Altered Connectivity Patterns Research Articles

Multi-modal Neuroimaging Phenotyping of Mnemonic Anosognosia in the Aging Brain

BackgroundUnawareness is a behavioral condition characterized by a lack of self-awareness of objective memory decline. In the context of Alzheimer’s Disease (AD), unawareness may develop in predementia stages and contributes to disease severity and progression. Here, we use in-vivo multi-modal neuroimaging to profile the brain phenotype of individuals presenting altered self-awareness of memory during aging.MethodsAmyloid- and tau-PET (N = 335) and resting-state functional MRI (N = 713) imaging data of individuals from the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s Disease (A4)/Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) Study were used in this research. We applied whole-brain voxel-wise and region-of-interest analyses to characterize the cortical intersections of tau, amyloid, and functional connectivity networks underlying unawareness in the aging brain compared to aware, complainer and control groups.ResultsIndividuals with unawareness present elevated amyloid and tau burden in midline core regions of the default mode network compared to aware, complainer or control individuals. Unawareness is characterized by an altered network connectivity pattern featuring hyperconnectivity in the medial anterior prefrontal cortex and posterior occipito-parietal regions co-locating with amyloid and tau deposition.ConclusionsUnawareness is an early behavioral biomarker of AD pathology. Failure of the self-referential system in unawareness of memory decline can be linked to amyloid and tau burden, along with functional network connectivity disruptions, in several medial frontal and parieto-occipital areas of the human brain.

Reduced frontocingulate theta connectivity during emotion regulation in major depressive disorder

BackgroundCognitive reappraisal is an essential emotion regulation skill for social life and psychological health. However, individuals with major depressive disorder (MDD) cannot use this skill effectively. Successful cognitive reappraisal in healthy controls (HC) has been shown to be associated with theta activity in a frontal and subcortical network. In the present study, we investigated whether MDD patients are characterized by altered theta power and connectivity pattern during cognitive reappraisal compared to HC. MethodsUsing EEG and eLORETA, we examined both theta activity and connectivity when 25 controls and 24 patients with MDD were asked to complete the emotion cognitive reappraisal task of viewing neutral and negative pictures and reappraise negative pictures. Habitual use of emotion regulation skills was collected using the Cognitive Emotion Regulation Questionnaire (CERQ). ResultsThe results showed that MDD patients had (1) reduced theta activity in the left dorsolateral (dlPFC), dorsomedial prefrontal (dmPFC), and rostral-ventral cingulate cortices (rvACC), as well as (2) reduced dlPFC-rvACC theta connectivity than HC during reappraisal. In addition, left dlPFC-rvACC theta connectivity was positively correlated with self-reported cognitive reappraisal in HC. This relation was not observed in MDD. In contrast, CERQ revealed significantly greater use of inadequate regulations skills and significantly lower use of adaptive skills in MDD. LimitationSample size, limited solution space to cortical grey matter excluding regions such as the amygdala. ConclusionThis study may indicate a putative frontocingulate dysfunction leading either to an increased use of inadequate emotion regulation or a decreased use of skills that serve to boost positive emotion.

Altered resting-state functional connectivity and dynamic network properties in cognitive impairment: an independent component and dominant-coactivation pattern analyses study.

Cognitive impairment (CI) due to Alzheimer's disease (AD) encompasses a decline in cognitive abilities and can significantly impact an individual's quality of life. Early detection and intervention are crucial in managing CI, both in the preclinical and prodromal stages of AD prior to dementia. In this preliminary study, we investigated differences in resting-state functional connectivity and dynamic network properties between 23 individual with CI due to AD based on clinical assessment and 15 healthy controls (HC) using Independent Component Analysis (ICA) and Dominant-Coactivation Pattern (d-CAP) analysis. The cognitive status of the two groups was also compared, and correlations between cognitive scores and d-CAP switching probability were examined. Results showed comparable numbers of d-CAPs in the Default Mode Network (DMN), Executive Control Network (ECN), and Frontoparietal Network (FPN) between HC and CI groups. However, the Visual Network (VN) exhibited fewer d-CAPs in the CI group, suggesting altered dynamic properties of this network for the CI group. Additionally, ICA revealed significant connectivity differences for all networks. Spatial maps and effect size analyses indicated increased coactivation and more synchronized activity within the DMN in HC compared to CI. Furthermore, reduced switching probabilities were observed for the CI group in DMN, VN, and FPN networks, indicating less dynamic and flexible functional interactions. The findings highlight altered connectivity patterns within the DMN, VN, ECN, and FPN, suggesting the involvement of multiple functional networks in CI. Understanding these brain processes may contribute to developing targeted diagnostic and therapeutic strategies for CI due to AD.

