Arousal Dissociates Amygdala and Hippocampal Fear Responses: Evidence from Simultaneous fMRI and Skin Conductance Recording

NeuroImage 14, 1070 –1079 (2001) doi:10.1006/nimg.2001.0904, available online at http://www.idealibrary.com on

Arousal Dissociates Amygdala and Hippocampal Fear Responses: Evidence from Simultaneous fMRI and Skin Conductance Recording Leanne M. Williams,* ,† Mary L. Phillips,‡ Michael J. Brammer,‡ David Skerrett,§ Jim Lagopoulos,¶ Chris Rennie,† ,§ ,㛳 Homayoun Bahramali,† ,** Gloria Olivieri,†† Anthony S. David,‡ Anthony Peduto,†† and Evian Gordon† ,** *The Brain Dynamics Centre, §Department of Medical Physics, Nuclear Medicine and Ultrasound, and ††MRI Unit, Department of Radiology, Westmead Hospital, Westmead NSW, 2145, Australia; †Department of Psychology, 㛳School of Physics, and **Department of Psychological Medicine, University of Sydney, NSW, 2006, Australia; ‡Institute of Psychiatry, London, De Crespigny Park, London SE5 8AZ, United Kingdom; and ¶Neuroscience Institute of Schizophrenia and Allied Disorders (NISAD) Received February 20, 2001

The experience and appraisal of threat is essential to human and animal survival. Lesion evidence suggests that the subjective experience of fear relies upon amygdala-medial frontal activity (as well as autonomic arousal), whereas the factual context of threat stimuli depends upon hippocampal-lateral frontal activity. This amygdala-hippocampus dissociation has not previously been demonstrated in vivo. To explore this differentiation, we employed functional magnetic resonance imaging (fMRI) and simultaneous skin conductance response (SCR) measures of phasic arousal, while subjects viewed fearful versus neutral faces. fMRI activity was subaveraged according to whether or not the subject evoked an arousal SCR to each discrete face stimulus. The fMRI-with arousal and fMRIwithout arousal data provided a distinct differentiation of amygdala and hippocampal networks. Amygdala-medial frontal activity was observed only with SCRs, whereas hippocampus-lateral frontal activity occurred only in the absence of SCRs. The findings provide direct evidence for a dissociation between human amygdala and hippocampus networks in the visceral experience versus declarative fact processing of fear. © 2001 Academic Press Key Words: fMRI; amygdala; hippocampus; arousal; fear; facial emotion.

INTRODUCTION We sought to examine whether distinct neural substrates underpin the experiential versus factual processing of fear in the human brain. Animal and lesion studies suggest that threatening or traumatic stimuli are processed in parallel by two distinct neural systems (Bechara et al., 1995; Le Doux, 1998; Wehner et al., 1997). The implicit emotional system relies upon activation of the amygdala, particularly in threat-re1053-8119/01 $35.00 Copyright © 2001 by Academic Press All rights of reproduction in any form reserved.

lated emotional responses, fear conditioning, and the appraisal of fearful facial expressions (Adolphs et al., 1994; Calder et al., 1996; Le Doux, 1998; Sprengelmeyer et al., 1999; Wehner et al., 1997). By contrast, the explicit system is dependent upon the hippocampus to remember the “cold hard” declarative facts of the threat stimulus, and to establish its context (Bechara et al., 1995; Le Doux, 1998; Wehner et al., 1997). This conceptualisation of the fact network is consistent with models in which the hippocampus functions as a comparator for the context, rather than the content, of threat-related sensory input (Davidson et al., 2000; Gray, 1987). Primates are distinguished from nonprimates by the planning and executive control of their automatic fear reactions. Limbic structures (including amygdala, hippocampus) are thought to be modulated by the frontal executive networks (Goldberg, 1989), which have shown the largest development in humans (Aboitiz and Garcia, 1997). The medial frontal region receives significant projections from the amygdala, and may be activated directly by “feeling” system information in its response to threat (Damasio, 1996; Rolls, 1985). In contrast, the lateral frontal cortex receives considerable innervation from the hippocampus (with only meagre amygdala connections) and may be involved in forming cortical representations of the factual context of threatening stimuli in working memory (GoldmanRakic, 1987; Le Doux, 1998). There are a number of additional interconnections between frontal and limbic networks (Mai et al., 1997). We focused on the proposed dissociation of amygdala-medial and hippocampus-lateral frontal systems, since the functional differentiation of these networks has not yet been elucidated in vivo in the human brain. To explore this dissociation we used functional neuroimaging (functional magnetic resonance imaging; fMRI) with on-line measurements of autonomic arousal.

