Most recent paper

Disrupted dynamic network attribution associated with gait disorder in cerebral small vessel disease

Fri, 06/14/2024 - 18:00

Brain Connect. 2024 Jun 14. doi: 10.1089/brain.2023.0092. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Previous research has focused on static functional connectivity in gait disorders caused by cerebral small vessel disease (CSVD), neglecting dynamic functional connections and network attribution. This study aims to investigate alterations in dynamic functional network connectivity (dFNC) and topological organization variance in CSVD-related gait disorders.

METHODS: A total of 85 patients with CSVD, including 41 CSVD patients with gait disorders (CSVD-GD), 44 CSVD patients with non-gait disorders (CSVD-NGD), and 32 health controls (HC) were enrolled in this study. Five networks composed of 10 independent components were selected using independent component analysis. Sliding time window and k-means clustering methods were used for dFNC analysis. The relationship between alterations in the dFNC properties and gait metrics was further assessed.

RESULTS: Three reproducible dFNC states were determined (State 1: sparsely connected, State 2: intermediate pattern, State 3: strongly connected). CSVD-GD showed significantly higher fractional windows (FW) and mean dwell time (MDT) in State 1 compared to CSVD-NGD. Higher local efficiency variance was observed in the CSVD-GD group compared to HC, but no differences were found in the global efficiency comparison. Both the FW and MDT in State 1 were negatively correlated with gait speed and step length, and the relationship between MDT of State 1 and gait speed was mediated by overall cognition, information processing speed and executive function.

CONCLUSIONS: Our study uncovered abnormal dFNC indicators and variations in topological organization in CSVD-GD, offering potential early prediction indicators and freshening insights into the underlying pathogenesis of gait disturbances in CSVD.

PMID:38874973 | DOI:10.1089/brain.2023.0092

Resting-State Network Analysis Reveals Altered Functional Brain Connectivity in Essential Tremor

Fri, 06/14/2024 - 18:00

Brain Connect. 2024 Jun 14. doi: 10.1089/brain.2024.0004. Online ahead of print.

ABSTRACT

INTRODUCTION: Essential tremor (ET) comprises motor and non-motor related features, while the current neuro-pathogenetic basis is still insufficient to explain the etiologies of ET. While cerebellum associated circuits have been discovered, the large-scale cerebral network connectivity in ET remains unclear. This study aimed to characterize the ET in terms of functional connectivity as well as network. We hypothesized that the resting-state network within cerebrum could be altered in ET patients.

METHODS: Resting-state functional MRI (fMRI) was used to evaluate the inter- and intra-network connectivity as well as the functional activity in ET and normal control. Correlation analysis was performed to explore the relationship between resting-state network metrics and tremor features.

RESULTS: Comparison of inter-network connectivity indicated a decreased connectivity between default mode network and ventral attention network in ET group (P<0.05). Differences in functional activity (assessed by amplitude of low frequency fluctuation, ALFF) were found in several brain regions participating in various resting-state networks (P<0.05). ET group generally have higher degree centrality over normal control. Correlation analysis has revealed that tremor features are associated with inter-network connectivity (|r|=0.135-0.506), ALFF (|r|=0.313-0.766), and degree centrality (|r|=0.523-0.710).

CONCLUSION: Alterations in the cerebral network of ET was detected by using resting-state fMRI, demonstrating a potentially useful approach to explore the cerebral alterations in ET.

PMID:38874971 | DOI:10.1089/brain.2024.0004

Threat- and Reward-Related Brain Circuitry, Perceived Stress, and Anxiety in Adolescents During the COVID-19 Pandemic: A Longitudinal Investigation

Fri, 06/14/2024 - 18:00

Soc Cogn Affect Neurosci. 2024 Jun 14:nsae040. doi: 10.1093/scan/nsae040. Online ahead of print.

