Brain function complexity during dual-tasking is associated with cognitive impairment and age.

BACKGROUND AND PURPOSE: Early diagnosis of cognitive impairment is important because symptoms can be delayed through therapies. Synaptic disconnections are the key characteristics of dementia, and through nonlinear complexity analysis of brain function, it is possible to identify long-range synaptic disconnections in the brain. METHODS: We investigated the capability of a novel upper-extremity function (UEF) dual-task paradigm in the functional MRI (fMRI) setting, where the participant flexes and extends their arm while counting, to differentiate between cognitively normal (CN) and those with mild cognitive impairment (MCI). We used multiscale entropy (MSE) complexity analysis of the blood oxygen-level dependent time-series across neural networks and brain regions. Outside of the fMRI, we used the UEF dual-task test, while the elbow kinematics were measured using motion sensors, to record the motor function score. RESULTS: Results showed 34% lower MSE values in MCI compared to CN (p<.04 for all regions and networks except cerebellum when counting down by one; effect size = 1.35±0.15) and a negative correlation between MSE values and age (average r2 of 0.30 for counting down by one and 0.36 for counting backward by three). Results also showed an improvement in the logistic regression model sensitivity by 14-24% in predicting the presence of MCI when brain function measure was added to the motor function score (kinematics data). CONCLUSIONS: Current findings suggest that combining measures of neural network and motor function, in addition to neuropsychological testing, may provide an accurate tool for assessing early-stage cognitive impairment and age-related decline in cognition.

Towards high-accuracy classifying attention-deficit/hyperactivity disorders using CNN-LSTM model.

Objective. The neurocognitive attention functions involve the cooperation of multiple brain regions, and the defects in the cooperation will lead to attention-deficit/hyperactivity disorder (ADHD), which is one of the most common neuropsychiatric disorders for children. The current ADHD diagnosis is mainly based on a subjective evaluation that is easily biased by the experience of the clinicians and lacks the support of objective indicators. The purpose of this study is to propose a method that can effectively identify children with ADHD.Approach. In this study, we proposed a CNN-LSTM model to solve the three-class problems of classifying ADHD, attention deficit disorder (ADD) and healthy children, based on a public electroencephalogram (EEG) dataset that includes event-related potential (ERP) EEG signals of 144 children. The convolution visualization and saliency map methods were used to observe the features automatically extracted by the proposed model, which could intuitively explain how the model distinguished different groups.Main results. The results showed that our CNN-LSTM model could achieve an accuracy as high as 98.23% in a five-fold cross-validation method, which was significantly better than the current state-of-the-art CNN models. The features extracted by the proposed model were mainly located in the frontal and central areas, with significant differences in the time period mappings among the three different groups. The P300 and contingent negative variation (CNV) in the frontal lobe had the largest decrease in the healthy control (HC) group, and the ADD group had the smallest decrease. In the central area, only the HC group had a significant negative oscillation of CNV waves.Significance. The results of this study suggest that the CNN-LSTM model can effectively identify children with ADHD and its subtypes. The visualized features automatically extracted by this model could better explain the differences in the ERP response among different groups, which is more convincing than previous studies, and it could be used as more reliable neural biomarkers to help with more accurate diagnosis in the clinics.

Multimodal investigation of the association between shift work and the brain in a population-based sample of older adults.

Neuropsychological studies reported that shift workers show reduced cognitive performance and circadian dysfunctions which may impact structural and functional brain networks. Here we tested the hypothesis whether night shift work is associated with resting-state functional connectivity (RSFC), cortical thickness and gray matter volume in participants of the 1000BRAINS study for whom information on night shift work and imaging data were available. 13 PRESENT and 89 FORMER night shift workers as well as 430 control participants who had never worked in shift (NEVER) met these criteria and were included in our study. No associations between night shift work, three graph-theoretical measures of RSFC of 7 functional brain networks and brain morphology were found after multiple comparison correction. Preceding multiple comparison correction, our results hinted at an association between more years of shift work and higher segregation of the visual network in PRESENT shift workers and between shift work experience and lower gray matter volume of the left thalamus. Extensive neuropsychological investigations supplementing objective imaging methodology did not reveal an association between night shift work and cognition after multiple comparison correction. Our pilot study suggests that night shift work does not elicit general alterations in brain networks and affects the brain only to a limited extent. These results now need to be corroborated in studies with larger numbers of participants.