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Previous functional neuroimaging studies of human fear perception have not addressed the amygdala versus hippocampus distinction. These studies have focused on demonstrating amygdala activity in response to fear stimuli, particularly facial expressions of fear (Brieter et al., 1996; Morris et al., 1996; Phillips et al., 1997, 1999; Whalen et al., 1998) and aversive conditioning of faces (Buchel et al., 1998). Concomittant hippocampus activity was therefore not considered in those studies employing region of interest (amygdala) analyses (e.g., Buchel et al., 1998). When hippocampal activity was observed in voxel-by-voxel analyses, we have previously reported it as part of a combined amygdala/hippocampus complex (e.g., Phillips et al., 1999). Most neuroimaging studies have also relied upon the analysis method of averaging across neural responses to fear stimuli. This is a sound method, but does not allow for disentangling of distinctive neural subsystems (such as amygdala and hippocampus) that have overlapping responses within the same recording trial. Our on-line arousal recording provided an independent index to extract and subaverage neural activity associated with amygdala versus hippocampal network processing of fear stimuli. The amygdala system is distinguished by the automatic activation of visceral (bodily) responses, that may underlie the gut feeling of fear (Damasio, 1995). These responses include increases in autonomic nervous system arousal (such as sweating, heart rate, blood pressure) and the release of stress hormones (Le Doux, 1998). Arousal responses, triggered by the amygdala, provide reciprocal feedback to the amygdala that is essential to sustaining the feeling of fear. The coactivation of amygdala with arousal systems is thought to allow the cortex to distinguish fear signals from other arousal responses to novel stimuli (Damasio, 1995; Le Doux, 1996). Damasio’s (1995) somatic marker hypothesis proposes that bodily (somatic) arousal can also be represented as a cognitive disposition (“as if” state), that feeds back to the amygdala via the medial frontal cortex. In this study, we obtained electrodermal skin conductance responses (SCRs), as an index of autonomic arousal. SCRs provide a robust measure of phasic increases in sweat rate (Boucsein, 1992) and were recorded simultaneously with fMRI using our customised MRI-compatible SCR system (Williams et al., 2000). The on-line arousal data allowed us to subaverage fMRI responses according to whether or not subjects evoked an SCR to individual fear stimuli. Our sigmoidexponential SCR analysis model allows overlapping SCRs to be disentangled (Lim et al., 1999) and therefore makes it possible to link individual face stimuli to concomitant SCRs (see Materials and Methods for details). During fMRI scanning, healthy volunteer subjects viewed standardised grey-scale pictures of faces, de-