ABSTRACT

The COVID-19 pandemic has been related to heightened anxiety in adolescents. The basolateral amygdala (BLA) and the nucleus accumbens (NAcc) have been implicated in response to stress and may contribute to anxiety. The role of threat- and reward-related circuitry in adolescent anxiety during the COVID-19 pandemic, however, is not clear. Ninety-nine adolescents underwent resting-state fMRI approximately one year before the pandemic. Following shelter-in-place orders, adolescents reported their perceived stress and, one month later, their anxiety. Generalized multivariate analyses identified BLA and NAcc seed-based whole-brain connectivity maps with perceived stress. We examined associations between seed-based connectivity in significant clusters and subsequent anxiety. Perceived stress was associated with bilateral BLA and NAcc connectivity across distributed clusters that included prefrontal, limbic, temporal, and cerebellar regions. Several NAcc connectivity clusters located in ventromedial prefrontal, parahippocampal, and temporal cortices were positively associated with anxiety; whereas NAcc connectivity with the inferior frontal gyrus was negatively associated. BLA connectivity was not associated with anxiety. These results underscore the integrative role of the NAcc in responding to acute stressors and its relation to anxiety in adolescents. Elucidating the involvement of subcortical-cortical circuitry in adolescents' capacity to respond adaptively to environmental challenges can inform treatment approaches for anxiety-related disorders.

PMID:38874967 | DOI:10.1093/scan/nsae040

The distinct and potentially conflicting effects of tDCS and tRNS on brain connectivity, cortical inhibition, and visuospatial memory

Fri, 06/14/2024 - 18:00

Front Hum Neurosci. 2024 May 30;18:1415904. doi: 10.3389/fnhum.2024.1415904. eCollection 2024.

ABSTRACT

Noninvasive brain stimulation (NIBS) techniques, including transcranial direct current stimulation (tDCS) and transcranial random noise stimulation (tRNS), are emerging as promising tools for enhancing cognitive functions by modulating brain activity and enhancing cognitive functions. Despite their potential, the specific and combined effects of tDCS and tRNS on brain functions, especially regarding functional connectivity, cortical inhibition, and memory performance, are not well-understood. This study aims to explore the distinct and combined impacts of tDCS and tRNS on these neural and cognitive parameters. Using a within-subject design, ten participants underwent four stimulation conditions: sham, tDCS, tRNS, and combined tDCS + tRNS. We assessed the impact on resting-state functional connectivity, cortical inhibition via Cortical Silent Period (CSP), and visuospatial memory performance using the Corsi Block-tapping Test (CBT). Our results indicate that while tDCS appears to induce brain lateralization, tRNS has more generalized and dispersive effects. Interestingly, the combined application of tDCS and tRNS did not amplify these effects but rather suggested a non-synergistic interaction, possibly due to divergent mechanistic pathways, as observed across fMRI, CSP, and CBT measures. These findings illuminate the complex interplay between tDCS and tRNS, highlighting their non-additive effects when used concurrently and underscoring the necessity for further research to optimize their application for cognitive enhancement.

PMID:38873654 | PMC:PMC11169625 | DOI:10.3389/fnhum.2024.1415904

Sex differences of neural connectivity in internet gaming disorder and its association with sleep quality: an exploratory fMRI study

Fri, 06/14/2024 - 18:00

Front Psychiatry. 2024 May 30;15:1379259. doi: 10.3389/fpsyt.2024.1379259. eCollection 2024.

ABSTRACT

OBJECTIVES: Sex-specific differences in internet gaming disorder (IGD) neurophysiology remain underexplored. Here we investigated sex-related variability in regional homogeneity (ReHo) and functional connectivity (FC) in IGD and their correlations with sleep quality.

METHODS: Resting-state functional magnetic resonance imaging (fMRI) scans were performed on 52 subjects with IGD and 50 healthy controls (HCs). Two-way ANOVA was used to examine sex and diagnosis interactions in ReHo and FC, followed by post-hoc analyses to explore FC biomarkers for different sexes.

RESULTS: In ReHo analysis, the four groups showed significant sex and diagnosis interactions in the right middle frontal gyrus (rMFG). FC analysis with rMFG as the seed region revealed a significant sex and diagnosis interaction effect in FC of the rMFG with the bilateral postcentral gyrus (PoCG). In male IGD group, FC between the rMFG and the bilateral PoCG correlates strongly with daytime dysfunction score and the Pittsburgh sleep quality inventory (PSQI) total score.

CONCLUSION: These findings emphasize the importance of considering sexual dimorphism in the neurobiology of IGD, which might influence subsequent treatment strategies.

PMID:38873537 | PMC:PMC11169786 | DOI:10.3389/fpsyt.2024.1379259

Impaired effective functional connectivity in the social preference of children with autism spectrum disorder

Fri, 06/14/2024 - 18:00

Front Neurosci. 2024 May 30;18:1391191. doi: 10.3389/fnins.2024.1391191. eCollection 2024.