Beyond network connectivity: A classification approach to brain age prediction with resting-state fMRI

The brain is a complex, dynamic organ that shows differences in the same subject at various periods. Understanding how brain activity changes across age as a function of the brain networks has been greatly abetted by fMRI. Canonical analysis consists of determining how alterations in connectivity patterns (CPs) of certain regions are affected. An alternative approach is taken here by not considering connectivity but rather features computed from recordings at the regions of interest (ROIs). Using machine learning (ML) we assess how neural signals are altered by and prospectively predictive of age and sex via a methodology that is novel in drawing upon pairwise classification across six decades of subjects’ chronological ages. ML is used to answer the equally important questions of what properties of the computed features are most predictive as well as which brain networks are most affected by aging. It was found that there is decreased differentiation among the neural signals of older subjects that are separated in age by the same number of years as younger subjects. Furthermore, the burstiness of the signals change at different rates between males and females. The findings provide insight into brain aging via an ROI-based analysis, the consideration of several feature groups, and a novel classification-based ML pipeline. There is also a contribution to understanding the effects of data aggregated from different recording centers on the conclusions of fMRI studies.

Conectividad cerebral, empatía, insensibilidad emocional y toma de decisiones en el trastorno de la conducta: Una revisión sistemática.

The deficits in empathy, emotional insensitivity, and decision-making constitute the core of symptoms defining conduct disorder. Although several studies have established some correlates between brain connectivity and symptoms separately, there has been little effort to systematize such information. The current systematic review aimed to describe the findings obtained through analyzing brain connectivity networks by functional magnetic resonance imaging associated with alterations in empathy, emotional insensitivity, and decision-making in subjects with conduct disorder. A systematic search was carried out for original studies published in Medline (PubMed), Scopus, Scielo, Google Scholar, Scopus, and Nature. Articles published between 2000 and 2022 were included; a qualitative synthesis was obtained with the six selected articles at the end of the process. The findings show altered brain connectivity patterns in brain regions associated with empathy and insensitivity in subjects with conduct disorder.

Connecting the dots: Motor and default mode network crossroads in post-stroke motor learning deficits

BackgroundStrokes frequently result in long-term motor deficits, imposing significant personal and economic burdens. However, our understanding of the underlying neural mechanisms governing motor learning in stroke survivors remains limited - a fact that poses significant challenges to the development and optimisation of therapeutic strategies. ObjectiveThis study investigates the diversity in motor learning aptitude and its associated neurological mechanisms. We hypothesised that stroke patients exhibit compromised overall motor learning capacity, which is associated with altered activity and connectivity patterns in the motor- and default-mode-network in the brain. MethodsWe assessed a cohort of 40 chronic-stage, mildly impaired stroke survivors and 39 age-matched healthy controls using functional Magnetic Resonance Imaging (fMRI) and connectivity analyses. We focused on neural activity and connectivity patterns during an unilateral motor sequence learning task performed with the unimpaired or non-dominant hand. Primary outcome measures included task-induced changes in neural activity and network connectivity. ResultsCompared to controls, stroke patients showed significantly reduced motor learning capacity, associated with diminished cerebral lateralization. Task induced activity modulation was reduced in the motor network but increased in the default mode network. The modulated activation strength was associated with an opposing trend in task-induced functional connectivity, with increased connectivity in the motor network and decreased connectivity in the DMN. ConclusionsStroke patients demonstrate altered neural activity and connectivity patterns during motor learning with their unaffected hand, potentially contributing to globally impaired motor learning skills. The reduced ability to lateralize cerebral activation, along with the enhanced connectivity between the right and left motor cortices in these patients, may signify maladaptive neural processes that impede motor adaptation, possibly affecting long-term rehabilitation post-stroke. The contrasting pattern of activity modulation and connectivity alteration in the default mode network suggests a nuanced role of this network in post-stroke motor learning. These insights could have significant implications for the development of customised rehabilitation strategies for stroke patients.

