Association of Resting Metabolism in the Fear Neural Network With Extinction Recall Activations and Clinical Measures in Trauma-Exposed Individuals

Abstract

Objective:

Exposure-based therapy is an effective treatment for posttraumatic stress disorder (PTSD) that relies upon extinction learning principles. In PTSD patients, dysfunctional patterns in the neural circuitry underlying fear extinction, which includes the amygdala, hippocampus, dorsal anterior cingulate cortex (dACC) and ventromedial prefrontal cortex (vmPFC), have been observed using resting-state or functional activation measures. It remains undetermined whether resting activity predicts activations during extinction recall or PTSD symptom severity. Moreover, it remains unclear whether trauma exposure per se (as studied by comparing trauma-exposed non-PTSD to trauma-unexposed participants) affects resting activity in this circuitry. Here we employed a multi-modal approach to examine the relationships among resting metabolism, clinical symptoms, and activations during extinction recall.

Methods:

Three cohorts were recruited: PTSD patients (n=24), trauma-exposed non-PTSD (TENP) participants (n=20), and trauma-unexposed healthy comparison (HC) participants (n=21). Participants underwent a resting PET-FDG scan 4 days prior to an fMRI fear conditioning and extinction paradigm.

Results:

Amygdala resting metabolism negatively correlated with clinical functioning (as measured by the GAF scale) in the TENP group, whereas hippocampal resting metabolism negatively correlated with clinical functioning in the PTSD group. In the PTSD group, dACC resting metabolism positively correlated with PTSD symptom severity, and it predicted increased dACC, but decreased hippocampal and vmPFC activations during extinction recall. The TENP group had lower amygdala resting metabolism compared to PTSD and HC, and it exhibited lower hippocampus resting metabolism relative to HC.

Conclusions:

Our data show that resting metabolism in the fear circuitry correlates with functioning, PTSD symptoms, and extinction recall activations, further supporting the relevance of this network to the pathophysiology of PTSD. Our findings also highlight the fact that chronic dysfunction in the amygdala and hippocampus is demonstrable in PTSD and other trauma-exposed individuals, even without exposure to an evocative stimulus.

INTRODUCTION

The pathophysiology of posttraumatic stress disorder (PTSD) has been heavily examined within the past several decades using different imaging modalities such as positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) (1–7). In the laboratory, a number of experimental paradigms have been employed to uncover the dysfunctional brain circuits that contribute to persistent fear and anxiety symptoms commonly observed in PTSD patients. Pavlovian fear conditioning and extinction is one of those paradigms that has been studied translationally across various species as well as in PTSD patients (5; 8). The advantages and relevance of this model to PTSD are two-fold. First, fear conditioning is relevant to the cause of PTSD. Second, exposure-based therapy, an effective form of PTSD treatment, relies heavily on the principles of fear extinction and its retention (recall). As such, further examination of the brain network underlying fear extinction could improve our understanding of PTSD and contribute to improved PTSD therapies (9).

During fear conditioning, a neutral cue predicts an aversive event that causes an unconditioned fear response. After several trials, an association is formed between the neutral cue and the negative outcome, and the presentation of the neutral cue alone comes to elicit conditioned fear responses. Subsequent multiple presentations of the cue without any reinforcement lead to fear extinction (10). Animal and human neuroimaging studies of fear extinction learning and its recall have identified an essential network of regions that includes amygdala, hippocampus, ventromedial prefrontal cortex (vmPFC), and dorsal anterior cingulate cortex (dACC) (11–17). Compared to trauma-exposed participants, patients with PTSD show normal within-session extinction learning but impaired extinction recall when tested after a delay (18–20), as well as an impaired ability to inhibit fear in presence of a safety signal (21). The impairments in extinction recall and contextual safety signal processing observed in PTSD have been associated with vmPFC and hippocampus hypoactivation, and with dACC and amygdala hyperactivation (20; 22–24). Dysfunctional resting state activity in these same brain regions has also been reported. Specifically, studies examining resting regional cerebral blood flow in individuals suffering from PTSD have reported hyperactive amygdala (25; 26) and dACC (27), but hypoactive mPFC (26).