Neonatal brain injury influences structural connectivity and childhood functional outcomes.

Neonatal brain injury may impact brain development and lead to lifelong functional impairments. Hypoxic-ischemic encephalopathy (HIE) and congenital heart disease (CHD) are two common causes of neonatal brain injury differing in timing and mechanism. Maturation of whole-brain neural networks can be quantified during development using diffusion magnetic resonance imaging (dMRI) in combination with graph theory metrics. DMRI of 35 subjects with CHD and 62 subjects with HIE were compared to understand differences in the effects of HIE and CHD on the development of network topological parameters and functional outcomes. CHD newborns had worse 12-18 month language (P<0.01) and 30 month cognitive (P<0.01), language (P = 0.05), motor outcomes (P = 0.01). Global efficiency, a metric of brain integration, was lower in CHD (P = 0.03) than in HIE, but transitivity, modularity and small-worldness were similar. After controlling for clinical factors known to affect neurodevelopmental outcomes, we observed that global efficiency was highly associated with 30 month motor outcomes (P = 0.02) in both groups. To explore neural correlates of adverse language outcomes in CHD, we used hypothesis-based and data-driven approaches to identify pathways with altered structural connectivity. We found that connectivity strength in the superior longitudinal fasciculus (SLF) tract 2 was inversely associated with expressive language. After false discovery rate correction, a whole connectome edge analysis identified 18 pathways that were hypoconnected in the CHD cohort as compared to HIE. In sum, our study shows that neonatal structural connectivity predicts early motor development after HIE or in subjects with CHD, and regional SLF connectivity is associated with language outcomes. Further research is needed to determine if and how brain networks change over time and whether those changes represent recovery or ongoing dysfunction. This knowledge will directly inform strategies to optimize neurologic functional outcomes after neonatal brain injury.

Phase synchronization and measure of criticality in a network of neural mass models.

Synchronization has an important role in neural networks dynamics that is mostly accompanied by cognitive activities such as memory, learning, and perception. These activities arise from collective neural behaviors and are not totally understood yet. This paper aims to investigate a cortical model from this perspective. Historically, epilepsy has been regarded as a functional brain disorder associated with excessive synchronization of large neural populations. Epilepsy is believed to arise as a result of complex interactions between neural networks characterized by dynamic synchronization. In this paper, we investigated a network of neural populations in a way the dynamics of each node corresponded to the Jansen-Rit neural mass model. First, we study a one-column Jansen-Rit neural mass model for four different input levels. Then, we considered a Watts-Strogatz network of Jansen-Rit oscillators. We observed an epileptic activity in the weak input level. The network is considered to change various parameters. The detailed results including the mean time series, phase spaces, and power spectrum revealed a wide range of different behaviors such as epilepsy, healthy, and a transition between synchrony and asynchrony states. In some points of coupling coefficients, there is an abrupt change in the order parameters. Since the critical state is a dynamic candidate for healthy brains, we considered some measures of criticality and investigated them at these points. According to our study, some markers of criticality can occur at these points, while others may not. This occurrence is a result of the nature of the specific order parameter selected to observe these markers. In fact, The definition of a proper order parameter is key and must be defined properly. Our view is that the critical points exhibit clear characteristics and invariance of scale, instead of some types of markers. As a result, these phase transition points are not critical as they show no evidence of scaling invariance.

Disrupted Dynamic Functional Connectivity of the Visual Network in Episodic Patients with Migraine without Aura.

