Brain Connectivity Patterns Research Articles

Functional Brain Connectivity Patterns Associated with Visual Hallucinations in Dementia with Lewy Bodies.

Background:The presence of recurrent, complex visual hallucinations (VH) is among the core clinical features of dementia with Lewy bodies (DLB). It has been proposed that VH arise from a disrupted organization of functional brain networks. However, studies are still limited, especially investigating the resting-state functional brain features underpinning VH in patients with dementia.Objective:The aim of the present pilot study was to investigate whether there were any alterations in functional connectivity associated with VH in DLB.Methods:Seed-based analyses and independent component analysis (ICA) of resting-state fMRI scans were carried out to explore differences in functional connectivity between DLB patients with and without VH.Results:Seed-based analyses reported decreased connectivity of the lateral geniculate nucleus, the superior parietal lobule and the putamen with the medial frontal gyrus in DLB patients with VH. Visual areas showed a pattern of both decreased and increased functional connectivity. ICA revealed between-group differences in the default mode network (DMN).Conclusion:Functional connectivity analyses suggest dysfunctional top-down and bottom-up processes and DMN-related alterations in DLB patients with VH. This impairment might foster the generation of false visual images that are misinterpreted, ultimately resulting in VH.

Large-Scale Replication of Bipolar Disorder Dysconnectivity: A Diffusion MRI Analysis of 959 Individuals From the ENIGMA Bipolar Disorder Working Group

Bipolar disorder (BD) involves disrupted mood regulation and cognition potentially associated with altered brain connectivity patterns, including altered integration and segregation of anatomical brain networks. Establishing this as a robust finding has been hindered by limited sample sizes, and by variation in methodological pipelines. We present the largest graph-theoretical analysis to date of structural brain networks in BD.

Regional and Temporal Differences in Brain Activity With Morally Good or Bad Judgments in Men: A Magnetoencephalography Study.

Many neuroimaging studies on morality focus on functional brain areas that relate to moral judgment specifically in morally negative situations. To date, there have been few studies on differences in brain activity under conditions of being morally good and bad along a continuum. To explore not only the brain regions involved but also their functional connections during moral judgments, we used magnetoencephalography (MEG), which is superior to other imaging modalities for analyzing time-dependent brain activities; only men were recruited because sex differences might be a confounding factor. While analyses showed that general patterns of brain activation and connectivity were similar between morally good judgments (MGJs) and morally bad judgments (MBJs), activation in brain areas that subserve emotion and “theory of mind” on the right hemisphere was larger in MGJ than MBJ conditions. In the left local temporal region, the connectivity between brain areas related to emotion and reward/punishment was stronger in MBJ than MGJ conditions. The time-frequency analysis showed distinct laterality (left hemisphere dominant) occurring during early moral information processing in MBJ conditions compared to MGJ conditions and phase-dependent differences in the appearance of theta waves between MBJ and MGJ conditions. During MBJs, connections within the hemispheric regions were more robust than those between hemispheric regions. These results suggested that the local temporal region on the left hemisphere is more important in the execution of MBJs during early moral valence processing than in that with MGJs. Shorter neuronal connections within the hemisphere may allow to make MBJs punctual.

Corpus callosum dysgenesis causes novel patterns of structural and functional brain connectivity

Developmental malformations (dysgenesis) of the corpus callosum lead to neurological conditions with a broad range of clinical presentations. Investigating the altered brain connectivity patterns is crucial to understanding both adaptive and maladaptive neuroplasticity in corpus callosum dysgenesis patients. Here, we acquired structural diffusion-weighted and resting-state functional MRI data from a cohort of 11 corpus callosum dysgenesis patients (five with agenesis and six with hypoplasia) and compared their structural and functional connectivity patterns to healthy subjects selected from the Human Connectome Project. We found that these patients have fewer structural inter- and intra-hemispheric brain connections relative to healthy controls. Interestingly, the patients with callosal agenesis have a scant number of inter-hemispheric connections but manage to maintain the full integrity of functional connectivity between the same cortical regions as the healthy subjects. On the other hand, the hypoplasic group presented abnormal structural and functional connectivity patterns relative to healthy controls while maintaining the same total amount of functional connections. These results demonstrate that acallosal patients can compensate for having fewer structural brain connections and present functional adaptation. However, hypoplasics present atypical structural connections to different brain regions, leading to entirely new and abnormal functional brain connectivity patterns.