Although much has been learned about neural circuits contributing to the pathophysiology of PTSD, knowledge gaps remain. The relationships among PTSD symptoms, resting state alterations, and abnormal functional brain activity have not been examined within the same individuals. It would be informative to learn whether alterations in resting regional brain functioning are related to variations in extinction recall in PTSD. No previous studies have measured both resting brain glucose metabolism and fear extinction-related functional activation within the same PTSD subjects. In addition, few previous studies have examined the effect of trauma exposure per se on resting activity and activation in the extinction network. The majority of published studies have employed either trauma-exposed non-PTSD groups, or non trauma-exposed groups, but not both groups simultaneously.

In the present study, trauma-exposed individuals with PTSD and trauma-exposed non-PTSD (TENP) individuals underwent a clinical interview to determine diagnostic status, symptom severity, and level of functioning, as measured by the Global Assessment of Functioning (GAF) scale. Using ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET), resting brain glucose metabolism was assessed in all participants. Approximately 4 days later, participants underwent a 2-day fear conditioning and extinction paradigm during functional magnetic resonance imaging (fMRI). Skin conductance responses (SCRs) were measured as a psychophysiological index of fear, and fMRI blood-oxygen-level-dependent (BOLD) signal was measured as a marker of functional regional brain activation. Previously published data on trauma-unexposed healthy participants who had undergone the same paradigm were also used for between-group comparisons (28). We hypothesized that in the trauma-exposed groups, resting glucose metabolism in the nodes of the fear extinction network would relate to clinical outcomes and to functional activations in the same brain regions during extinction recall. We also hypothesized the presence of differences among the 3 groups in resting glucose metabolism and extinction recall functional activations in amygdala, hippocampus, dACC, and vmPFC.

METHODS

Participants

Forty-four right-handed individuals aged 18 to 65 were recruited from the community. Of these, 24 met criteria for current PTSD diagnosis, and 20 were trauma-exposed non-PTSD (TENP). For the PET and fMRI between-group analyses, we also included 21 healthy comparison (HC) participants who had not been exposed to trauma, for whom the PET-fMRI results have already been published (28)). For a full description of the sample and a list of exclusion criteria, see Supplemental Materials and Table S1.

Procedure (Figure S1)

All subjects provided written informed consent for participation after a full explanation of the procedures, a detailed description of which is provided in the Supplemental Materials. Briefly, participants were first interviewed by the study diagnostician. They then underwent a PET-FDG scan during which brain glucose metabolism was obtained as a measure of resting brain activity (28). Approximately 4 days later, they took part in a 2-day fear conditioning and extinction paradigm during fMRI (11; 17; 18; 23; 24; 28). This paradigm consisted of a habituation phase in context A, followed by a conditioning phase also in context A, during which the participant viewed one of three different-colored lamps (CS+s), two of which were partially reinforced by an electrical stimulation to the index finger (US). The third colored lamp (CS−) was never reinforced. Immediately after conditioning, extinction training took place in context B. One of the CS+ stimuli (designated the CS+E) was repeatedly presented (along with the CS−) in the absence of the US. The following day, extinction recall (retention) was tested in context B by presenting the CS+E, the non-extinguished CS+ (designated the CS+NE), and the CS−.

Data Processing

Imaging:

All coordinates reported are based on the Montreal Neurological Institute (MNI) system. Region of interest (ROI) analyses were performed for both PET and fMRI. The Anatomical Automatic Labeling atlas (29) was used to define amygdala and hippocampus, and data were extracted bilaterally. The vmPFC was defined as a 5mm sphere centered at MNI_xyz= 5,35,-13, whereas the dACC was defined as a 5mm sphere centered at MNI_xyz= 2,22,29. The coordinates and the sphere size for the vmPFC and the dACC were based on our previous studies (17; 28; 30). For details on the treatment and processing of the PET-FDG and fMRI data, see Supplemental Materials.

Psychophysiological Data:

SCR to each stimulus was computed by subtracting the mean skin conductance level observed during the last 2 seconds of context alone preceding CS onset from the maximal skin conductance level reached during CS presentation. All SCR values were square root-transformed prior to analysis. To evaluate extinction recall, an extinction retention index (ERI) was computed for each individual using the following formula: (100 – [(mean SCR to the first 4 CS+E trials during recall / maximum SCR reached during conditioning for this same cue]) * 100.