ABSTRACT

BACKGROUND: The medial prefrontal cortex (mPFC), amygdala (Amyg), and nucleus accumbens (NAc) have been identified as critical players in the social preference of individuals with ASD. However, the specific pathophysiological mechanisms underlying this role requires further clarification. In the current study, we applied Granger Causality Analysis (GCA) to investigate the neural connectivity of these three brain regions of interest (ROIs) in patients with ASD, aiming to elucidate their associations with clinical features of the disorder.

METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from the ABIDE II database, which included 37 patients with ASD and 50 typically developing (TD) controls. The mPFC, Amyg, and NAc were defined as ROIs, and the differences in fractional amplitude of low-frequency fluctuations (fALFF) within the ROIs between the ASD and TD groups were computed. Subsequently, we employed GCA to investigate the bidirectional effective connectivity between the ROIs and the rest of the brain. Finally, we explored whether this effective connectivity was associated with the social responsiveness scale (SRS) scores of children with ASD.

RESULTS: The fALFF values in the ROIs were reduced in children with ASD when compared to the TD group. In terms of the efferent connectivity from the ROIs to the whole brain, the ASD group exhibited increased connectivity in the right cingulate gyrus and decreased connectivity in the right superior temporal gyrus. Regarding the afferent connectivity from the whole brain to the ROIs, the ASD group displayed increased connectivity in the right globus pallidus and decreased connectivity in the right cerebellar Crus 1 area and left cingulate gyrus. Additionally, we demonstrated a positive correlation between effective connectivity derived from GCA and SRS scores.

CONCLUSION: Impairments in social preference ASD children is linked to impaired effective connectivity in brain regions associated with social cognition, emotional responses, social rewards, and social decision-making. This finding further reveals the potential neuropathological mechanisms underlying ASD.

PMID:38872942 | PMC:PMC11169607 | DOI:10.3389/fnins.2024.1391191

Adaptive spatial-temporal neural network for ADHD identification using functional fMRI

Fri, 06/14/2024 - 18:00

Front Neurosci. 2024 May 30;18:1394234. doi: 10.3389/fnins.2024.1394234. eCollection 2024.

ABSTRACT

Computer aided diagnosis methods play an important role in Attention Deficit Hyperactivity Disorder (ADHD) identification. Dynamic functional connectivity (dFC) analysis has been widely used for ADHD diagnosis based on resting-state functional magnetic resonance imaging (rs-fMRI), which can help capture abnormalities of brain activity. However, most existing dFC-based methods only focus on dependencies between two adjacent timestamps, ignoring global dynamic evolution patterns. Furthermore, the majority of these methods fail to adaptively learn dFCs. In this paper, we propose an adaptive spatial-temporal neural network (ASTNet) comprising three modules for ADHD identification based on rs-fMRI time series. Specifically, we first partition rs-fMRI time series into multiple segments using non-overlapping sliding windows. Then, adaptive functional connectivity generation (AFCG) is used to model spatial relationships among regions-of-interest (ROIs) with adaptive dFCs as input. Finally, we employ a temporal dependency mining (TDM) module which combines local and global branches to capture global temporal dependencies from the spatially-dependent pattern sequences. Experimental results on the ADHD-200 dataset demonstrate the superiority of the proposed ASTNet over competing approaches in automated ADHD classification.

PMID:38872940 | PMC:PMC11169645 | DOI:10.3389/fnins.2024.1394234

Familial risk for depression moderates neural circuitry in healthy preadolescents to predict adolescent depression symptoms in the Adolescent Brain Cognitive Development (ABCD) Study

Thu, 06/13/2024 - 18:00

Dev Cogn Neurosci. 2024 Jun 4;68:101400. doi: 10.1016/j.dcn.2024.101400. Online ahead of print.

ABSTRACT

BACKGROUND: There is an imminent need to identify neural markers during preadolescence that are linked to developing depression during adolescence, especially among youth at elevated familial risk. However, longitudinal studies remain scarce and exhibit mixed findings. Here we aimed to elucidate functional connectivity (FC) patterns among preadolescents that interact with familial depression risk to predict depression two years later.

METHODS: 9-10 year-olds in the Adolescent Brain Cognitive Development (ABCD) Study were classified as healthy (i.e., no lifetime psychiatric diagnoses) at high familial risk for depression (HR; n=559) or at low familial risk for psychopathology (LR; n=1203). Whole-brain seed-to-voxel resting-state FC patterns with the amygdala, putamen, nucleus accumbens, and caudate were calculated. Multi-level, mixed-effects regression analyses were conducted to test whether FC at ages 9-10 interacted with familial risk to predict depression symptoms at ages 11-12.