Characterizing changes in network connectivity following chronic head trauma in special forces military personnel: a combined resting-fMRI and DTI study

ABSTRACT Background Soldiers are exposed to significant repetitive head trauma, which may disrupt functional and structural brain connectivity patterns. Purpose/hypothesis Integrate resting-state functional MRI (rs-fMRI) and diffusion tensor imaging (DTI) to characterize changes in connectivity biomarkers within Canadian Special Operations Forces (CANSOF), hypothesizing that alterations in architectural organization of cortical hubs may follow chronic repetitive head trauma. Methods Fifteen CANSOFs with a history of chronic exposure to sub-concussive head trauma and concussive injuries (1.9 ± 2.0 concussions (range: [0–6])), as well as an equal age-matched cohort of controls (CTLs) were recruited. BOLD-based rs-fMRI was combined with DTI to reconstruct functional and structural networks using independent component analyses and probabilistic tractography. Connectivity markers were computed based on the distance between functional seeds to assess for possible differences in injury susceptibility of short- and long-range connections. Results/discussion Significant hyper- and hypo-connectivity differences in cortical connections were observed suggesting that chronic head trauma may predispose soldiers to changes in the functional organization of brain networks. Significant structural alterations in axonal fibers directly connecting disrupted functional nodes were specific to hyper-connected long-range connections, suggesting a potential relationship between axonal injury and increases in neural recruitment following repetitive head trauma from high-exposure military duties.

Functional network estimation using multigraph learning with application to brain maturation study.

Although most dramatic structural changes occur in the perinatal period, a growing body of evidences demonstrates that adolescence and early adulthood are also important for substantial neurodevelopment. We were thus motivated to explore brain development during puberty by evaluating functional connectivity network (FCN) differences between childhood and young adulthood using multi‐paradigm task‐based functional magnetic resonance imaging (fMRI) measurements. Different from conventional multigraph based FCN construction methods where the graph network was built independently for each modality/paradigm, we proposed a multigraph learning model in this work. It promises a better fitting to FCN construction by jointly estimating brain network from multi‐paradigm fMRI time series, which may share common graph structures. To investigate the hub regions of the brain, we further conducted graph Fourier transform (GFT) to divide the fMRI BOLD time series of a node within the brain network into a range of frequencies. Then we identified the hub regions characterizing brain maturity through eigen‐analysis of the low frequency components, which were believed to represent the organized structures shared by a large population. The proposed method was evaluated using both synthetic and real data, which demonstrated its effectiveness in extracting informative brain connectivity patterns. We detected 14 hub regions from the child group and 12 hub regions from the young adult group. We show the significance of these findings with a discussion of their functions and activation patterns as a function of age. In summary, our proposed method can extract brain connectivity network more accurately by considering the latent common structures between different fMRI paradigms, which are significant for both understanding brain development and recognizing population groups of different ages.

Atypical Resting-State Functional Connectivity of Intra/Inter-Sensory Networks Is Related to Symptom Severity in Young Boys With Autism Spectrum Disorder.