Background: Visual symptoms are common in patients with migraine, even in interictal periods. The purpose was to assess the association between dynamic functional connectivity (dFC) of the visual cortex and clinical characteristics in migraine without aura (MwoA) patients. Methods: We enrolled fifty-five MwoA patients as well as fifty gender- and age-matched healthy controls. Regional visual cortex alterations were investigated using regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF). Then, significant regions were selected as seeds for conducting dFC between the visual cortex and the whole brain. Results: Relative to healthy controls, MwoA patients exhibited decreased ReHo and ALFF values in the right lingual gyrus (LG) and increased ALFF values in the prefrontal cortex. The right LG showed abnormal dFC within the visual cortex and with other core brain networks. Additionally, ReHo values for the right LG were correlated with duration of disease and ALFF values of the right inferior frontal gyrus and middle frontal gyrus were correlated with headache frequency and anxiety scores, respectively. Moreover, the abnormal dFC of the right LG with bilateral cuneus was positively correlated with anxiety scores. Conclusions: The dFC abnormalities of the visual cortex may be involved in pain integration with multinetworks and associated with anxiety disorder in episodic MwoA patients.

Accelerated Aging Characterizes the Early Stage of Alzheimer's Disease.

For Alzheimer's disease (AD), aging is the main risk factor, but whether cognitive impairments due to aging resemble early AD deficits is not yet defined. When working with mouse models of AD, the situation is just as complicated, because only a few studies track the progression of the disease at different ages, and most ignore how the aging process affects control mice. In this work, we addressed this problem by comparing the aging process of PS2APP (AD) and wild-type (WT) mice at the level of spontaneous brain electrical activity under anesthesia. Using local field potential recordings, obtained with a linear probe that traverses the posterior parietal cortex and the entire hippocampus, we analyzed how multiple electrical parameters are modified by aging in AD and WT mice. With this approach, we highlighted AD specific features that appear in young AD mice prior to plaque deposition or that are delayed at 12 and 16 months of age. Furthermore, we identified aging characteristics present in WT mice but also occurring prematurely in young AD mice. In short, we found that reduction in the relative power of slow oscillations (SO) and Low/High power imbalance are linked to an AD phenotype at its onset. The loss of SO connectivity and cortico-hippocampal coupling between SO and higher frequencies as well as the increase in UP-state and burst durations are found in young AD and old WT mice. We show evidence that the aging process is accelerated by the mutant PS2 itself and discuss such changes in relation to amyloidosis and gliosis.

Cortical diurnal rhythms remain intact with microglial depletion.

Microglia are subject to change in tandem with the endogenously generated biological oscillations known as our circadian rhythm. Studies have shown microglia harbor an intrinsic molecular clock which regulates diurnal changes in morphology and influences inflammatory responses. In the adult brain, microglia play an important role in the regulation of condensed extracellular matrix structures called perineuronal nets (PNNs), and it has been suggested that PNNs are also regulated in a circadian and diurnal manner. We sought to determine whether microglia mediate the diurnal regulation of PNNs via CSF1R inhibitor dependent microglial depletion in C57BL/6J mice, and how the absence of microglia might affect cortical diurnal gene expression rhythms. While we observe diurnal differences in microglial morphology, where microglia are most ramified at the onset of the dark phase, we do not find diurnal differences in PNN intensity. However, PNN intensity increases across many brain regions in the absence of microglia, supporting a role for microglia in the regulation of PNNs. Here, we also show that cortical diurnal gene expression rhythms are intact, with no cycling gene changes without microglia. These findings demonstrate a role for microglia in the maintenance of PNNs, but not in the maintenance of diurnal rhythms.

Investigation of synapses in the cortical white matter in human temporal lobe epilepsy.