RESULTS: HR youth demonstrated stronger associations between preadolescent FC and adolescent depression symptoms (ps<0.001) as compared to LR youth (ps>0.001), primarily among amygdala/striatal FC with visual and sensory/somatomotor networks.

CONCLUSIONS: Preadolescent amygdala and striatal FC may be useful biomarkers of adolescent-onset depression, particularly for youth with family histories of depression. This research may point to neurobiologically-informed approaches to prevention and intervention for depression in adolescents.

PMID:38870601 | DOI:10.1016/j.dcn.2024.101400

Autism spectrum disorders detection based on multi-task transformer neural network

Thu, 06/13/2024 - 18:00

BMC Neurosci. 2024 Jun 13;25(1):27. doi: 10.1186/s12868-024-00870-3.

ABSTRACT

Autism Spectrum Disorders (ASD) are neurodevelopmental disorders that cause people difficulties in social interaction and communication. Identifying ASD patients based on resting-state functional magnetic resonance imaging (rs-fMRI) data is a promising diagnostic tool, but challenging due to the complex and unclear etiology of autism. And it is difficult to effectively identify ASD patients with a single data source (single task). Therefore, to address this challenge, we propose a novel multi-task learning framework for ASD identification based on rs-fMRI data, which can leverage useful information from multiple related tasks to improve the generalization performance of the model. Meanwhile, we adopt an attention mechanism to extract ASD-related features from each rs-fMRI dataset, which can enhance the feature representation and interpretability of the model. The results show that our method outperforms state-of-the-art methods in terms of accuracy, sensitivity and specificity. This work provides a new perspective and solution for ASD identification based on rs-fMRI data using multi-task learning. It also demonstrates the potential and value of machine learning for advancing neuroscience research and clinical practice.

PMID:38872076 | DOI:10.1186/s12868-024-00870-3

Causal evidence for cholinergic stabilization of attractor landscape dynamics

Thu, 06/13/2024 - 18:00

Cell Rep. 2024 Jun 12;43(6):114359. doi: 10.1016/j.celrep.2024.114359. Online ahead of print.

ABSTRACT

There is substantial evidence that neuromodulatory systems critically influence brain state dynamics; however, most work has been purely descriptive. Here, we quantify, using data combining local inactivation of the basal forebrain with simultaneous measurement of resting-state fMRI activity in the macaque, the causal role of long-range cholinergic input to the stabilization of brain states in the cerebral cortex. Local inactivation of the nucleus basalis of Meynert (nbM) leads to a decrease in the energy barriers required for an fMRI state transition in cortical ongoing activity. Moreover, the inactivation of particular nbM sub-regions predominantly affects information transfer in cortical regions known to receive direct anatomical projections. We demonstrate these results in a simple neurodynamical model of cholinergic impact on neuronal firing rates and slow hyperpolarizing adaptation currents. We conclude that the cholinergic system plays a critical role in stabilizing macroscale brain state dynamics.

PMID:38870015 | DOI:10.1016/j.celrep.2024.114359

Self-construal modulates default mode network connectivity in refugees with PTSD

Wed, 06/12/2024 - 18:00

J Affect Disord. 2024 Jun 10:S0165-0327(24)00925-X. doi: 10.1016/j.jad.2024.06.009. Online ahead of print.

ABSTRACT

BACKGROUND: While self-construal and posttraumatic stress disorder (PTSD) are independently associated with altered self-referential processes and underlying default mode network (DMN) functioning, no study has examined how self-construal affects DMN connectivity in PTSD.

METHODS: A final sample of 93 refugee participants (48 with DSM-5 PTSD or sub-syndromal PTSD and 45 matched trauma-exposed controls), who reported a range individualistic-collectivistic self-construal, completed a 5-minute resting state fMRI task to enable the observation of connectivity in the DMN and other core networks.

RESULTS: Independent components analysis identified 9 active networks-of-interest, and functional network connectivity was determined. A significant interaction effect between PTSD and self-construal was observed in the anterior ventromedial DMN, with spatial maps localizing this to the left ventromedial prefrontal cortex (vmPFC), extending to the ventral anterior cingulate cortex. This effect revealed that connectivity in the vMPFC showed greater reductions in those with PTSD with higher levels of collectivistic self-construal.

LIMITATIONS: This is an observational study and causality cannot be assumed. The specialized sample of refugees means that the findings may not generalize to other trauma-exposed populations.

