Restless 'rest': intrinsic sensory hyperactivity and disinhibition in post-traumatic stress disorder

Sensory Responsiveness, Sexual Mindful Awareness, and Sexual Satisfaction Among Survivors of Childhood Sexual Abuse: A Cross-Sectional Mediation Analysis

Previous studies have demonstrated that a history of childhood sexual abuse (CSA) is associated with reduced sexual satisfaction among adult survivors. Recent studies have suggested that survivors of traumatic experiences may display sensory modulation dysfunction, manifested as either over- or under-responsiveness to sensory stimuli. In this study we examined a moderated mediation model according to which: a) the effect of history of CSA on adult sexual satisfaction would be mediated by both high and low sensory responsiveness, and b) these mediation effects would be moderated by sexual mindful awareness. Five-hundred-and-eighty adults completed questionnaires assessing history of CSA, sensory responsiveness, sexual mindful awareness, and sexual satisfaction. As hypothesized, high sensory responsiveness mediated the association between history of CSA and reduced sexual satisfaction. However, sexual mindful awareness moderated this mediation effect, and the indirect effect between history of CSA and sexual satisfaction through the mediation of high sensory responsiveness was significant among individuals with mean and high levels of sexual mindful awareness, but not among those with low levels of sexual mindful awareness. Given the cross-sectional study design, these effects warrant further longitudinal examination. Nevertheless, the findings suggest the need to address sensory modulation dysfunction to promote sexual satisfaction among survivors of CSA.

Early processing of traumatic material and contextual information in posttraumatic stress disorder and its relation to memory impairments

Posttraumatic stress disorder (PTSD) is characterized by exaggerated responses to trauma-relevant cues and impairments in relation to contextual information. However, it is not clear whether this dysfunction is related only to memory processes, or whether early perceptual and attentional processing is already dysfunctional. We examined early processing and retrieval of trauma-related cues and neutral contexts in 20 individuals diagnosed with PTSD (PTSD) and 20 trauma-exposed controls without diagnosis of PTSD (NPTSD) using simultaneous high-density electroencephalography and eye-tracking. A group of 20 non-trauma-exposed healthy controls (HC) was employed to test for responses to trauma-unrelated cues and contexts. The earliest visual event-related potential (C1) was positive for individuals diagnosed with PTSD and negative for NPTSD, suggesting enhanced early visual processing of the cue. Eye-tracking showed that PTSD but not NPTSD displayed significantly longer latencies before looking at contexts than at trauma-related cues. The PTSD group performed significantly worse than the NPTSD group in correctly retrieving rearranged cue/context associations compared to consistent associations. Memory strength for rearranged cue-context pairs was significantly predicted by the early processing measures of the context. Perception of traumatic cues in neutral contexts is biased in PTSD at early processing stages and contributes significantly to the impairment in context-relational memories. For trauma-unrelated cues and contexts no significant differences emerged between PTSD and trauma-exposed as well as non-trauma-exposed controls. Treatments for individuals diagnosed with PTSD should focus on early processing, perception and attention of cue/context traumatic associations in addition to contextual memory.

Climate trauma from wildfire exposure impacts cognitive decision-making

Climate trauma refers to the chronic mental health sequalae of climate disaster events. We have previously shown evidence for such trauma with accompanying anxiety and depression symptoms after California's 2018 Camp Fire wildfire. Here, we investigate whether this climate trauma also impacts cognitive decision-making and its neural correlates. One year after the wildfire, we recruited three groups - those directly exposed (n = 27), indirectly exposed (community members who witnessed the wildfire but not directly exposed, n = 21), versus non-exposed controls (n = 27). Participants performed a decision-making task that led to immediate and cumulative point rewards on each trial with simultaneous electroencephalography (EEG) recordings. We evaluated Win-Stay behavior in choosing to stay with the greater expected value (cumulative reward) option. Directly-exposed individuals showed significantly reduced Win-Stay behavior relative to the other groups. EEG analyses showed significantly greater parietal alpha activity for the selected choice and ensuing rewards in directly fire-exposed individuals, with an underlying cortical source of this activity in posterior cingulate cortex. Overall, these findings suggest that climate trauma may significantly impact neuro-cognitive processing in the context of value-based decision-making, which may serve as a useful biomarker target for future mental health interventions in climate change impacted communities.

A comprehensive investigation of intracortical and corticothalamic models of the alpha rhythm

The electroencephalographic alpha rhythm is one of the most robustly observed and widely studied empirical phenomena in all of neuroscience. However, despite its extensive implication in a wide range of cognitive processes and clinical pathologies, the mechanisms underlying alpha generation in neural circuits remain poorly understood. In this paper we offer a renewed foundation for research on this question, by undertaking a systematic comparison and synthesis of the most prominent theoretical models of alpha rhythmogenesis in the published literature. We focus on four models, each studied intensively by multiple authors over the past three decades: (i) Jansen-Rit, (ii) Moran-David-Friston, (iii) Robinson-Rennie-Wright, and (iv) Liley-Wright. Several common elements are identified, such as the use of second-order differential equations and sigmoidal potential-to-rate operators to represent population-level neural activity. Major differences are seen in other features such as wiring topologies and conduction delays. Through a series of mathematical analyses and numerical simulations, we nevertheless demonstrate that the selected models can be meaningfully compared, by associating parameters and circuit motifs of analogous biological significance. With this established, we conduct explorations of rate constant and synaptic connectivity parameter spaces, with the aim of identifying common patterns in key behaviours, such as the role of excitatory-inhibitory interactions in the generation of oscillations. Finally, using linear stability analysis we identify two qualitatively different alpha-generating dynamical regimes across the models: (i) noise-driven fluctuations and (ii) self-sustained limit-cycle oscillations, emerging due to an Andronov-Hopf bifurcation. The comprehensive survey and synthesis developed here can, we suggest, be used to help guide future theoretical and experimental work aimed at disambiguating these and other candidate theories of alpha rhythmogenesis.

Alpha-frequency stimulation strengthens coupling between temporal fluctuations in alpha oscillation power and default mode network connectivity

Alpha (8-12 Hz) oscillations and default mode network (DMN) activity dominate the brain's intrinsic activity in the temporal and spatial domains, respectively. They are thought to play crucial roles in the spatiotemporal organization of the complex brain system. Relatedly, both have been implicated, often concurrently, in diverse neuropsychiatric disorders, with accruing electroencephalogram/magnetoencephalogram (EEG/MEG) and functional magnetic resonance imaging (fMRI) data linking these two neural activities both at rest and during key cognitive operations. Prominent theories and extant findings thus converge to suggest a mechanistic relationship between alpha oscillations and the DMN. Here, we leveraged simultaneous EEG-fMRI data acquired before and after alpha-frequency transcranial alternating current stimulation (α-tACS) and observed that α-tACS tightened the dynamic coupling between spontaneous fluctuations in alpha power and DMN connectivity (especially, in the posterior DMN, between the posterior cingulate cortex and the bilateral angular gyrus). In comparison, no significant changes were observed for temporal correlations between power in other oscillatory frequencies and connectivity in other major networks. These results thus suggest an inherent coupling between alpha and DMN activity in humans. Importantly, these findings highlight the efficacy of α-tACS in regulating the DMN, a clinically significant network that is challenging to target directly with non-invasive methods.Significance Statement Alpha (8-12 Hz) oscillations and the default mode network (DMN) represent two major intrinsic activities of the brain. Prominent theories and extant findings converge to suggest a mechanistic relationship between alpha oscillations and the DMN. Combining simultaneous electroencephalogram-functional-magnetic-resonance imaging (EEG-fMRI) with alpha-frequency transcranial alternating current stimulation (α-tACS), we demonstrated tightened coupling between alpha oscillations and DMN connectivity. These results lend credence to an inherent alpha-DMN link. Given DMN dysfunctions in multiple major neuropsychiatric conditions, the findings also highlight potential utility of α-tACS in clinical interventions by regulating the DMN.

