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Cellular and Molecular Neurobiology, Vol. 21, No. 6, December 2001 ( C© 2002)

Emotion–Perception Interplay in the Visual Cortex:“The Eyes Follow the Heart”

Talma Hendler,1,3,4 Pia Rotshtein,1,2 and Uri Hadar2

Received November 2, 2001; accepted November 7, 2001

SUMMARY

Emotive aspects of stimuli have been shown to modulate perceptual thresholds. Lately,studies using functional Magnetic Resonance Imaging (fMRI) showed that emotive aspectsof visual stimuli activated not only canonical limbic regions, but also sensory areas in thecerebral cortex. However, it is still arguable to what extent such emotive, related activationin sensory areas of the cortex are affected by physical characteristic or attribute difference ofstimuli. To manipulate valence of stimuli while keeping visual features largely unchanged, wetook advantage of the Expressional Transfiguration (ET) of faces. In addition, to explore thesensitivity of high level visual regions, we compared repeated with unrepeated (i.e. different)stimuli presentations (fMR adaptation). Thus, the dynamics of brain responses was deter-mined according to the relative signal reduction during “repeated” relative to “different”presentations (“adaptation ratio”). Our results showed, for the first time, that emotionalvalence produced significant differences in fMR adaptation, but not in overall levels of acti-vation of lateral occipital complex (LOC). We then asked whether this emotion modulationon sensory cortex could be related to previous personal experience that attached negativeattributes of stimuli. To clarify this, we investigated Posttraumatic Stress Disorder (PTSD)and non-PTSD veterans. PTSD is characterized by recurrent revival of trauma-related sen-sations. Such phenomena have been attributed to a disturbed processing of trauma-relatedstimuli, either at the perceptual level or at the cognitive level. We assumed that PTSD vet-erans would differ from non-PTSD veterans (who have similar combat experience) in theirhigh order visual cortex responses to combat-related visual stimuli that are associated withtheir traumatic experience. An fMRI study measured the cerebral activation of subjectswhile viewing pictures with and without combat content, in “repeated” or “different” pre-sentation conditions. The emotive effect on the visual cortex was found, again, only in thefMR-adaptation paradigm. Visual cortical regions showed significant differences betweenPTSD and non-PTSD veterans only in “repeated” presentations of trauma-related stimuli(i.e. combat). In these regions, PTSD veterans showed less decrease in signal with repeatedpresentations of the same combat-related stimuli. This finding points to the possibility thattraumatic experience modulates brain activity at the level of sensory cortex itself.

KEY WORDS: emotional modulation; high order visual cortex fMRI; emotional valence;traumatic experience; PTSD.

1 Wohl Institute for Advanced Imaging, Functional Brain Imaging Laboratory, Tel Aviv Sourasky MedicalCenter, Tel Aviv, Israel.

2 Department of Psychology, Tel Aviv University, Tel Aviv, Israel.3 Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.4 To whom correspondence should be addressed at Whole Institute for Advanced Imaging, Functional

Brain Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; e-mail: talma@tasmc.health.gov.il.

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INTRODUCTION

The question whether the emotional valence of a visual stimulus affects its percep-tion has been asked since the early days of modern neuropsychology (Niedenthaland Kitayama, 1994). The answers tended to be positive, and the evidence for emo-tional modulation of visual perception came from several directions. For example,psychophysically, it was shown that perceptual thresholds were modulated by theemotional load of the visual stimuli: conflictual stimuli yielded higher thresholds(Broadbant and Gregory, 1967; Watt and Morris, 1995). However, contradictoryfindings and weak research methods often hindered drawing clear theoretical con-clusions in this regard. The present study offers a step towards clarifying these issuesby measuring the extent of brain reactivity to emotive aspects in visual stimuli.

Brain studies point to distinct sensory and limbic regions that could be in-volved in emotion–perception interaction. For example, anatomical studies in pri-mates showed that the amygdala receives direct input from high order visual areasin the ventral stream, and projects to a much greater region of the visual cortex,consisting essentially of all portions of the ventral stream (Amaral et al., 1992). Thefunction of these efferent projections on the visual stream were suggested to be po-tentially neuromodulatory, perhaps in relation to an emotional state of the animalor its “mood” (Emery and Amaral, 2000). Furthermore, Conturo et al. (Bat-ShevaSeminar 2001) recently showed fibers connecting the calcarine sulcus with the lateralnucleus of the amygdala using diffusion tensor MRI (DTI) in healthy humans. In ad-dition, functional brain-imaging findings in healthy subjects demonstrated both anemotional effect in visual cortex (Breiter et al., 1996; Critchley et al., 2000a; Georgeet al., 1995; Kosslyn et al., 1996; Lane et al., 1997, 1999; Lang et al., 1996, 1998; Morriset al., 1998; Reiman et al., 1997; Taylor et al., 1998, 2000) and an association be-tween visual cortex and amygdala activation during emotional stimulation (Dolanand Morris, 2000; Rotshtein et al., 2001).