Clinical Data:

PTSD symptom severity was calculated by adding the frequency and intensity scores for each item on the Clinician-Administered PTSD Scale (CAPS) for DSM-IV. A total CAPS severity score, and scores for each cluster of symptoms (re-experiencing, avoidance/numbing, hyperarousal), were calculated. The DSM-IV Global Assessment of Functioning (GAF) Scale was assessed in both trauma-exposed groups. GAF scores range between 0 and 100, with higher scores signifying better functioning. Because the CAPS scores were all close to zero in the TENP group, the GAF offered the advantage of measuring functioning in trauma-exposed participants. Therefore, GAF scores were analyzed for both trauma-exposed groups, whereas CAPS scores were analyzed only in the PTSD group.

Data Analysis

In order to determine whether glucose resting metabolism within the a priori defined nodes of the fear extinction network predicts functional activation in that same circuit during extinction recall, FDG values within the predefined ROIs were used as regressors for the fMRI contrast (whole-brain voxel-wise analysis). This was done for each of the trauma-exposed groups separately. Because the same analytic approach was already published for HC, we did not include this group in these analyses. For the early CS+E vs. early CS+NE BOLD contrast, the following extracted PET FDG values were used as a single regressor in separate analyses: i) average of left and right amygdala, ii) average of left and right hippocampus, (iii) dACC, and iv) vmPFC. An initial criterion of p<0.005, with a minimum of 10 contiguous voxels, was used to detect positive or negative correlations between resting FDG measures and BOLD signal during extinction learning and recall in the following brain regions: amygdala, hippocampus, dACC and vmPFC. Clusters detected within these regions that survived small volume family-wise error (FWE) correction (p<0.05) were considered significant. After conducting the PET-fMRI analyses within each group, follow up interaction tests were conducted to test between-group differences in this measure (PET-fMRI correlations). A threshold of p<0.005 with 10 contiguous voxels was applied.

In order to investigate differences between the trauma-exposed (TENP) and trauma-unexposed (HC) comparison groups, for the 4 fear extinction network ROIs (averaged left and right amygdala, averaged left and right hippocampus, dACC, and vmPFC, separately), ANCOVAs were performed on the extracted PET resting glucose metabolism data, using group as the between-subjects factor and age and years of education as covariates (given that these variables show significant group differences – see Supplemental). If the ANCOVA revealed a significant main effect of group at a p<0.05 level, Tukey LSD post-hoc tests were run on the estimated marginal means (controlled for age and years of education) to identify significant group differences.

RESULTS

Sample characteristics (Table S1)

A Fisher exact probability test confirmed that gender did not significantly differ among the three groups, p>0.05. One-way ANOVAs revealed the presence of a significant group difference for age, F_(2,61)=8.0, p=0.001 and years of education F_(2,57)=13.1, p<0.001. Scheffe’s post-hoc t-tests confirmed that the HC group was significantly more educated than the two trauma-exposed groups and younger than the PTSD group, all ps ≤0.05. All analyses investigating differences among these three groups therefore included age and years of education as covariates. An independent samples t-test was performed on CAPS scores between the two trauma-exposed groups and confirmed significantly higher PTSD symptom severity in PTSD, p<0.001.

Psychophysiological data

An independent samples t-test performed on extinction retention index (ERI) revealed that the PTSD group tended to exhibit lower ERI than the TENP group, t₍₂₆₎=1.79, p=0.086 (Figure 1A). After applying a Bonferroni correction for multiple comparisons (0.05 / 4 ROIs = 0.0125), no correlations between ERI and PET data from each ROI survive, in either trauma-exposed group.

Figure 1.

