Intrinsic sensory disinhibition contributes to intrusive re-experiencing in combat veterans

Daily life participation in PTSD: pilot study on patterns and correlators

Introduction

Participation in daily life activities with both the personal and community meaning is an important component of health and well-being. Even though there are mounting reports on the challenges in various aspects of daily-life functioning among individuals with post-traumatic stress disorder (PTSD), to date little research has been conducted on their comprehensive patterns of participation. The study aimed to describe objective and subjective participation dimensions in PTSD compared to healthy controls and investigate the association between personal and environmental factors and participation.

Methods

Sixty-one individuals were enrolled in two groups: PTSD (N=31; age: M=34.3; women:77.4%) and healthy controls matched by age and gender. The PTSD group completed standard assessments for symptom severity, general cognition, executive function (EF), sensory processing, self-efficacy, functional capacity, and environmental properties. Both groups completed a participation questionnaire.

Results

Individuals with PTSD participated with low intensity and diversity, more occupations were abandoned (-4.73

Discussion

The study demonstrates profound restrictions in participation in PTSD raising serious concerns. There are unique patterns of association between objective participation dimensions, subjective cognitive indices, sensory modulation, and environmental factors, suggesting a need for PTSD feature-specific intervention approaches to advance the participation of those with PTSD as a means of promoting health and well-being.

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Key Words

• environmental impacts
• functional capacity
• neurocognition
• objective participation
• subjective participation

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Affiliation(s)

Ruth Shapira Day care ward, School of Occupational Therapy, Faculty of Medicine, the Hebrew University, Jerusalem, Israel The Jerusalem Mental Health Center, Jerusalem, Israel
Yisca Jessica Baris Ginat The Jerusalem Mental Health Center, Jerusalem, Israel
Lena Lipskaya-Velikovsky Day care ward, School of Occupational Therapy, Faculty of Medicine, the Hebrew University, Jerusalem, Israel

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Spatiotemporal dynamics of hippocampal-cortical networks underlying the unique phenomenological properties of trauma-related intrusive memories

Trauma-related intrusive memories (TR-IMs) possess unique phenomenological properties that contribute to adverse post-traumatic outcomes, positioning them as critical intervention targets. However, transdiagnostic treatments for TR-IMs are scarce, as their underlying mechanisms have been investigated separate from their unique phenomenological properties. Extant models of more general episodic memory highlight dynamic hippocampal-cortical interactions that vary along the anterior-posterior axis of the hippocampus (HPC) to support different cognitive-affective and sensory-perceptual features of memory. Extending this work into the unique properties of TR-IMs, we conducted a study of eighty-four trauma-exposed adults who completed daily ecological momentary assessments of TR-IM properties followed by resting-state functional magnetic resonance imaging (rs-fMRI). Spatiotemporal dynamics of anterior and posterior hippocampal (a/pHPC)-cortical networks were assessed using co-activation pattern analysis to investigate their associations with different properties of TR-IMs. Emotional intensity of TR-IMs was inversely associated with the frequency and persistence of an aHPC-default mode network co-activation pattern. Conversely, sensory features of TR-IMs were associated with more frequent co-activation of the HPC with sensory cortices and the ventral attention network, and the reliving of TR-IMs in the "here-and-now" was associated with more persistent co-activation of the pHPC and the visual cortex. Notably, no associations were found between HPC-cortical network dynamics and conventional symptom measures, including TR-IM frequency or retrospective recall, underscoring the utility of ecological assessments of memory properties in identifying their neural substrates. These findings provide novel insights into the neural correlates of the unique features of TR-IMs that are critical for the development of individualized, transdiagnostic treatments for this pervasive, difficult-to-treat symptom.

Evaluating a novel 8-factor dimensional model of PTSD in U.S. military veterans: Results from the National Health and Resilience in Veterans Study

BACKGROUND

Accumulating data suggest that the structure of posttraumatic stress disorder (PTSD) symptoms may be more nuanced than proposed by prevailing nosological models. Emerging theory further suggests that an 8-factor model with separate internally- (e.g., flashbacks) and externally- (e.g., trauma cue-related emotional reactivity) generated intrusive symptoms may best represent PTSD symptoms. To date, however, scarce research has evaluated the fit of this model and whether index traumas are differentially associated with it in populations at high risk for trauma exposure, such as military veterans.