By contrast, lesion studies in humans demonstrated a double dissociation be-tween visual perception and the related emotional processes (Adolphs et al., 1995;Aggelton and Young, 2000; Young et al., 1993). Thus, face recognition could be im-paired even with no impairment in the ability to recognize the related emotionalexpression (Bauer, 1984; de Gelder et al., 1999; Tranel and Damasio, 1988). Also,emotional deficits did not entail visual deficits in patients with amygdala lesions(Adolphs et al., 1994, 1995; Bechara et al., 1995; Calder et al., 1996; Young et al.,1995, 1996). In primates, single-cell recordings showed that magnitude of neuronalactivation in the inferior temporal cortex was not affected by the associated valenceof the stimuli, generated by reward or punishment (Rolls et al., 1977). Finally, func-tional brain imaging in humans showed that negatively conditioned faces did notelicit different activation in the visual cortex compared with unconditioned faces(Buchel et al., 1998). Thus, emotional context alone did not seem to affect visualcortex activation.

One possible explanation for the above discrepancy between studies is thatthe emotional effect found in the visual system was confounded by nonemotionalvariables that could interact with the emotional valence of visual stimuli. Anotherpossibility is a problem of measurement sensitivity. Nonemotive confounds could be

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related to processing factors such as attention (Corbetta et al., 1998; Lane et al., 1999;Vuileumier et al., 2001), recognition (Bar et al., 2001; Grill-Spector et al., 2000) andarousal (Critchley et al., 2000b; Lane et al., 1999; Taylor et al., 2000), or to stimulifactors such as categorical features (i.e., faces, objects; Ishai et al., 1997; Kanwisher,2001; Kanwisher et al., 1997), or visual features (Lerner et al., 2001; Malach et al.,1995).

Few studies directly addressed these confounds. For example, Taylor et al. (2000)in a PET study controlled for stimulus complexity and other physical characteristicswhile manipulating emotional valence of visual stimuli. They showed increased acti-vation for aversive stimuli in high order visual areas. However, they failed to controlfor arousal and attention. Other studies controlled visual features by manipulatingfacial expression (Breiter et al., 1996; Critchley et al., 2000a; Dolan and Morris, 2000).Still, it is unclear whether facial expression evokes emotion in the same manner asthe nonexpressive features of visual stimuli. Furthermore, the question remains asto the extent of sensory brain reactivity to the emotional aspect of stimuli and theeffect of individual life experience on the modulation of sensory cortex by emotiveaspects of the stimulus. To investigate both questions, brain signals were measuredby fMRI in response to visual stimuli of different emotive load and in relation toemotional life experience.

Previous work has demonstrated that comparing neural activation betweenrepeated and nonrepeated conditions can enhance fMRI resolution and producesignificant differences where actual signal change does not. This approach, calledfMR-adaptation (fMR-A), evaluates the extent of signal decay that is attributable tostimulus repetition, and thus provides a measure of brain sensitivity (Grill-Spectoret al., 1999; Grill-Spector and Malach, 2001). High order visual cortex was shown tobe particularly sensitive to this manipulation. (Grill-Spector et al., 1999; Jiang et al.,2000). fMR-A was applied here to detect effects of emotion in relation to the natureof reactivity of high order visual cortex.

Our paper presents two fMRI studies. The aim of the first study was to test theemotional effect of nonexpressive visual stimuli on activation in high order visual cor-tex in healthy volunteers. The study manipulated emotional attributes of visual stim-uli while keeping visual features and attention load largely the same (Rotshtein et al.,2001). We used human faces as visual stimuli, because these offered well-definedstructures with distinct features and organization. We took advantage of an Expres-sional Transfiguration (ET) effect by adapting the Thatcher Illusion (Thompson,1980), in which inversion of the eyes and the mouth in a face—while keeping most ofthe elements of the stimuli unchanged—produced a marked change in its emotionalvalence.

The aim of the second study was to examine the effect of negative emotionalexperience on the activation of visual cortex. Stressful life experiences have beenshown to affect brain structure and function (Bremner, 1999; Haley et al., 2000). Aparticularly striking condition for such investigation is Posttraumatic Stress Disorder(PTSD), where specific past experience involving a death threat to oneself or to othersis accompanied by intense fear and helplessness. This is followed by recurrent revivalof trauma-related sensations that occur either spontaneously or in response to a slightreminder. The vividness of such sensations evokes overwhelming, intense unpleasant

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feelings, and is experienced as flashbacks (American Psychiatric Association, 1987).It was lately suggested that disturbance in sensory processing might play a significantrole in the development of PTSD symptoms (Newport and Nemeroff, 2000). Forexample, studies applying sensory evoked potentials showed that PTSD differedfrom controls in reactivity to deviant auditory stimuli. Moreover, this difference wasdetected at the early processing stages of auditory pathway (Morgan and Grillon,1999). Thus, some of the PTSD phenomenology could be related to disturbed sensorygating in the brain and through that to emotion-induced perceptual biases. It istherefore assumed that PTSD manifests an interaction between sensory processingand emotional experience. We tested this assumption in an fMRI study that wasdesigned to measure fMR-A in relation to combat-specific stimuli in PTSD and non-PTSD veterans.