Multimodal associations between posterior hippocampus glutamate metabolism, visual cortex connectivity, and intrusive trauma reexperiencing symptoms

Objective

Hippocampal dysfunction is implicated in posttraumatic stress disorder (PTSD), particularly intrusive reexperiencing symptoms, and may be mediated by glutamatergic excitotoxicity. Markers of glutamate dysfunction (higher glutamate to N-acetyl aspartate levels; Glu/NAA) in the hippocampus (HPC) have been linked to reexperiencing symptoms. However, the HPC demonstrates heterogeneity along its anterior-posterior axis, with different functional connectivity patterns and PTSD symptom associations, motivating investigations into glutamate metabolism in anterior and posterior HPC subregions (a/pHPC).

Methods

121 symptomatic trauma-exposed adults (93 female) with current trauma reexperiencing symptoms completed magnetic resonance spectroscopy and resting-state functional magnetic resonance imaging to examine the regional specificity of HPC Glu/NAA associations with reexperiencing, and the link to a/pHPC functional connectivity. PTSD symptoms were assessed with the Clinician-Administered PTSD Scale for DSM-5.

Results

Reexperiencing symptom severity was associated with greater Glu/NAA in the pHPC, but not aHPC. pHPC Glu/NAA was further linked to stronger functional connectivity between the pHPC and visual cortex (VC), which in turn correlated with more severe reexperiencing symptoms. This strengthened pHPC-VC connectivity explained the shared variance between pHPC Glu/NAA and reexperiencing severity, suggesting dysregulated glutamate metabolism in the pHPC may contribute to reexperiencing symptoms through functional connectivity with the VC.

Conclusions

These findings replicate prior work linking HPC Glu/NAA to trauma reexperiencing symptoms and provide novel evidence this association may be specific to the pHPC and mediated by its functional connectivity with the VC. This multimodal investigation supports translational models of glutamatergic dysfunction in trauma-related disorders and highlights new targets for pharmacological and neuromodulatory interventions.

Alpha-frequency stimulation strengthens coupling between temporal fluctuations in alpha oscillation power and default mode network connectivity

Alpha (8-12 Hz) oscillations and default mode network (DMN) activity dominate the brain's intrinsic activity in the temporal and spatial domains, respectively. They are thought to play crucial roles in the spatiotemporal organization of the complex brain system. Relatedly, both have been implicated, often concurrently, in diverse neuropsychiatric disorders, with accruing electroencephalogram/magnetoencephalogram (EEG/MEG) and functional magnetic resonance imaging (fMRI) data linking these two neural activities both at rest and during key cognitive operations. Prominent theories and extant findings thus converge to suggest a mechanistic relationship between alpha oscillations and the DMN. Here, we leveraged simultaneous EEG-fMRI data acquired before and after alpha-frequency transcranial alternating current stimulation (α-tACS) and observed that α-tACS tightened the dynamic coupling between spontaneous fluctuations in alpha power and DMN connectivity (especially, in the posterior DMN, between the posterior cingulate cortex and the bilateral angular gyrus). In comparison, no significant changes were observed for temporal correlations between power in other oscillatory frequencies and connectivity in other major networks. These results thus suggest an inherent coupling between alpha and DMN activity in humans. Importantly, these findings highlight the efficacy of α-tACS in regulating the DMN, a clinically significant network that is challenging to target directly with non-invasive methods.

Plasticity of human resilience mechanisms

The hippocampus's vulnerability to trauma-induced stress can lead to pathophysiological disturbances that precipitate the development of posttraumatic stress disorder (PTSD). The mechanisms of resilience that foster remission and mitigate the adverse effects of stress remain unknown. We analyzed the evolution of hippocampal morphology between 2016/2017 and 2018/2019, as well as the memory control mechanisms crucial for trauma resilience. Participants were individuals exposed to the 2015 Paris terrorist attacks (N = 100), including chronic (N = 34) and remitted (N = 19) PTSD, and nonexposed (N = 72). We found that normalization of inhibitory control processes, which regulate the resurgence of intrusive memories in the hippocampus, not only predicted PTSD remission but also preceded a reduction in traumatic memories. Improvement in control mechanisms was associated with the interruption of stress-induced atrophy in a hippocampal region that includes the dentate gyrus. Human resilience to trauma is characterized by the plasticity of memory control circuits, which interacts with hippocampal neuroplasticity.

Aberrant neural event segmentation during a continuous social narrative in trauma-exposed older adolescents and young adults

Post-traumatic stress and major depressive disorders are associated with "overgeneral" autobiographical memory, or impaired recall of specific life events. Interpersonal trauma exposure, a risk factor for both conditions, may influence how symptomatic trauma-exposed (TE) individuals segment everyday events. The ability to parse experience into units (event segmentation) supports memory. Neural state transitions occur within a cortical hierarchy and play a key role in event segmentation, with regions like the occipital cortex, angular gyrus, and striatum involved in parsing event structure. We examined whether interpersonal trauma exposure was associated with alterations in the cortical hierarchy and striatal activity at neural state transitions in symptomatic TE versus healthy control (HC) individuals. Fifty older adolescents and young adults (29 TE, 21 HC) viewed the film "Partly Cloudy" during functional magnetic resonance imaging. A greedy-state boundary search algorithm assessed the optimal number of events, quality, and segmentation agreement of neural state transitions in the occipital cortex and angular gyrus. Striatal (nucleus accumbens, caudate, and putamen) activity was assessed at occipital and angular gyrus-evoked state transitions. Compared to HCs, TE participants displayed less occipital and greater angular gyrus-evoked optimal number of neural state transitions. TE participants also displayed lower quality of neural state segmentation solutions in occipital and angular cortices compared to HCs. Additionally, TE participants had less putamen activity at angular gyrus-evoked state transitions than HCs. This investigation provides neurobiological insights into aberrant event segmentation in symptomatic TE individuals, shedding light on mechanisms influencing overgeneral memory in trauma-related disorders.

Characterizing PTSD Using Electrophysiology: Towards A Precision Medicine Approach

Objective. Resting-state EEG measures have shown potential in distinguishing individuals with PTSD from healthy controls. ERP components such as N2, P3, and late positive potential have been consistently linked to cognitive abnormalities in PTSD, especially in tasks involving emotional or trauma-related stimuli. However, meta-analyses have reported inconsistent findings. The understanding of biomarkers that can classify the varied symptoms of PTSD remains limited. This study aimed to develop a concise set of electrophysiological biomarkers, using neutral cognitive tasks, that could be applied across psychiatric conditions, and to identify biomarkers associated with the anxiety and depression dimensions of PTSD. Approach. Continuous simultaneous recordings of EEG and electrocardiogram (ECG) were obtained in veterans with PTSD (n = 29) and healthy controls (n = 62) during computerized tasks. EEG, ERP, and heart rate measures were evaluated in terms of their ability to discriminate between the groups or correlate with psychological measures. Results. The PTSD cohort exhibited faster alpha oscillations, reduced alpha power, and a flatter power spectrum. Furthermore, stronger reduction in alpha power was associated with higher trait anxiety, while a flatter slope was related to more severe depression symptoms in individuals with PTSD. In ERP tasks of visual memory and sustained attention, the PTSD cohort demonstrated delayed and exaggerated early components, along with attenuated LPP amplitudes. The three tasks revealed distinct and complementary EEG signatures PTSD. Significance. Multimodal individualized biomarkers based on EEG, cognitive ERPs, and ECG show promise as objective tools for assessing mood and anxiety disturbances within the PTSD spectrum.