METHODS

Data were analyzed from a nationally representative sample of 3847 trauma-exposed U.S. veterans who participated in the National Health and Resilience in Veterans Study. Confirmatory factor analyses were conducted to evaluate the fit of a novel 8-factor model of PTSD symptoms relative to 4-factor DSM-5 and empirically-supported 7-factor hybrid models.

RESULTS

The 8-factor model fit the data significantly better than the 7-factor hybrid and 4-factor DSM-5 models. Combat exposure and harming others were more strongly associated with internally-generated intrusions, while interpersonal violence and disaster/accident showed stronger significant associations with externally-generated intrusions.

LIMITATIONS

The 8-factor model requires validation in non-veteran and more diverse trauma-exposed populations, as well as with clinician-administered interviews.

CONCLUSIONS

Results of this study provide support for a novel 8-factor model of PTSD symptoms that is characterized by separate internally- and externally-generated intrusions. They also suggest that certain index traumas may lead to differential expression of these symptoms.

Sensory alterations in post-traumatic stress disorder

PTSD is characterized by difficulties in accurately evaluating the threat value of sensory stimuli. While the role of canonical fear and threat neural circuitry in this ability has been well studied, recent lines of evidence suggest a need to include more emphasis on sensory processing in the conceptualization of PTSD symptomology. Specifically, studies have demonstrated a strong association between variability in sensory processing regions and the severity of PTSD symptoms. In this review, we summarize recent findings that underscore the importance of sensory processing in PTSD, in addition to the structural and functional characteristics of associated sensory brain regions. First, we discuss the link between PTSD and various behavioral aspects of sensory processing. This is followed by a discussion of recent findings that link PTSD to variability in the structure of both gray and white matter in sensory brain regions. We then delve into how brain activity (measured with task-based and resting-state functional imaging) in sensory regions informs our understanding of PTSD symptomology.

Pattern differentiation and tuning shift in human sensory cortex underlie long-term threat memory

The amygdala-prefrontal-cortex circuit has long occupied the center of the threat system,¹ but new evidence has rapidly amassed to implicate threat processing outside this canonical circuit.^2-4 Through nonhuman research, the sensory cortex has emerged as a critical substrate for long-term threat memory,^5-9 underpinned by sensory cortical pattern separation/completion^10,11 and tuning shift.^12,13 In humans, research has begun to associate the human sensory cortex with long-term threat memory,^14,15 but the lack of mechanistic insights obscures a direct linkage. Toward that end, we assessed human olfactory threat conditioning and long-term (9 days) threat memory, combining affective appraisal, olfactory psychophysics, and functional magnetic resonance imaging (fMRI) over a linear odor-morphing continuum (five levels of binary mixtures of the conditioned stimuli/CS+ and CS- odors). Affective ratings and olfactory perceptual discrimination confirmed (explicit) affective and perceptual learning and memory via conditioning. fMRI representational similarity analysis (RSA) and voxel-based tuning analysis further revealed associative plasticity in the human olfactory (piriform) cortex, including immediate and lasting pattern differentiation between CS and neighboring non-CS and a late onset, lasting tuning shift toward the CS. The two plastic processes were especially salient and lasting in anxious individuals, among whom they were further correlated. These findings thus support an evolutionarily conserved sensory cortical system of long-term threat representation, which can underpin threat perception and memory. Importantly, hyperfunctioning of this sensory mnemonic system of threat in anxiety further implicates a hitherto underappreciated sensory mechanism of anxiety.

