Exploring the impact of biological sex on intrinsic connectivity networks in PTSD: A data-driven approach.

INTRODUCTION: Sex as a biological variable (SABV) may help to account for the differential development and expression of post-traumatic stress disorder (PTSD) symptoms among trauma-exposed males and females. Here, we investigate the impact of SABV on PTSD-related neural alterations in resting-state functional connectivity (rsFC) within three core intrinsic connectivity networks (ICNs): the salience network (SN), central executive network (CEN), and default mode network (DMN). METHODS: Using an independent component analysis (ICA), we compared rsFC of the SN, CEN, and DMN between males and females, with and without PTSD (n = 47 females with PTSD, n = 34 males with PTSD, n = 36 healthy control females, n = 20 healthy control males) via full factorial ANCOVAs. Additionally, linear regression analyses were conducted with clinical variables (i.e., PTSD and depression symptoms, childhood trauma scores) in order to determine intrinsic network connectivity characteristics specific to SABV. Furthermore, we utilized machine learning classification models to predict the biological sex and PTSD diagnosis of individual participants based on intrinsic network activity patterns. RESULTS: Our findings revealed differential network connectivity patterns based on SABV and PTSD diagnosis. Males with PTSD exhibited increased intra-SN (i.e., SN-anterior insula) rsFC and increased DMN-right superior parietal lobule/precuneus/superior occipital gyrus rsFC as compared to females with PTSD. There were also differential network connectivity patterns for comparisons between the PTSD and healthy control groups for males and females, separately. We did not observe significant correlations between clinical measures of interest and brain region clusters which displayed significant between group differences as a function of biological sex, thus further reinforcing that SABV analyses are likely not confounded by these variables. Furthermore, machine learning classification models accurately predicted biological sex and PTSD diagnosis among novel/unseen participants based on ICN activation patterns. CONCLUSION: This study reveals groundbreaking insights surrounding the impact of SABV on PTSD-related ICN alterations using data-driven methods. Our discoveries contribute to further defining neurobiological markers of PTSD among females and males and may offer guidance for differential sex-related treatment needs.

A tale of two targets: examining the differential effects of posterior cingulate cortex- and amygdala-targeted fMRI-neurofeedback in a PTSD pilot study.

Introduction: Real-time fMRI-based neurofeedback (rt-fMRI-NFB) is a non-invasive technology that enables individuals to self-regulate brain activity linked to neuropsychiatric symptoms, including those associated with post-traumatic stress disorder (PTSD). Selecting the target brain region for neurofeedback-mediated regulation is primarily informed by the neurobiological characteristics of the participant population. There is a strong link between PTSD symptoms and multiple functional disruptions in the brain, including hyperactivity within both the amygdala and posterior cingulate cortex (PCC) during trauma-related processing. As such, previous rt-fMRI-NFB studies have focused on these two target regions when training individuals with PTSD to regulate neural activity. However, the differential effects of neurofeedback target selection on PTSD-related neural activity and clinical outcomes have not previously been investigated. Methods: Here, we compared whole-brain activation and changes in PTSD symptoms between PTSD participants (n = 28) that trained to downregulate activity within either the amygdala (n = 14) or the PCC (n = 14) while viewing personalized trauma words. Results: For the PCC as compared to the amygdala group, we observed decreased neural activity in several regions implicated in PTSD psychopathology - namely, the bilateral cuneus/precuneus/primary visual cortex, the left superior parietal lobule, the left occipital pole, and the right superior temporal gyrus/temporoparietal junction (TPJ) - during target region downregulation using rt-fMRI-NFB. Conversely, for the amygdala as compared to the PCC group, there were no unique (i.e., over and above that of the PCC group) decreases in neural activity. Importantly, amygdala downregulation was not associated with significantly improved PTSD symptoms, whereas PCC downregulation was associated with reduced reliving and distress symptoms over the course of this single training session. In this pilot analysis, we did not detect significant between-group differences in state PTSD symptoms during neurofeedback. As a critical control, the PCC and amygdala groups did not differ in their ability to downregulate activity within their respective target brain regions. This indicates that subsequent whole-brain neural activation results can be attributed to the effects of the neurofeedback target region selection in terms of neurophysiological function, rather than as a result of group differences in regulatory success. Conclusion: In this study, neurofeedback-mediated downregulation of the PCC was differentially associated with reduced state PTSD symptoms and simultaneous decreases in PTSD-associated brain activity during a single training session. This novel analysis may guide researchers in choosing a neurofeedback target region in future rt-fMRI-NFB studies and help to establish the clinical efficacy of specific neurofeedback targets for PTSD. A future multi-session clinical trial of rt-fMRI-NFB that directly compares between PCC and amygdala target regions is warranted.

Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium.

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.

'I am afraid you will see the stain on my soul': Direct gaze neural processing in individuals with PTSD after moral injury recall.

Direct eye contact is essential to understanding others' thoughts and feelings in social interactions. However, those with post-traumatic stress disorder (PTSD) and exposure to moral injury (MI) may exhibit altered theory-of-mind (ToM)/mentalizing processes and experience shame which precludes one's capacity for direct eye contact. We investigated blood oxygenation level-dependent (BOLD) responses associated with direct vs averted gaze using a virtual reality paradigm in individuals with PTSD (n = 28) relative to healthy controls (n = 18) following recall of a MI vs a neutral memory. Associations between BOLD responses and clinical symptomatology were also assessed. After MI recall, individuals with PTSD showed greater activation in the right temporoparietal junction as compared to controls (T = 4.83; pFDR < 0.001; k = 237) during direct gaze. No significant activation occurred during direct gaze after neutral memory recall. Further, a significant positive correlation was found between feelings of distress and right medial superior frontal gyrus activation in individuals with PTSD (T = 5.03; pFDR = 0.049; k = 123). These findings suggest that direct gaze after MI recall prompts compensatory ToM/mentalizing processing. Implications for future interventions aimed at mitigating the effects of PTSD on social functioning are discussed.

How the body remembers: Examining the default mode and sensorimotor networks during moral injury autobiographical memory retrieval in PTSD.

Neural representations of sensory percepts and motor responses constitute key elements of autobiographical memory. However, these representations may remain as unintegrated sensory and motor fragments in traumatic memory, thus contributing toward re-experiencing and reliving symptoms in trauma-related conditions such as post-traumatic stress disorder (PTSD). Here, we investigated the sensorimotor network (SMN) and posterior default mode network (pDMN) using a group independent component analysis (ICA) by examining their functional connectivity during a script-driven memory retrieval paradigm of (potentially) morally injurious events in individuals with PTSD and healthy controls. Moral injury (MI), where an individual acts or fails to act in a morally aligned manner, is examined given its inherent ties to disrupted motor planning and thus sensorimotor mechanisms. Our findings revealed significant differences in functional network connectivity across the SMN and pDMN during MI retrieval in participants with PTSD (n = 65) as compared to healthy controls (n = 25). No such significant group-wise differences emerged during retrieval of a neutral memory. PTSD-related alterations included hyperconnectivity between the SMN and pDMN, enhanced within-network connectivity of the SMN with premotor areas, and increased recruitment of the supramarginal gyrus into both the SMN and the pDMN during MI retrieval. In parallel with these neuroimaging findings, a positive correlation was found between PTSD severity and subjective re-experiencing intensity ratings after MI retrieval. These results suggest a neural basis for traumatic re-experiencing, where reliving and/or re-enacting a past morally injurious event in the form of sensory and motor fragments occurs in place of retrieving a complete, past-contextualized narrative as put forth by Brewin and colleagues (1996) and Conway and Pleydell-Pearce (2000). These findings have implications for bottom-up treatments targeting directly the sensory and motoric elements of traumatic experiences.

Homeostatic normalization of alpha brain rhythms within the default-mode network and reduced symptoms in post-traumatic stress disorder following a randomized controlled trial of electroencephalogram neurofeedback.