EXPRESSIONAL-TRANSFIGURATION (ET) EXPERIMENT

To explore the impact of the emotional manipulation on brain activity, whilecontrolling for features and arousal, we conducted the ET experiment.

Materials and Methods

Subjects

Sixteen healthy volunteers (ages 23–49; 10 males) participated in the fMRIexperiment. All subjects signed an informed consent form that was approved byTel Aviv Sourasky Medical Center and Tel Aviv University ethical committees. Onesubject was excluded from the final analysis because of successive head movement.

Visual Stimuli

The baseline visual stimuli consisted of 40 photographs of faces, presented inclose-up, front view. From the above, four types of faces were created by adobePhotoshop 5.0 on a PC computer (Fig. 1(a)). Faces were achromatic and a red fixationpoint was added in the center of the image. These images comprised the “original”faces condition. The ET faces conditions were obtained by rotating the eyes andthe mouth of each original face by about 180◦. The original and ET faces, turnedupside down, created the conditions of the inverted-original and the inverted-ETfaces respectively. Four of the faces—used in the repeated presentation conditions—had an additional version in which their overall contrast level was reduced by 15%because of task requirements (see below). This was not expected to affect activationin high order visual areas (Grill-Spector et al., 1998b).

Stimulus Judgment Experiment

Fifteen subjects (six of them also participated in the fMRI experiment) viewedall faces (4 types× 38 faces) in a random order on a PC screen. They were requested

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Fig. 1. Type of stimuli and paradigm for ET experiment. (A) Example of the type of stimulipresented during the experiment. (B) Repetition manipulation of paradigm: each face type waspresented in two conditions – Different (Diff) or repeated (Rep) condition. In the Rep condition,one presentation differed slightly in contrast: this difference is presented (see Materials andMethods for more details). (C) The sequence of blocks: each stimuli type appeared in fourblocks for the upright-Rep conditions, three times for the inverted-Rep conditions and twice inthe Diff conditions, alternating with epochs of blank. Altogether a run lasted 504 s. Up: Upright;In: Inverted; Or: Original.

to rate each stimulus on two scales: a Bizarreness scale and an Emotional Expe-rience scale. The rationale underlying the Emotional Experience scale was thatemotional experience could be reduced into two orthogonal processes of valenceand arousal. Valence related to direction of emotional behaviour (i.e., positive ornegative) and arousal to the intensity of emotional response regardless of its di-rection (Lang et al., 1995). Accordingly, we converted the measures obtained by thebipolar Emotional Experience scale into two unipolar subscales: An Unpleasantness

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Fig. 2. Stimulus judgment of ET experiment. Emotional and bizarreness judgments wereperformed on all the pictures. Judgment was based on 5-point self-rating scales (see Mate-rials and Methods for the procedure). (A) The rating obtained for bizarreness (white) andcalculated scores for unpleasantness (dark gray). (B) The calculated scores for emotionalload measure.

(valence) scale, measuring the distance from positive, and an Emotional Load(arousal) scale, measuring the distance of the emotional response from neutral foreither positive or negative valence.

Statistical analyses were performed using STATISTICA software (Version 5.0)in a two-way ANOVA for repeated measures, where ET manipulation and inversionwere the factors.

fMRI Experimental Procedure

Visual stimuli were presented in a block design fashion. Epochs consisted ofeither different pictures (Diff) or repeated pictures (Rep) conditions (Fig. 1(b)).In the Rep condition the same picture was presented 15 times, while in the Diffcondition, 15 different pictures from the same type were presented. The epochswere separated by 6–9 s during which subjects viewed a fixation point on a graybackground (Fig. 1(c)). Each condition was presented 2–4 times within each scansession, in a design that balanced for the order of conditions. Stimuli presentationrate was 1 Hz (0.9 s a face interposed with 0.1 s blank). A 100 ms blank of meanluminance interposed between consecutive images to match the interimage transientsin all blocks. The stimuli sequences were generated on PC and projected via an LCDprojector (Epson MP 7200) onto a translucent tangent screen located on the head coilin front of the subject forehead. Subjects viewed the screen through a tilted mirrorfixed to the head coil. To equally engage the observer’s attention across conditions,subjects in both experiments were asked to fixate on the red point and to performa covert “one-back-matching” task through the whole run. They were instructed toindicate whether two successive images were identical. In the Rep conditions, thedifference was related to the contrast of the stimuli (see Fig. 1(b)), while in the Diffconditions the difference was related to identity of image. In each epoch, 3–4 (out of15) stimuli created these differences.