Temporal lobe epilepsy (TLE) is one of the most common focal pharmacotherapy-resistant epilepsy in adults. Previous studies have shown significantly higher numbers of neurons in the neocortical white matter in TLE patients than in controls. The aim of this work was to investigate whether white matter neurons are part of the neuronal circuitry. Therefore, we studied the distribution and density of synapses in surgically resected neocortical tissue of pharmacotherapy-resistant TLE patients. Neocortical white matter of temporal lobe from non-epileptic patients were used as controls. Synapses and neurons were visualized with immunohistochemistry using antibodies against synaptophysin and NeuN, respectively. The presence of synaptophysin in presynaptic terminals was verified by electron microscopy. Quantification of immunostaining was performed and the data of the patients' cognitive tests as well as clinical records were compared to the density of neurons and synapses. Synaptophysin density in the white matter of TLE patients was significantly higher than in controls. In TLE, a significant correlation was found between synaptophysin immunodensity and density of white matter neurons. Neuronal as well as synaptophysin density significantly correlated with scores of verbal memory of TLE patients. Neurosurgical outcome of TLE patients did not significantly correlate with histological data, although, higher neuronal and synaptophysin densities were observed in patients with favorable post-surgical outcome. Our results suggest that white matter neurons in TLE patients receive substantial synaptic input and indicate that white matter neurons may be integrated in epileptic neuronal networks responsible for the development or maintenance of seizures.

Brain network modulation in Alzheimer's and frontotemporal dementia with transcranial electrical stimulation.

The default mode (DMN) and the salience (SN) networks show functional hypo-connectivity in Alzheimer's disease (AD) and the behavioral variant of frontotemporal dementia (bvFTD), respectively, along with patterns of hyper-connectivity. We tested the clinical and neurobiological effects of noninvasive stimulation over these networks in 45 patients (AD and bvFTD) who received either anodal (target network: DMN in AD, SN in bvFTD) or cathodal stimulation (target network: SN in AD, DMN in bvFTD). We evaluated changes in clinical, cognitive, functional and structural connectivity, and perfusion measures. In both patient groups, cathodal stimulation was followed by behavioral improvement, whereas anodal stimulation led to cognitive improvement. Neither functional connectivity nor perfusion showed significant effects. A significant interaction between DMN and SN functional connectivity changes and stimulation protocol was reported in AD. These results suggest a protocol-dependent response, whereby the protocols studied show divergent effects on cognitive and clinical measures, along with a divergent modulatory pattern of connectivity in AD.

Resting-state Functional Connectivity After Occipital Stroke.

BACKGROUND: Resting-state functional magnetic resonance imaging (rsfMRI) reflects spontaneous activation of cortical networks. After stroke, these networks reorganize, both due to structural lesion and reorganization of functional connectivity (FC). OBJECTIVE: We studied FC in chronic phase occipital stroke patients with homonymous visual field defects before and after repetitive transorbital alternating current stimulation (rtACS). METHODS: This spin-off study, embedded in the randomized, sham-controlled REVIS trial, comprised 16 chronic occipital stroke patients with visual field defect and 12 healthy control subjects. The patients underwent rsfMRI at baseline, after two weeks of rtACS or sham treatment, and after two months of treatment-free follow-up, whereas the control subjects were measured once. We used a multivariate regression connectivity model to determine mutual prediction accuracy between 74 cortical regions of interest. Additionally, the model parameters were included into a graph to analyze average path length, centrality eigenvector, centrality degree, and clustering of the network. The patients and controls at baseline and the two treatment groups were compared with multilevel modeling. RESULTS: Before treatment, the patients and controls had similar whole-network prediction accuracy and network parameters, whereas centrality eigenvector differed in perilesional regions, indicating local modification in connectivity. In line with behavioral results, neither prediction accuracy nor any network parameter changed systematically as a result of rtACS rehabilitation compared to sham. CONCLUSIONS: Whole-network FC showed no difference between occipital stroke patients and healthy population, congruent with the peripheral location of the visual network in relation to the high-density cortical core. rtACS treatment in the given setting did not affect FC.

Aerobic Exercise Alters Brain Function and Structure in Parkinson's Disease: A Randomized Controlled Trial.