CONCLUSIONS: Such a finding indicates that self-construal may shape the core neural architecture of PTSD, given that functional disruptions to the vmPFC underpin the core mechanisms of extinction learning, emotion dysregulation and self-referential processing in PTSD. Results have important implications for understanding the universality of neural disturbances in PTSD, and suggest that self-construal could be an important consideration in the assessment and treatment of post-traumatic stress reactions.

PMID:38866252 | DOI:10.1016/j.jad.2024.06.009

Dysfunction of neurovascular coupling in patients with cerebral small vessel disease: A combined resting-state fMRI and arterial spin labeling study

Wed, 06/12/2024 - 18:00

Exp Gerontol. 2024 Jun 10:112478. doi: 10.1016/j.exger.2024.112478. Online ahead of print.

ABSTRACT

BACKGROUND: Cerebral small vessel disease (CSVD) closely correlates to cognitive impairment, but its pathophysiology and the neurovascular mechanisms of cognitive deficits were unclear. We aimed to explore the dysfunctional patterns of neurovascular coupling (NVC) in patients with CSVD and further investigate the neurovascular mechanisms of CSVD-related cognitive impairment.

METHODS: Forty-three patients with CSVD and twenty-four healthy controls were recruited. We adopted resting-state functional magnetic resonance imaging combined with arterial spin labeling to investigate the NVC dysfunctional patterns in patients with CSVD. The Human Brain Atlas with 246 brain regions was applied to extract the NVC coefficients for each brain region. Partial correlation analysis and mediation analysis were used to explore the relationship between CSVD pathological features, NVC dysfunctional patterns, and cognitive decline.

RESULTS: 8 brain regions with NVC dysfunction were found in patients with CSVD (p < 0.025, Bonferroni correction). The NVC dysfunctional patterns in regions of the default mode network and subcortical nuclei were negatively associated with lacunes, white matter hyperintensities burden, and the severity of CSVD (FDR correction, q < 0.05). The NVC decoupling in regions located in the default mode network positively correlated with delayed recall deficits (FDR correction, q < 0.05). Mediation analysis suggested that the decreased NVC pattern of the left superior frontal gyrus partially mediated the impact of white matter hyperintensities on delayed recall (Mediation effect: -0.119; 95%CI: -11.604,-0.458; p < 0.05).

CONCLUSION: The findings of this study reveal the NVC dysfunctional pattern in patients with CSVD and illustrate the neurovascular mechanism of CSVD-related cognitive impairment. The NVC function in the left superior frontal gyrus may serve as a promising biomarker and therapeutic target for memory deficits in patients with CSVD.

PMID:38866193 | DOI:10.1016/j.exger.2024.112478

Network and state specificity in connectivity-based predictions of individual behavior

Wed, 06/12/2024 - 18:00

Hum Brain Mapp. 2024 Jun 1;45(8):e26753. doi: 10.1002/hbm.26753.

ABSTRACT

Predicting individual behavior from brain functional connectivity (FC) patterns can contribute to our understanding of human brain functioning. This may apply in particular if predictions are based on features derived from circumscribed, a priori defined functional networks, which improves interpretability. Furthermore, some evidence suggests that task-based FC data may yield more successful predictions of behavior than resting-state FC data. Here, we comprehensively examined to what extent the correspondence of functional network priors and task states with behavioral target domains influences the predictability of individual performance in cognitive, social, and affective tasks. To this end, we used data from the Human Connectome Project for large-scale out-of-sample predictions of individual abilities in working memory (WM), theory-of-mind cognition (SOCIAL), and emotion processing (EMO) from FC of corresponding and non-corresponding states (WM/SOCIAL/EMO/resting-state) and networks (WM/SOCIAL/EMO/whole-brain connectome). Using root mean squared error and coefficient of determination to evaluate model fit revealed that predictive performance was rather poor overall. Predictions from whole-brain FC were slightly better than those from FC in task-specific networks, and a slight benefit of predictions based on FC from task versus resting state was observed for performance in the WM domain. Beyond that, we did not find any significant effects of a correspondence of network, task state, and performance domains. Together, these results suggest that multivariate FC patterns during both task and resting states contain rather little information on individual performance levels, calling for a reconsideration of how the brain mediates individual differences in mental abilities.

PMID:38864353 | DOI:10.1002/hbm.26753

Dose-dependent LSD effects on cortical/thalamic and cerebellar activity: brain oxygen level-dependent fMRI study in awake rats

Wed, 06/12/2024 - 18:00

Brain Commun. 2024 Jun 4;6(3):fcae194. doi: 10.1093/braincomms/fcae194. eCollection 2024.