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picting fearful and neutral expressions (Calder et al., 1997; Phillips et al., 1997; see Figs. 1A and 1B). fMRI data were analysed first by block design averaging, in which presentations of fearful faces were contrasted with neutral faces. In the subsequent subaveraging analysis, single-trial fear faces associated with SCRs and without SCRs were extracted separately from the same dataset. fMRI activity generated by fearful faces that evoked an SCR was contrasted to fMRI activity associated with fear faces that did not evoke an SCR. Analyses were conducted using non-parametric voxelby-voxel statistical mapping, rather than a region of interest approach, to ensure that activation observed in specific anatomical locations was relative to the whole brain. On the basis of previous block design neuroimaging studies of threat stimuli, we hypothesized that the averaged contrast of fear versus neutral would reveal specific activity to fear in both amygdala and hippocampal regions of the limbic system. From lesion evidence, we proposed that in the single-trial subaveraged analysis, with-SCR responses to fear stimuli would be associated specifically with amygdala-medial frontal activity, whereas without-arousal responses to fear would be associated with activity in hippocampus-lateral frontal networks. MATERIALS AND METHODS Subjects Eleven right-handed healthy volunteers (all male; mean age, 30 years; mean NART IQ estimate, 112) participated in the study. Data for a twelfth subject was excluded due to lack of electrodermal responses. Other exclusion criteria included history of psychiatric illness, neurological disorder or head injury, and current intake of regular medication, drugs, or alcohol. Experimental Design During the fMRI scanning session, subjects viewed the faces of eight different individuals, from a standardized set of prototype facial expressions of emotion (Calder et al., 1997; Phillips et al., 1997). The eight faces depicting fear were presented one at a time on a computer screen in randomized order, followed by eight randomized neutral faces. The experiment comprised eight separate presentation blocks of fear (block A) and neutral (block B). Blocks A and B were presented alternately, and the first block (A or B) was counterbalanced across subjects. Individual faces were presented for 3 s, with an interval of 0.75 s between each face. The duration of each presentation phase was 30 s. An additional block of eight neutral faces was presented before the experimental stimuli (but not included in subsequent analyses) as a means of controlling for initial SCRs produced as a result of stimulus novelty.

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FIG. 1. Brain activation maps for the block design analysis, in which prototypical fear (A) faces were contrasted to neutral (B) faces. The activation maps were derived using voxel-by-voxel averaging of the individual EPI images of all 11 subjects, following transformation into standardized space. Significant (P ⬍ 0.001) activation in the right amygdala is marked in C as A (x ⫽ 25 mm, y ⫽ ⫺4 mm, z ⫽ ⫺11 mm). Activation in the hippocampus (marked as Hi) is also shown in C (x ⫽ 18 mm, y ⫽ ⫺21 mm, z ⫽ ⫺11 mm). A coronal view of the activation map is shown in D. Activation maps are shown in the radiological view. Additional areas of ativity include the fusiform (GF), inferior temporal (GTi), and the anterior cingulate gyrus (CG). Reprinted by permission from Nature (Phillips et al., 1997), Macmillan Magazines Ltd.

For each face stimulus, the explicit task was to make a sex classification (male or female) by pressing one of two buttons with the right thumb. Postscan briefings confirmed that subjects were not aware of the implicit emotion manipulation. All 11 subjects were able to perform correctly on this task (range: 87.5–100%). Image Acquisition and Statistical Analysis Echoplanar MR images were acquired using a Siemens 1.5 Tesla Magnetom VISION Plus system. T2*weighted images depicting BOLD contrast (Bihan and Karni, 1995) were acquired for each face stimulus at 18 axial noncontiguous 6-mm-thick planes (slices), parallel to the intercommissural (AC–PC) line (total of 64 images at each slice): TE 40 msec, TR 3 s, matrix 128 ⫻

128, interslice gap 0.6 mm. This protocol provided whole-brain coverage. Prior to analysis, images were preprocessed to minimise the effects of subject motion and remove low frequency confounds (Brammer et al., 1997; Bullmore et al., 1999). The experimental design was then convolved with two Poisson functions representing haemodynamic delays of 4 and 8 s. The best fit (least-squares) weighted sum of these two convolutions was then computed at each voxel (Friston et al., 1998), yielding coefficients a and b (scaling factors for each convolution) and allowing hemodynamic delays to be automatically accommodated. The sums of squares attributable to the fitted time series (SSQfit) and residuals (SSQresid) were then cal-

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FIG. 2. The sigmoid-exponential skin conductance response (SCR) model (Lim et al., 1997) allows overlapping SCRs (as depicted above) to be decomposed and scored for both peak amplitude and latency (indicated by arrows). The modeled SCRs are curve-fitted to the actual SCRs using the parameters; time at which reponse starts, gain factor, rise time, time constant of the decay, constant (skin conductance level) and size of tail of previous SCR.