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MRI Setup

Imaging was performed on GE 1.5 T Sigma Horizon LX 8.25 echo speed scan-ner (Milwaukee, W1) with resonant gradient echoplanar imaging system. All im-ages were acquired using a standard quadrature head coil. The scanning sessionincluded anatomical and functional imaging. The anatomical 17 contiguous, axialT1-weighted slices of 4-mm thickness, 1-mm gap, were prescribed, based on the sag-ital localizer, covering the whole brain except the most dorsal and ventral tips. Inaddition, a 3D spoiled gradient echo (SPGR) sequence, with high resolution, was ac-quired for each subject, to allow volume statistical analyses of signal changes duringthe experiment. Functional T2∗-weighted images were acquired (at the same loca-tions as the spin-echo T1-weighted anatomical images) in runs of 2856–2890 images(168–170 images per slice). fMRI acquisition parameters were as follows: TR/TE/Flipangle = 3000/55/90◦; with FOV 24 × 24 cm2 matrix size 80 × 80.

Data Analysis

fMRI data were processed using BrainVoyager 4.1 and 4.4 software package(Goebel et al., 1998a,b). For each subject, comparison of the raw functional datawith the 2D structural scan enabled an estimate of the extent of signal dropoutattributable to susceptibility artifact. Functional images were then superimposed onthe 2D anatomical images and incorporated into the 3D data sets through trilinearinterpolation. The complete data set was transformed into Talairach space (Talairachand Tournoux, 1988). Preprocessing of functional scans included head movementassessment (scans with head movement >1.5 mm were rejected), high frequencytemporal filtering and removal of linear trends. To allow for T2∗ equilibration effects,the first six images of each functional scan were rejected. Lateral occipital complex(LOC) was defined as a region of interest for each individual subject on this basis ofanatomical landmark and functional localizer. Anatomically it includes the lateraloccipital complex, extending to the fusiform gyrus. This region is located anterior toearly retinotopic visual areas (for more details see Grill-Spector et al., 1998a), and wasshown to be relatively more sensitive to objects than nonobjects (Malach et al., 1995;Grill-Spector et al., 2000). The representation of the vertical and horizontal visual fieldmeridians were mapped on the basis of anatomical and functional characteristics foreach subject, to establish the location of retinotopic areas (DeYoe et al., 1996; Tootellet al., 1996). Details of this procedure can be found elsewhere (Grill-Spector et al.,1998a). Voxels that showed significant activation (r > 0.5) for visual stimuli (GLMcontrast all stimuli as positive predictors; Friston et al., 1995) in the nonretinotopicareas were collected for farther statistical analysis (Fig. 3). Note that this functionaldefinition for region of interest (ROI) does not impose any a priori assumptions onthe behavior of the time course.

Statistical analysis applied to the averaged time courses of activation in all voxelswithin the predetermined ROI. Analyses were performed using STATISTICA soft-ware (Version 5.0). Significance tests were performed on the average signal for eachcondition over the whole epoch (i.e., 15 s per 5 MR images). ANOVA for repeatedmeasures was performed separately for each orientation with category (ET/original)and picture condition (Diff/Rep) as factors.

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Fig. 3. Region of interest in high order visual cortex. Parametric maps obtained from onesubject in ET experiment by using General Linear Model (GLM) with contrast of all faces aspositive predictors. Maps are presented in 2D coronal (left), ventral view of unfolded brain(middle), and posterior part of flattened hemisphere (right). Region of interest is marked byorange color: lateral occipital complex (LOC, orange), was defined by anatomical markers(see Materials and Methods). Retinotopic borders are marked in white dotted lines. Blue-greenish color demonstrates other voxels that show similar level of activation (r > 0.5) inresponse to the above contrast.

For each stimuli type, fMR-adaptation (fMR-A) was calculated as an adapta-tion ratio by dividing the Rep condition by its corresponding Diff condition. Thiswas performed separately for each subject. Thus calculated, an fMR-A value of 1indicated no adaptation.

Scatter plots were calculated using Pearson correlation; the average measurefor an individual subject of a condition was plotted for each behavioral rating andfMR-A.