ABSTRACT

Lysergic acid diethylamide is a hallucinogen with complex neurobiological and behavioural effects. This is the first study to use MRI to follow functional changes in brain activity in response to different doses of lysergic acid diethylamide in fully awake, drug-naive rats. We hypothesized that lysergic acid diethylamide would show a dose-dependent increase in activity in the prefrontal cortex and thalamus while decreasing hippocampal activity. Female and male rats were given intraperitoneal injections of vehicle or lysergic acid diethylamide in doses of 10 or 100 µg/kg while fully awake during the imaging session. Changes in blood oxygen level-dependent signal were recorded over a 30-min window. Approximately 45-min post-injection data for resting-state functional connectivity were collected. All data were registered to rat 3D MRI atlas with 173 brain regions providing site-specific increases and decreases in global brain activity and changes in functional connectivity. Treatment with lysergic acid diethylamide resulted in a significant dose-dependent increase in negative blood oxygen level-dependent signal. The areas most affected were the primary olfactory system, prefrontal cortex, thalamus and hippocampus. This was observed in both the number of voxels affected in these brains regions and the changes in blood oxygen level-dependent signal over time. However, there was a significant increase in functional connectivity between the thalamus and somatosensory cortex and the cerebellar nuclei and the surrounding brainstem areas. Contrary to our hypothesis, there was an acute dose-dependent increase in negative blood oxygen level-dependent signal that can be interpreted as a decrease in brain activity, a finding that agrees with much of the behavioural data from preclinical studies. The enhanced connectivity between thalamus and sensorimotor cortices is consistent with the human literature looking at lysergic acid diethylamide treatments in healthy human volunteers. The unexpected finding that lysergic acid diethylamide enhances connectivity to the cerebellar nuclei raises an interesting question concerning the role of this brain region in the psychotomimetic effects of hallucinogens.

PMID:38863575 | PMC:PMC11166175 | DOI:10.1093/braincomms/fcae194

Altered intra- and inter-network connectivity in autism spectrum disorder

Tue, 06/11/2024 - 18:00

Aging (Albany NY). 2024 Jun 10;16. doi: 10.18632/aging.205913. Online ahead of print.

ABSTRACT

OBJECTIVE: A neurodevelopmental illness termed as the autism spectrum disorder (ASD) is described by social interaction impairments. Previous studies employing resting-state functional imaging (rs-fMRI) identified both hyperconnectivity and hypoconnectivity patterns in ASD people. However, specific patterns of connectivity within and between networks linked to ASD remain largely unexplored.

METHODS: We utilized a meticulously selected subset of high-quality data, comprising 45 individuals diagnosed with ASD and 47 HCs, obtained from the ABIDE dataset. The pre-processed rs-fMRI time series signals were partitioned into ninety regions of interest. We focused on eight intrinsic connectivity networks and further performed intra- and inter-network analysis. Finally, support vector machine was used to discriminate ASD from HC.

RESULTS: Through different sparsities, ASD exhibited significantly decreased intra-network connectivity within default mode network and dorsal attention network, increased connectivity between limbic network and subcortical network, and decreased connectivity between default mode network and limbic network. Using the classifier trained on altered intra- and inter-network connectivity, multivariate pattern analyses classified the ASD from HC with 71.74% accuracy, 70.21% specificity and 75.56% sensitivity in 10% sparsity of functional connectivity.

CONCLUSIONS: ASD showed characteristic reorganization of the brain networks and this provided new insight into the underlying process of the functional connectome dysfunction in ASD.

PMID:38862259 | DOI:10.18632/aging.205913

Atypical dynamic neural configuration in autism spectrum disorder and its relationship to gene expression profiles

Tue, 06/11/2024 - 18:00

Eur Child Adolesc Psychiatry. 2024 Jun 11. doi: 10.1007/s00787-024-02476-w. Online ahead of print.