Autism spectrum disorder (ASD) has been reported to have altered brain connectivity patterns in sensory networks, assessed using resting-state functional magnetic imaging (rs-fMRI). However, the results have been inconsistent. Herein, we aimed to systematically explore the interaction between brain sensory networks in 3–7-year-old boys with ASD (N = 29) using independent component analysis (ICA). Participants were matched for age, head motion, and handedness in the MRI scanner. We estimated the between-group differences in spatial patterns of the sensory resting-state networks (RSNs). Subsequently, the time series of each RSN were extracted from each participant’s preprocessed data and associated estimates of interaction strength between intra- and internetwork functional connectivity (FC) and symptom severity in children with ASD. The auditory network (AN), higher visual network (HVN), primary visual network (PVN), and sensorimotor network (SMN) were identified. Relative to TDs, individuals with ASD showed increased FC in the AN and SMN, respectively. Higher positive connectivity between the PVN and HVN in the ASD group was shown. The strength of such connections was associated with symptom severity. The current study might suggest that the abnormal connectivity patterns of the sensory network regions may underlie impaired higher-order multisensory integration in ASD children, and be associated with social impairments.

Functional MRI in Parkinson's disease with freezing of gait: a systematic review of the literature.

Freezing of gait (FOG), a common and disabling symptom of Parkinson's disease (PD), is characterized by an episodic inability to generate effective stepping. Functional MRI (fMRI) has been used to evaluate abnormal brain connectivity patterns at rest and brain activation patterns during specific tasks in patients with PD-FOG. This review has examined the existing functional neuroimaging literature in PD-FOG, including those with treatment. Summarizing these articles provides an opportunity for a better understanding of the underlying pathophysiology in PD-FOG. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we performed a literature review of studies using fMRI to investigate the underlying pathophysiological mechanisms of PD-FOG. We initially identified 201 documents. After excluding the duplicates, reviews, and other irrelevant articles, 39 articles were finally identified, including 18 task-based fMRI studies and 21 resting-state fMRI studies. Studies using fMRI techniques to evaluate PD-FOG have found dysfunctional connectivity in widespread cortical and subcortical regions. Standardized imaging protocols and detailed subtypes of PD-FOG are furthered required to elucidate current findings.

Post-traumatic Headache and Mild Traumatic Brain Injury: Brain Networks and Connectivity.

Post-traumatic headache (PTH) consequent to mild traumatic brain injury (mTBI) is a complex, multidimensional, chronic neurological disorder. The purpose of this review is to evaluate the current neuroimaging studies on mTBI and PTH with a specific focus on brain networks and connectivity patterns. We present findings on PTH incidence and prevalence, as well as the latest neuroimaging research findings on mTBI and PTH. Additionally, we propose a new strategy in studying PTH following mTBI. The diversity and heterogeneity of pathophysiological mechanisms underlying mild traumatic brain injury pose unique challenges on how we interpret neuroimaging findings in PTH. Evaluating alterations in the intrinsic brain network connectivity patterns using novel imaging and analytical techniques may provide additional insights into PTH disease state and therefore inform effective treatment strategies.

Multi-dimensional persistent feature analysis identifies connectivity patterns of resting-state brain networks in Alzheimer’s disease

Objective. The characterization of functional brain network is crucial to understanding the neural mechanisms associated with Alzheimer’s disease (AD) and mild cognitive impairment (MCI). Some studies have shown that graph theoretical analysis could reveal changes of the disease-related brain networks by thresholding edge weights. But the choice of threshold depends on ambiguous cognitive conditions, which leads to the lack of interpretability. Recently, persistent homology (PH) was proposed to record the persistence of topological features of networks across every possible thresholds, reporting a higher sensitivity than graph theoretical features in detecting network-level biomarkers of AD. However, most research on PH focused on zero-dimensional features (persistence of connected components) reflecting the intrinsic topology of the brain network, rather than one-dimensional features (persistence of cycles) with an interesting neurobiological communication pattern. Our aim is to explore the multi-dimensional persistent features of brain networks in the AD and MCI patients, and further to capture valuable brain connectivity patterns. Approach. We characterized the change rate of the connected component numbers across graph filtration using the functional derivative curves, and examined the persistence landscapes that vectorize the persistence of cycle structures. After that, the multi-dimensional persistent features were validated in disease identification using a K-nearest neighbor algorithm. Furthermore, a connectivity pattern mining framework was designed to capture the disease-specific brain structures. Main results. We found that the multi-dimensional persistent features can identify statistical group differences, quantify subject-level distances, and yield disease-specific connectivity patterns. Relatively high classification accuracies were received when compared with graph theoretical features. Significance. This work represents a conceptual bridge linking complex brain network analysis and computational topology. Our results can be beneficial for providing a complementary objective opinion to the clinical diagnosis of neurodegenerative diseases.