Localization of brain neuronal IL-1R1 reveals specific neural circuitries responsive to immune signaling

Interleukin-1 (IL-1) is a pro-inflammatory cytokine that exerts a wide range of neurological and immunological effects throughout the central nervous system (CNS) and is associated with the etiology of affective and cognitive disorders. The cognate receptor for IL-1, Interleukin-1 Receptor Type 1 (IL-1R1), is primarily expressed on non-neuronal cells (e.g., endothelial cells, choroidal cells, ventricular ependymal cells, astrocytes, etc.) throughout the brain. However, the presence and distribution of neuronal IL-1R1 (nIL-1R1) has been controversial. Here, for the first time, a novel genetic mouse line that allows for the visualization of IL-1R1 mRNA and protein expression (Il1r1GR/GR) was used to map all brain nuclei and determine the neurotransmitter systems which express nIL-1R1 in adult male mice. The direct responsiveness of nIL-1R1-expressing neurons to both inflammatory and physiological levels of IL-1β in vivo was tested. Neuronal IL-1R1 expression across the brain was found in discrete glutamatergic and serotonergic neuronal populations in the somatosensory cortex, piriform cortex, dentate gyrus, and dorsal raphe nucleus. Glutamatergic nIL-1R1 comprises most of the nIL-1R1 expression and, using Vglut2-Cre-Il1r1r/r mice, which restrict IL-1R1 expression to only glutamatergic neurons, an atlas of glutamatergic nIL-1R1 expression across the brain was generated. Analysis of functional outputs of these nIL-1R1-expressing nuclei, in both Il1r1GR/GR and Vglut2-Cre-Il1r1r/r mice, reveals IL-1R1+ nuclei primarily relate to sensory detection, processing, and relay pathways, mood regulation, and spatial/cognitive processing centers. Intracerebroventricular (i.c.v.) injections of IL-1 (20 ng) induces NFκB signaling in IL-1R1+ non-neuronal cells but not in IL-1R1+ neurons, and in Vglut2-Cre-Il1r1r/r mice IL-1 did not change gene expression in the dentate gyrus of the hippocampus (DG). GO pathway analysis of spatial RNA sequencing 1mo following restoration of nIL-1R1 in the DG neurons reveals IL-1R1 expression downregulates genes related to both synaptic function and mRNA binding while increasing select complement markers (C1ra, C1qb). Further, DG neurons exclusively express an alternatively spliced IL-1R Accessory protein isoform (IL-1RAcPb), a known synaptic adhesion molecule. Altogether, this study reveals a unique network of neurons that can respond directly to IL-1 via nIL-1R1 through non-autonomous transcriptional pathways; earmarking these circuits as potential neural substrates for immune signaling-triggered sensory, affective, and cognitive disorders.

Sex-specific alterations in visual properties induced by single prolonged stress model

Patients with post-traumatic stress disorder (PTSD) exhibit sex differences in symptomology, with women more likely to report higher rates of intrusive and avoidance symptoms than men, underscoring the need for sex-informed approaches to research and treatment. Our study delved into the sex-specific aspects of stress-induced visual impairments using the single prolonged stress (SPS) model, a partially validated rodent model for PTSD. Male SPS mice exhibit heightened optimal spatial frequency (SF) of primary visual cortex (V1) neurons, while female counterparts exhibit decreased optimal temporal frequency (TF) of V1 neurons. This phenomenon persisted until the 29th day after SPS modeling, and it may be the physiological basis for the observed increase in visual acuity in male SPS mice in visual water task. Furthermore, our study found that corticotropin-releasing factor receptor 1 regulated optimal TF and optimal SF of V1 in mice, but did not exhibit sex differences. These findings indicated that severe stress induces sex-specific effects on visual function.

Beyond Pharmacology: A Narrative Review of Alternative Therapies for Anxiety Disorders

BACKGROUND

Anxiety disorders significantly reduce patients' quality of life. Current pharmacological treatments, primarily benzodiazepines and antidepressants, are associated with numerous side effects. Consequently, there is a continual search for alternative methods to traditional therapies that are less burdensome for patients and broaden their therapeutic options. Our objective was to determine the role of selected alternative methods in the treatment of anxiety disorders.

METHODS

In this review, we examined recent evidence on alternative treatments for anxiety disorders, including physical activity, mindfulness, virtual reality (VR) technology, biofeedback, herbal remedies, transcranial magnetic stimulation (TMS), cryotherapy, hyperbaric therapy, vagus nerve stimulation (VNS), 3,4-methylenedioxymethamphetamine (MDMA), electroconvulsive therapy (ECT), and eye movement desensitization and reprocessing (EMDR) therapy. For this purpose we reviewed PubMed and after initial search, we excluded works unrelated to our aim, non-orginal data and animal studies. We conducted second search to cover all minor methods.

RESULTS

We included 116 studies, which data is presented in Tables. We have investigated which methods can support treatment and which can be used as a stand-alone treatment. We assessed the risks to benefits of using alternative treatments.

CONCLUSION

Alternative treatments significantly expand the options available to patients and clinicians, with many serving as adjuncts to traditional therapies. Among the methods presented, mindfulness has the most significant therapeutic potential.

A biomarker of brain arousal mediates the intergenerational link between maternal and child post-traumatic stress disorder

This study examined whether there is a biological basis in the child's resting brain activity for the intergenerational link between maternal interpersonal violence-related posttraumatic stress disorder (IPV-PTSD) and child subclinical symptoms. We used high-density EEG recordings to investigate the resting brain activity in a sample of 57 children, 34 from mothers with IPV-PTSD, and 23 from mothers without PTSD. These children were part of a prospective, longitudinal study focusing on the offspring of mothers with and without IPV-PTSD, reporting how the severity of a mother's IPV-PTSD can impact her child's emotional regulation and risk for developing mental illness. However, we had not yet looked into potential EEG biomarkers during resting state that might mediate and/or moderate effects of maternal IPV-PTSD severity on child mental health, and in particular the risk for PTSD. The alpha band spectral power as well as the aperiodic exponent of the power spectrum (PLE; power-law exponent) were examined as mediators of maternal IPV-PTSD and child PTSD. While there was no difference in alpha spectral power between the two groups, PLE was significantly reduced in children of mothers with IPV-PTSD compared to control children, indicating cortical hyper-arousal. Interestingly, child PLE was negatively correlated with the severity of maternal IPV-PTSD, suggesting an intergenerational interaction. This interpretation was reinforced by a negative correlation between child PLE and child PTSD symptoms. Finally, causal analyses using structural equation modelling indicated that child PLE mediated the relationship between maternal PTSD severity and child PTSD. Our observations suggest that maternal IPV-PTSD has an intergenerational impact on the child neurobehavioral development through a correlated abnormal marker of brain arousal (i.e. child PLE). These findings are potentially relevant to psychotherapy research and to the development of more effective psycho-neurobehavioral therapies (i.e. neurofeedback) among affected individuals.