ABSTRACT

Although it is well recognized that autism spectrum disorder (ASD) is associated with atypical dynamic functional connectivity patterns, the dynamic changes in brain intrinsic activity over each time point and the potential molecular mechanisms associated with atypical dynamic temporal characteristics in ASD remain unclear. Here, we employed the Hidden Markov Model (HMM) to explore the atypical neural configuration at every scanning time point in ASD, based on resting-state functional magnetic resonance imaging (rs-fMRI) data from the Autism Brain Imaging Data Exchange. Subsequently, partial least squares regression and pathway enrichment analysis were employed to explore the potential molecular mechanism associated with atypical neural dynamics in ASD. 8 HMM states were inferred from rs-fMRI data. Compared to typically developing, individuals on the autism spectrum showed atypical state-specific temporal characteristics, including number of states and occurrences, mean life time and transition probability between states. Moreover, these atypical temporal characteristics could predict communication difficulties of ASD, and states assoicated with negative activation in default mode network and frontoparietal network, and positive activation in somatomotor network, ventral attention network, and limbic network, had higher predictive contribution. Furthermore, a total of 321 genes was revealed to be significantly associated with atypical dynamic brain states of ASD, and these genes are mainly enriched in neurodevelopmental pathways. Our study provides new insights into characterizing the atypical neural dynamics from a moment-to-moment perspective, and indicates a linkage between atypical neural configuration and gene expression in ASD.

PMID:38861168 | DOI:10.1007/s00787-024-02476-w

Altered functional connectivity of insular subregions in subjective cognitive decline

Tue, 06/11/2024 - 18:00

Front Hum Neurosci. 2024 May 27;18:1404759. doi: 10.3389/fnhum.2024.1404759. eCollection 2024.

ABSTRACT

OBJECTIVE: Recent research has highlighted the insula as a critical hub in human brain networks and the most susceptible region to subjective cognitive decline (SCD). However, the changes in functional connectivity of insular subregions in SCD patients remain poorly understood. The present study aims to clarify the altered functional connectivity patterns within insular subregions in individuals with SCD using resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS: In this study, we collected rs-fMRI data from 30 patients with SCD and 28 healthy controls (HCs). By defining three subregions of the insula, we mapped whole-brain resting-state functional connectivity (RSFC). We identified several distinct RSFC patterns of the insular subregions. Specifically, for positive connectivity, three cognitive-related RSFC patterns were identified within the insula, suggesting anterior-to-posterior functional subdivisions: (1) a dorsal anterior zone of the insula that shows RSFC with the executive control network (ECN); (2) a ventral anterior zone of the insula that shows functional connectivity with the salience network (SN); and (3) a posterior zone along the insula that shows functional connectivity with the sensorimotor network (SMN).

RESULTS: Compared to the controls, patients with SCD exhibited increased positive RSFC to the sub-region of the insula, demonstrating compensatory plasticity. Furthermore, these abnormal insular subregion RSFCs are closely correlated with cognitive performance in the SCD patients.

CONCLUSION: Our findings suggest that different insular subregions exhibit distinct patterns of RSFC with various functional networks, which are affected differently in patients with SCD.

PMID:38859994 | PMC:PMC11163085 | DOI:10.3389/fnhum.2024.1404759

Salience Network Segregation Mediates the Effect of Tau Pathology on Mild Behavioral Impairment

Mon, 06/10/2024 - 18:00

medRxiv [Preprint]. 2024 May 27:2024.05.26.24307943. doi: 10.1101/2024.05.26.24307943.

ABSTRACT

INTRODUCTION: A recently developed mild behavioral impairment (MBI) diagnostic framework standardizes the early characterization of neuropsychiatric symptoms in older adults. However, the links between MBI, brain function, and Alzheimer's disease (AD) biomarkers are unclear.

METHODS: Using data from 128 participants with diagnosis of amnestic mild cognitive impairment and mild dementia - Alzheimer's type, we test a novel model assessing direct relationships between AD biomarker status and MBI symptoms, as well as mediated effects through segregation of the salience and default-mode networks.

RESULTS: We identified a mediated effect of tau positivity on MBI through functional segregation of the salience network from the other high-level, association networks. There were no direct effects of AD biomarkers status on MBI.

DISCUSSION: Our findings suggest an indirect role of tau pathology in MBI through brain network dysfunction and emphasize the role of the salience network in mediating relationships between neuropathological changes and behavioral manifestations.

PMID:38854100 | PMC:PMC11160832 | DOI:10.1101/2024.05.26.24307943

Delineating the Heterogeneity of Alzheimer's Disease and Mild Cognitive Impairment Using Normative Models of the Dynamic Brain Functional Networks

Mon, 06/10/2024 - 18:00

Biol Psychiatry. 2024 Jun 8:S0006-3223(24)01365-9. doi: 10.1016/j.biopsych.2024.05.025. Online ahead of print.