OBJECTIVE: Randomized clinical trials have shown that aerobic exercise attenuates motor symptom progression in Parkinson's disease, but the underlying neural mechanisms are unclear. Here, we investigated how aerobic exercise influences disease-related functional and structural changes in the corticostriatal sensorimotor network, which is involved in the emergence of motor deficits in Parkinson's disease. Additionally, we explored effects of aerobic exercise on tissue integrity of the substantia nigra, and on behavioral and cerebral indices of cognitive control. METHODS: The Park-in-Shape trial is a single-center, double-blind randomized controlled trial in 130 Parkinson's disease patients who were randomly assigned (1:1 ratio) to aerobic exercise (stationary home trainer) or stretching (active control) interventions (duration = 6 months). An unselected subset from this trial (exercise, n = 25; stretching, n = 31) underwent resting-state functional and structural magnetic resonance imaging (MRI), and an oculomotor cognitive control task (pro- and antisaccades), at baseline and at 6-month follow-up. RESULTS: Aerobic exercise, but not stretching, led to increased functional connectivity of the anterior putamen with the sensorimotor cortex relative to the posterior putamen. Behaviorally, aerobic exercise also improved cognitive control. Furthermore, aerobic exercise increased functional connectivity in the right frontoparietal network, proportionally to fitness improvements, and it reduced global brain atrophy. INTERPRETATION: MRI, clinical, and behavioral results converge toward the conclusion that aerobic exercise stabilizes disease progression in the corticostriatal sensorimotor network and enhances cognitive performance. ANN NEUROL 2022;91:203-216.

High-resolution virtual brain modeling personalizes deep brain stimulation for treatment-resistant depression: Spatiotemporal response characteristics following stimulation of neural fiber pathways.

Over the past 15 years, deep brain stimulation (DBS) has been actively investigated as a groundbreaking therapy for patients with treatment-resistant depression (TRD); nevertheless, outcomes have varied from patient to patient, with an average response rate of ∼50%. The engagement of specific fiber tracts at the stimulation site has been hypothesized to be an important factor in determining outcomes, however, the resulting individual network effects at the whole-brain scale remain largely unknown. Here we provide a computational framework that can explore each individual's brain response characteristics elicited by selective stimulation of fiber tracts. We use a novel personalized in-silico approach, the Virtual Big Brain, which makes use of high-resolution virtual brain models at a mm-scale and explicitly reconstructs more than 100,000 fiber tracts for each individual. Each fiber tract is active and can be selectively stimulated. Simulation results demonstrate distinct stimulus-induced event-related potentials as a function of stimulation location, parametrized by the contact positions of the electrodes implanted in each patient, even though validation against empirical patient data reveals some limitations (i.e., the need for individual parameter adjustment, and differential accuracy across stimulation locations). This study provides evidence for the capacity of personalized high-resolution virtual brain models to investigate individual network effects in DBS for patients with TRD and opens up novel avenues in the personalized optimization of brain stimulation.

Network Localization of Unconscious Visual Perception in Blindsight.

OBJECTIVE: Blindsight is a disorder where brain injury causes loss of conscious but not unconscious visual perception. Prior studies have produced conflicting results regarding the neuroanatomical pathways involved in this unconscious perception. METHODS: We performed a systematic literature search to identify lesion locations causing visual field loss in patients with blindsight (n = 34) and patients without blindsight (n = 35). Resting state functional connectivity between each lesion location and all other brain voxels was computed using a large connectome database (n = 1,000). Connections significantly associated with blindsight (vs no blindsight) were identified. RESULTS: Functional connectivity between lesion locations and the ipsilesional medial pulvinar was significantly associated with blindsight (family wise error p = 0.029). No significant connectivity differences were found to other brain regions previously implicated in blindsight. This finding was independent of methods (eg, flipping lesions to the left or right) and stimulus type (moving vs static). INTERPRETATION: Connectivity to the ipsilesional medial pulvinar best differentiates lesion locations associated with blindsight versus those without blindsight. Our results align with recent data from animal models and provide insight into the neuroanatomical substrate of unconscious visual abilities in patients. ANN NEUROL 2022;91:217-224.

