TN, USA), which had an intrinsic resolution of 4.5 mm full width at half maximum (FWHM) and simultaneously imaged 63 contiguous transverse planes with a thickness of 2.5 mm for a longitudinal field of view of 15.5 cm. All subjects for the activation study underwent eight consecutive PET scans whose order of presentation was randomly distributed among the subjects. Before the first and fifth injections of the tracer, 5-min transmission scans using triple 68Ge rod sources were performed for attenuation correction. Each task started 30 s prior to the injection of the tracer. Emission scans during the performance of the cognitive tasks started after an intravenous bolus injection of about 740 MBq of [15O]H2O in 3–5 ml saline. The PET data were acquired using 3D mode during a time period of 110 s. The acquired data were reconstructed in a 128  128  63 matrix with a pixel size of 1.7 mm  1.7 mm  2.4 mm by means of the ordered subsets expectation maximization (OSEM) algorithm employing a Gaussian filter with a kernel FWHM of 6.0 mm. Based on time-activity curves, only data reflecting the 60 s after the arrival at a peak was summed. Injections were repeated at intervals of 10 min. Spatial pre-processing and statistical analysis were performed using Statistical Parametric Mapping 99 (Department of Neurology, University College of London, UK). All reconstructed images were realigned and transformed into a standard stereotactic anatomical space to remove the inter-subject anatomical variability (Talairach and Tournoux, 1988). Affine transformation was performed in order to determine the 12 optimal parameters to register the brain on a standard PET template. Subtle differences between the transformed image and the template were removed by a nonlinear registration method using the weighted sum of the pre-defined smooth basis functions used in a discrete cosine transformation. Spatially normalized images were then smoothed by convolution with an isotropic Gaussian kernel with 10 mm FWHM, in order to increase the signal-to-noise ratio and accommodate the subtle variations in the anatomical structures.

2.4. Data analysis Within-subject subtraction of relevant injections was performed and followed by across-subject averaging of the subtraction images. For each voxel in stereotactic space, the analysis of covariance generated a condition-specific adjusted mean rCBF value and an associated adjusted error variance. The analysis of covariance permitted comparison of the means across conditions using the tstatistics of the rCBF changes. For easy interpretation, the resulting t-values were then transformed into Z-scores in the standard Gaussian distribution. The neural correlates of evaluative processing were investigated from contrasts between different conditions. The contrasts were mainly based on the assumption that the neutral–neutral pair and positive–negative pair elicited

Y.C. Jung et al. / Biological Psychology 73 (2006) 253–261

255

Table 1 Behavioral performances for both picture and word stimuli Stimuli

Response percentage (S.D., %) Missing Positive Negative Neither Reaction time (S.D., ms) Positive Negative Neither

Neutral–neutral

Positive–positive

Negative–negative

Positive–negative

6.4 (20.3) 41.5 (27.1) 7.9 (9.4) 44.2* (27.9)

5.5 (14.6) 88.1* (19.0) 0.7 (1.4) 5.7 (13.1)

3.6 (11.3) 0.6 (1.7) 94.9* (11.8) 0.9 (3.2)

5.0 (11.5) 8.9 (14.5) 61.2 (30.6) 24.9* (29.0)

1312.3 (364.7) 1630.6 (521.9) 1425.8y (372.4)

1035.0y (313.7) 1282.9 (383.8) 1718.3 (279.9)

1391.3 (1062.2) 1025.9y (343.4) 958.4 (730.5)

1623.2 (520.1) 1434.1 (345.2) 1578.7y (387.8)

Analysis of variance revealed a significant effect of task condition for the response percentages (*P < 0.001) and for the reaction time of the appropriate response (yP < 0.001). ‘nonreciprocal activation’, that is the stimuli increase the activation of both the positive and negative system, while the positive–positive pair and negative– negative affected only the positive or negative system. The conjunction analysis (Price and Friston, 1997) was used to determine the overlapping regions both activated in response to picture and word stimuli. The threshold of significance for the clusters was defined as exceeding an uncorrected P level of 0.001 and containing at least 10 contiguous voxels.