Collective research has identified a key electroencephalogram signature in patients with post-traumatic stress disorder, consisting of abnormally reduced alpha (8-12 Hz) rhythms. We conducted a 20-session, double-blind, randomized controlled trial of alpha desynchronizing neurofeedback in patients with post-traumatic stress disorder over 20 weeks. Our objective was to provide mechanistic evidence underlying potential clinical improvements by examining changes in aberrant post-traumatic stress disorder brain rhythms (namely, alpha oscillations) as a function of neurofeedback treatment. We randomly assigned participants with a primary diagnosis of post-traumatic stress disorder (n = 38) to either an experimental group (n = 20) or a sham-control group (n = 18). A multichannel electroencephalogram cap was used to record whole-scalp resting-state activity pre- and post-neurofeedback treatment, for both the experimental and sham-control post-traumatic stress disorder groups. We first observed significantly reduced relative alpha source power at baseline in patients with post-traumatic stress disorder as compared to an age/sex-matched group of neurotypical healthy controls (n = 32), primarily within regions of the anterior default mode network. Post-treatment, we found that only post-traumatic stress disorder patients in the experimental neurofeedback group demonstrated significant alpha resynchronization within areas that displayed abnormally low alpha power at baseline. In parallel, we observed significantly decreased post-traumatic stress disorder severity scores in the experimental neurofeedback group only, when comparing baseline to post-treatment (Cohen's d = 0.77) and three-month follow-up scores (Cohen's d = 0.75), with a remission rate of 60.0% at the three-month follow-up. Overall, our results indicate that neurofeedback training can rescue pathologically reduced alpha rhythmicity, a functional biomarker that has repeatedly been linked to symptoms of hyperarousal and cortical disinhibition in post-traumatic stress disorder. This randomized controlled trial provides long-term evidence suggesting that the 'alpha rebound effect' (i.e. homeostatic alpha resynchronization) occurs within key regions of the default mode network previously implicated in post-traumatic stress disorder.

Posterior cingulate cortex targeted real-time fMRI neurofeedback recalibrates functional connectivity with the amygdala, posterior insula, and default-mode network in PTSD.

BACKGROUND: Alterations within large-scale brain networks-namely, the default mode (DMN) and salience networks (SN)-are present among individuals with posttraumatic stress disorder (PTSD). Previous real-time functional magnetic resonance imaging (fMRI) and electroencephalography neurofeedback studies suggest that regulating posterior cingulate cortex (PCC; the primary hub of the posterior DMN) activity may reduce PTSD symptoms and recalibrate altered network dynamics. However, PCC connectivity to the DMN and SN during PCC-targeted fMRI neurofeedback remains unexamined and may help to elucidate neurophysiological mechanisms through which these symptom improvements may occur. METHODS: Using a trauma/emotion provocation paradigm, we investigated psychophysiological interactions over a single session of neurofeedback among PTSD (n = 14) and healthy control (n = 15) participants. We compared PCC functional connectivity between regulate (in which participants downregulated PCC activity) and view (in which participants did not exert regulatory control) conditions across the whole-brain as well as in a priori specified regions-of-interest. RESULTS: During regulate as compared to view conditions, only the PTSD group showed significant PCC connectivity with anterior DMN (dmPFC, vmPFC) and SN (posterior insula) regions, whereas both groups displayed PCC connectivity with other posterior DMN areas (precuneus/cuneus). Additionally, as compared with controls, the PTSD group showed significantly greater PCC connectivity with the SN (amygdala) during regulate as compared to view conditions. Moreover, linear regression analyses revealed that during regulate as compared to view conditions, PCC connectivity to DMN and SN regions was positively correlated to psychiatric symptoms across all participants. CONCLUSION: In summary, observations of PCC connectivity to the DMN and SN provide emerging evidence of neural mechanisms underlying PCC-targeted fMRI neurofeedback among individuals with PTSD. This supports the use of PCC-targeted neurofeedback as a means by which to recalibrate PTSD-associated alterations in neural connectivity within the DMN and SN, which together, may help to facilitate improved emotion regulation abilities in PTSD.

Increased top-down control of emotions during symptom provocation working memory tasks following a RCT of alpha-down neurofeedback in PTSD.

BACKGROUND: Posttraumatic stress disorder (PTSD) has been found to be associated with emotion under-modulation from the prefrontal cortex and a breakdown of the top-down control of cognition and emotion. Novel adjunct therapies such as neurofeedback (NFB) have been shown to normalize aberrant neural circuits that underlie PTSD psychopathology at rest. However, little evidence exists for NFB-linked neural improvements under emotionally relevant cognitive load. The current study sought to address this gap by examining the effects of alpha-down NFB in the context of an emotional n-back task. METHODS: We conducted a 20-week double-blind randomized, sham-controlled trial of alpha-down NFB and collected neuroimaging data before and after the NFB protocol. Participants performed an emotional 1-back and 2-back working memory task, with interleaved trauma-neutral and trauma-relevant cues in the fMRI scanner. Data from 35 participants with a primary diagnosis of PTSD were analyzed in this study (n = 18 in the experimental group undergoing alpha-down NFB, n = 17 in the sham-control group). RESULTS: Firstly, within-group analyses showed clinically significant reductions in PTSD symptom severity scores at the post-intervention timepoint and 3-month follow-up for the experimental group, and not for the sham-control group. The neuroimaging analyses revealed that alpha-down NFB enhanced engagement of top-down cognitive and emotional control centers, such as the dorsolateral prefrontal cortex (dlPFC), and improved integration of the anterior and posterior parts of the default mode network (DMN). Finally, our results also indicate that increased alpha-down NFB performance correlated with increased activity in brain regions involved in top-down control and bodily consciousness/embodied processing of self (TPJ and posterior insula). CONCLUSION: This is the first study to provide mechanistic insights into how NFB may normalize dysfunctional brain activity and connectivity in PTSD under cognitive load with simultaneous symptom provocation, adding to a growing body of evidence supporting the therapeutic neuromodulatory effects of NFB. This preliminary study highlights the benefits of alpha-down NFB training as an adjunctive therapy for PTSD and warrants further investigation into its therapeutic effects on cognitive and emotion control in those with PTSD.