Neurofeedback for post-traumatic stress disorder: systematic review and meta-analysis of clinical and neurophysiological outcomes

Background: Posttraumatic stress disorder (PTSD) is a debilitating condition affecting millions of people worldwide. Existing treatments often fail to address the complexity of its symptoms and functional impairments resulting from severe and prolonged trauma. Electroencephalographic Neurofeedback (NFB) has emerged as a promising treatment that aims to reduce the symptoms of PTSD by modulating brain activity.Objective: We conducted a systematic review and meta-analysis of ten clinical trials to answer the question: how effective is NFB in addressing PTSD and other associated symptoms across different trauma populations, and are these improvements related to neurophysiological changes?Method: The review followed the Preferred Reporting Items for Systematic Reviews and Meta analyses guidelines. We considered all published and unpublished randomised controlled trials (RCTs) and non-randomised studies of interventions (NRSIs) involving adults with PTSD as a primary diagnosis without exclusion by type of trauma, co-morbid diagnosis, locality, or sex. Ten controlled studies were included; seven RCTs and three NRSIs with a total number of participants n = 293 (128 male). Only RCTs were included in the meta-analysis (215 participants; 88 male).Results: All included studies showed an advantage of NFB over control conditions in reducing symptoms of PTSD, with indications of improvement in symptoms of anxiety and depression and related neurophysiological changes. Meta-analysis of the pooled data shows a significant reduction in PTSD symptoms post-treatment SMD of -1.76 (95% CI -2.69, -0.83), and the mean remission rate was higher in the NFB group (79.3%) compared to the control group (24.4%). However, the studies reviewed were mostly small, with heterogeneous populations and varied quality.Conclusions: The effect of NFB on the symptoms of PTSD was moderate and mechanistic evidence suggested that NFB leads to therapeutic changes in brain functioning. Future research should focus on more rigorous methodological designs, expanded sample size and longer follow-up.

Chronic Gq activation of ventral hippocampal neurons and astrocytes differentially affects memory and behavior

Network dysfunction is implicated in numerous diseases and psychiatric disorders, and the hippocampus serves as a common origin for these abnormalities. To test the hypothesis that chronic modulation of neurons and astrocytes induces impairments in cognition, we activated the hM3D(Gq) pathway in CaMKII+ neurons or GFAP+ astrocytes within the ventral hippocampus across 3, 6, and 9 months. CaMKII-hM3Dq activation impaired fear extinction at 3 months and acquisition at 9 months. Both CaMKII-hM3Dq manipulation and aging had differential effects on anxiety and social interaction. GFAP-hM3Dq activation impacted fear memory at 6 and 9 months. GFAP-hM3Dq activation impacted anxiety in the open field only at the earliest time point. CaMKII-hM3Dq activation modified the number of microglia, while GFAP-hM3Dq activation impacted microglial morphological characteristics, but neither affected these measures in astrocytes. Overall, our study elucidates how distinct cell types can modify behavior through network dysfunction, while adding a more direct role for glia in modulating behavior.

Sensing fear: fast and precise threat evaluation in human sensory cortex

Animal models of threat processing have evolved beyond the amygdala to incorporate a distributed neural network. In human research, evidence has intensified in recent years to challenge the canonical threat circuitry centered on the amygdala, urging revision of threat conceptualization. A strong surge of research into threat processing in the sensory cortex in the past decade has generated particularly useful insights to inform the reconceptualization. Here, synthesizing findings from both animal and human research, we highlight sensitive, specific, and adaptable threat representations in the sensory cortex, arising from experience-based sculpting of sensory coding networks. We thus propose that the human sensory cortex can drive smart (fast and precise) threat evaluation, producing threat-imbued sensory afferents to elicit network-wide threat responses.

The maternal brain is more flexible and responsive at rest: effective connectivity of the parental caregiving network in postpartum mothers

The field of neuroscience has largely overlooked the impact of motherhood on brain function outside the context of responses to infant stimuli. Here, we apply spectral dynamic causal modelling (spDCM) to resting-state fMRI data to investigate differences in brain function between a group of 40 first-time mothers at 1-year postpartum and 39 age- and education-matched women who have never been pregnant. Using spDCM, we investigate the directionality (top-down vs. bottom-up) and valence (inhibition vs excitation) of functional connections between six key left hemisphere brain regions implicated in motherhood: the dorsomedial prefrontal cortex, ventromedial prefrontal cortex, posterior cingulate cortex, parahippocampal gyrus, amygdala, and nucleus accumbens. We show a selective modulation of inhibitory pathways related to differences between (1) mothers and non-mothers, (2) the interactions between group and cognitive performance and (3) group and social cognition, and (4) differences related to maternal caregiving behaviour. Across analyses, we show consistent disinhibition between cognitive and affective regions suggesting more efficient, flexible, and responsive behaviour, subserving cognitive performance, social cognition, and maternal caregiving. Together our results support the interpretation of these key regions as constituting a parental caregiving network. The nucleus accumbens and the parahippocampal gyrus emerging as 'hub' regions of this network, highlighting the global importance of the affective limbic network for maternal caregiving, social cognition, and cognitive performance in the postpartum period.

Heart and brain traumatic stress biomarker analysis with and without machine learning: A scoping review

The enigma of post-traumatic stress disorder (PTSD) is embedded in a complex array of physiological responses to stressful situations that result in disruptions in arousal and cognitions that characterise the psychological disorder. Deciphering these physiological patterns is complex, which has seen the use of machine learning (ML) grow in popularity. However, it is unclear to what extent ML has been used with physiological data, specifically, the electroencephalogram (EEG) and electrocardiogram (ECG) to further understand the physiological responses associated with PTSD. To better understand the use of EEG and ECG biomarkers, with and without ML, a scoping review was undertaken. A total of 124 papers based on adult samples were identified comprising 19 ML studies involving EEG and ECG. A further 21 studies using EEG data, and 84 studies employing ECG meeting all other criteria but not employing ML were included for comparison. Identified studies indicate classical ML methodologies currently dominate EEG and ECG biomarkers research, with derived biomarkers holding clinically relevant diagnostic implications for PTSD. Discussion of the emerging trends, algorithms used and their success is provided, along with areas for future research.

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.

Psychosis spectrum illnesses as disorders of prefrontal critical period plasticity

Emerging research on neuroplasticity processes in psychosis spectrum illnesses-from the synaptic to the macrocircuit levels-fill key gaps in our models of pathophysiology and open up important treatment considerations. In this selective narrative review, we focus on three themes, emphasizing alterations in spike-timing dependent and Hebbian plasticity that occur during adolescence, the critical period for prefrontal system development: (1) Experience-dependent dysplasticity in psychosis emerges from activity decorrelation within neuronal ensembles. (2) Plasticity processes operate bidirectionally: deleterious environmental and experiential inputs shape microcircuits. (3) Dysregulated plasticity processes interact across levels of scale and time and include compensatory mechanisms that have pathogenic importance. We present evidence that-given the centrality of progressive dysplastic changes, especially in prefrontal cortex-pharmacologic or neuromodulatory interventions will need to be supplemented by corrective learning experiences for the brain if we are to help people living with these illnesses to fully thrive.

Effects of comorbid posttraumatic stress disorder on cognitive dysfunction in Chinese male methamphetamine patients

OBJECTIVES

Cognitive dysfunction and posttraumatic stress disorder (PTSD) are common in methamphetamine patients. However, few studies have investigated the cognitive performance of methamphetamine patients with PTSD. The purpose of this study was to investigate the impact of comorbid PTSD on cognitive function in Chinese male methamphetamine patients.

METHODS

We analyzed 464 methamphetamine patients and 156 healthy volunteers. The PTSD Screening Scale (PCL-5) was used to assess PTSD and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was used to assess cognitive function.