The Impact of Cannabidiol on Human Brain Function: A Systematic Review.

Background: Accumulating evidence suggests that the non-intoxicating cannabinoid compound cannabidiol (CBD) may have antipsychotic and anxiolytic properties, and thus may be a promising new agent in the treatment of psychotic and anxiety disorders. However, the neurobiological substrates underlying the potential therapeutic effects of CBD are still unclear. The aim of this systematic review is to provide a detailed and up-to-date systematic literature overview of neuroimaging studies that investigated the acute impact of CBD on human brain function. Methods: Papers published until May 2020 were included from PubMed following a comprehensive search strategy and pre-determined set of criteria for article selection. We included studies that examined the effects of CBD on brain function of healthy volunteers and individuals diagnosed with a psychiatric disorder, comprising both the effects of CBD alone as well as in direct comparison to those induced by ∆9-tetrahydrocannabinol (THC), the main psychoactive component of Cannabis. Results: One-ninety four studies were identified, of which 17 met inclusion criteria. All studies investigated the acute effects of CBD on brain function during resting state or in the context of cognitive tasks. In healthy volunteers, acute CBD enhanced fronto-striatal resting state connectivity, both compared to placebo and THC. Furthermore, CBD modulated brain activity and had opposite effects when compared to THC following task-specific patterns during various cognitive paradigms, such as emotional processing (fronto-temporal), verbal memory (fronto-striatal), response inhibition (fronto-limbic-striatal), and auditory/visual processing (temporo-occipital). In individuals at clinical high risk for psychosis and patients with established psychosis, acute CBD showed intermediate brain activity compared to placebo and healthy controls during cognitive task performance. CBD modulated resting limbic activity in subjects with anxiety and metabolite levels in patients with autism spectrum disorders. Conclusion: Neuroimaging studies have shown that acute CBD induces significant alterations in brain activity and connectivity patterns during resting state and performance of cognitive tasks in both healthy volunteers and patients with a psychiatric disorder. This included modulation of functional networks relevant for psychiatric disorders, possibly reflecting CBD’s therapeutic effects. Future studies should consider replication of findings and enlarge the inclusion of psychiatric patients, combining longer-term CBD treatment with neuroimaging assessments.

Identifying Diurnal Variability of Brain Connectivity Patterns Using Graph Theory.

Significant differences exist in human brain functions affected by time of day and by people’s diurnal preferences (chronotypes) that are rarely considered in brain studies. In the current study, using network neuroscience and resting-state functional MRI (rs-fMRI) data, we examined the effect of both time of day and the individual’s chronotype on whole-brain network organization. In this regard, 62 participants (39 women; mean age: 23.97 ± 3.26 years; half morning- versus half evening-type) were scanned about 1 and 10 h after wake-up time for morning and evening sessions, respectively. We found evidence for a time-of-day effect on connectivity profiles but not for the effect of chronotype. Compared with the morning session, we found relatively higher small-worldness (an index that represents more efficient network organization) in the evening session, which suggests the dominance of sleep inertia over the circadian and homeostatic processes in the first hours after waking. Furthermore, local graph measures were changed, predominantly across the left hemisphere, in areas such as the precentral gyrus, putamen, inferior frontal gyrus (orbital part), inferior temporal gyrus, as well as the bilateral cerebellum. These findings show the variability of the functional neural network architecture during the day and improve our understanding of the role of time of day in resting-state functional networks.