The Vestibulocerebellum and the Shattered Self: a Resting-State Functional Connectivity Study in Posttraumatic Stress Disorder and Its Dissociative Subtype.

The flocculus is a region of the vestibulocerebellum dedicated to the coordination of neck, head, and eye movements for optimal posture, balance, and orienting responses. Despite growing evidence of vestibular and oculomotor impairments in the aftermath of traumatic stress, little is known about the effects of chronic psychological trauma on vestibulocerebellar functioning. Here, we investigated alterations in functional connectivity of the flocculus at rest among individuals with post-traumatic stress disorder (PTSD) and its dissociative subtype (PTSD + DS) as compared to healthy controls. Forty-four healthy controls, 57 PTSD, and 32 PTSD + DS underwent 6-min resting-state MRI scans. Seed-based functional connectivity analyses using the right and left flocculi as seeds were performed. These analyses revealed that, as compared to controls, PTSD and PTSD + DS showed decreased resting-state functional connectivity of the left flocculus with cortical regions involved in bodily self-consciousness, including the temporo-parietal junction, the supramarginal and angular gyri, and the superior parietal lobule. Moreover, as compared to controls, the PTSD + DS group showed decreased functional connectivity of the left flocculus with the medial prefrontal cortex, the precuneus, and the mid/posterior cingulum, key regions of the default mode network. Critically, when comparing PTSD + DS to PTSD, we observed increased functional connectivity of the right flocculus with the right anterior hippocampus, a region affected frequently by early life trauma. Taken together, our findings point toward the crucial role of the flocculus in the neurocircuitry underlying a coherent and embodied self, which can be compromised in PTSD and PTSD + DS.

Contrasting Associations Between Heart Rate Variability and Brainstem-Limbic Connectivity in Posttraumatic Stress Disorder and Its Dissociative Subtype: A Pilot Study.

Background: Increasing evidence points toward the need to extend the neurobiological conceptualization of posttraumatic stress disorder (PTSD) to include evolutionarily conserved neurocircuitries centered on the brainstem and the midbrain. The reticular activating system (RAS) helps to shape the arousal state of the brain, acting as a bridge between brain and body. To modulate arousal, the RAS is closely tied to the autonomic nervous system (ANS). Individuals with PTSD often reveal altered arousal patterns, ranging from hyper- to blunted arousal states, as well as altered functional connectivity profiles of key arousal-related brain structures that receive direct projections from the RAS. Accordingly, the present study aims to explore resting state functional connectivity of the RAS and its interaction with the ANS in participants with PTSD and its dissociative subtype. Methods: Individuals with PTSD (n = 57), its dissociative subtype (PTSD + DS, n = 32) and healthy controls (n = 40) underwent a 6-min resting functional magnetic resonance imaging and pulse data recording. Resting state functional connectivity (rsFC) of a central node of the RAS - the pedunculopontine nuclei (PPN) - was investigated along with its relation to ANS functioning as indexed by heart rate variability (HRV). HRV is a prominent marker indexing the flexibility of an organism to react adaptively to environmental needs, with higher HRV representing greater effective adaptation. Results: Both PTSD and PTSD + DS demonstrated reduced HRV as compared to controls. HRV measures were then correlated with rsFC of the PPN. Critically, participants with PTSD and participants with PTSD + DS displayed inverse correlations between HRV and rsFC between the PPN and key limbic structures, including the amygdala. Whereas participants with PTSD displayed a positive relationship between HRV and PPN rsFC with the amygdala, participants with PTSD + DS demonstrated a negative relationship between HRV and PPN rsFC with the amygdala. Conclusion: The present exploratory investigation reveals contrasting patterns of arousal-related circuitry among participants with PTSD and PTSD + DS, providing a neurobiological lens to interpret hyper- and more blunted arousal states in PTSD and PTSD + DS, respectively.