RESULTS

Compared with healthy controls, methamphetamine patients had more cognitive dysfunction in immediate memory, visuospatial/constructional, language, attention and delayed memory. Moreover, methamphetamine patients with PTSD had less cognitive dysfunction in immediate memory, attention, and delayed memory than methamphetamine patients without PTSD. Further stepwise regression analysis showed that PTSD alterations in arousal and reactivity cluster were risk predictors for language, and PTSD negative alteration in cognition and mood cluster were risk predictors for delayed memory.

CONCLUSIONS

Our results indicate that methamphetamine patients without PTSD have poorer cognitive dysfunction than those with PTSD. Some demographic and PTSD symptom clusters are protective or risk factors for cognitive dysfunction in methamphetamine patients.

Resting-state EEG functional connectivity predicts post-traumatic stress disorder subtypes in veterans

Objective. Post-traumatic stress disorder (PTSD) is highly heterogeneous, and identification of quantifiable biomarkers that could pave the way for targeted treatment remains a challenge. Most previous electroencephalography (EEG) studies on PTSD have been limited to specific handpicked features, and their findings have been highly variable and inconsistent. Therefore, to disentangle the role of promising EEG biomarkers, we developed a machine learning framework to investigate a wide range of commonly used EEG biomarkers in order to identify which features or combinations of features are capable of characterizing PTSD and potential subtypes.Approach. We recorded 5 min of eyes-closed and 5 min of eyes-open resting-state EEG from 202 combat-exposed veterans (53% with probable PTSD and 47% combat-exposed controls). Multiple spectral, temporal, and connectivity features were computed and logistic regression, random forest, and support vector machines with feature selection methods were employed to classify PTSD. To obtain robust results, we performed repeated two-layer cross-validation to test on an entirely unseen test set.Main results. Our classifiers obtained a balanced test accuracy of up to 62.9% for predicting PTSD patients. In addition, we identified two subtypes within PTSD: one where EEG patterns were similar to those of the combat-exposed controls, and another that were characterized by increased global functional connectivity. Our classifier obtained a balanced test accuracy of 79.4% when classifying this PTSD subtype from controls, a clear improvement compared to predicting the whole PTSD group. Interestingly, alpha connectivity in the dorsal and ventral attention network was particularly important for the prediction, and these connections were positively correlated with arousal symptom scores, a central symptom cluster of PTSD.Significance. Taken together, the novel framework presented here demonstrates how unsupervised subtyping can delineate heterogeneity and improve machine learning prediction of PTSD, and may pave the way for better identification of quantifiable biomarkers.

Etiopathogenic Models of Psychosis Spectrum Illnesses Must Resolve Four Key Features

Etiopathogenic models for psychosis spectrum illnesses are converging on a number of key processes, such as the influence of specific genes on the synthesis of proteins important in synaptic functioning, alterations in how neurons respond to synaptic inputs and engage in synaptic pruning, and microcircuit dysfunction that leads to more global cortical information processing vulnerabilities. Disruptions in prefrontal operations then accumulate and propagate over time, interacting with environmental factors, developmental processes, and homeostatic mechanisms, eventually resulting in symptoms of psychosis and disability. However, there are 4 key features of psychosis spectrum illnesses that are of primary clinical relevance but have been difficult to assimilate into a single model and have thus far received little direct attention: 1) the bidirectionality of the causal influences for the emergence of psychosis, 2) the catastrophic clinical threshold seen in first episodes of psychosis and why it is irreversible in some individuals, 3) observed biotypes that are neurophysiologically distinct but clinically both convergent and divergent, and 4) a reconciliation of the role of striatal dopaminergic dysfunction with models of prefrontal cortical state instability. In this selective review, we briefly describe these 4 hallmark features and we argue that theoretically driven computational perspectives making use of both algorithmic and neurophysiologic models are needed to reduce this complexity and variability of psychosis spectrum illnesses in a principled manner.

A Web-Based Cognitive Behavioral Therapy, Mindfulness Meditation, and Yoga Intervention for Posttraumatic Stress Disorder: Single-Arm Experimental Clinical Trial

BACKGROUND

Posttraumatic stress disorder (PTSD) is a debilitating, undertreated condition. The web-based delivery of cognitive behavioral therapy supplemented with mindfulness meditation and yoga is a viable treatment that emphasizes self-directed daily practice.

OBJECTIVE

This study aims to examine the effectiveness of a web-based cognitive behavioral therapy, mindfulness, and yoga (CBT-MY) program designed for daily use.

METHODS

We conducted an 8-week, single-arm, experimental, registered clinical trial on adults reporting PTSD symptoms (n=22; aged 18-35 years). Each participant received web-based CBT-MY content and an hour of web-based counseling each week. Pre-post outcomes included self-reported PTSD symptom severity, depression, anxiety, chronic pain, and mindfulness. Pre-post psychophysiological outcomes included peak pupil dilation (PPD) and heart rate variability (HRV). HRV and PPD were also compared with cross-sectional data from a non-PTSD comparison group without a history of clinical mental health diagnoses and CBT-MY exposure (n=46).

RESULTS

Pre-post intention-to-treat analyses revealed substantial improvements in PTSD severity (d=1.60), depression (d=0.83), anxiety (d=0.99), and mindfulness (d=0.88). Linear multilevel mixed models demonstrated a significant pre-post reduction in PPD (B=-0.06; SE=0.01; P<.001; d=0.90) but no significant pre-post change in HRV (P=.87). Overall, participants spent an average of 11.53 (SD 22.76) min/day on self-directed mindfulness practice.

CONCLUSIONS

Web-based CBT-MY was associated with clinically significant symptom reductions and significant PPD changes, suggesting healthier autonomic functioning. Future randomized controlled trials are needed to further examine the gains apparent in this single-arm study.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03684473; https://clinicaltrials.gov/ct2/show/NCT03684473.

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.

Spectral decomposition of EEG microstates in post-traumatic stress disorder

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EEG microstates reveal significant temporal differences in PTSD.

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Microstate E (with centro-posterior maximum) is temporally underrepresented in PTSD.

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In PTSD, microstate E has a reduced occurrence and a shorter mean duration.

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Spectral decomposition of EEG microstates improves microstate-based classification.

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Alpha band SVM features yield the highest classification accuracy of PTSD (76%).

Microstates offer a promising framework to study fast-scale brain dynamics in the resting-state electroencephalogram (EEG). However, microstate dynamics have yet to be investigated in post-traumatic stress disorder (PTSD), despite research demonstrating resting-state alterations in PTSD. We performed microstate-based segmentation of resting-state EEG in a clinical population of participants with PTSD (N = 61) and a non-traumatized, healthy control group (N = 61). Microstate-based measures (i.e., occurrence, mean duration, time coverage) were compared group-wise using broadband (1–30 Hz) and frequency-specific (i.e., delta, theta, alpha, beta bands) decompositions. In the broadband comparisons, the centro-posterior maximum microstate (map E) occurred significantly less frequently (d = -0.64, pFWE = 0.03) and had a significantly shorter mean duration in participants with PTSD as compared to controls (d = -0.71, pFWE < 0.01). These differences were reflected in the narrow frequency bands as well, with lower frequency bands like delta (d = -0.78, pFWE < 0.01), theta (d = -0.74, pFWE = 0.01), and alpha (d = -0.65, pFWE = 0.02) repeating these group-level trends, only with larger effect sizes. Interestingly, a support vector machine classification analysis comparing broadband and frequency-specific measures revealed that models containing only alpha band features significantly out-perform broadband models. When classifying PTSD, the classification accuracy was 76 % and 65 % for the alpha band and the broadband model, respectively (p = 0.03). Taken together, we provide original evidence supporting the clinical utility of microstates as diagnostic markers of PTSD and demonstrate that filtering EEG into distinct frequency bands significantly improves microstate-based classification of a psychiatric disorder.