Extinction retention and Global Assessment of Functioning (GAF) results. (A) depicts extinction retention index (%) exhibited on the second day as a function of group (p=0.086). (B) illustrates the GAF score as a function of group. (C) depicts a significant correlation between PET resting glucose metabolism in the amygdala and GAF scores in TENP subjects whereas (D) depicts a significant correlation between the PET resting glucose metabolism in the hippocampus and GAF scores in PTSD participants. The grey bars or circles represent the trauma-exposed non-PTSD (TENP) group and the black bars or circles represent the post-traumatic stress disorder (PTSD) group. Asterisk indicates a significant difference, using a threshold of p<0.05 for A and B and p<0.05/4 = 0.13 for C and D given the Bonferroni corrections.

Clinical Data

An independent samples t-test confirmed significantly lower GAF scores in PTSD relative to TENP, t₍₃₈₎=11.40, p<0.001 (Figure 1B). We correlated the GAF scores with resting metabolism from each ROI for both trauma-exposed groups separately, using a Bonferroni correction (0.05 / 4 ROIs = 0.0125). PET resting metabolism in the amygdala was negatively correlated with GAF scores in the TENP group, r₍₁₇₎=−0.563, p=0.012 (Figure 1C) whereas PET resting metabolism in the hippocampus was negatively correlated with GAF scores in the PTSD group, r₍₁₉₎=−0.530, p=0.013 (Figure 1D).

When correlating PTSD symptom severity with resting metabolism extracted from the four ROIs of the fear extinction network in the PTSD group separately, no significant results were found. We therefore performed a supplemental whole-brain analysis to assess the relationship between glucose metabolism in the nodes of the fear extinction network and PTSD symptoms. Whole-brain analysis performed on PET-FDG data using total CAPS score as a regressor revealed a positive association in two different areas of the dACC (MNI_xyz= 18,14,32, cluster size=410, t₍₁₇₎=4.05, p_FWE=0.016 and MNI_xyz= 18,−8,38, cluster size=410, t₍₁₇₎=4.22, p_FWE=0.012) (Figure 2A). No associations were found with re-experiencing symptoms (Figure 2B). Avoidance symptoms were positively associated with resting metabolism in the dACC (MNI_xyz= 14,−6,42, cluster size=62, t₍₁₇₎=3.72, p_FWE=0.007) and the rostral ACC (rACC) (MNI_xyz= 16,44,8, cluster size=32, t₍₁₇₎=3.28, p_FWE=0.016) (Figure 2C). Finally, hyperarousal scores were positively associated with dACC resting metabolism (MNI_xyz= 16,-6,44, cluster size=70, t₍₁₇₎=3.44, p_FWE=0.014) (Figure 2D).

Figure 2.

Voxel-wise analyses: Resting glucose metabolism as a predictor of CAPS symptoms in the PTSD group. (A) indicates both dACC areas that show a positive correlation with total symptom severity (total CAPS) in PTSD participants. (B) indicates there is no significant relationship between re-experiencing symptoms and PET resting metabolism in the nodes of the fear extinction network. (C) indicates the dACC and the rACC regions that show a positive correlation with avoidance symptoms (C cluster on the DSM-IV CAPS). (F) indicates the dACC area that shows a positive correlation with hyperarousal symptoms (D cluster on the CAPS). All correlations between resting metabolism and symptom severity were positive. A display of p=0.005 is used for all results.

PET predicting BOLD during extinction recall in trauma-exposed groups

Amygdala (Figure 3 upper panel):

Figure 3.

PET resting metabolism in the subcortical regions predict functional activations in the nodes of the fear extinction network during extinction recall in trauma-exposed individuals with and without PTSD. The upper panel depicts how resting glucose metabolism in the amygdala predicts dACC, vmPFC, hippocampus and rACC activations in TENP participants. No significant findings were found in the PTSD participants. The lower panel depicts how hippocampus resting metabolism predicts its own functional activation in the PTSD participants. No significant findings were found in the TENP participants. All fMRI images are displayed at a threshold of p=0.005. For the PET images, the ROIs are indicated in green. Hot colors indicate positive associations.

For TENP, resting metabolism in amygdala positively predicted activations in the following regions: dACC (MNI_xyz= −12,20,46, cluster size=10, t₍₁₃₎=3.48, p_FWE=0.007), vmPFC (MNI_xyz= −12,60,−6, cluster size=19, t₍₁₃₎=4.10, p_FWE=0.012), hippocampus (MNI_xyz= 28,−18,−16, cluster size=79, t₍₁₃₎=5.56, p_FWE=0.001) as well as rACC (MNI_xyz= −2,40,16, cluster size=27, t₍₁₃₎=4.06, p_FWE=0.005). No significant findings were found in PTSD group.