Altered connectivity patterns of medial and lateral orbitofrontal cortex underlie the severity of bulimic symptoms

ObjectiveCompared to clinical bulimia nervosa, sub-threshold bulimic symptoms are becoming more prevalent in non-clinical or general population, which is repeatedly linked with the connectivity in orbitofrontal cortex (OFC), including functionally heterogeneous the medial and lateral OFC (mOFC; lOFC). However, the specific connectivity patterns of the mOFC and lOFC in individuals with severe or mild bulimic symptoms (SB; MB) remain poorly understood. MethodsWe first utilized resting-state functional connectivity (FC) and spectral dynamic causal modeling (spDCM) to investigate abnormal functional and effective connectivity (EC) of OFC subregions in adults with different severity of bulimic. The SB group (n = 21), MB group (n = 114), and healthy controls (HC, n = 91) underwent rs-fMRI scans. A generalized linear model was applied to determine the OFC-seeded whole-brain FC across the three groups. Subsequently, spDCM was used to estimate differences in EC among the three groups based on the FC results. ResultsWe observed a shared neural basis for SB and MB groups (i.e., weaker lOFC-superior parietal lobule connectivity), which may support the role of dysfunctional inhibitory control in general bulimic symptomatology. Whereas, SB group displayed greater lOFC-occipital pole connectivity than MB group, suggesting the specificity of the neural correlates of full-threshold/severe bulimia. The directional links from the mOFC to lOFC and amygdala could further explain the aberrant interactions of reward sensitivity with inhibitory control and homeostatic energy in sub-threshold/mild condition. ConclusionThe current study provides novel evidence that divergent connectivity patterns of the lOFC and mOFC may contribute to different severities of bulimia, which will expands our understanding of the neurobiological substrates underlying bulimia across a spectrum from healthy to unhealthy.

Abnormal causal connectivity of anterior cingulate cortex-visual cortex circuit related to nonsteroidal anti-inflammatory drug efficacy in migraine.

The anterior cingulate cortex (ACC) and visual cortex are integral components of the neurophysiological mechanisms underlying migraine, yet the impact of altered connectivity patterns between these regions on migraine treatment remains unknown. To elucidate this issue, we investigated the abnormal causal connectivity between the ACC and visual cortex in patients with migraine without aura (MwoA), based on the resting-state functional magnetic resonance imaging data, and its predictive ability for the efficacy of nonsteroidal anti-inflammatory drugs (NSAIDs). The results revealed increased causal connectivity from the bilateral ACC to the lingual gyrus (LG) and decreased connectivity in the opposite direction in nonresponders compared with the responders. Moreover, compared with the healthy controls, nonresponders exhibited heightened causal connectivity from the ACC to the LG, right inferior occipital gyrus (IOG) and left superior occipital gyrus, while connectivity patterns from the LG and right IOG to the ACC were diminished. Based on the observed abnormal connectivity patterns, the support vector machine (SVM) models showed that the area under the receiver operator characteristic curves for the ACC to LG, LG to ACC and bidirectional models were 0.857, 0.898, and 0.939, respectively. These findings indicate that neuroimaging markers of abnormal causal connectivity in the ACC-visual cortex circuit may facilitate clinical decision-making regarding NSAIDs administration for migraine management.