Results

Characterization of Experimental Stimuli

Figure 2 presents the mean values of the behavioral measurements obtained foreach stimulus type. Upright-ET faces were judged to be more bizarre and moreunpleasant than upright-original faces (Fig. 2(a); simple effects in upright faces:Bizarreness: F(1, 14) = 537.46, p < 0.001; Unpleasantness: F(1, 14) = 306.3, p <0.001). The inverted faces (both ET and original) showed intermediate levels ofdeviation from upright faces (Two-way interaction, bizarreness: F(1, 14) = 170.782,p < 0.001; unpleasantness: F(1, 14) = 87, p < 0.001). It is important to note that un-pleasantness and bizarreness scales were highly correlated (r = 0.9). On the otherhand, in the emotional load scale there were no differences between ET and originalfaces, but only an overall inversion effect (Fig. 2(b)): inverted faces were judged tobe less emotionally loaded than upright faces (main effect for inversion: F(1, 14) =79.3, p < 0.001). A trend for positive correlation between activation for the Diffconditions and emotional load was also found (Pearson correlation, r = 0.37, t = 1.9,p = 0.069; not shown), suggesting some relation between emotional load and levelsof activation in LOC for the Diff conditions.

Control of attention was tested by performing a behavioral one-back-matchingtask (in a similar way as for the fMRI experiment). The results showed no significant

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Fig. 4. Activation in high order visual cortex for upright faces in ET experiment. Averagedtime courses presented as percent signal change from baseline (blank epochs): Activation forupright-original faces is marked in blue solid line, and activation for upright-ET faces in reddotted line. (A) Averaged time course obtained in the Diff condition and in the Rep condition.(B) Averaged activation across the whole epoch (15 s). (C) Adaptation ratio (fMR-A) for theupright conditions. The error bars are standard error of the mean (SEM). Asterisks indicatesignificant simple effects.

difference in reaction time (RT) and correct responses between ET and Originalfaces in both the Rep and Diff conditions (not shown).

Effects in High Order Visual Areas

Figure 4 shows the activation time courses and the averaged percent signalchange that was obtained from LOC for the upright faces in Diff and Rep conditions.Clearly, despite the substantial unpleasantness and bizarreness impact of the ETmanipulation (see Fig. 2(a)), it did not significantly affect the overall activation levelfor the Diff conditions in LOC (Fig. 4(a), left curves). Thus, these results argue against

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Fig. 5. Correlation between activation and stimulus judgment. Each point represents the aver-aged adaptation ratio in LOC related to behavioral score of one type of face condition (indciatedby four different colors and symbol).

a gross modulation by valence of stimuli on activation in high order visual areas.The picture changes substantially when the Rep condition is considered: the signaldecreased more in the original face than in the ET faces (Fig. 4(a) right curves andFig. 4(b); two-way interaction between ET manipulation and repetition: F(1, 13) =6.32, p < .05; simple effect for ET manipulation in the Rep condition: F(1, 13) =16.38, p < .01). These effects were also demonstrated as a difference in adaptationratios (see Materials and Methods) presented in Fig. 4(c). There was a significanteffect on fMR-A for the ET manipulation, showing smaller fMR-A for ET faces(i.e., smaller reduction in activation in the Rep condition: F(1, 13) = 12.21, p < .01).Similar effects were obtained for the inverted version of the faces in the Rep conditionand fMR-A.

Correlation Between the fMR-A and the Behavioral Measures

The results presented so far suggest that adaptation level in the LOC might be re-lated to the emotional/perceptual attributes of the stimuli. To test this possibility moredirectly, we plotted the adaptation ratios and behavioral measurements in scatterplots. fMR-A effects in LOC was positively correlated with the degree of bizarrenessand unpleasantness of the same type of face stimuli (Fig. 5: left to right; bizarreness:r = 0.63, t = 3.8, p < 0.01; unpleasantness: r = 0.54, t = 2.97, p < 0.01), suggestingthat more bizarre and unpleasant stimuli showed less fMR-A (i.e. ratio is closer to 1)in LOC. By contrast, emotional load rating was not correlated with adaptation ratio(Fig. 5 right scatter plot).

TRAUMATIC-EXPERIENCE (TE) EXPERIMENT

To examine the effect of experience on emotional modulation in high ordervisual areas we manipulated the content of visual stimuli in relation to traumaticexperience in PTSD and non-PTSD veterans. By applying the same stimuli in twogroups, we were able to examine the effect of emotional experience while controllingfor feature effects.

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Materials and Methods

Subjects

Nineteen male veterans with similar combat experience volunteered to partic-ipate in this experiment; all were interviewed by a psychiatrist (HT). Nine (ages25–63) of them were diagnosed as suffering from combat-related PTSD on the basisof DSM-IV and 10 were non-PTSD (ages 28–54). All subjects signed an informedconsent form that was approved by Tel Aviv Sourasky Medical Center committee.One PTSD veteran was excluded from the final analysis because of lack of responsein the visual cortex.