Enjoyment of watching pimple popping videos: An fMRI investigation

BackgroundMillions of people enjoy watching videos of pimple treatments. The underlying neural mechanisms of this enjoyment have not been investigated so far. MethodWe administered a total of 96 video clips from three categories: Pimple Popping (PP), Water Fountains (WF), and Steam Cleaning (SC). The PP videos showed a pimple or blackhead that was opened to squeeze out the pus or sebum. The female participants (mean age: 24 years) were assigned to one of two groups: females who reported to enjoy watching PP (PPE_high; n = 38) and those with little enjoyment (PPE_low; n = 42). We analyzed brain activity in regions of interest (ROI) involved in the encoding of pleasure and aversion (e.g., nucleus accumbens (NAc), insula). ResultsThe PPE_high group showed less deactivation of the NAc (ROI finding), more frontopolar activation (whole-brain finding), and stronger accumbens-insula coupling than the PPE_low group. ConclusionsA specific pattern of brain activity and connectivity that involves the NAc and insula (coding of aversion/pleasure) and the frontopolar region (prediction of outcomes of motor decisions) is associated with the enjoyment of PP videos.

A Review of Neuroimaging Studies in Persistent Postural-Perceptual Dizziness (PPPD).

Persistent postural-perceptual dizziness (PPPD) is a functional vestibular disease characterized by persistent dizziness, unsteadiness, and/or non-spinning vertigo, and is the most common vestibular syndrome in young adults. A stiffened postural control strategy, shift to reliance on visual over vestibular information, and hypervigilance to the environment have been suggested as possible pathophysiological mechanisms of PPPD. However, the exact mechanisms remain unclear. Recently, neuroimaging studies using magnetic resonance imaging and single photon emission computed tomography have provided pivotal insights into the pathophysiology of PPPD. The aim of this review was to evaluate and summarize the existing data on neuroimaging studies in PPPD. In summary, these studies fairly consistently reported decreased brain structure, function, and connectivity among the areas involved in multisensory vestibular processing and spatial cognition, and increased function and connectivity in the visual processing areas in patients with PPPD. The detected brain changes might reflect maladaptive and compensatory mechanisms including dysfunctional integration of multisensory vestibular information and visual dependence. Notably, various factors including personality traits (i.e., neuroticism), psychiatric comorbidities (i.e., anxiety and depression), and triggering factors (i.e., peripheral vestibular lesions) seem to modulate brain functional activity and connectivity patterns, possibly accounting for some differences across the results. Future studies should carefully control for these confounding effects in order to draw firm conclusions.

Effects of an Allostatic Closed-Loop Neurotechnology (HIRREM) on Brain Functional Connectivity Laterality in Military-Related Traumatic Stress.

ABSTRACTBACKGROUND AND PURPOSEBrain asymmetries are reported in posttraumatic stress disorder, but many aspects of laterality and traumatic stress remain underexplored. This study explores lateralization changes in resting state brain network functional connectivity in a cohort with symptoms of military‐related traumatic stress, associated with use of a closed‐loop neurotechnology, HIRREM.METHODSEighteen participants (17 males, mean age 41 years [SD = 7]) received 19.5 (1.1) HIRREM sessions over 12 days. Whole brain resting magnetic resonance imaging was done pre‐ and post‐HIRREM. Laterality of functional connectivity was assessed on a whole brain basis, and in six predefined networks or regions. Laterality of connectivity within networks or regions was assessed separately from laterality of connections between networks or regions.RESULTSBefore HIRREM, significant laterality effects of connection type (ipsilateral for either side, or contralateral in either direction) were observed for the whole brain, within networks or regions, and between networks or regions. Post‐HIRREM, there were significant changes for within‐network or within‐region analysis in the motor network, and changes for between‐network or between‐region analyses for the salience network and the motor cortex.CONCLUSIONSAmong military service members and Veterans with symptoms of traumatic stress, asymmetries of network and brain region connectivity patterns were identified prior to usage of HIRREM. A variety of changes in lateralized patterns of brain connectivity were identified postintervention. These laterality findings may inform future studies of brain connectivity in traumatic stress disorders, with potential to point to mechanisms of action for successful intervention.