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.

Temporally Targeted Interactions With Pathologic Oscillations as Therapeutical Targets in Epilepsy and Beyond

Self-organized neuronal oscillations rely on precisely orchestrated ensemble activity in reverberating neuronal networks. Chronic, non-malignant disorders of the brain are often coupled to pathological neuronal activity patterns. In addition to the characteristic behavioral symptoms, these disturbances are giving rise to both transient and persistent changes of various brain rhythms. Increasing evidence support the causal role of these "oscillopathies" in the phenotypic emergence of the disease symptoms, identifying neuronal network oscillations as potential therapeutic targets. While the kinetics of pharmacological therapy is not suitable to compensate the disease related fine-scale disturbances of network oscillations, external biophysical modalities (e.g., electrical stimulation) can alter spike timing in a temporally precise manner. These perturbations can warp rhythmic oscillatory patterns via resonance or entrainment. Properly timed phasic stimuli can even switch between the stable states of networks acting as multistable oscillators, substantially changing the emergent oscillatory patterns. Novel transcranial electric stimulation (TES) approaches offer more reliable neuronal control by allowing higher intensities with tolerable side-effect profiles. This precise temporal steerability combined with the non- or minimally invasive nature of these novel TES interventions make them promising therapeutic candidates for functional disorders of the brain. Here we review the key experimental findings and theoretical background concerning various pathological aspects of neuronal network activity leading to the generation of epileptic seizures. The conceptual and practical state of the art of temporally targeted brain stimulation is discussed focusing on the prevention and early termination of epileptic seizures.

EEG Neurofeedback for Anxiety Disorders and Post-Traumatic Stress Disorders: A Blueprint for a Promising Brain-Based Therapy

PURPOSE OF REVIEW

This review provides an overview of current knowledge and understanding of EEG neurofeedback for anxiety disorders and post-traumatic stress disorders.

RECENT FINDINGS

The manifestations of anxiety disorders and post-traumatic stress disorders (PTSD) are associated with dysfunctions of neurophysiological stress axes and brain arousal circuits, which are important dimensions of the research domain criteria (RDoC). Even if the pathophysiology of these disorders is complex, one of its defining signatures is behavioral and physiological over-arousal. Interestingly, arousal-related brain activity can be modulated by electroencephalogram-based neurofeedback (EEG NF), a non-pharmacological and non-invasive method that involves neurocognitive training through a brain-computer interface (BCI). EEG NF is characterized by a simultaneous learning process where both patient and computer are involved in modifying neuronal activity or connectivity, thereby improving associated symptoms of anxiety and/or over-arousal. Positive effects of EEG NF have been described for both anxiety disorders and PTSD, yet due to a number of methodological issues, it remains unclear whether symptom improvement is the direct result of neurophysiological changes targeted by EEG NF. Thus, in this work we sought to bridge current knowledge on brain mechanisms of arousal with past and present EEG NF therapies for anxiety and PTSD. In a nutshell, we discuss the neurophysiological mechanisms underlying the effects of EEG NF in anxiety disorder and PTSD, the methodological strengths/weaknesses of existing EEG NF randomized controlled trials for these disorders, and the neuropsychological factors that may impact NF training success.

Elevated Tau in Military Personnel Relates to Chronic Symptoms Following Traumatic Brain Injury

OBJECTIVE

To understand the relationships between traumatic brain injury (TBI), blood biomarkers, and symptoms of posttraumatic stress disorder (PTSD), depression, and postconcussive syndrome symptoms.

DESIGN

Cross-sectional cohort study using multivariate analyses.

PARTICIPANTS

One hundred nine military personnel and veterans, both with and without a history of TBI.

MAIN MEASURES

PTSD Checklist-Civilian Version (PCL-C); Neurobehavioral Symptom Inventory (NSI); Ohio State University TBI Identification Method; Patient Health Questionnaire-9 (PHQ-9); Simoa-measured concentrations of tau, amyloid-beta (Aβ) 40, Aβ42, and neurofilament light (NFL).

RESULTS

Controlling for age, sex, time since last injury (TSLI), and antianxiety/depression medication use, NFL was trending toward being significantly elevated in participants who had sustained 3 or more TBIs compared with those who had sustained 1 or 2 TBIs. Within the TBI group, partial correlations that controlled for age, sex, TSLI, and antianxiety/depression medication use showed that tau concentrations were significantly correlated with greater symptom severity, as measured with the NSI, PCL, and PHQ-9.

CONCLUSIONS

Elevations in tau are associated with symptom severity after TBI, while NFL levels are elevated in those with a history of repetitive TBIs and in military personnel and veterans. This study shows the utility of measuring biomarkers chronically postinjury. Furthermore, there is a critical need for studies of biomarkers longitudinally following TBI.

Theta-Range Oscillations in Stress-Induced Mental Disorders as an Oscillotherapeutic Target

Emotional behavior and psychological disorders are expressed through coordinated interactions across multiple brain regions. Brain electrophysiological signals are composed of diverse neuronal oscillations, representing cell-level to region-level neuronal activity patterns, and serve as a biomarker of mental disorders. Here, we review recent observations from rodents demonstrating how neuronal oscillations in the hippocampus, amygdala, and prefrontal cortex are engaged in emotional behavior and altered by psychiatric changes such as anxiety and depression. In particular, we focus mainly on theta-range (4–12 Hz) oscillations, including several distinct oscillations in this frequency range. We then discuss therapeutic possibilities related to controlling such mental disease-related neuronal oscillations to ameliorate psychiatric symptoms and disorders in rodents and humans.

A unifying translational framework to advance treatment research for comorbid PTSD and substance use disorders

We provide a unifying translational framework that can be used to synthesize extant lines of human laboratory research in four neurofunctional domains that underlie the co-occurrence of posttraumatic stress and substance use disorders (PTSD+SUD). We draw upon the Alcohol and Addiction Research Domain Criteria (AARDOC) to include executive functioning, negative emotionality, reward, and added social cognition from the National Institute of Mental Health (NIMH) Research Domain Criteria into our framework. We review research findings across each of the four domains, emphasizing human experimental studies in PTSD, SUD, and PTSD+SUD for each domain. We also discuss the implications of research findings for treatment development by considering new ways of conceptualizing risk factors and outcomes at the level of the individual patient, which will enhance treatment matching and advance innovations in intervention.

Behavioral, Physiological and EEG Activities Associated with Conditioned Fear as Sensors for Fear and Anxiety

Anxiety disorders impose substantial costs upon public health and productivity in the USA and worldwide. At present, these conditions are quantified by self-report questionnaires that only apply to behaviors that are accessible to consciousness, or by the timing of responses to fear- and anxiety-related words that are indirect since they do not produce fear, e.g., Dot Probe Test and emotional Stroop. We now review the conditioned responses (CRs) to fear produced by a neutral stimulus (conditioned stimulus CS+) when it cues a painful laser unconditioned stimulus (US). These CRs include autonomic (Skin Conductance Response) and ratings of the CS+ unpleasantness, ability to command attention, and the recognition of the association of CS+ with US (expectancy). These CRs are directly related to fear, and some measure behaviors that are minimally accessible to consciousness e.g., economic scales. Fear-related CRs include non-phase-locked phase changes in oscillatory EEG power defined by frequency and time post-stimulus over baseline, and changes in phase-locked visual and laser evoked responses both of which include late potentials reflecting attention or expectancy, like the P300, or contingent negative variation. Increases (ERS) and decreases (ERD) in oscillatory power post-stimulus may be generalizable given their consistency across healthy subjects. ERS and ERD are related to the ratings above as well as to anxious personalities and clinical anxiety and can resolve activity over short time intervals like those for some moods and emotions. These results could be incorporated into an objective instrumented test that measures EEG and CRs of autonomic activity and psychological ratings related to conditioned fear, some of which are subliminal. As in the case of instrumented tests of vigilance, these results could be useful for the direct, objective measurement of multiple aspects of the risk, diagnosis, and monitoring of therapies for anxiety disorders and anxious personalities.