3. Results 3.1. Behavioral observations Twenty-seven subjects took part in the behavioral measures, including 16 volunteers who participated in the pilot study. In the valence appraisal using the SAM affective rating system, the subjects gave the picture stimuli a rating of 1.9  0.7 for negative, 7.5  1.1 for positive and 4.9  0.8 for neutral, and gave the word stimuli a rating of 1.8  0.7 for negative, 7.9  0.8 for positive and 5.3  0.8 for neutral, suggesting that the stimuli used in our tasks were appropriate. The behavioral data are summarized in Table 1. The responses to positive–positive pairs and negative–negative pairs were significantly convergent (88.1  19.0% and 94.9  11.8%, respectively) than the responses to neutral–neutral pairs or positive–negative pairs. Although the responses were not as convergent, there was an interesting trend in the responses to neutral–neutral pairs and positive–negative pairs. The subjects assigned positive valence rather than negative valence to neutral– neutral pairs, i.e., positivity offset (44.2  27.9% for ‘‘neither’’, 41.5  27.1% for ‘‘positive’’, 7.9  9.4% for ‘‘negative’’, 6.4  20.3% for missing). In contrast, the same subjects tended to choose negative valence than positive valence to positive– negative pairs, i.e., negativity bias (61.2  30.6% for ‘‘negative’’, 24.9  29.0% for ‘‘neither’’, 8.9  14.5% for ‘‘positive’’, and 5.0  11.5% for missing). These results demonstrated that our emotional discrimination task succeeded to elicit affective asymmetries in experimental setting. The condition elicited by neutral–neutral pair was positivity offset, whereas the condition elicited by positive–negative pair was negativity bias. In contrary, we referred to the conditions elicited by positive– positive pair and negative–negative pair as pure positivity and pure negativity, respectively. Analysis of variance (ANOVA) for

the response percentage and reaction time revealed a significant effect of task condition {F(3,78) = 58.7, P < 0.001; F(3,69) = 31.4, P < 0.001}. The behavioral measures of the 11 participants who underwent PET scanning were estimated apart. Compared with the behavioral measures of the total 27 subjects, the participant who underwent PET scanning demonstrated similar patterns with even a stronger negativity bias and longer response latency. The subjects more frequently reported their subject feeling positive to neutral–neutral pairs, i.e., positivity Table 2 Brain activations during pure positivity and pure negativity Region

Side

Voxels

Z-max

Coordinates x

Pure positivity Orbitofrontal gyrus

y

z

Right Left

12 15

3.95 3.58

18 18

56 36

28 28

Left Left Left Right Left Right

61 10 12 41 24 200

4.23 3.49 3.48 3.67 3.66 4.35

50 28 16 70 38 34

42 12 6 32 76 96

0 16 24 20 50 16

Left Left Left Left Left Left Right

67 44 12 12 11 16 57

4.19 4.18 3.80 3.83 3.32 3.47 4.73

4 22 54 56 2 6 12

60 46 22 2 36 18 40

14 18 2 26 12 30 36

Caudate nucleus (head) Thalamus and brain stem

Left Right

49 123

4.08 4.18 3.49

2 10 4

8 26 18

4 6 4

Cerebellum Superior parietal lobule Lingual gyrus Precuneus

Left Left Left Right Left

14 49 45 69 27

3.36 4.16 3.60 3.83 3.45

22 30 20 2 6

48 52 60 58 72

14 66 2 40 22

Inferior frontal gyrus Insular cortex Caudate nucleus (tail) Inferior temporal gyrus Superior parietal lobule Occipital gyrus Pure negativity Frontal pole Middle frontal gyrus Inferior frontal gyrus Precentral gyrus Cingulate gyrus, anterior Cingulate gyrus, posterior

Commonly activated areas between both picture and word stimuli were evaluated using conjunction analysis.

256

Y.C. Jung et al. / Biological Psychology 73 (2006) 253–261

Table 3 Brain activations during positivity offset and negativity bias

3.2. PET activation findings

Region

Eleven subjects completed the PET activation study. We hypothesized that affective asymmetries are not merely due to asymmetric activations of the positive and negative system. That is, the negativity bias is manifested, not just because the negative system is more strongly activated than the positive system. If the negativity bias was simply due to quantitative asymmetric activation, then the subtraction of negativity bias minus pure positivity would just reveal the more activated negative system, showing little difference from the subtraction of pure negativity minus pure positivity. However, if the subtraction of negativity bias minus pure positivity reveals novel brain regions that are not observed in the subtraction of pure negativity minus pure positivity, these brain regions might be regarded as the neural substrates associated with negativity bias processing. Pure positivity and pure negativity (see Table 2). Diverse regions were activated during pure positivity condition, extending over the frontal, temporal, parietal and occipital lobe, such as the orbitofrontal cortex, inferior frontal cortex, insular cortex, inferior temporal gyrus, superior parietal lobule and occipital gyrus. However, no lateralization was observed in

Side

Voxels

Z-max

Coordinates x

y

z

Positivity offset Middle frontal gyrus Precentral gyrus

Left Left

18 15

3.66 3.62

36 56

36 8

40 38

Negativity bias Frontal pole Middle frontal gyrus

Right Left

12 52 106 12

3.32 4.05 4.04 3.64

28 20 36 48

64 60 54 2

14 18 6 52

Left

12

3.38

48

28

16

Inferior frontal gyrus

Commonly activated areas between both picture and word stimuli were evaluated using conjunction analysis.

offset (49.7  24.3% for ‘‘neither’’; 41.5  21.2% for ‘‘positive’’; 8.8  8.8% for ‘‘negative’’), and negative to positive– negative pairs, i.e., negativity bias (67.7  15.7% for ‘‘negative’’; 19.3  13.4% for ‘‘neither’’; 12.5  11.0% for ‘‘positive’’; 0.7  0.8% for missing) (see Appendix 1).