Visual Stimuli

Stimuli consisted of 68 images of people: mostly close-ups but some wholefigures. Half of the images were of civilian content and the other half were of combatcontent, (Fig. 6(a)). Eight of the pictures (four civilian and four combat)—used in therepeated presentation conditions (Rep, see below). These pictures had an additionalversion in which their overall contrast level was reduced by 15% because of taskrequirements (see ET-experiment’s methods).

fMRI Experimental Procedure

This procedure was similar to the ET experiment’s, but a control first epoch(marked in yellow) was added to the paradigm that was excluded from the final

Fig. 6. Stimuli type and paradigm in the TE experiment. (A) Examples of stimuli content(combat and civilian) shown in the repetition conditions: Different (Diff) or Repeated (Rep)(see Materials and Methods and Fig. 1 for details). (B) The sequence of blocks: each stimulicontent appeared in eight blocks, four in Rep presentation condition and four in Diff condition,alternating with epochs of blank. Altogether a run lasted 318 s.

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analysis, to avoid effect resulting from excitement because of the beginning of theexperiment (Fig. 6(b)).

MRI Setup

Parameters were similar to the ET-experiment’s. The only difference was theexperiment length, which was 1872 images (106 images per slice).

Data Analysis

Analysis procedures were similar as in the ET experiment, based on individualsubject analysis. LOC was defined as ROI based on the anatomical and functionallocalizers, separate for each subject. Functional localizer for LOC was defined in aseparate experiment (Hendler et al., 2001) as voxels that show relatively stronger ac-tivation for objects than for scrambled images. Voxels that show significant activation(r > 0.4) for the GLM contrast objects as positive predictors and scrambled imagesas negative predictors were collected for farther analysis. Note that as in the ETexperiment this ROI was defined using an orthogonal contrast that does not imposea priori assumptions on the behavior of the time course. ANOVA for mixed designwith group (PTSD/non-PTSD) as between factor and repetition as within factor, wasperformed using STATISTICA 5.0 software.

Results

Effects in High Order Visual Areas

Figure 7(a) shows the averaged time course of activation obtained from LOCfor the combat (upper row) and civilian (lower row) stimuli presentation in PTSDand non-PTSD. As in the ET experiment, a significant signal reduction was observedfor the Rep conditions as related to the Diff conditions, across stimuli content andgroup. In addition, overall, PTSD showed less reduction in signal for the Rep con-ditions than non-PTSD veterans, however this effect was a statistical trend onlyfor the combat-related stimuli (Fig. 7(a); F(1, 16) = 3.63, p = 0.074). To further ex-plore this effect fMR-A was calculated for each subject as in the ET experiment(Fig. 7(b)). This revealed a similar effect, in which PTSD showed less fMR-A adap-tation than non-PTSD only for combat stimuli (F(1, 16) = 3.7, p = 0.072). In orderto demonstrate this specific group difference in response to Rep-Combat, we createdstatistical parametric maps across subjects, separately for each group (Fig. 8), usingGLM’s contrast analysis. When contrasting within each group between civilian-Repand combat-Rep conditions in LOC, the PTSD group showed a dominant distributionof combat-Rep activation (red clusters), while non-PTSD had a similar distributionof civilian- and combat-Rep activation (green and red clusters).

DISCUSSION

Our results demonstrate that the interplay between emotion and perceptionis reflected in visual cortex activation. By manipulating both stimuli valence and

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Fig. 7. Averaged time course of activation in high order visual cortex for combat (upperraw) and civilian stimuli (lower raw) in TE experiment. Averaged activation is presentedas percent signal change from baseline (blank epochs). Activation for combat-relatedstimuli in upper row (red), and for civilian-related stimuli in lower row (green). (A)Averaged time course obtained for the Diff and Rep conditions, PTSD red line, non-PTSD black line. (B) Adaptation ratio (fMR-A) for PTSD (filled bar) and non-PTSD(white bar). The error bars are standard error of the mean (SEM). Asterisks indicatesignificant simple effects.

presentation procedure, we were able to probe on the sensitivity of the visual cortexto emotive aspects of the stimuli while controlling for feature effects. Emotionaleffects were not reflected in the overall activation of high order visual areas, but onlyin the adaptation to repeated presentation (fMR-A). Furthermore, PTSD differedfrom non-PTSD veterans (in high order visual cortex activation) only in the degreeof adaptation to repeated presentation of trauma-related stimuli. Thus, it is suggestedthat traumatic experience could modulate the reactivity of visual cortex to traumaticaspects of stimuli. Both findings point toward possible plasticity mechanisms in highorder visual cortex that are based on the emotional attributes of stimuli.