A randomized, controlled trial of alpha-rhythm EEG neurofeedback in posttraumatic stress disorder: A preliminary investigation showing evidence of decreased PTSD symptoms and restored default mode and salience network connectivity using fMRI

OBJECTIVE

The default-mode network (DMN) and salience network (SN) have been shown to display altered connectivity in posttraumatic stress disorder (PTSD). Restoring aberrant connectivity within these networks with electroencephalogram neurofeedback (EEG-NFB) has been shown previously to be associated with acute decreases in symptoms. Here, we conducted a double-blind, sham-controlled randomized trial of alpha-rhythm EEG-NFB in participants with PTSD (n = 36) over 20-weeks. Our aim was to provide mechanistic evidence underlying clinical improvements by examining changes in network connectivity via fMRI.

METHODS

We randomly assigned participants with a primary diagnosis of PTSD to either the experimental group (n = 18) or sham-control group (n = 18). We collected resting-state fMRI scans pre- and post-NFB intervention, for both the experimental and sham-control PTSD groups. We further compared baseline brain connectivity measures pre-NFB to age-matched healthy controls (n = 36).

RESULTS

With regard to the primary outcome measure of PTSD severity, we found a significant main effect of time in the absence of a group × time interaction. Nevertheless, we found significantly decreased PTSD severity scores in the experimental NFB group only, when comparing post-NFB (dz = 0.71) and 3-month follow-up scores (dz = 0.77) to baseline measures. Interestingly, we found evidence to suggest a shift towards normalization of DMN and SN connectivity post-NFB in the experimental group only. Both decreases in PTSD severity and NFB performance were correlated to DMN and SN connectivity post-NFB in the experimental group. Critically, remission rates of PTSD were significant higher in the experimental group (61.1%) as compared to the sham-control group (33.3%).

CONCLUSION

The current study shows mechanistic evidence for therapeutic changes in DMN and SN connectivity that are known to be associated with PTSD psychopathology with no patient dropouts. This preliminary investigation merits further research to demonstrate fully the clinical efficacy of EEG-NFB as an adjunctive therapy for PTSD.

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.

Distinguishing vigilance decrement and low task demands from mind-wandering: A machine learning analysis of EEG

Mind‐wandering is a ubiquitous mental phenomenon that is defined as self‐generated thought irrelevant to the ongoing task. Mind‐wandering tends to occur when people are in a low‐vigilance state or when they are performing a very easy task. In the current study, we investigated whether mind‐wandering is completely dependent on vigilance and current task demands, or whether it is an independent phenomenon. To this end, we trained support vector machine (SVM) classifiers on EEG data in conditions of low and high vigilance, as well as under conditions of low and high task demands, and subsequently tested those classifiers on participants' self‐reported mind‐wandering. Participants' momentary mental state was measured by means of intermittent thought probes in which they reported on their current mental state. The results showed that neither the vigilance classifier nor the task demands classifier could predict mind‐wandering above‐chance level, while a classifier trained on self‐reports of mind‐wandering was able to do so. This suggests that mind‐wandering is a mental state different from low vigilance or performing tasks with low demands—both which could be discriminated from the EEG above chance. Furthermore, we used dipole fitting to source‐localize the neural correlates of the most import features in each of the three classifiers, indeed finding a few distinct neural structures between the three phenomena. Our study demonstrates the value of machine‐learning classifiers in unveiling patterns in neural data and uncovering the associated neural structures by combining it with an EEG source analysis technique.

Altered information flow and microstructure abnormalities of visual cortex in normal-tension glaucoma: Evidence from resting-state fMRI and DKI

Normal tension glaucoma (NTG) is a neurodegenerative disease involves multiple brain areas, but the mechanism remains unclear. The aim of this study is to investigate the correlation between structural injury and functional reorganization in the brain of NTG, using resting-state functional MRI and diffusion kurtosis imaging (DKI) data acquired for 26 NTG patients and 24 control subjects. Granger causality analysis (GCA) was used to calculate the effective connectivity (EC) between visual cortices and the whole brain to reflect the information flow. The fractional anisotropy (FA), mean kurtosis (MK), axial kurtosis (AK), and radial kurtosis (RK) derived from DKI of visual cortices were extracted to evaluate structural injury. Microstructural abnormalities were detected in bilateral BA17, BA18, and BA19. NTG patients showed significantly decreased EC from BA17 to higher visual cortices and increase EC from higher visual cortices to BA17. The EC from BA17 to posterior cingulate cortex (PCC) and from PCC to BA17 both significantly increased, while the EC from right BA18 and BA19 to PCC significantly decreased. Decreased EC between somatosensory cortex and BA17, as well as the decreased ECs between supramarginal gyrus (SMA) and BA17/BA19 were detected. Several abnormal ECs were significantly correlated with microstructural injuries of BA17 and BA18. In conclusion, NTG causes reorganization of information flows among visual cortices and other brain areas, which is consistent with brain microstructural injury.

Rethinking post-traumatic stress disorder - A predictive processing perspective

Predictive processing has become a popular framework in neuroscience and computational psychiatry, where it has provided a new understanding of various mental disorders. Here, we apply the predictive processing account to post-traumatic stress disorder (PTSD). We argue that the experience of a traumatic event in Bayesian terms can be understood as a perceptual hypothesis that is subsequently given a very high a-priori likelihood due to its (life-) threatening significance; thus, this hypothesis is re-selected although it does not fit the actual sensory input. Based on this account, we re-conceptualise the symptom clusters of PTSD through the lens of a predictive processing model. We particularly focus on re-experiencing symptoms as the hallmark symptoms of PTSD, and discuss the occurrence of flashbacks in terms of perceptual and interoceptive inference. This account provides not only a new understanding of the clinical profile of PTSD, but also a unifying framework for the corresponding pathologies at the neurobiological level. Finally, we derive directions for future research and discuss implications for psychological and pharmacological interventions.

Classifying post-traumatic stress disorder using the magnetoencephalographic connectome and machine learning

Given the subjective nature of conventional diagnostic methods for post-traumatic stress disorder (PTSD), an objectively measurable biomarker is highly desirable; especially to clinicians and researchers. Macroscopic neural circuits measured using magnetoencephalography (MEG) has previously been shown to be indicative of the PTSD phenotype and severity. In the present study, we employed a machine learning-based classification framework using MEG neural synchrony to distinguish combat-related PTSD from trauma-exposed controls. Support vector machine (SVM) was used as the core classification algorithm. A recursive random forest feature selection step was directly incorporated in the nested SVM cross validation process (CV-SVM-rRF-FS) for identifying the most important features for PTSD classification. For the five frequency bands tested, the CV-SVM-rRF-FS analysis selected the minimum numbers of edges per frequency that could serve as a PTSD signature and be used as the basis for SVM modelling. Many of the selected edges have been reported previously to be core in PTSD pathophysiology, with frequency-specific patterns also observed. Furthermore, the independent partial least squares discriminant analysis suggested low bias in the machine learning process. The final SVM models built with selected features showed excellent PTSD classification performance (area-under-curve value up to 0.9). Testament to its robustness when distinguishing individuals from a heavily traumatised control group, these developments for a classification model for PTSD also provide a comprehensive machine learning-based computational framework for classifying other mental health challenges using MEG connectome profiles.