Subcortical Volumes as Early Predictors of Fatigue in Multiple Sclerosis.

OBJECTIVE: Fatigue is a frequent and severe symptom in multiple sclerosis (MS), but its pathophysiological origin remains incompletely understood. We aimed to examine the predictive value of subcortical gray matter volumes for fatigue severity at disease onset and after 4 years by applying structural equation modeling (SEM). METHODS: This multicenter cohort study included 601 treatment-naive patients with MS after the first demyelinating event. All patients underwent a standardized 3T magnetic resonance imaging (MRI) protocol. A subgroup of 230 patients with available clinical follow-up data after 4 years was also analyzed. Associations of subcortical volumes (included into SEM) with MS-related fatigue were studied regarding their predictive value. In addition, subcortical regions that have a central role in the brain network (hubs) were determined through structural covariance network (SCN) analysis. RESULTS: Predictive causal modeling identified volumes of the caudate (s [standardized path coefficient] = 0.763, p = 0.003 [left]; s = 0.755, p = 0.006 [right]), putamen (s = 0.614, p = 0.002 [left]; s = 0.606, p = 0.003 [right]) and pallidum (s = 0.606, p = 0.012 [left]; s = 0.606, p = 0.012 [right]) as prognostic factors for fatigue severity in the cross-sectional cohort. Moreover, the volume of the pons was additionally predictive for fatigue severity in the longitudinal cohort (s = 0.605, p = 0.013). In the SCN analysis, network hubs in patients with fatigue worsening were detected in the putamen (p = 0.008 [left]; p = 0.007 [right]) and pons (p = 0.0001). INTERPRETATION: We unveiled predictive associations of specific subcortical gray matter volumes with fatigue in an early and initially untreated MS cohort. The colocalization of these subcortical structures with network hubs suggests an early role of these brain regions in terms of fatigue evolution. ANN NEUROL 2022;91:192-202.

Exploring propriospinal neuron-mediated neural circuit plasticity using recombinant viruses after spinal cord injury.

Propriospinal neurons (PSNs) play a crucial role in motor control and sensory processing and contribute to plastic reorganization of spinal circuits responsible for recovery from spinal cord injury (SCI). Due to their scattered distribution and various intersegmental projection patterns, it is challenging to dissect the function of PSNs within the neuronal network. New genetically encoded tools, particularly cell-type-specific transgene expression methods using recombinant viral vectors combined with other genetic, pharmacologic, and optogenetic approaches, have enormous potential for visualizing PSNs in the neuronal circuits and monitoring and manipulating their activity. Furthermore, recombinant viral tools have been utilized to promote the intrinsic regenerative capacities of PSNs, towards manipulating the 'hostile' microenvironment for improving functional regeneration of PSNs. Here we summarize the latest development in this fast-moving field and provide a perspective for using this technology to dissect PSN physiological role in contributing to recovery of function after SCI.

Resting-state functional connectivity in adolescents experiencing subclinical and clinical symptoms of depression: a mini-review of recent evidence.

Adolescence is a developmental period associated with major neural reorganization and the onset of many psychological disorders. Depression in particular is prevalent and impairing in adolescents and rates have been rising in recent years. Recent advances in the neurobiology of adolescent depression contribute to a better understanding of functional connectivity among neural networks and represent a promising start for determining biomarkers of depression and potential areas of intervention.

Brunner syndrome associated MAOA mutations result in NMDAR hyperfunction and increased network activity in human dopaminergic neurons.