Multi‐modal Neuroimaging Phenotyping of Mnemonic Anosognosia in the Aging Brain

AbstractBackgroundMnemonic anosognosia (i.e., unawareness) is a behavioral condition characterized by a lack of self‐awareness of objective memory decline. In the context of Alzheimer’s Disease (AD), unawareness may be a sign of predementia stages. It contributes to disease severity, symptomatology worsening, and caregiver burden and is a good predictor of clinical progression. Here, we use in‐vivo multi‐modal neuroimaging to profile the brain phenotype of individuals presenting altered self‐awareness of memory during aging.MethodsWe used amyloid‐ and tau‐PET (N = 335) and resting‐state fMRI (N = 713) data of individuals from the Anti‐Amyloid Treatment in Asymptomatic Alzheimer’s Disease (A4)/Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) studies (Table1A). The neurocognitive profile of unawareness was characterized using between‐groups comparisons (omnibus and post‐hoc analyses) of the objective (LM delayed memory, and FCSRT free and cued scores) and subjective (MACQ) memory measurements of individuals classified as unaware of their memory impairment, compared to aware, subjective‐complainers and control individuals. To characterize the cortical burden of amyloid and tau and their modulatory effect on functional connectivity networks, we applied whole‐brain voxel‐wise GLM analyses, region‐of‐interest associations, and graph‐theory metrics (e.g., degree centrality).ResultsUnaware and aware individuals perform worse than the control group in objective memory tests, while unaware individuals differ from aware but not from controls in MACQ (Table1B). The unaware group presents elevated amyloid and tau burden in midline core regions of the default mode network (DMN) compared to aware, complainer or control individuals (p‐value<0.05) (Figure1AB). Tau spreading in controls showed significant connectivity toward DMN and lateral and medial occipito‐parietal regions (Figure1C). Unawareness is characterized by an altered network connectivity pattern modulated by tau accumulation in which hyperconnectivity is observed mainly in midline DMN and posterior occipito‐parietal regions (p‐value<0.05) (Figure2A). Degree centrality revealed the main connectivity hubs altered by tau deposits in unaware individuals (e.g., posterior regions) (Figure2B).ConclusionsMnemonic anosognosia is an early behavioral biomarker of AD pathology. Unawareness of memory decline leads to distinct brain phenotype, characterized by increased amyloid and tau burden, along with functional network connectivity disruptions, in several areas of the self‐referential brain network, including the posterior cerebral cortex of the human brain.

Alzheimer’s disease is associated with increased modularity and assortativity: Evidence from structural and metabolic connectivity

AbstractBackgroundAlzheimer’s disease (AD) is a progressive disorder associated with cognitive dysfunction that alters brain connectivity and assessing these altered connectivity patterns has become a topic of increasing interest. In this study, we examine the structural and metabolic connectivity using cortical thickness and [18F] Flouro deoxyglucose (FDG)‐positron emission tomography (PET) to identify the network modification in patient with AD when compared to mild cognitive impairment (MCI). To examine our hypothesis; we quantified a relatively newer graph theory measures including assortativity and modularity. We aimed to unravel the multimodal network alterations using simultaneous MRI‐PET acquisitions.MethodsPatients who underwent simultaneous FDG‐PET and MRI study on a 3T MRI were recruited for this exploratory study. After appropriate pre‐processing of structural‐MRI and PET‐metabolic data, graph measures were obtained using the BRAPH toolbox, and subsequently; global and nodal network measures were used to derive group‐level differences (corrected p<0.05). Regions that revealed significant differences were correlated with the cognitive scores (ACE‐III).Results83 demographically matched patients [MCI (n = 27), and AD (n = 56)] were analysed. There were no significant differences between the groups in the mean age (MCI 63.52 ±9.19 years and AD 63.73 ±9.60 years), gender (M: F) MCI 20:7 and AD 26:30, or the mean duration of disease (MCI 2.23±1.92 and AD 2.95 years) other than ACE scores (MCI‐87.30±5.53 and AD 46.02 ±20.61, p value <0.001) and the CDR (MCI‐very mild and AD‐Moderate and Severe). Patients with AD revealed significantly increased assortativity at the global level in both structural and metabolic connectivity analysis. In addition, metabolic connectivity revealed increased modularity and decreased participation coefficient in patients with AD. Cortical thickness and SUV abnormalities in several regions in bilateral parietotemporal lobes were proportional with the cognitive scores (ACE‐III).ConclusionProbable erroneous and homophilic network segregation paralleling the aging associated loss of whole brain integration was found proportional to the memory scores. Further studies in larger cohorts are required to ascertain the clinical relevance of these findings as an imaging biomarker.