Amygdala functional connectivity in the acute aftermath of trauma prospectively predicts severity of posttraumatic stress symptoms

Understanding neural mechanisms that confer risk for posttraumatic stress disorder (PTSD) is critical for earlier intervention, yet longitudinal work has been sparse. The amygdala is part of a core network consistently implicated in PTSD symptomology. Most neural models of PTSD have focused on the amygdala's interactions with the dorsal anterior cingulate cortex, ventromedial prefrontal cortex, and hippocampus. However, an increasing number of studies have linked PTSD symptoms to aberrations in amygdala functional connections with other brain regions involved in emotional information processing, self-referential processing, somatosensory processing, visual processing, and motor control. In the current study, trauma-exposed individuals (N = 54) recruited from the emergency department completed a resting state fMRI scan as well as a script-driven trauma recall fMRI task scan two-weeks post-trauma along with demographic, PTSD, and other clinical symptom questionnaires two-weeks and six-months post-trauma. We examined whether amygdala-whole brain functional connectivity (FC) during rest and task could predict six-month post-trauma PTSD symptoms. More negative amygdala-cerebellum and amygdala-postcentral gyrus FC during rest as well as more negative amygdala-postcentral gyrus and amygdala-midcingulate cortex during recall of the trauma memory predicted six-month post-trauma PTSD after controlling for scanner type. Follow-up multiple regression sensitivity analyses controlling for several other relevant predictors of PTSD symptoms, revealed that amygdala-cerebellum FC during rest and amygdala-postcentral gyrus FC during trauma recall were particularly robust predictors of six-month PTSD symptoms. The results extend cross-sectional studies implicating abnormal FC of the amygdala with other brain regions involved in somatosensory processing, motor control, and emotional information processing in PTSD, to the prospective prediction of risk for chronic PTSD. This work may contribute to earlier identification of at-risk individuals and elucidate potential intervention targets.

Individual Patterns of Abnormality in Resting-State Functional Connectivity Reveal Two Data-Driven PTSD Subgroups

OBJECTIVE

A major challenge in understanding and treating posttraumatic stress disorder (PTSD) is its clinical heterogeneity, which is likely determined by various neurobiological perturbations. This heterogeneity likely also reduces the effectiveness of standard group comparison approaches. The authors tested whether a statistical approach aimed at identifying individual-level neuroimaging abnormalities that are more prevalent in case subjects than in control subjects could reveal new clinically meaningful insights into the heterogeneity of PTSD.

METHODS

Resting-state functional MRI data were recorded from 87 unmedicated PTSD case subjects and 105 war zone-exposed healthy control subjects. Abnormalities were modeled using tolerance intervals, which referenced the distribution of healthy control subjects as the "normative population." Out-of-norm functional connectivity values were examined for enrichment in cases and then used in a clustering analysis to identify biologically defined PTSD subgroups based on their abnormality profiles.

RESULTS

The authors identified two subgroups among PTSD cases, each with a distinct pattern of functional connectivity abnormalities with respect to healthy control subjects. Subgroups differed clinically on levels of reexperiencing symptoms and improved case-control discriminability and were detectable using independently recorded resting-state EEG data.

CONCLUSIONS

The results provide proof of concept for the utility of abnormality-based approaches for studying heterogeneity within clinical populations. Such approaches, applied not only to neuroimaging data, may allow detection of subpopulations with distinct biological signatures so that further clinical and mechanistic investigations can be focused on more biologically homogeneous subgroups.

Regulating posttraumatic stress disorder symptoms with neurofeedback: Regaining control of the mind

Neurofeedback is emerging as a psychophysiological treatment where self-regulation is achieved through online feedback of neural states. Novel personalized medicine approaches are particularly important for the treatment of posttraumatic stress disorder (PTSD), as symptom presentation of the disorder, as well as responses to treatment, are highly heterogeneous. Learning to achieve control of specific neural substrates through neurofeedback has been shown to display therapeutic evidence in patients with a wide variety of psychiatric disorders, including PTSD. This article outlines the neural mechanisms underlying neurofeedback and examines converging evidence for the efficacy of neurofeedback as an adjunctive treatment for PTSD via both electroencephalography (EEG) and real-time functional magnetic resonance imaging (fMRI) modalities. Further, implications for the treatment of PTSD via neurofeedback in the military member and Veteran population is examined.

Sensory Modulation in Children Exposed to Continuous Traumatic Stress

Preliminary evidence supports a possible association between post-traumatic stress disorder (PTSD) and sensory modulation disorder (SMD). Nevertheless, the research focusing on this relationship in children is notably limited. This study examined children with and without PTS symptoms, by comparing their mothers' perceptions of their responses to sensory events in daily life. Mothers of 134 non-referred children aged 5-11, exposed to continuous traumatic stress due to political violence, completed the UCLA-RI and the Short Sensory Profile questionnaires. Significant differences emerged between children with different levels of PTS symptoms in various sensory modalities. Furthermore, half of the symptomatic children had suspected clinically significant deficits in sensory processing. In addition, PTSD symptoms were significantly associated with most of the sensory processing scores. Logistic regression indicated that the overall sensory processing score was a significant predictor of group classification. The results indicate that children with PTS symptoms may be at increased risk for sensory processing deficits. Evaluation of sensory processing should be incorporated into the routine evaluation of this population in order to determine whether this is an additional factor contributing to a child's difficulties in participating in daily activities. Subsequent intervention programs should then address the multiple needs of these children.

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

Intrusive re-experiencing of traumatic events is a hallmark symptom of posttraumatic stress disorder, characterized by rich and vivid sensory details as reported in "flashbacks". While prevailing models of trauma intrusions focus on dysregulated emotional processes, we hypothesize that a deficiency in intrinsic sensory inhibition could drive overactivation of sensory representations of trauma memories, precipitating sensory-rich intrusions. In a sample of combat veterans, we examined resting-state alpha (8-12 Hz) oscillatory activity (in both power and posterior→frontal connectivity), given its role in sensory cortical inhibition, in association with intrusive re-experiencing symptoms. Veterans further participated in an odor task (including both combat and non-combat odors) to assess olfactory trauma memory and emotional response. We observed an association between intrusive re-experiencing symptoms and attenuated resting-state posterior→frontal alpha connectivity, which were both correlated with olfactory trauma memory. Importantly, olfactory trauma memory was identified as a mediator of the relationship between alpha connectivity and intrusive re-experiencing, suggesting that deficits in intrinsic sensory inhibition contributed to intrusive re-experiencing of trauma via heightened trauma memory. Therefore, by permitting unfiltered sensory cues to enter information processing and activate sensory representations of trauma, sensory disinhibition can constitute a sensory mechanism of intrusive re-experiencing in trauma-exposed individuals.

Oscillotherapeutics - Time-targeted interventions in epilepsy and beyond

Oscillatory brain activities support many physiological functions from motor control to cognition. Disruptions of the normal oscillatory brain activities are commonly observed in neurological and psychiatric disorders including epilepsy, Parkinson's disease, Alzheimer's disease, schizophrenia, anxiety/trauma-related disorders, major depressive disorders, and drug addiction. Therefore, these disorders can be considered as common oscillation defects despite having distinct behavioral manifestations and genetic causes. Recent technical advances of neuronal activity recording and analysis have allowed us to study the pathological oscillations of each disorder as a possible biomarker of symptoms. Furthermore, recent advances in brain stimulation technologies enable time- and space-targeted interventions of the pathological oscillations of both neurological disorders and psychiatric disorders as possible targets for regulating their symptoms.