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positive activations that might result from multiple comparisons. Experimental contrasts were conducted by first calculating the difference between the mean SSQratios at each voxel for the contrast of interest across all subjects who took part in the study. To form the null distribution the data for each block (or phase) of the contrast were first combined and then randomly reallocated between the blocks. The random reallocation and recalculation analysis procedures used in this study permits estimation of the null distribution of mean differences. This distribution may be sampled with ease at any selected Type I error rate (as described above). Moreover, this permutation process makes no assumptions whatsoever about the form of the null distribution, but generates it directly from the observed data. Intra-subject variance before Talaraich mapping is accounted for in the process of standardisation for each individual subject. The present procedure for considering intra-subject variance (in which SSQratio represents a standardised effect) is equivalent to the classical adjustment for random effects in the parametric analysis methods. MR data were analysed first as a blocked design (contrast of fear versus neutral in the experimental design). An event-related analysis was then undertaken for the contrast of fear faces that evoked an arousal response (SCR) versus those that did not. SCR Acquisition and Statistical Analysis

culated and the ratio of these two sums of squares (SSratio) determined. This ratio was redetermined 10 times at each voxel, following multilevel, waveletbased permutation of the data (Bullmore et al., 2001). The SSQratio estimates from the permuted data were combined to give the null distribution of SSQratios under the hypothesis that there was no experimentally determined response. This procedure has been shown to give excellent control of nominal Type I error rates in the presence of non-random noise processes in fMRI data. The observed and randomized SSQratio statistic maps were then transformed into the standard space of Talaraich and Tournoux (1988). Median SSQratio maps were constructed at the relevant Type I error probability by thresholding (to the required critical value) the null distribution of median randomised statistics calculated at each voxel (Bullmore et al., 2001). Thus, with 20,000 intracerebral voxels in standard space a voxel-wise Type I error rate of .001 would yield an expectation of 0.001 ⫻ 20,000 ⫽ 20 false activations distributed over the whole Talaraich template. The use of a voxel-wise Type I error rate of 0.001 (which is substantially less than the .05 rate that would normally be used to test at a single voxel) therefore facilitates control of the expectation of false

Electrodermal SCR data were acquired using a skin conductance system, designed specifically to protect against interference from radio frequency pulses in the magnetic resonance environment. This system produced noise-free data that did not require either filtering or smoothing. The utility of this SCR system has been verified in a previous study of visual checkerboard stimuli (Williams et al., 2000). Electrodermal SCRs represent unambiguous changes in arousal level, but can be small in amplitude (traditionally defined as ⬎0.05 microSiemens above baseline; Boucsein, 1992). Therefore, it is essential that they be recorded in a noise-free environment. In the previous fMRI-SCR studies of arousal modulation, the focus has been on far larger SCRs (e.g., 2sd above baseline) that were not linked directly to discrete stimuli. These studies have therefore relied on standard GSR systems and postprocessing of SCR data (Critchley et al., 2000). Skin conductance was recorded using a pair of silversilver chloride electrodes with 0.05 M sodium chloride gel placed on the distal phalanges of digits II and III of the left hand. SCR data were analyzed using a Skin Conductance Response Evaluation System, (SCORES), based on a sigmoid-exponent model of phasic and tonic arousal that represents the SCR in mathematical form (Lim et