Moral wounds run deep: exaggerated midbrain functional network connectivity across the default mode network in posttraumatic stress disorder.

BACKGROUND: A moral injury occurs when a deeply held moral code has been violated, and it can lead to the development of symptoms of posttraumatic stress disorder (PTSD). However, the neural correlates that differentiate moral injury and PTSD remain largely unknown. Intrinsic connectivity networks such as the default mode network (DMN) appear to be altered in people with PTSD who have experienced moral injury. However, brainstem, midbrain and cerebellar systems are rarely integrated into the intrinsic connectivity networks; this is a critical oversight, because these systems display marked differences in people with PTSD and are thought to underlie strong moral emotions such as shame, guilt and betrayal. METHODS: We conducted an independent component analysis on data generated during script-driven memory recall of moral injury in participants with military- or law enforcement-related PTSD (n = 28), participants with civilian-related PTSD (n = 28) and healthy controls exposed to a potentially morally injurious event (n = 18). We conducted group-wise comparisons of functional network connectivity differences across a DMN-correlated independent component, with a particular focus on brainstem, midbrain and cerebellar systems. RESULTS: We found stronger functional network connectivity in the midbrain periaqueductal grey (t 71 = 4.95, p FDR = 0.028, k = 39) and cerebellar lobule IX (t 71 = 4.44, p FDR = 0.046, k = 49) in participants with civilian-related PTSD as compared to healthy controls. We also found a trend toward stronger functional network connectivity in the midbrain periaqueductal grey (t 71 = 4.22, p FDR = 0.076, k = 60) in participants with military- or law enforcement-related PTSD as compared to healthy controls. LIMITATIONS: The significant clusters were large, but resolution is generally lower for subcortical structures. CONCLUSION: In PTSD, the DMN appears to be biased toward lower-level, midbrain systems, which may drive toxic shame and related moral emotions that are common in PTSD, highlighting the depth at which moral injuries are represented neurobiologically.

Differential mechanisms of posterior cingulate cortex downregulation and symptom decreases in posttraumatic stress disorder and healthy individuals using real-time fMRI neurofeedback.

BACKGROUND: Intrinsic connectivity networks, including the default mode network (DMN), are frequently disrupted in individuals with posttraumatic stress disorder (PTSD). The posterior cingulate cortex (PCC) is the main hub of the posterior DMN, where the therapeutic regulation of this region with real-time fMRI neurofeedback (NFB) has yet to be explored. METHODS: We investigated PCC downregulation while processing trauma/stressful words over 3 NFB training runs and a transfer run without NFB (total n = 29, PTSD n = 14, healthy controls n = 15). We also examined the predictive accuracy of machine learning models in classifying PTSD versus healthy controls during NFB training. RESULTS: Both the PTSD and healthy control groups demonstrated reduced reliving symptoms in response to trauma/stressful stimuli, where the PTSD group additionally showed reduced symptoms of distress. We found that both groups were able to downregulate the PCC with similar success over NFB training and in the transfer run, although downregulation was associated with unique within-group decreases in activation within the bilateral dmPFC, bilateral postcentral gyrus, right amygdala/hippocampus, cingulate cortex, and bilateral temporal pole/gyri. By contrast, downregulation was associated with increased activation in the right dlPFC among healthy controls as compared to PTSD. During PCC downregulation, right dlPFC activation was negatively correlated to PTSD symptom severity scores and difficulties in emotion regulation. Finally, machine learning algorithms were able to classify PTSD versus healthy participants based on brain activation during NFB training with 80% accuracy. CONCLUSIONS: This is the first study to investigate PCC downregulation with real-time fMRI NFB in both PTSD and healthy controls. Our results reveal acute decreases in symptoms over training and provide converging evidence for EEG-NFB targeting brain networks linked to the PCC.

Assessment of brain age in posttraumatic stress disorder: Findings from the ENIGMA PTSD and brain age working groups.