Feeling or Features Effect in High Order Visual Cortex

The overall activation in LOC was found to be insensitive to face transfiguration(the ET manipulation), while the level of adaptation to ET faces was lower than to

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Fig. 8. Parametric maps of Rep condition for PTSD and non-PTSD veterans (a and b respec-tively). Each map was obtained by using a general linear model (GLM) of contrast on the Repcondition (combat vs. civilian). Maps are presented in a ventral view of inflated brain. The redclusters represent area of significantly by more activation to combat than civilian stimuli in theRep condition. The Green clusters represent the opposite. Note that the group maps differed inthe amount of red clusters, suggesting less adaptation for combat stimuli in PTSD.

original faces. Furthermore, adaptation ratio correlated with changes in the emo-tional valence and bizarreness of the perceived faces (Fig. 5). Similar results werereported by Sugase et al. (1999), who showed that neurons in inferior temporal cortexof monkeys (corresponding to the LOC in humans) were activated for a longer dura-tion when presented with faces with negative expressions than when presented withfaces with positive or neutral expressions. A related finding has also been reportedby Ohman et al. (1974), who employed autonomic measures and showed slow habit-uation for negative stimuli. Two plausible mechanisms may account for the reducedadaptation for ET faces. A top-down modulation is possible if the negative valenceproduced a special cognitive value, perhaps through association with threat, whichcould prevent neurons in the visual cortex from adapting. The amygdala formationcan be a possible candidate for initiating this modulation. Anderson and Phelps(2001) have shown that healthy subjects had lower perceptual threshold for negativestimuli than for neutral stimuli, and that this hypersensitivity was lacking when test-ing a patient with a bilateral amygdala lesion. We have also showed (Rotshtein et al.,in press) that the amygdala was more sensitive than the visual cortex to emotionalmanipulation. Thus, unlike the high order visual areas, the amygdala did show a signif-icant increase in overall activation to upright-ET, as compared with upright-originalfaces. Furthermore, LOC activation was to be significantly correlated with amyg-dala activation during ET presentation (Rotshtein et al., in press). This, of course, is

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consistent with the proposed role of the amygdala in the processing of negative emo-tion (Aggelton and Young, 2000; Ledoux, 1996, 2000), as has been demonstrated re-peatedly in neuropsychological (Adolphs et al., 1994, 1995; Anderson and Phelps,2001; Bechara et al., 1995; Calder et al., 1996; LaBar et al., 1995; Young et al.,1993, 1995, 1996), neurophysiological (Davis, 1992; Ledoux, 1996), and neuroimagingstudies (Breiter et al., 1996; Critchley et al., 2000a; Dolan and Morris, 2000; Lane et al.,1999; Morris et al., 1996, 1998; Phillips et al., 1997; Taylor et al., 2000).

Alternatively, the reduced LOC adaptation to ET faces may have been due toperceptual, nonemotional factors related to subtle feature or configurational aspectsof the images. For example, the rating of bizarreness could have been based on theestimation of the distance of a face from prototype, resulting in relatively inefficientprocessing. A reduction of MR signal is thought to be related to more efficientprocessing of stimuli, similar to repetition priming (Buckner et al., 1998; Miller et al.,1993; Rolls, 2000; Wiggs and Martin, 1998). In our study, the distance of ET facesfrom the prototype could impair processing and result in less fMR-A.

Another plausible explanation of the fMR-A modulation by ET is an attentiondifference between ET and original faces. It could be that, while subjects attendedcontinuously to the ET faces because of their bizarreness, they gradually lost interestin the original faces because of their regularity. This possibility was not supported byour behavioral measurement of attention, since no significant differences in the reac-tion time and correct response were found between ET and original faces. However,we cannot rule out the possibility of some effect of attention that was not shownstatistically by our behavioral results but could be suggested by the slight overallslower RT to ET than to original faces (Rotshtein et al., in press).

Emotion or Arousal Modulation in High Order Visual Cortex

Despite the fact that the ET-upright manipulation elicited a dramatic changein a subject’s evaluation of unpleasantness and bizarreness, we did not see differ-ential levels of activation in LOC (Figs. 2 and 4), contrary to previous reports onemotional effect in visual cortex (Kosslyn et al., 1996; Lane et al., 1997, 1999; Langet al., 1998; Reiman et al., 1997; Taylor et al., 1998, 2000). This disagreement could,perhaps, be explained by several differences in perceptual and attentional aspectsin the respective experimental designs. In our study, we applied a behavioral task ofone-back-matching, which was almost equally demanding in terms of attention forboth face types (original and ET), as was shown by lack of difference in reactiontimes to these stimuli. Another possible difference may be related to the amount ofemotional load associated with the stimuli, which in the present study was similar forpositive and negative valence (Fig. 2(b)). Emotional load could be associated withlevels of arousal (Lang, 1995; Taylor et al., 2000) and, through this, affect levels ofactivation in high order visual areas (Critchley et al., 2000b). The correlation foundhere only in the Diff condition between emotional load and LOC activation suggeststhat arousal, more than negative valence, may have contributed to the previouslyreported changes in overall activation in high order visual areas.