Fig. 1. Distinct PET activation pattern between pure positivity (A) and positivity offset (B). The ventromedial prefrontal cortex (orbitofrontal gyrus) is activated during pure positivity, whereas the dorsolateral prefrontal cortex (middle frontal gyrus) is activated during positivity offset.

Y.C. Jung et al. / Biological Psychology 73 (2006) 253–261

257

Fig. 2. Distinct PET activation pattern between and pure negativity (A) and negativity bias (B). The medial prefrontal cortex (frontal pole) is activated during pure negativity, whereas the dorsolateral prefrontal cortex (middle frontal gyrus) is activated during negativity offset.

pure positivity. Considering the prefrontal area, the ventromedial prefrontal cortex (inferior frontal gyrus and orbital gyrus) was associated with pure positivity. Pure negativity was associated with the various activations of the medial portion, including subcortical regions. The anterior and posterior cingulate gyrus, caudate nucleus (head), thalamus, brainstem area, and precuneus were activated during pure negativity. Positivity offset and negativity bias (see Table 3). Brain activations in positivity offset was observed at the lateral frontal cortex – the middle frontal gyrus and the precentral gyrus – both characteristically lateralized to the left hemisphere (see Fig. 1). This activation pattern was more prominent in negativity bias. The middle frontal gyrus and inferior frontal gyrus, both lateralized to the left, were associated with negativity bias together with the frontal pole area (see Fig. 2). 4. Discussion Our study investigated the neural correlates of affective processing, not only when the positive and negative systems

were activated separately, but also when the positive and negative systems were co-activated with asymmetries manifested. In contrast to previous studies that mainly investigated brain activations associated with conflict (ambivalent) conditions (Cunningham et al., 2003), we expanded the focus to brain activations associated with integrative processing for response selection in order to resolve the conflict condition. The hypothesis of our study was that affective asymmetries are not merely due to asymmetric activation of the positive and negative evaluative systems but additional integrative processing of higher neocortical level is engaged and so the key question addressed in the current study was the degree to which the neural substrates associated with affective asymmetries would be different from the simple subtraction between elementary positive and negative affect substrates. The results indicated that the pattern of activations was quite distinct: The dorsolateral prefrontal activation was associated with positivity offset and negativity bias conditions, whereas the ventromedial prefrontal activation, together with limbic and subcortical activations, was associated with univalent evaluative conditions. Of importance,

258

Y.C. Jung et al. / Biological Psychology 73 (2006) 253–261

though the behavioral data reflect operation of the positivity offset and negativity bias in this paradigm, it does not follow that the brain regions activated by this task are necessarily the neural substrates of positivity offset and negativity bias. Therefore, it would be more reasonable to conclude that the dorsolateral prefrontal activation in our study reflects the integrative processing involved in response selection during co-activation of positivity and negativity rather than a unique substrate associated with positivity offset and negativity bias. In addition, it is noteworthy that dorsolateral prefrontal activations observed in positivity offset and negativity bias were lateralized to the left. Although, functional imaging studies have produced conflicting results with regard to hemispheric lateralization for emotion, many investigators have reported right hemisphere superiority for the perception of emotion (Borod, 1992; Heller, 1993). It may be matched with our results by the assumption that pure affective processing is governed by the right hemisphere, but in case additional integrative processing is required the left hemisphere gets involved. Our PET findings are consistent with recent imaging studies exploring the neural substrates of evaluative processing. Davidson and Irwin (1999) proposed that the ventromedial prefrontal cortex is most directly involved in the representation of elementary positive and negative emotional states while the dorsolateral prefrontal cortex may be involved in the representation of the goal states towards which these elementary positive and negative states are directed. Schaefer et al. (2003) hypothesized a similar distinction by contrasting different emotional processes: the schematic process (‘‘hot emotion’’) was associated with increased activity in the ventromedial prefrontal cortex, whereas propositional process (‘‘cold emotion’’) was associated with the lateral prefrontal cortex. In a recent review of emotion perception, Phillips et al. (2003) suggested that emotional perception may be dependent on two neural systems: the ventral system, including the amygdala, insula, ventral striatum, ventral cingulate cortex and ventral prefrontal cortex, is important for automatic responses to emotive stimuli and in contrast the dorsal system, including the hippocampus and dorsolateral prefrontal cortex, is important for effortful rather than automatic regulation of affective states. In our case, the positivity offset and negativity bias condition would have required effortful regulation of affective state, while the responses to pure positivity or pure negativity condition would be closer to automatic responses. The PET activation patterns may be linked to the behavioral measures of significantly prolonged reaction time in the positivity offset and negativity bias condition. The prolongation of the reaction time has been attributed to high cognitive demand required for decision-making, and thus the dorsolateral prefrontal activations in the positivity offset and negativity bias condition might just reflect the additional cognitive load. In previous studies, the dorsolateral prefrontal cortex has been implicated in cognitively demanding tasks to play significant roles in working memory (Friedman and Goldman-Rakic, 1994; Kim et al., 2002). From this perspective, it could be inferred that positivity offset and negative bias may just be a