Aberrant triple-network connectivity patterns discriminate biotypes of first-episode medication-naive schizophrenia in two large independent cohorts.

Schizophrenia is a complex disorder associated with aberrant brain functional connectivity. This study aims to demonstrate the relation of heterogeneous symptomatology in this disorder to distinct brain connectivity patterns within the triple-network model. The study sample comprised 300 first-episode antipsychotic-naive patients with schizophrenia (FES) and 301 healthy controls (HCs). At baseline, resting-state functional magnetic resonance imaging data were captured for each participant, and concomitant neurocognitive functions were evaluated outside the scanner. Clinical information of 49 FES in the discovery dataset were reevaluated at a 6-week follow-up. Differential features between FES and HCs were selected from triple-network connectivity profiles. Cutting-edge unsupervised machine learning algorithms were used to define patient subtypes. Clinical and cognitive variables were compared between patient subgroups. Two FES subgroups with differing triple-network connectivity profiles were identified in the discovery dataset and confirmed in an independent hold-out cohort. One patient subgroup appearing to have more severe clinical symptoms was distinguished by salience network (SN)-centered hypoconnectivity, which was associated with greater impairments in sustained attention. The other subgroup exhibited hyperconnectivity and manifested greater deficits in cognitive flexibility. The SN-centered hypoconnectivity subgroup had more persistent negative symptoms at the 6-week follow-up than the hyperconnectivity subgroup. The present study illustrates that clinically relevant cognitive subtypes of schizophrenia may be associated with distinct differences in connectivity in the triple-network model. This categorization may foster further analysis of the effects of therapy on these network connectivity patterns, which may help to guide therapeutic choices to effectively reach personalized treatment goals.

A Graph Gaussian Embedding Method for Predicting Alzheimer's Disease Progression With MEG Brain Networks.

Characterizing the subtle changes of functional brain networks associated with the pathological cascade of Alzheimer's disease (AD) is important for early diagnosis and prediction of disease progression prior to clinical symptoms. We developed a new deep learning method, termed multiple graph Gaussian embedding model (MG2G), which can learn highly informative network features by mapping high-dimensional resting-state brain networks into a low-dimensional latent space. These latent distribution-based embeddings enable a quantitative characterization of subtle and heterogeneous brain connectivity patterns at different regions, and can be used as input to traditional classifiers for various downstream graph analytic tasks, such as AD early stage prediction, and statistical evaluation of between-group significant alterations across brain regions. We used MG2G to detect the intrinsic latent dimensionality of MEG brain networks, predict the progression of patients with mild cognitive impairment (MCI) to AD, and identify brain regions with network alterations related to MCI.

Blue-Light Therapy Strengthens Resting-State Effective Connectivity within Default-Mode Network after Mild TBI.

Background:Emerging evidence suggests that post concussive symptoms, including mood changes, may be improved through morning blue-wavelength light therapy (BLT). However, the neurobiological mechanisms underlying these effects remain unknown. We hypothesize that BLT may influence the effective brain connectivity (EC) patterns within the default-mode network (DMN), particularly involving the medial prefrontal cortex (MPFC), which may contribute to improvements in mood.Methods:Resting-state functional MRI data were collected from 41 healthy-controls (HCs) and 28 individuals with mild traumatic brain injury (mTBI). Individuals with mTBI also underwent a diffusion-weighted imaging scan and were randomly assigned to complete either 6 weeks of daily morning BLT (N = 14) or amber light therapy (ALT; N = 14). Advanced spectral dynamic causal modeling (sDCM) and diffusion MRI connectometry were used to estimate EC patterns and structural connectivity strength within the DMN, respectively.Results:The sDCM analysis showed dominant connectivity pattern following mTBI (pre-treatment) within the hemisphere contralateral to the one observed for HCs. BLT, but not ALT, resulted in improved directional information flow (ie, EC) from the left lateral parietal cortex (LLPC) to MPFC within the DMN. The improvement in EC from LLPC to MPFC was accompanied by stronger structural connectivity between the 2 areas. For the BLT group, the observed improvements in function and structure were correlated (at a trend level) with changes in self-reported happiness.Conclusions:The current preliminary findings provide empirical evidence that morning short-wavelength light therapy could be used as a novel alternative rehabilitation technique for mTBI.Trial registry:The research protocols were registered in the ClinicalTrials.gov database (CT Identifiers NCT01747811 and NCT01721356).