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Trauma or Arousal Effect in High Order Visual Cortex

In the second experiment, we were able to demonstrate that it is not just theemotional experience (negative attributes of stimuli) that generates differences in vi-sual cortex activation but also a previous experience of a life-threatening (traumatic)event and the subsequent development of PTSD. It is interesting to note that therewas no overall group effect in activation of visual cortex, but rather in relation toadaptation effect with combat stimuli. Again, the effect of PTSD in the visual cortexwas specific to trauma-related stimuli (i.e., combat) only in fMR-A (less adaptation),and not in overall activation differences (Fig. 7(b)). On the basis of our previous ETexperiment, it is suggested that the trauma-related effect in the adaptation ratio ofvisual cortex in PTSD is more related to the emotional valence than to the emotionalload (i.e., arousal) of the combat stimuli.

These findings are in accord with previous evoked-response potential studiesshowing less neuronal habituation when PTSD subjects were asked to ignore combatstimuli (Attias et al., 1996; Bleich et al., 1996). Our findings suggest that such reducedadaptation to trauma-related stimuli could originate in the reactivation of sensorycortex, and subsequently to the evocation of emotional memories by the stimuli. Therelation between remembering and sensory cortex reactivation was demonstrated byfMRI in healthy subjects (Wheeler et al., 2000). It was shown that while subjects weretrying to recall previously presented auditory or visual stimuli, the specific sensorycortical regions were activated. Furthermore, the activated regions were composedof a subset of voxels that were activated during a separate perception task (i.e.,viewed or heard the stimuli). Furthermore, previous neuroimaging studies in PTSDshowed increased activation in high order visual cortex during the performance ofan imagery task of previous traumatic experience (Rauch et al., 1966). It is thusplausible to assume that at least some of the increased sensitivity of visual cortexto combat-related stimuli in PTSD (i.e. less fMR-A) is related to the reactivation oftraumatic memories. It was shown that PTSD patients tended to exhibit an implicitmemory bias for primed—relative to unprimed—combat words. Moreover, on a cuedrecall task, PTSD subjects showed poorer memory than controls, except for combatwords (Zeitlin and McNally, 1991). Another indication of such disturbed elaborationof trauma-related memory was shown by the tendency of PTSD patients to have adelayed response to trauma-related words in a “stroop” paradigm (Thrasher et al.,1994). Taken together, these data suggest that trauma-related representations arehighly elaborated and readily or even chronically reactivated in PTSD. This idea issupported by our finding of less signal adaptation to combat stimuli in PTSD alreadyat the sensory level of information processing. The decreased adaptation could not beexplained by greater familiarity or expertise because our control group (non-PTSDveterans) had similar preexposure to combat experiences. It is rather an indicationfor neuronal plasticity following traumatic experience.

The finding of group effect on fMR-A supports the explanation of top-downmodulation of visual cortex. Both groups were stimulated by exactly the same pic-tures; thus, any difference between them could not be feature-related, but ratherexperience- or processing-related. It has been argued that negative valence that isassociated with a stimulus produced a special cognitive construct, perhaps through

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the experience of threat (Lang, 1977). The activation of such an emotional–cognitiveconstruct could be more extensive when trauma-related stimuli are processed inPTSD, and this could prevent neurons in the visual cortex from adapting througha top-down modulation. Whether such modulation is related to a pretraumatic per-sonality bias or other biological predispositions is an issue for future prospectivestudies.

To sum up, our research shows a complex and highly specific emotion-perceptioninteraction already at the sensory systems. It does so in two very different, but comple-mentary paradigms, one that manipulates the emotional valence of stimuli, and onethat “manipulates” the emotional responsiveness to traumatic content, of differentsubject groups. We suggest that fMRI research is remarkably applicable to clarify-ing neurophysiological, neurological, and psychological issues in an integrated brainresearch frame.

ACKNOWLEDGMENTS

This study was funded by grants from Adams Super Center for Brain Research,Tel Aviv University, to U. Hadar and T. Hendler, and by the Israel Science Foundation(grant no. 38507) to T. Hendler. We thank Y. Yeshurun for essential help with runningand analyzing the PTSD study, R. Malach for valuable ideas and comments, A. Bleichand T. Weizmann for referring the PTSD patients, I. Levy for her help with theretinotopic mapping, M. Harel for help with the brain flattening, D. Ben Bashatfor her physicist’s insights, and I. Kahn for his homemade software. Finally, we aregrateful to all the subjects and especially to the PTSD veterans who volunteered toparticipate in the various experiments.

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