Hippocampus (Figure 3 lower panel):

For TENP, no significant results were found. For PTSD, hippocampus resting glucose metabolism predicted its own activation (MNI_xyz= −32,−14,−20, cluster size=27, t₍₁₆₎=3.67, p_FWE=0.008).

vmPFC (Figure 4 upper panel):

Figure 4.

PET resting metabolism in the cortical regions predict functional activations in the nodes of the fear extinction network during extinction recall in trauma-exposed individuals without PTSD and with PTSD. The upper panel depicts how resting glucose metabolism in the vmPFC predicts posterior hippocampus activation in both TENP and PTSD participants. Resting metabolism of the vmPFC was also predictive of dACC activation in the TENP group. The lower panel depicts how dACC resting metabolism predicts functional activation in the dACC and the hippocampus in the TENP group. For the PTSD participants, dACC resting metabolism was predictive of vmPFC, hippocampus and dACC activations. All fMRI images are displayed at a threshold of p=0.005. For the PET images, the ROIs are indicated in green. Hot colors indicate positive associations whereas cold colors indicate negative associations.

For TENP, vmPFC resting metabolism negatively predicted posterior hippocampus (MNI_xyz= −28,−36,−12, cluster size=11, t₍₁₃₎=3.85, p_FWE=0.005) and dACC activations (MNI_xyz= 12,24,38, cluster size=19, t₍₁₃₎=3.62, p_FWE=0.009). For PTSD, vmPFC resting metabolism negatively predicted posterior hippocampus activations (MNI_xyz= 22,−42,−4, cluster size=19, t₍₁₆₎=4.02, p_FWE=0.003).

dACC (Figure 4 lower panel):

For TENP, dACC resting metabolism negatively predicted its own activation (MNI_xyz= 12,26,36, cluster size=26, t₍₁₃₎=3.54, p_FWE=0.013) and activation in the posterior hippocampus (MNI_xyz= 30,−38,−8, cluster size=34, t₍₁₃₎=3.62, p_FWE=0.013). For PTSD, dACC resting metabolism positively predicted its own activation (MNI_xyz= −8,10,42, cluster size=24, t₍₁₆₎=3.28, p_FWE=0.015) and negatively predicted activation in the vmPFC (MNI_xyz= 14,38,−30, cluster size=372, t₍₁₆₎=5.67, p_FWE=0.002) and the hippocampus (MNI_xyz= 24,−10,−26, cluster size=19, t₍₁₆₎=3.29, p_FWE=0.012).

Between-group PET FDG differences (Figure 5)

Figure 5.

PET-FDG resting glucose metabolism between-group differences. The bilateral amygdala (A) and bilateral hippocampus (C) were anatomically defined whereas we used 5mm spheres for the dACC (E) and the vmPFC (G) using functional activation coordinates from previous papers. Extracted FDG metabolism is depicted as a function of group for each node of the fear extinction circuit (B: averaged left and right amygdala, D: averaged left and right hippocampus, F: dACC and H: vmPFC). Global mean normalization of data at 50. All results are controlled for age and years of education. The white bars represent the non-traumatized healthy comparison (HC) group, the grey bars represent the trauma-exposed non-PTSD (TENP) group and the black bars represent the PTSD group. Error bars are S.D. Asterisk indicates p<0.05. rCMRglu: regional cerebral metabolic rate for glucose, units: μmol/min/100g.

We then added the previously published data from healthy non-trauma-exposed comparison (HC) participants. One-way ANCOVAs performed on FDG values from the 4 nodes of the fear extinction network yielded a main effect of group for bilateral amygdala, F_(2,55)=3.97, p=0.025 and bilateral hippocampus F_(2,55)=3.26, p=0.012. Post-hoc tests revealed that the TENP group had lower resting metabolism in the amygdala relative to PTSD and HC groups, both ps≤0.044, as well as lower hippocampal resting metabolism when compared to the HC group, p=0.004. There was no main effect of group for the dACC and the vmPFC, both ps>0.05.