BACKGROUND: Posttraumatic stress disorder (PTSD) is associated with markers of accelerated aging. Estimates of brain age, compared to chronological age, may clarify the effects of PTSD on the brain and may inform treatment approaches targeting the neurobiology of aging in the context of PTSD. METHOD: Adult subjects (N = 2229; 56.2% male) aged 18-69 years (mean = 35.6, SD = 11.0) from 21 ENIGMA-PGC PTSD sites underwent T1-weighted brain structural magnetic resonance imaging, and PTSD assessment (PTSD+, n = 884). Previously trained voxel-wise (brainageR) and region-of-interest (BARACUS and PHOTON) machine learning pipelines were compared in a subset of control subjects (n = 386). Linear mixed effects models were conducted in the full sample (those with and without PTSD) to examine the effect of PTSD on brain predicted age difference (brain PAD; brain age - chronological age) controlling for chronological age, sex, and scan site. RESULTS: BrainageR most accurately predicted brain age in a subset (n = 386) of controls (brainageR: ICC = 0.71, R = 0.72, MAE = 5.68; PHOTON: ICC = 0.61, R = 0.62, MAE = 6.37; BARACUS: ICC = 0.47, R = 0.64, MAE = 8.80). Using brainageR, a three-way interaction revealed that young males with PTSD exhibited higher brain PAD relative to male controls in young and old age groups; old males with PTSD exhibited lower brain PAD compared to male controls of all ages. DISCUSSION: Differential impact of PTSD on brain PAD in younger versus older males may indicate a critical window when PTSD impacts brain aging, followed by age-related brain changes that are consonant with individuals without PTSD. Future longitudinal research is warranted to understand how PTSD impacts brain aging across the lifespan.

Altered basal forebrain BOLD signal variability at rest in posttraumatic stress disorder: A potential candidate vulnerability mechanism for neurodegeneration in PTSD.

Individuals with posttraumatic stress disorder (PTSD) are at increased risk for the development of various forms of dementia. Nevertheless, the neuropathological link between PTSD and neurodegeneration remains unclear. Degeneration of the human basal forebrain constitutes a pathological hallmark of neurodegenerative diseases, such as Alzheimer's and Parkinson's disease. In this seed-based resting-state (rs-)fMRI study identifying as outcome measure the temporal BOLD signal fluctuation magnitude, a seed-to-voxel analyses assessed temporal correlations between the average BOLD signal within a bilateral whole basal forebrain region-of-interest and each whole-brain voxel among individuals with PTSD (n = 65), its dissociative subtype (PTSD+DS) (n = 38) and healthy controls (n = 46). We found that compared both with the PTSD and healthy controls groups, the PTSD+DS group exhibited increased BOLD signal variability within two nuclei of the seed region, specifically in its extended amygdaloid region: the nucleus accumbens and the sublenticular extended amygdala. This finding is provocative, because it mimics staging models of neurodegenerative diseases reporting allocation of neuropathology in early disease stages circumscribed to the basal forebrain. Here, underlying candidate etiopathogenetic mechanisms are neurovascular uncoupling, decreased connectivity in local- and large-scale neural networks, or disrupted mesolimbic dopaminergic circuitry, acting indirectly upon the basal forebrain cholinergic pathways. These abnormalities may underpin reward-related deficits representing a putative link between persistent traumatic memory in PTSD and anterograde memory deficits in neurodegeneration. Observed alterations of the basal forebrain in the dissociative subtype of PTSD point towards the urgent need for further exploration of this region as a potential candidate vulnerability mechanism for neurodegeneration in PTSD.

Mapping alexithymia: Level of emotional awareness differentiates emotion-specific somatosensory maps.

BACKGROUND: Emotions have been associated with culturally universal and distinct bodily sensation "maps". Despite this knowledge, to date few studies have explored emotion-specific topography along clinically relevant dimensions, such as alexithymia. OBJECTIVE: We aimed to investigate emotion-specific topographies among individuals exposed to childhood maltreatment or neglect with absent (n = 51) or with probable (n = 46) alexithymia in adulthood, as defined by scores on the Toronto Alexithymia Scale (TAS-20). PARTICIPANTS AND SETTING: Ninety eight adult participants with exposure to childhood maltreatment or neglect were recruited to complete an online survey. METHODS: Using the well-validated emBODY tool (Nummenmaa et al., 2014), participants reported on their somatic experience of 17 emotions. RESULTS: Random effects analyses revealed topographically distinct bodily sensation t-maps that differentiated participants who endorsed probable alexithymia from those who did not (p-FDR < .05). Consistent with our a priori hypothesis, the probable alexithymia group reported a muted, diffuse and undifferentiated pattern of emotion-specific bodily sensation, whereas the non-alexithymia group reported a more distinct and localized pattern. CONCLUSIONS: These results suggest that difficulty identifying and labeling emotions, as observed in alexithymia, may arise, in part, from an altered perception of somatic activation. It is well-established that childhood maltreatment predicts the development of alexithymia symptoms. The preliminary findings presented here expand our working understanding of the physical markers of childhood trauma, which may be used in practice to aid detection and to monitor treatment outcomes.

Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium.

A growing number of studies have examined alterations in white matter organization in people with posttraumatic stress disorder (PTSD) using diffusion MRI (dMRI), but the results have been mixed which may be partially due to relatively small sample sizes among studies. Altered structural connectivity may be both a neurobiological vulnerability for, and a result of, PTSD. In an effort to find reliable effects, we present a multi-cohort analysis of dMRI metrics across 3047 individuals from 28 cohorts currently participating in the PGC-ENIGMA PTSD working group (a joint partnership between the Psychiatric Genomics Consortium and the Enhancing NeuroImaging Genetics through Meta-Analysis consortium). Comparing regional white matter metrics across the full brain in 1426 individuals with PTSD and 1621 controls (2174 males/873 females) between ages 18-83, 92% of whom were trauma-exposed, we report associations between PTSD and disrupted white matter organization measured by lower fractional anisotropy (FA) in the tapetum region of the corpus callosum (Cohen's d = -0.11, p = 0.0055). The tapetum connects the left and right hippocampus, for which structure and function have been consistently implicated in PTSD. Results were consistent even after accounting for the effects of multiple potentially confounding variables: childhood trauma exposure, comorbid depression, history of traumatic brain injury, current alcohol abuse or dependence, and current use of psychotropic medications. Our results show that PTSD may be associated with alterations in the broader hippocampal network.

Shame on the brain: Neural correlates of moral injury event recall in posttraumatic stress disorder.

BACKGROUND: Moral injury (MI) is consistently associated with adverse mental health outcomes, including the development of posttraumatic stress disorder (PTSD) and suicidality. METHODS: We investigated neural activation patterns associated with MI event recall using functional magnetic resonance imaging in participants with military and public safety-related PTSD, relative to civilian MI-exposed controls. RESULTS: MI recall in the PTSD as compared to control group was associated with increased neural activation among salience network nodes involved in viscerosensory processing and hyperarousal (right posterior insula, dorsal anterior cingulate cortex; dACC), regions involved in defensive responding (left postcentral gyrus), and areas responsible for top-down cognitive control of emotions (left dorsolateral prefrontal cortex; dlPFC). Within the PTSD group, measures of state and trait shame correlated negatively with activity among default mode network regions associated with self-related processing and moral cognition (dorsomedial prefrontal cortex; dmPFC) and salience network regions associated with viscerosensory processing (left posterior insula), respectively. CONCLUSIONS: These findings suggest that MI event processing is altered in military and public safety-related PTSD, relative to MI-exposed controls. Here, it appears probable that as individuals with PTSD recall their MI event, they experience a surge of blame-related processing of bodily sensations within salience network regions, including the right posterior insula and the dACC, which in turn, prompt regulatory strategies at the level of the left dlPFC aimed at increasing cognitive control and inhibiting emotional affect. These results are consistent with previous findings showing enhanced sensory processing and altered top-down control in PTSD samples during autobiographical memory recall.

The hijacked self: Disrupted functional connectivity between the periaqueductal gray and the default mode network in posttraumatic stress disorder using dynamic causal modeling.

