Altered Connectivity Patterns Research Articles

Neurophysiological correlates of trait and behavioral impulsivity across methamphetamine and gambling Addiction

Investigating neurophysiological markers linked to impulsivity in individuals with gambling and methamphetamine addiction using resting-state EEG data offers valuable insights into the underlying neurophysiological mechanisms associated with impulsivity in individuals with addiction. This study aims to use resting-state EEG to explore the connection between various types of addiction and different aspects of impulsivity. Participants from the methamphetamine, gambling, and healthy control groups (abbreviation: MA, GB, HC) underwent EEG recordings and completed measures of impulsivity. Group differences in trait scores and behavioral tendencies were analyzed. Abnormal connections with node linkage and importance changes were analyzed through the resting-state EEG power spectral and network analyses. Further, relationships between impulsivity scores and connectivity differences in groups were explored through correlation analysis. Finally, these abnormal connections related to impulsivity were tested for their effect of distinguishing individuals with addiction from healthy controls through the ROC analysis. Results revealed that GB displayed the highest trait impulsivity on the overall score, while MA exhibited greater attentional impulsivity. Variations in behavioral impulsivity were reflected in response times. Resting-state EEG analysis showed higher beta power in GB. Specific channel pairs demonstrated abnormal connections and altered connectivity patterns in the beta band, with MA displaying a less efficient network compared to GB. Correlation analyses uncovered associations between impulsivity scores and connectivity, which were influenced by group differences. Furthermore, resting-state EEG connections effectively differentiated individuals with addiction from healthy controls. Overall, this study contributes valuable insights into the neural mechanisms of addiction-related impulsivity, emphasizing the potential of resting-state EEG connections as an important neurophysiological correlate.

In silico and functional analysis identifies key gene networks and novel gene candidates in obesity-linked human visceral fat.

Visceral adiposity is associated with increased proinflammatory activity, insulin resistance, diabetes risk, and mortality rate. Numerous individual genes have been associated with obesity, but studies investigating gene regulatory networks in human visceral obesity have been lacking. We analyzed gene regulatory networks in human visceral adipose tissue (VAT) from 48 and 11 Chinese patients with and without obesity, respectively, using gene coexpression and gene regulatory network construction from RNA-sequencing data. We also conducted RNA interference-based functional tests on selected genes for effects on adipocyte differentiation. A scale-free gene coexpression network was constructed from 360 differentially expressed genes between VAT samples from patients with and without obesity (absolute log fold change > 1, false discovery rate [FDR] < 0.05), with edge probability > 0.8. Gene regulatory network analysis identified candidate transcription factors associated with differentially expressed genes. A total of 15 subnetworks (communities) displayed altered connectivity patterns between obesity and nonobesity networks. Genes in proinflammatory pathways showed increased network connectivity in VAT samples with obesity, whereas the oxidative phosphorylation pathway displayed reduced connectivity (enrichment FDR < 0.05). Functional screening via RNA interference identified genes such as SOX30, SIRPB1, and OSBPL3 as potential network-derived candidates influencing adipocyte differentiation. This approach highlights the network architecture in human obesity, identifies novel candidate genes, and generates new hypotheses regarding network-assisted gene regulation in VAT.

Investigating visuo-tactile mirror properties in borderline personality disorder: A TMS-EEG study

ObjectivesPatients with borderline personality disorder (pw-BPD) have decreased levels of cognitive empathy, which may be subtended by mirror-like mechanisms in the somatosensory cortices, i.e., the Tactile Mirror System (TaMS). Here, we aimed to shed light on the TaMS and empathic deficits in pw-BPD focusing on connectivity, using transcranial magnetic stimulation and electroencephalography (TMS-EEG). MethodsAfter study preregistration, we collected self-report measures of empathic abilities, behavioral performance in a visuo-tactile spatial congruency task investigating TaMS activity, and TMS-evoked potentials (TEPs) from 20 pw-BPD and 20 healthy controls. TMS was delivered over the right primary somatosensory cortex (S1) during touch observation and real touch delivery. ResultsPw-BPD reported significantly lower levels of cognitive empathy than controls and made significantly more errors in reporting the side of real touches during touch observation. Moreover, pw-BPD presented an altered connectivity pattern from S1-TEPs during touch perception and touch observation, in the last case without differences between human- and object-directed touches. ConclusionsThe results do not support a specific impairment of TaMS in pw-BPD, but reveal significant behavioral and connectivity alterations within the somatosensory network during touch processing. SignificanceThe present findings temper the proposed role of the TaMS in BPD, while still highlighting the involvement of somatosensory network alterations.

Multiclass classification of Autism Spectrum Disorder, attention deficit hyperactivity disorder, and typically developed individuals using fMRI functional connectivity analysis.