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TABLE 1 Regions of Activity for Fear vs Neutral and Arousal Contrasts Side

xa

ya

za

P

L L L L R R R L R R L L R R R L R R L L R R L R L

⫺40 ⫺47 ⫺51 ⫺4 11 18 25 ⫺32 51 11 ⫺29 ⫺25 51 54 25 ⫺25 18 18 ⫺11 ⫺18 11 18 ⫺36 11 ⫺7

⫺74 ⫺70 ⫺60 ⫺70 ⫺77 22 4 ⫺32 ⫺23 ⫺42 ⫺56 ⫺14 ⫺32 ⫺14 ⫺4 ⫺7 ⫺21 ⫺22 42 ⫺18 ⫺24 ⫺18 ⫺63 ⫺56 ⫺52

⫺11 ⫺8 ⫺8 20 27 20 32 36 32 0 ⫺33 4 8 4 ⫺11 ⫺8 ⫺11 ⫺8 24 18 4 50 24 8 18

0.000004 0.000004 0.000008 0.0001 0.00008 0.000008 0.000008 0.0001 0.000004 0.000008 0.000004 0.000004 0.000004 0.000004 0.00008 0.001 0.000004 0.000004 0.0003 0.000004 0.0002 0.00005 0.005 0.000004 0.001

R R R L

14 58 25 ⫺24

32 ⫺32 ⫺24 ⫺7

38 38 42 ⫺11

0.001 0.0008 0.005 0.001

Anterior cingulate gyrus (BA24) Fusiform gyrus (BA18) Hippocampus

L L R

18 ⫺32 7 ⫺47 ⫺29 ⫺4 ⫺16 29 29

⫺18 ⫺66 ⫺77 4 14 22 ⫺88 ⫺21 ⫺23

15 ⫺24 ⫺14 30 11 24 ⫺14 ⫺14 ⫺11

0.000009 0.000005

Lateral frontal cortex (BA44)

R L R L

Area Fear (contrasted to neutral) responses Fusiform/inferior temporal/middle occipital gyri (BA18/19/37)

Parieto-occipital sulcus (BA18) Anterior cingulate gyrus (BA24) Lateral frontal cortex (BA44) Inferior parietal lobule (BA40) Cerebellum Putamen Superior temporal gyrus (BA22) Amygdala Hippocampus Medial frontal cortex (BA9) Thalamus Primary Motor Middle temporal gyrus (BA19) Posterior cingulate gyrus (BA23) Fear with-arousal responses Medial frontal cortex (BA8) Inferior parietal lobule (BA40) Primary motor Amygdala Fear without-arousal responses Thalamus Cerebellum

0.00001 0.001 0.0001 0.0008 0.002 0.001

a The cluster with the largest number of voxels within each region is reported. Talaraich coordinates (x, y, z, in millimeters) refer to the voxel with the maximum FPQ in each cluster.

al., 1997; see Fig. 2). The segments of electrodermal data containing composite skin conductance signals and often overlapping responses were decomposed into phasic SCRs and tonic skin conductance level (SCL) components using the curve-fitting procedures of this sigmoid-exponent model. SCRs were defined as an unambiguous increase in skin conductance of ⬎0.05 microSiemens with respect to each prestimulus baseline, and occuring 1–3 s after the stimulus (Barry and Sokolov, 1993). The ability of our model to disentangle overlapping SCRs in a short interstimulus interval paradigm overcomes one of the fundamental issues that has plagued

attempts to simultaneously assess SCRs and brain function in cognitive paradigms. Because the time course of phasic SCRs is 4 – 6 s, previous studies have not been able to link SCRs to individual stimuli without introducing poststimulus delays of up to 5 s (e.g., Buchel et al., 1998). Our quantitative SCR method was applied successfully in previous examinations of online arousal with both event-related potential and fMRI recordings, using poststimulus intervals of 0.75 to 1 s (Bahramali et al., 1997; Williams et al., 2000). In this study, with-arousal stimuli were those in which the onset of a phasic SCR occurred within the 3-s stimulus duration. Without-arousal stimuli were clas-

