New resting-state fMRI related studies at PubMed

High-order Brain Networks Abnormalities in Osteonecrosis of the Femoral Head Patients: An Independent Component Analysis of Resting-state fMRI

Fri, 01/06/2023 - 11:00

Pain Physician. 2022 Dec;25(9):E1475-E1484.

ABSTRACT

BACKGROUND: Patients with osteonecrosis of the femoral head commonly present with sensorimotor anomalies. With independent component analysis, it is possible to explore the intrinsic alternations in highly specific functional networks. We used independent component analysis to examine the intrinsic changes and interactive connectivity between related functional resting-state networks.

OBJECTIVE: The purpose of this study was to strengthen the theoretical basis of brain plasticity after osteonecrosis of the femoral head to provide new insights into clinical treatment.

STUDY DESIGN: Observational study.

SETTING: School of rehabilitation science of a university.

METHODS: Functional magnetic resonance imaging data were acquired from 14 patients with osteonecrosis of the femoral head and 20 healthy controls. All the data underwent preprocessing and analysis of the intrinsic brain functional connectivity within and between resting-state networks.

RESULTS: Nine resting-state networks were identified via independent component analysis. When compared to healthy controls, the osteonecrosis of the femoral head patients showed abnormal activity in these networks. With respect to the internetwork interactions, increased functional connectivity was detected between the sensorimotor network and right frontoparietal network and between the dorsal attention network and frontoparietal network bilaterally.

LIMITATIONS: This study was a cross-sectional design. A longitudinal study of the dynamic changes in multinetwork functional connectivity can help to elucidate the central mechanisms of osteonecrosis of the femoral head.

CONCLUSIONS: This study investigated the alterations in resting-state network functional connectivity in osteonecrosis of the femoral head patients. Examining the large-scale functional reorganization in osteonecrosis of the femoral head patients may be helpful for us to understand the pathological mechanisms underlying dysfunction and shed light on potential behavioral treatments for osteonecrosis of the femoral head based on functional magnetic resonance imaging in clinical practice. Understanding the mechanisms of the disease may shed light on potential behavioral treatments for patients with osteonecrosis of the femoral head based on functional magnetic resonance imaging findings.

PMID:36608019

Changes in resting state networks in high school football athletes across a single season

Fri, 01/06/2023 - 11:00

Br J Radiol. 2023 Jan 6:20220359. doi: 10.1259/bjr.20220359. Online ahead of print.

ABSTRACT

OBJECTIVES: The aim of this pilot cohort study was to examine changes in the organization of resting-state brain networks in high school football athletes and its relationship to exposure to on-field head impacts over the course of a single season.

METHODS: 17 male high school football players underwent functional magnetic resonance imaging (fMRI) and computerized neurocognitive testing (CNS Vital Signs) before the start of contact practices and again after the conclusion of the season. The players were equipped with helmet accelerometer systems (Head Impact Telemetry System) to record head impacts in practices and games. Graph theory analysis was applied to study intra network local efficiency and strength of connectivity within six anatomically defined brain networks.

RESULTS: We observed a significant decrease in the local efficiency (-24.9 ± 51.4%, r = 0.7, p < 0.01) and strength (-14.5 ± 26.8%, r = 0.5, p < 0.01) of functional connectivity within the frontal lobe resting-state network and strength within the parietal lobe resting-state network (-7.5 ± 17.3%, r = 0.1, p < 0.01), as well as a concomitant increase in the local efficiency (+55.0 +/- 59.8%, r = 0.5, p < 0.01) and strength (+47.4 +/- 47.3%, r = 0.5, p < 0.01) within the mediotemporal networks. These alterations in network organization were associated with changes in performance on verbal memory (p < 0.05) and executive function (p < 0.05). We did not observe a significant relationship between the frequency or cumulative magnitude of impacts sustained during the season and neurocognitive or imaging outcomes (p > 0.05).

CONCLUSIONS: Our findings suggest the efficiency and strength of resting-state networks are altered across a season of high school football, but the association of exposure levels to subconcussive impacts is unclear.

ADVANCES IN KNOWLEDGE: The efficiency of resting-state networks is dynamic in high school football athletes; such changes may be related to impacts sustained during the season, although further study is needed.

PMID:36607807 | DOI:10.1259/bjr.20220359

Hyperbolic disc embedding of functional human brain connectomes using resting-state fMRI

Fri, 01/06/2023 - 11:00

Netw Neurosci. 2022 Jul 1;6(3):745-764. doi: 10.1162/netn_a_00243. eCollection 2022 Jul.

ABSTRACT

The brain presents a real complex network of modular, small-world, and hierarchical nature, which are features of non-Euclidean geometry. Using resting-state functional magnetic resonance imaging, we constructed a scale-free binary graph for each subject, using internodal time series correlation of regions of interest as a proximity measure. The resulting network could be embedded onto manifolds of various curvatures and dimensions. While maintaining the fidelity of embedding (low distortion, high mean average precision), functional brain networks were found to be best represented in the hyperbolic disc. Using the

Functional Network Alterations Associated with Cognition in Preclinical Alzheimer's Disease

Fri, 01/06/2023 - 11:00

Brain Connect. 2023 Jan 6. doi: 10.1089/brain.2022.0032. Online ahead of print.

ABSTRACT

OBJECTIVE: Accumulation of cerebral amyloid-β (Aβ) is a risk factor for cognitive decline and defining feature of Alzheimer's disease (AD). Aβ is implicated in brain network disruption, but the extent to which these changes correspond with observable cognitive deficits in preclinical AD has not been tested. This study utilized individual-specific functional parcellations to sensitively evaluate the relationship between network connectivity and cognition in adults with and without Aβ deposition.