Neural mechanisms of working memory dysfunction in patients with chronic insomnia disorder

ObjectiveThis study aimed to investigate the neural mechanisms underlying working memory impairment in patients with chronic insomnia disorder (CID) using event-related potentials (ERP) and resting-state functional connectivity (rsFC) approaches. MethodsParticipants, including CID patients and healthy controls (HCs), completed clinical scales and underwent electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). EEG analysis compared reaction times, P3 amplitudes, event-related spectral perturbations (ERSP), and inter-trial phase synchronisation (ITPS) between CID patients and HCs. Subsequently, frontal regions (i.e., the Superior Frontal Gyrus [SFG] and Middle Frontal Gyrus [MFG]) corresponding to the EEG were selected as seeds for rsFC analysis. Correlation analyses were conducted to further investigate the relationship between functional connectivity abnormalities in brain regions and clinical symptom severity and P3 amplitude in CID patients. ResultsCompared to HCs, CID patients exhibited slower reaction times across all working memory conditions, with the deficits becoming more pronounced as memory load increased. ERP analysis revealed increased P3 amplitude, theta wave power, and reduced inter-trial synchrony in CID patients. rsFC analysis showed decreased connectivity of SFG-posterior cingulated cortex (PCC), SFG-MFG, and MFG-frontal pole (FP), and increased connectivity of MFG- Middle Temporal Gyrus (MTG)in CID patients. Importantly, a significant correlation was found between the rsFC of SFG-MTG and P3 amplitude during 1-back. ConclusionThis study confirms deficits in working memory capacity in patients with CID, specifically in the neural mechanisms of cognitive processing that vary depending on the level of cognitive load. Alterations in connectivity patterns within and between the frontal and temporal regions may be the neural basis of the cognitive impairment.

Disentangling the Individual-Shared and Individual-Specific Subspace of Altered Brain Functional Connectivity in Autism Spectrum Disorder

BackgroundDespite considerable effort toward understanding the neural basis of autism spectrum disorder (ASD) using case-control analyses of resting-state functional magnetic resonance imaging data, findings are often not reproducible, largely due to biological and clinical heterogeneity among individuals with ASD. Thus, exploring the individual-shared and individual-specific altered functional connectivity (AFC) in ASD is important to understand this complex, heterogeneous disorder. MethodsWe considered 254 individuals with ASD and 295 typically developing individuals from the Autism Brain Imaging Data Exchange to explore the individual-shared and individual-specific subspaces of AFC. First, we computed AFC matrices of individuals with ASD compared with typically developing individuals. Then, common orthogonal basis extraction was used to project AFC of ASD onto 2 subspaces: an individual-shared subspace, which represents altered connectivity patterns shared across ASD, and an individual-specific subspace, which represents the remaining individual characteristics after eliminating the individual-shared altered connectivity patterns. ResultsAnalysis yielded 3 common components spanning the individual-shared subspace. Common components were associated with differences of functional connectivity at the group level. AFC in the individual-specific subspace improved the prediction of clinical symptoms. The default mode network–related and cingulo-opercular network–related magnitudes of AFC in the individual-specific subspace were significantly correlated with symptom severity in social communication deficits and restricted, repetitive behaviors in ASD. ConclusionsOur study decomposed AFC of ASD into individual-shared and individual-specific subspaces, highlighting the importance of capturing and capitalizing on individual-specific brain connectivity features for dissecting heterogeneity. Our analysis framework provides a blueprint for parsing heterogeneity in other prevalent neurodevelopmental conditions.