Monoamine neurotransmitter abundance affects motor control, emotion, and cognitive function and is regulated by monoamine oxidases. Among these, Monoamine oxidase A (MAOA) catalyzes the degradation of dopamine, norepinephrine, and serotonin into their inactive metabolites. Loss-of-function mutations in the X-linked MAOA gene have been associated with Brunner syndrome, which is characterized by various forms of impulsivity, maladaptive externalizing behavior, and mild intellectual disability. Impaired MAOA activity in individuals with Brunner syndrome results in bioamine aberration, but it is currently unknown how this affects neuronal function, specifically in dopaminergic (DA) neurons. Here we generated human induced pluripotent stem cell (hiPSC)-derived DA neurons from three individuals with Brunner syndrome carrying different mutations and characterized neuronal properties at the single cell and neuronal network level in vitro. DA neurons of Brunner syndrome patients showed reduced synaptic density but exhibited hyperactive network activity. Intrinsic functional properties and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)-mediated synaptic transmission were not affected in DA neurons of individuals with Brunner syndrome. Instead, we show that the neuronal network hyperactivity is mediated by upregulation of the GRIN2A and GRIN2B subunits of the N-methyl-d-aspartate receptor (NMDAR), resulting in increased NMDAR-mediated currents. By correcting a MAOA missense mutation with CRISPR/Cas9 genome editing we normalized GRIN2A and GRIN2B expression, NMDAR function and neuronal population activity to control levels. Our data suggest that MAOA mutations in Brunner syndrome increase the activity of dopaminergic neurons through upregulation of NMDAR function, which may contribute to the etiology of Brunner syndrome associated phenotypes.

Altered executive control network connectivity in anti-NMDA receptor encephalitis.

OBJECTIVE: The goal of this study was to examine whether the static functional connectivity (FC) of the executive control network (ECN) and the temporal properties of dynamic FC states in the ECN can characterize the underlying nature of anti-N-methyl-d-aspartate (anti-NMDA) receptor encephalitis and their correlations with cognitive functions. METHODS: In total, 21 patients with anti-NMDA receptor encephalitis past the acute stage and 23 healthy controls (HCs) underwent a set of neuropsychological tests and participated in a resting-state fMRI study to analyse the static FC of the ECN and the temporal properties of dynamic FC states in the ECN. In addition, correlation analyses were performed to determine the correlations between the FC metrics and cognitive performance. RESULTS: Patients with anti-NMDA receptor encephalitis past the acute stage showed significant cognitive impairments compared to HCs. In accord with the results of neuropsychological tests, static intrinsic FC alterations and changed dynamic FC metrics of ECN were observed in the patients. Importantly, we observed significant correlations between altered ECN metrics and working memory, information processing speed, executive function performance in the patients. INTERPRETATION: Our findings suggest that cognitive impairments in patients with anti-NMDA receptor encephalitis past the acute stage are likely related to altered static and dynamic ECN connectivity. These observations may enhance our understanding of the pathophysiological mechanisms underlying cognitive function in this population.

Neurocircuitry basis of the opioid use disorder-post-traumatic stress disorder comorbid state: conceptual analyses using a dimensional framework.

Understanding the interface between opioid use disorder (OUD) and post-traumatic stress disorder (PTSD) is challenging. By use of a dimensional framework, such as research domain criteria, convergent and targetable neurobiological processes in OUD-PTSD comorbidity can be identified. We hypothesise that, in OUD-PTSD, circuitry that is implicated in two research domain criteria systems (ie, negative valence and cognitive control) underpins dysregulation of incentive salience, negative emotionality, and executive function. We also propose that the OUD-PTSD state might be systematically investigated with approaches outlined within a neuroclinical assessment framework for addictions and PTSD. Our dimensional analysis of the OUD-PTSD state shows how first-line therapeutic approaches (ie, partial µ-type opioid receptor [MOR1] agonism) modulate overlapping neurobiological and clinical features and also provides mechanistic rationale for evaluating polytherapeutic strategies (ie, partial MOR1 agonism, κ-type opioid receptor [KOR1] antagonism, and α-2A adrenergic receptor [ADRA2A] agonism). A combination of these therapeutic mechanisms is projected to facilitate recovery in patients with OUD-PTSD by mitigating negative valence states and enhancing executive control.