Fronto-striatal changes along the menstrual cycle during working memory: Effect of sex hormones on activation and connectivity patterns

Frontal and striatal areas are the neuroanatomical basis for working memory (WM), as well as targets for sex steroids. However, up to date little is known regarding menstrual cycle (MC) effects on brain activation and connectivity patterns during verbal WM. To the best of our knowledge, this is the first longitudinal dataset to study dorsolateral prefrontal cortex, putamen and caudate activation and connectivity patterns during a verbal WM task along the natural MC. Thirty-nine naturally cycling healthy women were scanned three times locked to their MC (menses, pre-ovulatory and luteal phase). They performed an N-back task with two trial types, targets and lures, assessing (i) updating and (ii) inhibitory process respectively. Distinct patterns of fronto-striatal activation and connectivity changes were observed for each process. (i) For targets, we observed decreased connectivity between left striatum- and inferior frontal and parietal areas, the circuit underlying phonological WM, in response to elevated progesterone during the luteal phase. Simultaneously, we observed an alleviation of inhibition from fronto-striatal areas on areas related to higher cognitive effort and the salience network. (ii) For lures, negative inter-hemispheric connectivity between fronto-parietal areas during the pre-ovulatory phase, as well as increased connectivity between bilateral dorsolateral prefrontal cortex and posteromedial structures during the luteal phase. Overall, we corroborated a hormone mediated inter-hemispheric decoupling, enhanced frontal activity and disinhibition of the salience brain network and striatum during the luteal phase. In summary, we interpret these results in relation to a differential top-down regulation in higher hormone levels phases and hyperactive bottom-up network during the luteal phase, which could explain the vulnerability of this phase to MC associated disorders.

Temporal-thalamic and cingulo-opercular connectivity in people with schizophrenia

A growing body of research has suggested that people with schizophrenia (SZ) exhibit altered patterns of functional and anatomical brain connectivity. For example, many previous resting state functional connectivity (rsFC) studies have shown that, compared to healthy controls (HC), people with SZ demonstrate hyperconnectivity between subregions of the thalamus and sensory cortices, as well as hypoconnectivity between subregions of the thalamus and prefrontal cortex. In addition to thalamic findings, hypoconnectivity between cingulo-opercular brain regions thought to be involved in salience detection has also been commonly reported in people with SZ. However, previous studies have largely relied on seed-based analyses. Seed-based approaches require researchers to define a single a priori brain region, which is then used to create a rsFC map across the entire brain. While useful for testing specific hypotheses, these analyses are limited in that only a subset of connections across the brain are explored. In the current manuscript, we leverage novel network statistical techniques in order to detect latent functional connectivity networks with organized topology that successfully differentiate people with SZ from HCs. Importantly, these techniques do not require a priori seed selection and allow for whole brain investigation, representing a comprehensive, data-driven approach to determining differential connectivity between diagnostic groups. Across two samples, (Sample 1: 35 SZ, 44 HC; Sample 2: 65 SZ, 79 HC), we found evidence for differential rsFC within a network including temporal and thalamic regions. Connectivity in this network was greater for people with SZ compared to HCs. In the second sample, we also found evidence for hypoconnectivity within a cingulo-opercular network of brain regions in people with SZ compared to HCs. In summary, our results replicate and extend previous studies suggesting hyperconnectivity between the thalamus and sensory cortices and hypoconnectivity between cingulo-opercular regions in people with SZ using data-driven statistical and graph theoretical techniques.