Transcranial stimulation of alpha oscillations up-regulates the default mode network

The default mode network (DMN) is the most-prominent intrinsic connectivity network, serving as a key architecture of the brain's functional organization. Conversely, dysregulated DMN is characteristic of major neuropsychiatric disorders. However, the field still lacks mechanistic insights into the regulation of the DMN and effective interventions for DMN dysregulation. The current study approached this problem by manipulating neural synchrony, particularly alpha (8 to 12 Hz) oscillations, a dominant intrinsic oscillatory activity that has been increasingly associated with the DMN in both function and physiology. Using high-definition alpha-frequency transcranial alternating current stimulation (α-tACS) to stimulate the cortical source of alpha oscillations, in combination with simultaneous electroencephalography and functional MRI (EEG-fMRI), we demonstrated that α-tACS (versus Sham control) not only augmented EEG alpha oscillations but also strengthened fMRI and (source-level) alpha connectivity within the core of the DMN. Importantly, increase in alpha oscillations mediated the DMN connectivity enhancement. These findings thus identify a mechanistic link between alpha oscillations and DMN functioning. That transcranial alpha modulation can up-regulate the DMN further highlights an effective noninvasive intervention to normalize DMN functioning in various disorders.

Human Sensory Cortex Contributes to the Long-Term Storage of Aversive Conditioning

Growing animal data evince a critical role of the sensory cortex in the long-term storage of aversive conditioning, following acquisition and consolidation in the amygdala. Whether and how this function is conserved in the human sensory cortex is nonetheless unclear. We interrogated this question in a human aversive conditioning study using multidimensional assessments of conditioning and long-term (15 d) retention. Conditioned stimuli (CSs; Gabor patches) were calibrated to differentially activate the parvocellular (P) and magnocellular (M) visual pathways, further elucidating cortical versus subcortical mechanisms. Full-blown conditioning and long-term retention emerged for M-biased CS (vs limited effects for P-biased CS), especially among anxious individuals, in all four dimensions assessed: threat appraisal (threat ratings), physiological arousal (skin conductance response), perceptual learning [discrimination sensitivity (d') and response speed], and cortical plasticity [visual evoked potentials (VEPs) and cortical current density]. Interestingly, while behavioral, physiological, and VEP effects were comparable at immediate and delayed assessments, the cortical substrates evolved markedly over time, transferring from high-order cortices [inferotemporal/fusiform cortex and orbitofrontal cortex (OFC)] immediately to the primary and secondary visual cortex after the delay. In sum, the contrast between P- and M-biased conditioning confirms privileged conditioning acquisition via the subcortical pathway while the immediate cortical plasticity lends credence to the triadic amygdala-OFC-fusiform network thought to underlie threat processing. Importantly, long-term retention of conditioning in the basic sensory cortices supports the conserved role of the human sensory cortex in the long-term storage of aversive conditioning.SIGNIFICANCE STATEMENT A growing network of neural substrates has been identified in threat learning and memory. The sensory cortex plays a key role in long-term threat memory in animals, but such a function in humans remains unclear. To explore this problem, we conducted multidimensional assessments of immediate and delayed (15 d) effects of human aversive conditioning. Behavioral, physiological, and scalp electrophysiological data demonstrated conditioning effects and long-term retention. High-density EEG intracranial source analysis further revealed the cortical underpinnings, implicating high-order cortices immediately and primary and secondary visual cortices after the long delay. Therefore, while high-order cortices support aversive conditioning acquisition (i.e., threat learning), the human sensory cortex (akin to the animal homolog) underpins long-term storage of conditioning (i.e., long-term threat memory).

Traces of Trauma: A Multivariate Pattern Analysis of Childhood Trauma, Brain Structure, and Clinical Phenotypes

BACKGROUND

Childhood trauma (CT) is a major yet elusive psychiatric risk factor, whose multidimensional conceptualization and heterogeneous effects on brain morphology might demand advanced mathematical modeling. Therefore, we present an unsupervised machine learning approach to characterize the clinical and neuroanatomical complexity of CT in a larger, transdiagnostic context.

METHODS

We used a multicenter European cohort of 1076 female and male individuals (discovery: n = 649; replication: n = 427) comprising young, minimally medicated patients with clinical high-risk states for psychosis; patients with recent-onset depression or psychosis; and healthy volunteers. We employed multivariate sparse partial least squares analysis to detect parsimonious associations between combinations of items from the Childhood Trauma Questionnaire and gray matter volume and tested their generalizability via nested cross-validation as well as via external validation. We investigated the associations of these CT signatures with state (functioning, depressivity, quality of life), trait (personality), and sociodemographic levels.