problem of cognition rather than emotion. However, it should be noted that although emotion and cognition may be separable, multiple processing processes exist in which emotion and cognition can conjointly contribute to the control of responses (Ekman and Davidson, 1994; Dalgleish and Power, 1999; LeDoux, 2000; Martin and Clore, 2001; Gray, 2001). A recent study indicated that emotion and cognition could be truly integrated with functional specialization lost, in the lateral prefrontal cortex (Gray et al., 2002) and it may be assumed that the dorsolateral prefrontal activation in out study reflects the integration of cognition and emotion during the positivity offset and negativity bias processing. A question could be raised whether the crucial asymmetry pattern reported for the whole group of 27 participants held as well for the smaller subgroup of 11 participants who underwent PET scanning. The integrative neural processes demonstrated in our study might be related to ‘‘informational negativity effect’’ (Peeters and Czapinski, 1990) or ‘‘minimization process’’ (Taylor, 1991) that would reduce asymmetry effects, particularly the negativity bias. So there would be a chance that the participants, who knew that their brain processes were observed, were motivated to think carefully before pressing the answer button, which may have resulted, not only in increased integrative brain activity, but also in a reduction of the affective asymmetry tapped by behavioral response. However, the behavioral measures of the 11 participants who underwent PET scanning showed even a stronger negativity bias and longer response latency. Although the participant took more time in selecting the answer button, this did not lead to a reduction in the affective asymmetry pattern, probably because the subjects were encouraged to select between ‘positive’ and ‘negative’. Besides, the PET activation findings of contrasts between pure emotional conditions were consistent with previous functional imaging studies. One of the characteristic activations in the current study was observed in the anterior cingulate cortex during pure negativity but not pure positivity. The mediodorsal thalamic nuclei and ventral striatum were coactivated with the anterior cingulate gyrus during pure negativity condition in our study. Many researchers have identified the anterior cingulate cortex as an important component of emotional networks associated with emotional information processing and production of affective states (Mayberg et al., 1999; Shin et al., 2000; Elliott et al., 2000). Although recent neuroimaging studies (Bush et al., 2000) have showed that cognitive and emotional information might be processed separately, the dorsal division and the ventral division were both activated during pure negativity condition in our study. In contrast the insula activation was observed only during pure positivity condition but not pure negativity condition. The insula has been previously implicated in internally generated recalled emotions and to monitor the ongoing internal emotional state (Reiman et al., 1997; Damasio et al., 2000). So far, insular activations in response to negative emotional stimuli, such as pain and trauma, have been reported (Casey et al., 1996; Charney and Drevets, 2002), but the role of insula in processing positive stimuli is still uncertain. Another significant finding is the ventromedial frontal cortex activation,

Y.C. Jung et al. / Biological Psychology 73 (2006) 253–261

in both pure positivity and pure negativity conditions. The role of ventromedial prefrontal cortex, especially the orbitofrontal cortex, in emotion has been previously observed in various types of emotional conditions (George et al., 1995; Morris et al., 1996; Blood et al., 1999; Rolls, 2000; Bechara et al., 2000). Functionally, the medial orbitofrontal cortex seems to be specialized for emotional processing, whereas the lateral orbitofrontal cortex has been related to a more general function of associating emotions with cognitions (Baker et al., 1997; Drevets and Raichle, 1998). Meanwhile, neural correlates that have been considered as key structures in emotional processing, such as the amygdala (Adolphs et al., 1995; Breiter et al., 1996; Phillips et al., 1997; Hamann et al., 1999, 2002; Davis and Whalen, 2001; Wright et al., 2002; Liberzon et al., 2003), should have been subtracted during the opposite valence contrast. Another possibility is that the amygdala is more likely to be activated in automatic responses rather than effortful evaluative responses that involve higher cognitive processing (Reiman et al., 1997; Drevets and Raichle, 1998; Teasdale et al., 1999; Phan et al., 2002). The results of this study must be considered within the context of several limitations. First, the brain activations elicited in our study probably speaks strongly to issues of approach–avoidance associated evaluative dimension. Since Wundt (1896), there has been a tradition to associate the valence of affective positive–negative responses with behavioral approach–avoidance tendencies, however recently, several studies have given evidence indicating that there is another positive–negative dimension that is not associated with behavioral approach versus avoidance tendencies (Wentura et al., 2000; Peeters, 2001). Cacioppo et al. (1999) have described affective asymmetries within the context of evaluative processing and thus we should also demarcate particular boundaries of the observed brain activations in our study to the approach–avoidance associated evaluative dimension of the positive–negative system. Second, the arousal level of the subjects when they saw emotional stimuli should have affected the performance, especially in the positive–negative condition, but we only considered the valence and frequency but not the arousal rating of the stimuli in our study. Emotional words and pictures differ not only in terms of valence, but may also differ in terms of arousal level (Osgood and Tammenbaum, 1957). Thus, it is unclear whether the differential brain activation observed in neuroimaging studies is due to stimulus valence or whether the results are confounded by arousal level. This issues is further compounded by the findings that pictures with strong valence are also rated with as highly arousing (Lang et al., 1999). Therefore, it is important to try to unravel the contributions of valence and arousal during emotional stimuli processing, which was not considered in our present study. Third, the positivity offset condition was not sufficiently elicited. The neutral–neutral pair elicited a condition which was a mix of positivity offset (41.5%) and pure neutrality (44.2%) rather than a homogenous positivity offset condition. In contrast, the responses to the positive–negative pair showed a more apparent trend to select ‘‘negative’’ (61.2%). If the