Conectividad cerebral, empatía, insensibilidad emocional y toma de decisiones en el trastorno de la conducta: Una revisión sistemática.

The deficits in empathy, emotional insensitivity, and decision-making constitute the core of symptoms defining conduct disorder. Although several studies have established some correlates between brain connectivity and symptoms separately, there has been little effort to systematize such information. The current systematic review aimed to describe the findings obtained through analyzing brain connectivity networks by functional magnetic resonance imaging associated with alterations in empathy, emotional insensitivity, and decision-making in subjects with conduct disorder. A systematic search was carried out for original studies published in Medline (PubMed), Scopus, Scielo, Google Scholar, Scopus, and Nature. Articles published between 2000 and 2022 were included; a qualitative synthesis was obtained with the six selected articles at the end of the process. The findings show altered brain connectivity patterns in brain regions associated with empathy and insensitivity in subjects with conduct disorder.

Neuroimaging markers of Alice in Wonderland syndrome in patients with migraine with aura.

The Alice in Wonderland syndrome (AIWS) is a transient neurological disturbance characterized by sensory distortions most frequently associated with migraine in adults. Some lines of evidence suggest that AIWS and migraine might share common pathophysiological mechanisms, therefore we set out to investigate the common and distinct neurophysiological alterations associated with these conditions in migraineurs. We conducted a case-control study acquiring resting-state fMRI data from 12 migraine patients with AIWS, 12 patients with migraine with typical aura (MA) and 24 age-matched healthy controls (HC). We then compared the interictal thalamic seed-to-voxel and ROI-to-ROI cortico-cortical resting-state functional connectivity between the 3 groups. We found a common pattern of altered thalamic connectivity in MA and AIWS, compared to HC, with more profound and diffuse alterations observed in AIWS. The ROI-to-ROI functional connectivity analysis highlighted an increased connectivity between a lateral occipital region corresponding to area V3 and the posterior part of the superior temporal sulcus (STS) in AIWS, compared to both MA and HC. The posterior STS is a multisensory integration area, while area V3 is considered the starting point of the cortical spreading depression (CSD), the neural correlate of migraine aura. This interictal hyperconnectivity might increase the probability of the CSD to directly diffuse to the posterior STS or deactivating it, causing the AIWS symptoms during the ictal phase. Taken together, these results suggest that AIWS in migraineurs might be a form of complex migraine aura, characterized by the involvement of associative and multisensory integration areas.

The Co-Occurrence of Post-Traumatic Stress Disorder and Depression in Individuals with and without Traumatic Brain Injury: A Comprehensive Investigation.

Post-traumatic stress disorder (PTSD) is a prevalent psychiatric disorder that often occurs following war trauma. Despite its high prevalence, there is still a lack of comprehensive understanding regarding the mechanisms underlying its progression and treatment resistance. Recent research has shed light on the biological basis of PTSD, with neuroimaging studies revealing altered brain connectivity patterns in affected individuals. In war contexts, traumatic brain injury (TBI) is a common occurrence and is associated with a high prevalence of PTSD. This study aimed to compare the severity of PTSD and depression in patients with and without a history of TBI to shed light on the impact of comorbid TBI on the presentation of PTSD symptoms. To achieve this goal, a cross-sectional study was conducted involving a sample of 60 outpatients who were diagnosed with both PTSD and Depressive Disorder. The inclusion criteria required participants to meet the diagnostic criteria for both disorders using validated tools. The severities of PTSD and depressive symptoms were assessed using scales that have been widely used and validated in previous research. By utilizing these standardized assessment tools, this study aimed to ensure the reliability and validity of the obtained data. The results of this study revealed that patients with comorbid PTSD and TBI exhibited a significantly higher severity of PTSD symptoms compared to those with PTSD only. Specifically, the comorbid group demonstrated higher ratings of symptom intensity across all symptom clusters. These findings are consistent with previous research that has highlighted the impact of comorbid TBI on the intensity and persistence of PTSD symptoms. When controlling for PTSD severity, no significant differences were observed in the severity of depressive symptoms between the two groups. This suggests that the increased depressive symptoms observed in the comorbid group may be primarily driven by the presence of more intense PTSD symptoms rather than TBI per se. The findings highlight the need for an accurate diagnosis of TBI in individuals with PTSD to guide appropriate treatment interventions. Further research is warranted to delve into the underlying mechanisms that contribute to the interaction between TBI and PTSD and to develop targeted interventions for individuals with comorbid PTSD and TBI.