RESULTS

We discovered signatures of age-dependent sexual abuse and sex-dependent physical and sexual abuse, as well as emotional trauma, which projected onto gray matter volume patterns in prefronto-cerebellar, limbic, and sensory networks. These signatures were associated with predominantly impaired clinical state- and trait-level phenotypes, while pointing toward an interaction between sexual abuse, age, urbanicity, and education. We validated the clinical profiles for all three CT signatures in the replication sample.

CONCLUSIONS

Our results suggest distinct multilayered associations between partially age- and sex-dependent patterns of CT, distributed neuroanatomical networks, and clinical profiles. Hence, our study highlights how machine learning approaches can shape future, more fine-grained CT research.

Machine learning and individual variability in electric field characteristics predict tDCS treatment response

BACKGROUND

Transcranial direct current stimulation (tDCS) is widely investigated as a therapeutic tool to enhance cognitive function in older adults with and without neurodegenerative disease. Prior research demonstrates that electric current delivery to the brain can vary significantly across individuals. Quantification of this variability could enable person-specific optimization of tDCS outcomes. This pilot study used machine learning and MRI-derived electric field models to predict working memory improvements as a proof of concept for precision cognitive intervention.

METHODS

Fourteen healthy older adults received 20 minutes of 2 mA tDCS stimulation (F3/F4) during a two-week cognitive training intervention. Participants performed an N-back working memory task pre-/post-intervention. MRI-derived current models were passed through a linear Support Vector Machine (SVM) learning algorithm to characterize crucial tDCS current components (intensity and direction) that induced working memory improvements in tDCS responders versus non-responders.

MAIN RESULTS

SVM models of tDCS current components had 86% overall accuracy in classifying treatment responders vs. non-responders, with current intensity producing the best overall model differentiating changes in working memory performance. Median current intensity and direction in brain regions near the electrodes were positively related to intervention responses (r=0.811,p<0.001 and r=0.774,p=0.001).

CONCLUSIONS

This study provides the first evidence that pattern recognition analyses of MRI-derived tDCS current models can provide individual prognostic classification of tDCS treatment response with 86% accuracy. Individual differences in current intensity and direction play important roles in determining treatment response to tDCS. These findings provide important insights into mechanisms of tDCS response as well as proof of concept for future precision dosing models of tDCS intervention.

Posttraumatic Stress Disorder Is Associated with α Dysrhythmia across the Visual Cortex and the Default Mode Network

Anomalies in default mode network (DMN) activity and α (8–12 Hz) oscillations have been independently observed in posttraumatic stress disorder (PTSD). Recent spatiotemporal analyses suggest that α oscillations support DMN functioning via interregional synchronization and sensory cortical inhibition. Therefore, we examined a unifying pathology of α deficits in the visual-cortex-DMN system in PTSD. Human patients with PTSD (N = 25) and two control groups, patients with generalized anxiety disorder (GAD; N = 24) and healthy controls (HCs; N = 20), underwent a standard eyes-open resting state (S-RS) and a modified resting state (M-RS) of passively viewing salient images (known to deactivate the DMN). High-density electroencephalogram (hdEEG) were recorded, from which intracortical α activity (power and connectivity/Granger causality) was extracted using the exact low-resolution electromagnetic tomography (eLORETA). Patients with PTSD (vs GAD/HC) demonstrated attenuated α power in the visual cortex (VC) and key hubs of the DMN [posterior cingulate cortex (PCC) and medial prefrontal cortex (mPFC)] at both states, the severity of which further correlated with hypervigilance symptoms. With increased visual input (at M-RS vs S-RS), patients with PTSD further demonstrated reduced α-frequency directed connectivity within the DMN (PCC→mPFC) and, importantly, from the VC to both DMN hubs (VC→PCC and VC→mPFC), linking α deficits in the two systems. These interrelated α deficits align with DMN hypoactivity/hypoconnectivity, sensory disinhibition, and hypervigilance in PTSD, representing a unifying neural underpinning of these anomalies. The identification of visual-cortex-DMN α dysrhythmia in PTSD further presents a novel therapeutic target, promoting network-based intervention of neural oscillations.