259

positivity offset condition was more effectively elicited, we might have got a chance to investigate whether there are differences between the neural substrates associated with positivity offset and negativity bias. In conclusion, our study investigated the neural substrates associated with evaluative processing during co-activation of positivity and negativity. The findings of our study during positivity offset and negativity bias conditions indicated that the dorsolateral prefrontal cortex is activated when the positive and negative evaluative systems are co-activated for parallel and integrative processing. These findings suggest that the left dorsolateral prefrontal cortex might be involved in affective processing to integrate and expand the functionality of the affect system. Acknowledgement This study was supported by a grant of the Korea Health 21 R&D Project, Ministry of Health & Welfare, Republic of Korea (A050495). Appendix A Behavioral performances of 11 subjects who underwent PET scanning. Stimuli Neutral– neutral

Positive– positive

Response percentage (S.D., %) Missing 0.0 (0.0) 0.8 (1.3) Positive 41.5 (21.2) 97.5 (2.6) Negative 8.8 (8.8) 0.8 (1.3) Neither 49.7 (24.3) 1.8 (1.8)

Negative– negative

Positive– negative

1.7 0.3 98.1 0.3

0.7 12.5 67.7 19.3

(2.0) (0.6) (1.9) (0.6)

(0.8) (11.0) (15.7) (13.4)

Reaction time (S.D., ms) Positive 1324.6 (379.1) 1232.4 (385.2) 2388.5 (435.6) 1536.9 (520.1) Negative 1655.7 (402.4) 1734.6 (382.7) 1178.4 (323.3) 1573.9 (389.4) Neither 1462.0 (476.3) 1562.2 (270.1) 866.0 (786.0) 1828.5 (338.5)

References Aalto, S., Naatanen, P., Wallius, E., Metsahonkala, L., stenman, H., Niemi, P.M., 2002. Neuroanatomical substrata of amuement and sadness: a PET activation study. NeuroReport 13, 67–73. Adolphs, R., Tranel, D., Damasio, H., Damasio, A.R., 1995. Fear and the human amygdala. Journal of Neuroscience 15, 5879–5891. Baker, S.C., Frith, C.D., Dolan, R.J., 1997. The interaction between mood and cognitive function studied with PET. Psychological Medicine 27, 565–578. Bechara, A., Damasio, H., Damasio, A.R., 2000. Emotion, decision making and the orbitofrontal cortex. Cerebral Cortex 10, 295–307. Blood, A.J., Zatorre, R.J., Bermundez, P., Evans, A.C., 1999. Emotional responses to pleasant and unpleasant music correlate with activity in paralimbic brain regions. Nature neuroscience 2, 382–387. Borod, J., 1992. Interhemispheric and intrahemispheric control of emotion: a focus on unilateral brain damage. Journal of Consult Clinical Psychology 60, 339–348. Breiter, H.C., Etcoff, N.L., Whalen, P.J., Kennedy, W.A., Rauch, S.L., Buckner, R.L., Strauss, M.M., Hyman, S.E., Rosen, B.R., 1996. Response and