ABSTRACT

BACKGROUND: Alzheimer's Disease (AD), identified as the most common type of dementia, presents considerable heterogeneity in clinical manifestations. Early intervention at the stage of mild cognitive impairment (MCI) holds potential in AD prevention. However, characterizing the heterogeneity of neurobiological abnormalities and identifying MCI subtypes pose significant challenges.

METHODS: We constructed sex-specific normative age models of dynamic brain functional networks and mapped the deviations of the brain characteristics for individuals from multiple datasets, including 295 AD patients, 441 MCI patients, and 1160 normal controls (NC). Then, based on these individual deviation patterns, subtypes for both AD and MCI were identified using the clustering method and comprehensively assessed their similarity and differences.

RESULTS: Individuals with AD and MCI were clustered into 2 subtypes, and these subtypes exhibited significant differences in both their intrinsic brain functional phenotypes and spatial atrophy patterns, as well as in disease progression and cognitive decline trajectories. The subtypes with positive deviations in AD and MCI shared similar deviation patterns, as well as those with negative deviations. There was a potential transformation of MCI with negative deviation patterns into AD, and these MCI have a more severe cognitive decline rate.

CONCLUSIONS: This study quantifies neurophysiological heterogeneity by analyzing deviation patterns from the dynamic functional connectome normative model and identifies disease subtypes in AD and MCI using a comprehensive resting-state fMRI multicenter dataset. It provides new insights for developing early prevention and personalized treatment strategies for AD.

PMID:38857821 | DOI:10.1016/j.biopsych.2024.05.025

Longitudinal neurofunctional changes in medication overuse headache patients after mindfulness practice in a randomized controlled trial (the MIND-CM study)

Mon, 06/10/2024 - 18:00

J Headache Pain. 2024 Jun 11;25(1):97. doi: 10.1186/s10194-024-01803-5.

ABSTRACT

BACKGROUND: Mindfulness practice has gained interest in the management of Chronic Migraine associated with Medication Overuse Headache (CM-MOH). Mindfulness is characterized by present-moment self-awareness and relies on attention control and emotion regulation, improving headache-related pain management. Mindfulness modulates the Default Mode Network (DMN), Salience Network (SN), and Fronto-Parietal Network (FPN) functional connectivity. However, the neural mechanisms underlying headache-related pain management with mindfulness are still unclear. In this study, we tested neurofunctional changes after mindfulness practice added to pharmacological treatment as usual in CM-MOH patients.

METHODS: The present study is a longitudinal phase-III single-blind Randomized Controlled Trial (MIND-CM study; NCT03671681). Patients had a diagnosis of CM-MOH, no history of neurological and severe psychiatric comorbidities, and were attending our specialty headache centre. Patients were divided in Treatment as Usual (TaU) and mindfulness added to TaU (TaU + MIND) groups. Patients underwent a neuroimaging and clinical assessment before the treatment and after one year. Longitudinal comparisons of DMN, SN, and FPN connectivity were performed between groups and correlated with clinical changes. Vertex-wise analysis was performed to assess cortical thickness changes.

RESULTS: 177 CM-MOH patients were randomized to either TaU group or TaU + MIND group. Thirty-four patients, divided in 17 TaU and 17 TaU + MIND, completed the neuroimaging follow-up. At the follow-up, both groups showed an improvement in most clinical variables, whereas only TaU + MIND patients showed a significant headache frequency reduction (p = 0.028). After one year, TaU + MIND patients showed greater SN functional connectivity with the left posterior insula (p-FWE = 0.007) and sensorimotor cortex (p-FWE = 0.026). In TaU + MIND patients only, greater SN-insular connectivity was associated with improved depression scores (r = -0.51, p = 0.038). A longitudinal increase in cortical thickness was observed in the insular cluster in these patients (p = 0.015). Increased anterior cingulate cortex thickness was also reported in TaU + MIND group (p-FWE = 0.02).

CONCLUSIONS: Increased SN-insular connectivity might modulate chronic pain perception and the management of negative emotions. Enhanced SN-sensorimotor connectivity could reflect improved body-awareness of painful sensations. Expanded cingulate cortex thickness might sustain improved cognitive processing of nociceptive information. Our findings unveil the therapeutic potential of mindfulness and the underlying neural mechanisms in CM-MOH patients.

TRIAL REGISTRATION: Name of Registry; MIND-CM study; Registration Number ClinicalTrials.gov identifier: NCT0367168; Registration Date: 14/09/2018.

PMID:38858629 | DOI:10.1186/s10194-024-01803-5