For a report of between-group fMRI differences during extinction recall, see Supplemental Results.

DISCUSSION

In a multi-modal imaging study, we gathered PET-FDG, fMRI BOLD, psychophysiological, and clinical measures from trauma-exposed participants with and without a PTSD diagnosis. We also added previously published data from a group of healthy comparison participants and tested between-group differences within each imaging modality to unveil the effects of trauma exposure and diagnosis on resting metabolism and reactivity of the fear extinction network during extinction recall. When focusing on the trauma-exposed groups, resting metabolism in the amygdala and the hippocampus was associated with global functioning. In the PTSD group, dACC resting metabolism was associated with PTSD symptom severity and was also predictive of activation patterns during extinction recall that have been shown to be characteristic of PTSD psychopathology. At rest and during extinction recall, between-group differences were observed. Lower resting metabolism in the amygdala and the hippocampus was observed in the trauma-exposed non-PTSD group, whereas hypoactivation of the vmPFC during extinction recall was observed in the PTSD group. Together, these results suggest that resting metabolism in the nodes of the fear extinction network is correlated with both self-reported and biologically based clinically relevant measures in trauma-exposed individuals. Importantly, the alterations observed in the resting metabolism of the amygdala and hippocampus indicate that trauma-exposed individuals with and without PTSD show long-lasting signs of perturbations in brain function, even in the absence of stimuli probing the fear circuitry or the recall of the trauma.

The inclusion of a non-traumatized healthy comparison group enabled us to examine the effects of trauma exposure and diagnostic status on both resting metabolism and functional activation during extinction recall. Our results showed that the TENP group had lower amygdala resting metabolism when compared to HC and PTSD and lower hippocampal resting metabolism relative to HC. Importantly, PTSD patients have often been compared only to a trauma-exposed non-PTSD group. Therefore, the elevated amygdala resting metabolism is often thought to be an acquired sign of PTSD or to be a pre-existing vulnerability to develop the psychopathology. However, in the current study, the resting metabolism of the amygdala and the hippocampus in the PTSD group was similar to that of the HC group. This suggests that reduced glucose metabolism in TENP could reflect a resilience factor (e.g., trauma exposure might lead to reduced amygdala and hippocampus resting metabolism only in resilient individuals). Interestingly, in the TENP group, amygdala resting glucose metabolism was negatively associated with level of functioning as measured by Global Assessment of Functioning (GAF) scores. This further supports the point that suppressing resting metabolism in the amygdala following trauma-exposure might be a key resilience factor to prevent the development of PTSD and to improve functioning. In PTSD, lower hippocampus resting metabolism was associated with better functioning. When focusing on between-group differences during extinction recall, PTSD individuals exhibited lower vmPFC activation relative to TENP and HC. For this comparison, the TENP group did not differ significantly from the HC group. These data suggest that lower vmPFC activation during extinction recall might be a characteristic of PTSD, rather than trauma exposure per se. While the comparison between PTSD and TENP replicates previous findings from our group and other laboratories (20; 23–24), the addition of the HC group adds an extra layer of information suggesting that trauma exposure per se does not significantly affect the ability to activate the vmPFC during extinction memory recall. Taken together, these results suggest that lower resting metabolism in the subcortical regions seems to be associated with resilience following trauma, and that hypoactivation of the prefrontal cortex during extinction recall is a specific characteristic of the PTSD group.