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sified by the failure to detect the onset of an SCR in this period. RESULTS Averaged Fear versus Neutral Contrast For the hypothesized comparison of fear versus neutral control faces, we demonstrated limbic region activity at the voxel-wise probability of type I (false-positive) error, P ⬍ 0.001. Fearful faces produced specific and significant areas of activation in both the bilateral amygdala (right, P ⬍ 10 ⫺4; left, P ⬍ 0.001) and right hippocampus (P ⬍ 10 ⫺5), relative to neutral face blocks (see Figs. 1C and 1D; Table 1). Other areas of significant fear-specific activity included the anterior cingulate gyrus, superior temporal gyrus, thalamus, putamen, cerebellum, fusiform gyrus, and related occipitoparietal, and inferior temporal lobe visual areas (Table 1). On-Line Skin Conductance Responses The presence of an electrodermal SCR was determined by customised software (Skin Conductance Response Evaluation System, SCORES), based on a sigmoid-exponential model of SCRs (Lim et al., 1997) (see Fig. 2). With-arousal fear stimuli were those in which the onset of an arousal SCR occurred within the stimulus duration (3 s), and without-arousal stimuli were those that did not evoke an SCR in this period (see Materials and Methods for details of SCR analysis). The mean number of fear stimuli associated with an SCR was 7.0 ⫾ 2.4, and the mean amplitude of these SCRs was 0.12 ⫾ 0.04 microSiemens. Additional analyses were conducted to ensure that SCRs followed a randomised distribution, and were not evoked only in particular stimulus blocks (for example, only in the initial blocks) or to select individual fear face stimuli. Chi-squared analyses confirmed that the eight individual fear face stimuli were not differentially associated with number of SCRs [␹ 2 (2I) ⫽ 27.64, P ⫽ 0.15], and that SCRs were not distributed differentially across the four stimulus blocks [␹ 2 (9) ⫽ 6.62, P ⫽ 0.68]. Additionally, one-way ANOVAs ensured that the mean SCR amplitude did not differ according to either face stimulus [F (7,70) ⫽ 0.50, P ⫽ 0.83] or stimulus block [F (3,74) ⫽ 1.21, P ⫽ 0.31]. Figure 3A provides a graphical display of the random spread of SCRs across face stimuli the 11 individual subjects and Fig. 3B shows the random distribution of SCR amplitude across trials for each subject. Subaveraged With-Arousal versus Without-Arousal Contrast fMRI subaveraging analysis for the hypothesised dissociation between amygdala and hippocampal net-

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works was also conducted at a voxel-wise error level of P ⬍ 0.001. Fear faces that evoked an arousal response produced significant localized activity in the left amygdala (P ⬍ 0.001) and medial frontal cortex (P ⬍ 0.0005), but not in the hippocampus (Figs. 4A, 4B, and 4D; Table 1). Amygdala responses (represented by the SSQratio values described under statistical analysis above) were observed consistently across the majority of individual subjects (see Fig. 4C). The only other areas of significant neural activity in this fMRI subaverage were the primary motor cortex (P ⬍ 0.005), and inferior parietal lobule (P ⬍ 0.0008, Table 1). By contrast, significant activity observed in response to fear faces that failed to induce an arousal response was restricted to the right hippocampus (P ⬍ 0.001) and lateral frontal cortex (P ⬍ 10 ⫺5) (see Figs. 4E, 4F, and 4H; Table 1). Hippocampal responses also occurred consistently across the individual subjects (see Fig. 4G). Additional areas of response for without-arousal fear responses included only the thalamus, cerebellum, anterior cingulate (P ⬍ 0.001) and fusiform gyrus (P ⬍ 0.002, Table 1). DISCUSSION We undertook simultaneous recording of functional MRI and autonomic arousal (skin conductance measures of sweat rate) to explore the proposed dissociation between amygdala (with-arousal) and hippocampus (without-arousal) networks in response to fear. Our results provide the first direct in vivo evidence in the same individuals to suggest that the amygdala and hippocampal networks subserve distinct yet parallel functions in human fear perception. In line with previous neuroimaging studies of fear stimuli, we first used block design averaging to reveal activation observed during the visual processing of fear faces relative to neutral control faces. As predicted, significant activity was observed in both amygdala and hippocampal regions of the limbic system. The pattern of concomitant activity in anterior cingulate gyrus, superior temporal gyrus, thalamus, putamen, cerebellum, fusiform gyrus, and related occipito-parietal and temporal lobe visual regions is consistent with previous human neuroimaging studies of face and fearful expression stimuli (Brieter et al., 1996; Morris et al., 1996; Phillips et al., 1997; Schmahmann, 2000). The conjunction of activity in the amygdala and thalamus also provides further support for animal evidence that thalamo-amygdala networks underlie the triggering of the amygdala by low-level sensory features of emotional stimuli (Le Doux, 1993). Amygdala-Medial Frontal Network In the subsequent subaveraging analysis of withversus without-arousal fear faces, a clear dissociation between amygdala and hippocampal networks was re-