260

Y.C. Jung et al. / Biological Psychology 73 (2006) 253–261

habituation of the human amygdala during visual processing of facial expression. Neuron 17, 875–887. Bush, G., Luu, P., Posner, M., 2000. Cognitive and emotional influences in anterior cingualte cortex. Trends in Cognitive Sciences 4, 215–222. Cacioppo, J.T., Bernston, C.G., 1994. Relationship between attitudes and evaluative space: a critical review, with emphasis on the separability of positive and negative substrates. Psychological Bulletin 115, 401–423. Cacioppo, J.T., Gardner, W.L., Berston, C.G., 1999. The affect system has parallel and integrative processing components: form follows function. Journal of Personality and Social Psychology 76, 839–855. Cacioppo, J.T., Gardner, W.L., 1999. Emotion. Annual Review of Psychology 50, 191–214. Casey, K.L., Minoshima, S., Morrow, T.J., Koeppe, R.A., 1996. Comparison of human cerebral activation pattern during cutaneous warmth, heat pain, and deep cold pain. Journal of Neurophysiology 76, 571–581. Charney, D.S., Drevets, W.C., 2002. The neurobiological basis of anxiety disorders. In: Davis, K., Charney, D.S., Coyle, J., Nemeroff, C.B. (Eds.), Psychopharmacology: The Fifth Generation of Progress. Lipponcott, Philadelphia. Cunningham, W.A., Johnson, M.K., Gatenby, J.C., Gore, J.C., Banaji, M.R., 2003. Neural components of social evaluation. Journal of Personality and Social Psychology 85, 639–649. Damasio, A.R., Grabowski, T.J., Bechara, A., Damasio, H., Ponto, L.L., Parvizi, J., Hichwa, R.D., 2000. Subcortical and cortical brain activity during the feeling of self-generated emotions. Nature Neuroscience 3, 1049–1056. Dalgleish, T., Power, M.J., 1999. Handbook of Cognition and Emotion. Wiley, New York. Davidson, R.J., Irwin, W., 1999. The functional neuroanatomy of emotion and affective style. Trends in Cognitive Science 3, 11–21. Davis, M., Whalen, P.J., 2001. The amygdala: vigilance and emotion. Molecular Psychiatry 6, 3–34. Drevets, W.C., Raichle, M., 1998. Reciprocal suppression of regional cerebral blood flow during emotional versus higher cognitive processes: implications for interactions between emotion and cognition. Cognition and Emotion 12, 353–385. Ekman, P., Davidson, R.J., 1994. The Nature of Emotion. Oxford, New York. Elliott, R., Friston, K.J., Dolan, R.J., 2000. Dissociable neural responses in human reward systems. Journal of Neuroscience 20, 659–6165. First, M.B., Spitzer, R.L., Gibbon, M., Williams, J.B.W., 1996. Structured Clinical Interview for DSM-IVAxis I Disorders. New York State Psychiatric Institute, Biometrics Research, New York. Friedman, H.R., Goldman-Rakic, P.S., 1994. Coactivation of prefrontal cortex and inferior parietal cortex in working memory tasks revealed by 2DG functional mapping in the rhesus monkey. Journal of Neuroscience 14, 2775–2788. George, M.S., Ketter, T.A., Parekh, P.I., Horwitz, B., Herscovitch, P., Post, R.M., 1995. Brain activity during transient sadness and happiness in healthy women. American Journal of Psychiatry 152, 341–351. Gilbert, P., 1993. Defense and Safety: their function in social behavior and psychopathology. British Journal of Clinical Psychology 32, 131–153. Gray, J.A., 1994. Personality dimensions and emotion systems. In: Ekman, P., Davidson, R.J. (Eds.), The Nature of Emotion: Fundamental Questions. Oxford University Press, New York. Gray, J.R., 2001. Emotional modulation of cognitive control: approach–withdrawal states double-dissociate spatial from verbal two-back task performance. Journal of Experimental Psychology: General 130, 436–452. Gray, J.R., Braver, T.S., Raichle, M.E., 2002. Integration of emotion and cognition in the lateral prefrontal cortex. Proceedings of the National Academy of Science 19, 4115–4120. Hamann, S.B., Ely, T., Grafton, S., Kilts, C., 1999. Amygdala activity related to enhanced memory for pleasant and aversive stimuli. Nature Neuroscience 2, 289–293. Hamann, S.B., Ely, T., Hoffman, J.M., et al., 2002. Activation of the human amygdala in positive and negative emotion. Psychological Science 13, 135–141. Heller, W., 1993. Neuropsychological mechanisms of individual differences in emotion, personality, and arousal. Neuropsychology 7, 476–489. Imaizumi, S., Mori, K., Kirtani, S., Kawashima, R., Suguira, M., Fukuda, H., Itoh, K., Kato, T., Nakamusa, A., Hatano, K., Kojima, S., Nakamura, K.,