Children at Familial High risk of Schizophrenia and Bipolar Disorder Exhibit Altered Connectivity Patterns During Pre-attentive Processing of an Auditory Prediction Error.

Individuals with schizophrenia or bipolar disorder have attenuated auditory mismatch negativity (MMN) responses, indicating impaired sensory information processing. Computational models of effective connectivity between brain areas underlying MMN responses show reduced connectivity between fronto-temporal areas in individuals with schizophrenia. Here we ask whether children at familial high risk (FHR) of developing a serious mental disorder show similar alterations. We recruited 67 children at FHR for schizophrenia, 47 children at FHR for bipolar disorder as well as 59 matched population-based controls from the Danish High Risk and Resilience study. The 11-12-year-old participants engaged in a classical auditory MMN paradigm with deviations in frequency, duration, or frequency and duration, while we recorded their EEG. We used dynamic causal modeling (DCM) to infer on the effective connectivity between brain areas underlying MMN. DCM yielded strong evidence for differences in effective connectivity among groups in connections from right inferior frontal gyrus (IFG) to right superior temporal gyrus (STG), along with differences in intrinsic connectivity within primary auditory cortex (A1). Critically, the 2 high-risk groups differed in intrinsic connectivity in left STG and IFG as well as effective connectivity from right A1 to right STG. Results persisted even when controlling for past or present psychiatric diagnoses. We provide novel evidence that connectivity underlying MMN responses in children at FHR for schizophrenia and bipolar disorder is altered at the age of 11-12, echoing findings that have been found in individuals with manifest schizophrenia.

Altered default mode network causal connectivity patterns in autism spectrum disorder revealed by Liang information flow analysis.

Autism spectrum disorder (ASD) is a pervasive developmental disorder with severe cognitive impairment in social communication and interaction. Previous studies have reported that abnormal functional connectivity patterns within the default mode network (DMN) were associated with social dysfunction in ASD. However, how the altered causal connectivity pattern within the DMN affects the social functioning in ASD remains largely unclear. Here, we introduced the Liang information flow method, widely applied to climate science and quantum mechanics, to uncover the brain causal network patterns in ASD. Compared with the healthy controls (HC), we observed that the interactions among the dorsal medial prefrontal cortex (dMPFC), ventral medial prefrontal cortex (vMPFC), hippocampal formation, and temporo-parietal junction showed more inter-regional causal connectivity differences in ASD. For the topological property analysis, we also found the clustering coefficient of DMN and the In-Out degree of anterior medial prefrontal cortex were significantly decreased in ASD. Furthermore, we found that the causal connectivity from dMPFC to vMPFC was correlated with the clinical symptoms of ASD. These altered causal connectivity patterns indicated that the DMN inter-regions information processing was perturbed in ASD. In particular, we found that the dMPFC acts as a causal source in the DMN in HC, whereas it plays a causal target in ASD. Overall, our findings indicated that the Liang information flow method could serve as an important way to explore the DMN causal connectivity patterns, and it also can provide novel insights into the nueromechanisms underlying DMN dysfunction in ASD.