Previous studies from our group and others have shown that individuals with PTSD exhibit poorer extinction memory recall (20; 23). This psychophysiological deficit has also been associated with a distinct pattern of brain activation, in which the vmPFC and the hippocampus are hypoactive but the dACC is hyperactive. As mentioned earlier, we replicated the finding pertaining to the hypoactivation of the vmPFC during extinction recall. Moreover, we replicated the psychophysiological finding at a trend level, by demonstrating lower extinction retention in the PTSD group when compared to the TENP group. A key finding of the current study is that, for the PTSD group, dACC resting metabolism predicted functional activations during extinction recall that were lower in vmPFC and hippocampus, but higher in dACC. This suggests that dACC resting metabolism could potentially serve as a predictor of the typical neural activation patterns observed in PTSD individuals during extinction recall. Importantly, when performing whole-brain analyses with PTSD symptom severity in the PTSD group, we found that dACC resting metabolism was positively associated with overall symptom severity, avoidance, and hyperarousal symptoms. Taken together, these data suggest that higher resting metabolism in dACC is associated with the altered pattern of activation during extinction recall that has been shown to be characteristic of PTSD and is also associated with greater PTSD symptom severity. After conducting interaction analyses to compare differences in correlation patterns between groups (see Table S2), we found that dACC resting metabolism was the node from which most of the interactions were yielded, suggesting that resting metabolism in that brain region predicts more distinct patterns between the two trauma-exposed groups.

Previous twin studies (27; 31) suggested that resting glucose metabolism and functional activation within the dACC are elevated in PTSD and may reflect a familial vulnerability factor for developing this disorder rather than an acquired feature of trauma exposure or PTSD. Our data are in apparent contradiction with those reported in the above studies given that we did not observe a significant between-group difference in dACC resting metabolism. One possible reason is that our sample was relatively young (PTSD group’s mean age=39.8, TENP group’s mean age=34.1) and consisted of men and women exposed to different types of trauma. In contrast, the twin study consisted of older men (PTSD group’s mean age=57.8, TENP group’s mean age=57.1) exposed specifically to combat-related trauma. Thus, age at testing, type of trauma, age at trauma onset, and sex differences may all be factors contributing to the apparent discrepancy between findings. In addition, the coordinates used for dACC in our study are different from the ones reported in the twin study. Despite these differences, the data are converging to show that dACC resting metabolism is an important correlate of neural activations and PTSD symptom severity. This supports previous data from one of the twin studies that not only demonstrated a positive correlation between dACC resting metabolism and symptom severity in individuals with PTSD, but also revealed a positive correlation between dACC resting metabolism in unexposed co-twins and their brothers’ PTSD symptom severity (27).

The current study’s limitations should be considered when interpreting the data. First, the HC group was significantly younger than the PTSD group and better educated relative to both trauma-exposed groups. However, controlling for these factors by covariance analysis should have mitigated the influence of these factors on our findings. Moreover, although each group is large enough to allow group comparisons, the sample size does not allow us to divide participants as a function of sex, age and other demographic variables that may impact the results. This is worthy of noting here, given that there are differences between the types of trauma in the TENP and PTSD groups. Larger groups would allow us to disentangle the contributions of such variables. Finally, the sample size for each group was not constant across the various analyses, due to movement in the scanner, data quality, and drop-out. These limitations highlight the need for replications of the current findings before drawing definitive conclusions.

The intricacy of the current results reflects the complex influence that trauma exposure and PTSD have on the neural circuitry mediating extinction recall. By incorporating two comparison groups differing in trauma history, our data enabled us to identify distinct patterns of resting metabolism and neural activation as a function of trauma exposure and diagnosis. This allows a better understanding of how trauma exposure affects the brain independently of PTSD symptoms and therefore helps to shed light on the biological underpinnings of the disorder. Our findings support the importance of examining resting metabolism in the fear extinction network. In fact, our results highlight that the neural effects of trauma exposure and PTSD diagnosis can be observed at rest, without probing the network with fear-related stimuli. Our findings also highlight the utility of examining resting metabolism in the nodes of the fear extinction network to predict activations in that same network during extinction recall. Given the established relationship between extinction and exposure-based therapy and the fact that individuals with PTSD show impairments in extinction recall at the psychophysiological and neural levels, it is crucial to identify predictors of such dysfunctional patterns to better inform treatment. Our data suggest a relationship between dACC resting metabolism and both PTSD symptom severity and the dysregulated pattern of brain activation observed in PTSD during extinction recall. Therefore, we suggest that dACC resting metabolism should be further examined as a potential biomarker for PTSD. Therapeutic interventions or brain stimulation techniques could be studied in the future as potential modifiers of resting brain metabolism. If successful, these targeted techniques could potentially be used to improve clinical outcomes in trauma-exposed individuals.