Neurodevelopmental conditions, such as Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD), present unique challenges due to overlapping symptoms, making an accurate diagnosis and targeted intervention difficult. Our study employs advanced machine learning techniques to analyze functional magnetic resonance imaging (fMRI) data from individuals with ASD, ADHD, and typically developed (TD) controls, totaling 120 subjects in the study. Leveraging multiclass classification (ML) algorithms, we achieve superior accuracy in distinguishing between ASD, ADHD, and TD groups, surpassing existing benchmarks with an area under the ROC curve near 98%. Our analysis reveals distinct neural signatures associated with ASD and ADHD: individuals with ADHD exhibit altered connectivity patterns of regions involved in attention and impulse control, whereas those with ASD show disruptions in brain regions critical for social and cognitive functions. The observed connectivity patterns, on which the ML classification rests, agree with established diagnostic approaches based on clinical symptoms. Furthermore, complex network analyses highlight differences in brain network integration and segregation among the three groups. Our findings pave the way for refined, ML-enhanced diagnostics in accordance with established practices, offering a promising avenue for developing trustworthy clinical decision-support systems.

Subjective cognitive decline is associated with altered patterns of brain activity and connectivity during performance of an old/new recognition memory task

IntroductionSubjective Cognitive Decline (SCD) is considered a preclinical stage within the AD continuum. Knowledge about the functional changes in the brain associated with episodic memory retrieval and novelty recognition in people with SCD is currently very limited. MethodThe study aimed to evaluate behavioural and neurofunctional changes in individuals with SCD, measured relative to a control group, during successful episodic memory retrieval and novelty recognition, as well as to compare the functional connectivity patterns related to these cognitive processes within the Default Mode Network (DMN) in both groups. Participants performed an old/new recognition memory task with words while the BOLD signal was acquired. ResultsNo between-group differences were observed in the performance of the episodic memory task. However, during the successful recognition of old words, the SCD group showed brain hypoactivity in the right rolandic operculum and reduced functional connectivity between the DMN and the fronto-parietal control network (FPCN). During the correct identification of new words, the SCD group also showed reduced connectivity between the DMN and the FPCN, and lower connectivity within the DMN. ConclusionDespite the absence of objective evidence of cognitive impairment, people with SCD display several changes in brain activity and connectivity associated with episodic memory retrieval and novelty recognition.

Functional MRI for the Assessment of Brain Connectivity in Neurodegenerative Diseases: An Observational Study in Mexico City

Introduction: Neurodegenerative diseases are characterized by progressive brain dysfunction and structural changes. Functional MRI (fMRI), a non-invasive imaging technique, offers the potential to assess brain connectivity and identify early biomarkers of these diseases. Methods: This observational study included patients with Alzheimer's disease (AD), Parkinson's disease (PD), and healthy controls in Mexico City. Resting-state fMRI data was acquired, and brain connectivity was analyzed using independent component analysis (ICA) and seed-based correlation analysis (SCA). Results: fMRI revealed altered brain connectivity patterns in AD and PD compared to healthy controls. In AD, decreased connectivity was observed within the default mode network (DMN), while PD patients showed reduced connectivity in the motor network. Conclusion: fMRI provides valuable insights into brain connectivity changes in neurodegenerative diseases. These findings contribute to the development of early diagnostic tools and potential therapeutic targets for AD and PD.

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.

Neurological activation during verbal fluency task and resting-state functional connectivity abnormalities in obsessive-compulsive disorder: a functional near-infrared spectroscopy study.

This study aims to investigate the activation of frontotemporal functional brain areas in patients with Obsessive-Compulsive Disorder (OCD) during a Verbal Fluency Task (VFT), and to compare their brain functional connectivity in a resting state with that of healthy controls. The goal is to deepen our understanding of the neuropathological mechanisms underlying OCD. 32 patients with OCD and 32 controls matched for age, gender, handedness, and years of education participated in this study, they were divided into OCD group and healthy comtrol group. We conducted VFT task tests and 10-minute resting state tests on both groups by using functional Near-Infrared Spectroscopy (fNIRS). The VFT was utilized to assess the activation (beta values) and the integral and centroid values of the frontal and bilateral temporal lobes, including brain areas BA9 and 46 (dorsolateral prefrontal cortex), BA10 (frontal pole), BA45 (inferior frontal gyrus), BA21 (middle temporal gyrus), and BA22 (superior temporal gyrus). We evaluated the functional connectivity levels of these areas during the resting state. Differences in these measures between OCD patients and healthy controls were analyzed using two-sample independent t-tests and non-parametric Mann-Whitney U tests. During VFT, OCD had smaller integral values(z=5.371, p<0.001; t=4.720, p<0.001), and larger centroid values(t=-2.281, p=0.026; z=-2.182, p=0.029) compared to healthy controls, along with a reduced number of activated channels detected by fNIRS. Additionally, activation values (β) in various functional brain areas, including BA9, BA46, BA10, BA45, BA21, and BA22, were significantly lower in the OCD group (all p< 0.01). In the resting state, notable disparities in functional connectivity were observed between the inferior frontal gyrus (IFG) and dorsolateral prefrontal cortex (DLPFC) in the OCD group, in comparison to the control group. Specifically, there was a significant increase in connectivity between the left IFG and right DLPFC, suggesting the presence of altered connectivity patterns in these areas. The study highlights significant disparities in neural activation and functional connectivity between OCD patients and healthy controls during VFT. Specifically, reduced activation was noted in the frontal and bilateral temporal lobes of OCD patients, alongside alterations in resting-state functional connectivity between the IFG and DLPFC. These findings contribute to our understanding of the neurobiological underpinnings of OCD and may guide future therapeutic strategies.

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&lt;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&lt;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&lt;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 &lt;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.