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FIG. 3. A shows the random distribution of phasic arousal responses (SCRs) across the eight fear face stimuli the 11 individual subjects. The random distribution of the magnitude of arousal responses (SCR amplitude) across each trial for each subject is shown in B.

vealed. Fear faces that evoked increases in phasic arousal (SCRs) were associated with activity in the amygdala and medial frontal cortex, but not in the hippocampus. The observation of left-sided witharousal amygdala activity is consistent the proposal that amygdala responses to fear are sustained by feedback from autonomic arousal (Le Doux, 1998). Indeed, our previous laterality study indicated that left amygdala responses to fear tend to decrease less rapidly than right amygdalar responses (Phillips et al., 2001), and a recent report suggests that the left amygdala is more active in sustained emotional stimulus evaluations (Rauch et al., 2001).

The additional regions of with-arousal activity were constrained to the primary motor cortex and inferior parietal lobule. Activity in these regions is consistent with evidence for a preparatory motor state associated with increased arousal and orienting (Boucsein, 1992; Sokolov, 1990), and the role of amygdala activity and negative emotional arousal in modulating visual cortices (Brieter et al., 1996; Morris et al., 1998). The combination of amygdala, medial frontal and inferior parietal activity also has some overlap with the patterns of activity revealed in studies where complex visual (film) stimuli have been used explicitly to generate emotional responses (Lane et al., 1997; Rieman et al., 1997). In

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FIG. 4. Brain activation maps for the subaveraging analysis in which with-arousal fear faces were contrasted to without-arousal fear faces. Responses to fear were separated according to the presence (Column 1; With-arousal) or absence (Column 2; Without-arousal) of phasic arousal, indexed by electrodermal skin conductance responses (SCRs). In this figure, an example of one block each of SCRs and absence of SCRs for an individual subject is shown to illustrate the fMRI subaveraged analyses. Brain activation maps are for the subaveraging analysis of 11 subjects for the contrast of with-arousal and without-arousal fear stimuli, at P ⬍ .001. With-arousal neural activity was observed specifically in the left amygdala (marked as A) and shown in A (x ⫽ ⫺24 mm, y ⫽ ⫺7 mm, z ⫽ ⫺11 mm) and medial frontal (Medial F) cortex, shown in C (x ⫽ 14 mm, y ⫽ 32 mm, z ⫽ 38 mm). Amygdala responses were observed consistently across subjects (B). Without-arousal activity was observed in the hippocampus (Hi), shown in D (x ⫽ 29 mm, y ⫽ ⫺21 mm, z ⫽ ⫺14 mm) and lateral frontal (Lat. F) cortex, shown in F (x ⫽ ⫺47 mm, y ⫽ 4 mm, x ⫽ 30 mm). Hippocampal activity was also consistent across individual subjects (E). D also depicts the additional without-arousal fusiform gyrus (x ⫽ ⫺16, y ⫽ ⫺88, z ⫽ ⫺14) and cerebellum (x ⫽ 7, y ⫽ ⫺77, z ⫽ ⫺14) activity.