Self-related processes define assorted self-relevant or social-cognitive functions that allow us to gather insight and to draw inferences related to our own mental conditions. Self-related processes are mediated by the default mode network (DMN), which, critically, shows altered functionality in individuals with posttraumatic stress disorder (PTSD). In PTSD, the midbrain periaqueductal gray (PAG) demonstrates stronger functional connectivity with the DMN [i.e., precuneus (PCN), medial prefrontal cortex (mPFC)] as compared to healthy individuals during subliminal, trauma-related stimulus processing. Here, we analyzed the directed functional connectivity between the PAG and the PCN, as well as between the PAG and the mPFC to more explicitly characterize the functional connectivity we have observed previously on the corresponding sample and paradigm. We evaluated three models varying with regard to context-dependent modulatory directions (i.e., bi-directional, bottom-up, top-down) among individuals with PTSD (n = 26) and healthy participants (n = 20), where Bayesian model selection was used to identify the most optimal model for each group. We then compared the effective connectivity strength for each parameter across the models and between our groups using Bayesian model averaging. Bi-directional models were found to be favoured across both groups. In PTSD, we revealed the PAG to show stronger excitatory effective connectivity to the PCN, as well as to the mPFC as compared to controls. In PTSD, we further demonstrated that PAG-mediated effective connectivity to the PCN, as well as to the mPFC were modulated more strongly during subliminal, trauma-related stimulus conditions as compared to controls. Clinical disturbances towards self-related processes are reported widely by participants with PTSD during trauma-related stimulus processing, where altered functional connectivity directed by the PAG to the DMN may elucidate experiential links between self- and trauma-related processing in traumatized individuals.

Classifying heterogeneous presentations of PTSD via the default mode, central executive, and salience networks with machine learning.

Intrinsic connectivity networks (ICNs), including the default mode network (DMN), the central executive network (CEN), and the salience network (SN) have been shown to be aberrant in patients with posttraumatic stress disorder (PTSD). The purpose of the current study was to a) compare ICN functional connectivity between PTSD, dissociative subtype PTSD (PTSD+DS) and healthy individuals; and b) to examine the use of multivariate machine learning algorithms in classifying PTSD, PTSD+DS, and healthy individuals based on ICN functional activation. Our neuroimaging dataset consisted of resting-state fMRI scans from 186 participants [PTSD (n = 81); PTSD + DS (n = 49); and healthy controls (n = 56)]. We performed group-level independent component analyses to evaluate functional connectivity differences within each ICN. Multiclass Gaussian Process Classification algorithms within PRoNTo software were then used to predict the diagnosis of PTSD, PTSD+DS, and healthy individuals based on ICN functional activation. When comparing the functional connectivity of ICNs between PTSD, PTSD+DS and healthy controls, we found differential patterns of connectivity to brain regions involved in emotion regulation, in addition to limbic structures and areas involved in self-referential processing, interoception, bodily self-consciousness, and depersonalization/derealization. Machine learning algorithms were able to predict with high accuracy the classification of PTSD, PTSD+DS, and healthy individuals based on ICN functional activation. Our results suggest that alterations within intrinsic connectivity networks may underlie unique psychopathology and symptom presentation among PTSD subtypes. Furthermore, the current findings substantiate the use of machine learning algorithms for classifying subtypes of PTSD illness based on ICNs.

PTSD and its dissociative subtype through the lens of the insula: Anterior and posterior insula resting-state functional connectivity and its predictive validity using machine learning.

Individuals with post-traumatic stress disorder (PTSD) typically experience states of reliving and hypervigilance; however, the dissociative subtype of PTSD (PTSD+DS) presents with additional symptoms of depersonalization and derealization. Although the insula is critical to emotion processing, its association with these contrasting symptom profiles is yet to be fully delineated. Accordingly, we investigated insula subregion resting-state functional connectivity patterns among individuals with PTSD, PTSD+DS, and healthy controls. Using SPM12 and PRONTO software, we implemented a seed-based resting-state functional connectivity approach, along with multiclass Gaussian process classification machine learning, respectively, in order to evaluate unique patterns and the predictive validity of insula subregion connectivity among individuals with PTSD (n = 84), PTSD+DS (n = 49), and age-matched healthy controls (n = 51). As compared to PTSD and PTSD+DS, healthy controls showed increased right anterior and posterior insula connectivity with frontal lobe structures. By contrast, PTSD showed increased bilateral posterior insula connectivity with subcortical structures, including the periaqueductal gray. Strikingly, as compared to PTSD and controls, PTSD+DS showed increased bilateral anterior and posterior insula connectivity with posterior cortices, including the left lingual gyrus and the left precuneus. Moreover, machine learning analyses were able to classify PTSD, PTSD+DS, and controls using insula subregion connectivity patterns with 80.4% balanced accuracy (p < .01). These findings suggest a neurobiological distinction between PTSD and its dissociative subtype with regard to insula subregion functional connectivity patterns. Furthermore, machine learning algorithms were able to utilize insula resting-state connectivity patterns to discriminate between participant groups with high predictive accuracy.