Atypical oscillatory dynamics during emotional face processing in paediatric obsessive–compulsive disorder with MEG

Children and youth with obsessive–compulsive disorder (OCD) demonstrate difficulties with social, emotional and cognitive functions in addition to the core diagnosis of obsessions and compulsions. This is the first magnetoencephalography (MEG) study to examine whole-brain neurophysiological functional connectivity of emotional face processing networks in paediatric OCD. Seventy-two participants (OCD: n = 36; age 8–17 yrs; typically developing controls: n = 36, age 8–17 yrs) completed an implicit emotional face processing task in the MEG. Functional connectivity networks in canonical frequency bands were compared between groups, and within OCD and control groups between emotions (angry vs. happy). Between groups, participants with OCD showed increased functional connectivity in the gamma band to angry faces, suggesting atypical perception of angry faces in OCD. Within groups, the OCD group showed greater engagement of the beta band, suggesting the over-use of top-down processing when perceiving happy versus angry emotions, while controls engaged in bottom-up gamma processing, also greater to happy faces. Over-activation of top-down processing has been linked to difficulties modifying one’s cognitive set. Findings establish altered patterns of neurophysiological connectivity in children with OCD, and are striking in their oscillatory specificity. Our results contribute to a greater understanding of the neurobiology of the disorder, and are foundational for the possibility of alternative targets for intervention.

Stable functional compensation within hippocampal-subregion networks in patients with temporal glioma before and after surgery.

ObjectiveTo identify whether tumor invasion of the temporal lobe induces functional compensation of the hippocampal-subregion (HIPsub) network connectivity before surgery, and to further validate the stability of this functional compensation within the HIPsub network in patients with temporal glioma tumor (TTumor) after surgical resection of the tumor.MethodsIn the first cohort, analysis of HIPsub functional connectivity (FC) was conducted to identify the functional compensation of the altered HIPsub connectivity pattern in TTumor through a pattern classification approach. Then, the second cohort investigated whether functional compensation in TTumor patients changed after surgical resection of the tumor.ResultsIn the first cohort, this study identified altered HIPsub network connectivity patterns and its functional compensation regions (i.e., left parahippocampal gyrus and bilateral cerebellum anterior lobe) in TTumor patients. Second, the altered HIPsub network connectivity patterns had the power to discriminate TTumor patients from healthy controls (CN) on an individual subject basis, with an AUC of 97.0%, sensitivity of 93.5%, and specificity of 90.3%. Finally, in the second cohort, we found that functional connectivities of functional compensation regions within the HIPsub network in TTumor patients did not change between before and after surgery.ConclusionThis study provides novel evidence regarding functional compensation within the HIPsub network in TTumor patients. It has been suggested that the fine hippocampal subregion was more sensitive, which reveals functional compensation induced by tumor invasion of the temporal lobe. Furthermore, this study verified the stability and persistence of this functional compensation in TTumor patients after surgical resection of the tumor.

The distinct disrupted plasticity in structural and functional network in mild stroke with basal ganglia region infarcts.

Stroke induced by basal ganglia infarction often impair cognitive function. The exploration of topological patterns in structural and functional networks associated cognitive impairment after stroke may contribute to understand the pathological mechanism of cognitive impairment caused by stroke. In this paper,graph theory analysis was applied to diffusion-weighted imaging (DWI) data and resting-state functional MRI (fMRI) data from 23 post-stroke patients with cognitive impairment (PSCI), 17 post-stroke patients without cognitive impairment (NPSCI), and 29 healthy controls (HC). Structural and functional connectivity between 90 cortical and subcortical brain regions was estimated and set threshold to construct a set of undirected graphs. Network-based statistics (NBS) was used to characterize altered connectivity patterns among the three groups. Compared to HC, the PSCI group demonstrated substantial reductions in all three types of connections-rich club, feeder, and local-in structural and functional networks. Specifically, in structural network analysis, reduced connections were observed within basal ganglia and basal ganglia-frontal networks, whereas in the functional network analysis, reduced connections were observed in fronto-parietal network (FPN) and cingulo-opercular networks (CON). Meanwhile, compared to HC, the NPSCI group demonstrated reductions in both feeder and local connections only within occipital area and occipital-temporal structural networks. The findings of reduced structural connectivity in regions stemming from a basal ganglia core and reduced functional connectivity in FPN and CON may indicate a bottom-up cognitive impairment induced by stroke. Graph analysis and connectomics may aid clinical diagnosis and serve as potential imaging biomarkers for post-stroke patients with cognitive impairment.