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this study, fear responses might be elicited by a similar mechanism of emotional imagery, triggered by associations with the fear faces. However, amygdala activity is observed consistently across studies of both explicit (via conditioning) and implicit (visual perception) studies of fear stimuli (Morris et al., 1996; Phillips et al., 1997), reflecting the likely role of this structure in both the direct appraisal of potential threat and the secondary appraisal of threat via the recognition of fear in others. Hippocampus-Lateral Frontal Network By contrast, fear faces that did not evoke an SCR (without-arousal) were associated with specific activity in the hippocampus and lateral frontal cortex. As for the averaged analysis, only right hippocampus activity was observed. While this lateralized effect requires replication, it is consistent with evidence that the right hippocampus is dominant in processing visual input (Rogers et al., 1996) and that the right hemisphere is preferentially involved in responding to relatively novel stimuli (Goldberg, 1989). Without-arousal activity in the fusiform gyrus, thalamus, and anterior cingulate gyrus was also observed. The concomitant hippocampus and fusiform gyrus activity accords with blood flow evidence for correlations between these regions in declarative encoding and retrieval processes (Tulving et al., 1999). Our results therefore suggest there may be distinct forms of visual cortex activity in relation to the visceral (amygdala) versus declarative fact (hippocampus) processing of fear. The presence of thalamic activity may reflect the distinct role of the visual thalamus in the spatial location and identification of visual stimuli, by relaying sensory input to the hippocampus and lateral frontal cortex (Desimone et al., 1995; Goldman-Rakic, 1988). Our observation of an arousal differentiation between anterior cingulate (without-arousal) and medial frontal (with-arousal) cortices parallels reports of the dissociable effects of lesions in these regions on emotionrelated reward behaviour (Bussey et al., 1997). The anterior cingulate gyrus is reportedly involved in emotional as well as attentional regulation (Bush et al., 2000), and our results suggest that this role may be effected as part of the hippocampal-lateral frontal network. Implications for Emotion Models The amygdala versus hippocampal network dissociation observed in our study is consistent with LeDoux’s (1993, 1998) emotional memory framework, derived from animal data. In LeDoux’s model, the lateral nucleus of the amygdala (and its connected structures) is critical to implicit responses to the emotional significance of threat, and automatic activation of arousal

and motor systems. The amygdala may subserve sensory-affect integration in emotional learning, which has implications for understanding the mechanism of disorders of anxiety and trauma. By contrast, it is proposed that the hippocampus provides explicit and general contextual cues about incoming threat signals, and may underlie sensory–sensory associations. A differentiation between sensory–affect (amygdala) and sensory–sensory (hippocampus) integration accords with our previous observation of with-arousal hippocampus (but not amygdala) activity in response to nonemotional visual stimuli (Williams et al., 2000). This distinction between the functional roles of the amygdala and hippocampus also accords with Gray’s (1987) model of the limbic system, which distinguishes between the automatic fight–flight response to fear (based on activation of the amygdala), and a behavioral inhibition (stop) system (in which the septo-hippocampal network is the primary site of controlled context processing). Our findings indicate that, in response to fear, the amygdala-medial frontal network is preferentially engaged in the visceral experience of threat, and the hippocampal-lateral frontal network underlies declarative and contextual processing of threat stimuli. ACKNOWLEDGMENTS The research was supported by Australian Research Council and Wellcome Trust Biomedical Collaborative Travel funding. We acknowledge Kryzstoff Kozek for SCORES support and NISAD for infrastructure support.

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