1997. Vocal identification of speaker and emotion activates different brain regions. NeuroReport 8, 2809–2812. Irwin, W., Davidson, R.J., Lowe, M.J., Mock, B.J., Sorenson, J.A., Turski, P.A., 1996. Human amygdala activation detected with echo-planar functional imaging resonance studies. NeuroReport 7, 1765–1769. Ito, T.A., Cacioppo, J.T., Lang, P.J., 1998a. Eliciting affect using the International Affective Picture System: Bivariate evaluation and ambivalence. Personality and Social Psychology Bulletin 24, 855–879. Ito, T.A., Larsen, J.T., Smith, N.K., Cacioppo, J.T., 1998b. Negative information weighs more heavily on the brain: the negative bias in evaluative categorizations. Journal of Personality Social Psychology 75, 887– 900. Ito, T.A., Cacioppo, J.T., 2000. Electrophysiological evidence of implicit and explicit categorization processes. Journal of Experimental Social Psychology 36, 660–676. Kaneman, D., Tvershy, A., 1984. Choices, values, and frames. American Psychologist 39, 341–350. Kanouse, D.E., Hansen Jr., L.R., 1971. Negativity in evaluations. In: Jones, E.E., Kanouse, D.E., Kelly, H.H., Nisbett, R.E., Valin, S., Weiner, B. (Eds.), Attribution: Perceiving the Causes of Behavior. General Learning Press, Morristown, NJ, pp. 47–62. Kaplan, K., 1973. On the ambivalence-indifference problem in attitude theory and measurement: a suggested modification of the semantic differential technique. Psychological Bulletin 77, 361–372. Kim, J.J., Kim, M.S., Lee, J.S., Lee, D.S., Lee, M.C., Kwon, J.S., 2002. Dissociation of working memory processing associated with native and second languages: PET investigation. Neuroimage 15, 879–891. Lane, R.D., Reiman, E.M., Ahern, G.L., Schwartz, G.E., Davidson, R.J., 1997. Neuroanatomical correlates of happiness, sadness, and disgust. American Journal of Psychiatry 154, 926–933. Lang, P.J., 1980. Behavioral treatment and bio-behavioral assessment: computer application. In: Sidowski, J.B., Johnson, J.H., Williams, T.A. (Eds.), Technology in Mental Health Care Delivery Systems. Ablex, Norwood, pp. 119– 137. Lang, P.J., Bradley, M.M., Cuthbert, B.N., 1990. Emotion, attention, and the startle reflex. Psychological Review 97, 377–395. Lang, P.J., Bradley, M.M., Fitzsimmons, J.R., Cuthbert, B.N., Scott, J.D., Moulder, B., Nangia, V., 1998a. Emotional arousal and activation of the visual cortex. An fMRI analysis. Psychophysiology 35, 199–210. Lang, P.J., Bradley, M.M., Cuthbert, B.N., 1998b. International Affective Picture System (IAPS): Photographic Slides. Center for Research in Psychophysiology, University of Florida, Gainesville. Lang, P.J., Bradley, M.M., Cuthbert, B.N., 1999. International Affective Picture System (IAPS): Instruction Manual and Affective Rating. NIMH Center for the Study of Emotion and Attention. LeDoux, J.E., 1996. The Emotional Brain: The Mysterious Underpinnings of Emotional Life. Simon and Schuster, New York. LeDoux, J.E., 2000. Emotion circuits in the brain. Annual Review of Neuroscience 23, 155–184. Lee, G.P., Meador, K.J., Loring, D.W., Allison, J.D., Brown, W.S., Paul, L.K., Pillai, J.J., Lavin, T.B., 2004. Cognitive and Behavior Neurology 17, 9– 17. Lee, S.J., 1998. Conscious/Nonconsious Processing of Affective Information: Affective Primacy Effect in Priming Paradigm (written in Korean language). The Graduate School of Yonsei University, Seoul. Liberzon, I., Phan, K.L., Decker, L.R., Taylor, S.F., 2003. Extended amygdala and emotional salience: a PET activation study of positive and negative affect. Neuropsychopharmacology 28, 726–733. Marcus, G.E., Sullivan, J.L., Theiss-Morse, E., Wood, S.L., 1995. With Malice Toward Some. Cambridge University Press, New York. Martin, L.L., Clore, G.L., 2001. Theories of Mood and Cognition. Erlbaum, Mahwah, NJ. Matlin, M.W., Stang, D.J., 1978. The Pollyanna Principle: Selectivity in Language, Memory and Thought. Schenkman, Cambridge, MA. Mayberg, H.S., Liotti, M., Brannan, S.K., McGinnis, S., Mahyrin, R.K., Jarabek, P.A., et al., 1999. Reciprocal limbic-cortical function and negative mood: converging PET findings in depression and normal sadness. American Journal of Psychiatry 156, 675–682.

Y.C. Jung et al. / Biological Psychology 73 (2006) 253–261 Morris, J.S., Frith, C.D., Perrett, D.I., Rowland, D., Young, A.W., Calder, A.J., Dolan, R.J., 1996. A differential neural response in the human amygdala to fearful and happy facial expressions. Nature 383, 812–815. Morris, J.S., Ohman, A., Dolan, R.J., 1998. Conscious and unconscious emotional learning in the human amygdala. Nature 393, 467–470. Northoff, G., Richter, A., Gessner, M., Schlagenhauf, F., Fell, J., Baumgart, F., Kaulisch, T., Kotter, R., Stephan, K.E., Leschinger, A., Hagner, T., Bargel, B., Witzel, T., Hinrichs, H., Bogerts, B., Scheich, H., Heinze, H.J., 2000. Functional dissociation between medial and lateral prefrontal cortical spatiotemporal activation in negative and positive emotions: a combined fMRI/MEG study. Cerebral Cortex 10, 93–107. Osgood, C.E., Tammenbaum, P.H., 1957. The Measurement of Meaning. University of Illinois Press, Urbana. Paradiso, S., Johnson, D.L., Andreasen, N.C., O’Leary, D.S., Watkins, G.L., Ponto, L.L., Hichwa, R.D., 1999. Cerebral blood flow changes associated with attribution of emotional valence to pleasant, unpleasant, and neutral visual stimuli in a PET study of normal subjects. American Journal of Psychiatry 156, 1618–1629. Peeters, G., Czapinski, J., 1990. Positive–negative asymmetry in evaluations: the distinction between affective and informational negativity effects. In: Stroebe, W., Hewstone, M. (Eds.), European Review of Social Psychology. Wiley, New York. Peeters, G., 2001. Do perceivers associate approach–avoidance tendencies with positive and negative evaluations? The role of evaluative trait dimensions. Psychologica Belgica 41, 187–203. Phan, K.L., Wager, T., Taylor, S.F., Liberzon, I., 2002. Functional neuroanatomy of emotion: a meta-analysis of emotion activation studies in PET and fMRI. Neuroimage 16, 331–348. Phillips, M.L., Young, A.W., Senior, C., Brammer, M., Andrew, C., Calder, A.J., Bullmore, E.T., Perrett, D.I., Rowland, D., Williams, S.C., Gray, J.A., David, A.S., 1997. A specific neural substrate for perceiving facial expressions of disgust. Nature 389, 495–498. Phillips, M.L., Drevets, C.D., Rauch, S.L., Lane, R., 2003. Neurobiology of emotion perception: the neural basis of normal emotion perception. Society of Biological Psychiatry 54, 504–514. Price, C.J., Friston, K.J., 1997. Cognitive conjunction: a new approach to brain activation experiments. Neuroimage 5, 261–270. Reiman, E.M., Lane, R.D., Ahern, G.L., Schwartz, G.E., Davidson, R.J., Friston, K.J., Yun, L.S., Chen, K., 1997. Neuroanatomical correlates of externally and internally generated human emotion. American Journal of Psychiatry 154, 918–925.

261

Rolls, E.T., 2000. The orbitofrontal cortex and reward. Cerebral Cortex 10, 284– 294. Schaefer, A., Collette, F., Philippot, P., Van der Linden, M., Laureys, S., Delfiore, G., Degueldre, C., Maquet, P., Luxen, Salmon, E., 2003. Neural correlates of ‘‘hot’’ and ‘‘cold’’ emotional processing: a multilevel approach to the functional anatomy of emotion. Neuroimage 18, 938– 949. Shin, L.M., Dougherty, D.D., Orr, S.P., Pitman, R.K., lasko, M., Macklin, M.L., Alpert, N.M., Fischman, A.J., Rauch, S.L., 2000. Activation of anterior paralimbic structures during guilt-related script-driven imagery. Biological Psychiatry 48, 43–50. Smith, N.K., Cacioppo, J.T., Larsen, J.T., Chartrand, T.L., 2002. May I have your attention, please: electrocortical response to positive and negative stimuli. Neuropsychologia 41, 171–183. Talairach, J., Tournoux, P., 1988. Co-planar Stereotaxic Atlas of the Human Brain. Thieme, New York. Taylor, S.E., 1991. Asymmetrical effects of positive and negative events: the mobilization–minimization hypothesis. Psychological Bulletin 110, 67– 85. Taylor, S.F., Phan, K.L., Decker, L.R., Liberzon, I., 2003. Subjective rating of emotionally salient stimuli modulates neural activity. Neuroimage 18, 650– 659. Teasdale, J.D., Howard, R.J., Cox, S.G., Ha, Y., Brammer, M.J., Williams, S.C., Checkley, S.A., 1999. Functional MRI study of the cognitive generation of affect. American Journal of Psychiatry 16, 209–215. Watson, D., Wiese, D., Vaidya, J., Tellegen, A., 1999. The two general activation systems of affect: structural findings, evolutionary considerations and psychobiological evidence. Journal of Personality and Social Psychology 76, 820–838. Wright, C.I., Martis, B., Shin, L.M., Fischer, H., Rauch, S.L., 2002. Enhanced amygdala response to emotional versus neutral schematic facial expressions. Neuroreport 13, 785–790. Wentura, D., Rothermund, K., Bak, P., 2000. Automatic vigilance: the attention-grabbing power of approach- and avoidance-related social information. Journal of Personality and Social Psychology 78, 1024– 1037. Wundt, W., 1896. Grundriss der Psychologie, 6th ed. Engelman, Leipzig. Zautra, A.J., Potter, P.T., Reich, J.W., 1997. The independence of affects is context-dependent: an integrative model of the relationship between positive and negative affect. Annual Review of Gerontology and Geriatrics 17, 75–103.