PARTICIPANTS AND METHODS: Cognitively unimpaired adults ages 45-85 completed amyloid PET, resting-state-fMRI, and neuropsychological tests of episodic memory and executive function. Participants in the upper tertile of mSUVr were considered Aβ+ (n = 50) while others were Aβ- (n = 99). Individualized functional network parcellations were generated from resting-state fMRI data. We examined the effects of group, network, and group-by-network interactions on memory and executive function.

RESULTS: We observed several interactions such that within the Aβ+ group, preserved network integrity (i.e., greater connectivity within specific networks) was associated with better cognition, whereas network desegregation (i.e., greater connectivity between relative to within networks) was associated with worse cognition. This dissociation was most apparent for cognitive networks (frontoparietal, dorsal and ventral attention, limbic, and default mode), with connectivity relating to executive function in the Aβ+ group specifically.

CONCLUSIONS: Using an innovative approach to constructing individual-specified resting-state functional connectomes, we were able to detect differences in brain-cognition associations in preclinical AD. Our findings provide novel insight into specific functional network alterations occurring in the presence of Aβ that relate to cognitive function in asymptomatic individuals.

PMID:36606679 | DOI:10.1089/brain.2022.0032

Probing the association between resting-state brain network dynamics and psychological resilience

Fri, 01/06/2023 - 11:00

Netw Neurosci. 2022 Feb 1;6(1):175-195. doi: 10.1162/netn_a_00216. eCollection 2022 Feb.

ABSTRACT

This study aimed at replicating a previously reported negative correlation between node flexibility and psychological resilience, that is, the ability to retain mental health in the face of stress and adversity. To this end, we used multiband resting-state BOLD fMRI (TR = .675 sec) from 52 participants who had filled out three psychological questionnaires assessing resilience. Time-resolved functional connectivity was calculated by performing a sliding window approach on averaged time series parcellated according to different established atlases. Multilayer modularity detection was performed to track network reconfigurations over time, and node flexibility was calculated as the number of times a node changes community assignment. In addition, node promiscuity (the fraction of communities a node participates in) and node degree (as proxy for time-varying connectivity) were calculated to extend previous work. We found no substantial correlations between resilience and node flexibility. We observed a small number of correlations between the two other brain measures and resilience scores that were, however, very inconsistently distributed across brain measures, differences in temporal sampling, and parcellation schemes. This heterogeneity calls into question the existence of previously postulated associations between resilience and brain network flexibility and highlights how results may be influenced by specific analysis choices.

PMID:36605891 | PMC:PMC9810279 | DOI:10.1162/netn_a_00216

Connectomic analysis of Alzheimer's disease using percolation theory

Fri, 01/06/2023 - 11:00

Netw Neurosci. 2022 Feb 1;6(1):213-233. doi: 10.1162/netn_a_00221. eCollection 2022 Feb.

ABSTRACT

Alzheimer's disease (AD) is a severe neurodegenerative disorder that affects a growing worldwide elderly population. Identification of brain functional biomarkers is expected to help determine preclinical stages for targeted mechanistic studies and development of therapeutic interventions to deter disease progression. Connectomic analysis, a graph theory-based methodology used in the analysis of brain-derived connectivity matrices was used in conjunction with percolation theory targeted attack model to investigate the network effects of AD-related amyloid deposition. We used matrices derived from resting-state functional magnetic resonance imaging collected on mice with extracellular amyloidosis (TgCRND8 mice, n = 17) and control littermates (n = 17). Global, nodal, spatial, and percolation-based analysis was performed comparing AD and control mice. These data indicate a short-term compensatory response to neurodegeneration in the AD brain via a strongly connected core network with highly vulnerable or disconnected hubs. Targeted attacks demonstrated a greater vulnerability of AD brains to all types of attacks and identified progression models to mimic AD brain functional connectivity through betweenness centrality and collective influence metrics. Furthermore, both spatial analysis and percolation theory identified a key disconnect between the anterior brain of the AD mice to the rest of the brain network.

PMID:36605889 | PMC:PMC9810282 | DOI:10.1162/netn_a_00221

Altered large-scale brain network interactions associated with HIV infection and error processing

Fri, 01/06/2023 - 11:00

Netw Neurosci. 2022 Jul 1;6(3):791-815. doi: 10.1162/netn_a_00241. eCollection 2022 Jul.

ABSTRACT

Altered activity within and between large-scale brain networks has been implicated across various neuropsychiatric conditions. However, patterns of network dysregulation associated with human immunodeficiency virus (HIV), and further impacted by cannabis (CB) use, remain to be delineated. We examined the impact of HIV and CB on resting-state functional connectivity (rsFC) between brain networks and associations with error awareness and error-related network responsivity. Participants (N = 106), stratified into four groups (HIV+/CB+, HIV+/CB-, HIV-/CB+, HIV-/CB-), underwent fMRI scanning while completing a resting-state scan and a modified Go/NoGo paradigm assessing brain responsivity to errors and explicit error awareness. We examined separate and interactive effects of HIV and CB on resource allocation indexes (RAIs), a measure quantifying rsFC strength between the default mode network (DMN), central executive network (CEN), and salience network (SN). We observed reduced RAIs among HIV+ (vs. HIV-) participants, which was driven by increased SN-DMN rsFC. No group differences were detected for SN-CEN rsFC. Increased SN-DMN rsFC correlated with diminished error awareness, but not with error-related network responsivity. These outcomes highlight altered network interactions among participants with HIV and suggest such rsFC dysregulation may persist during task performance, reflecting an inability to disengage irrelevant mental operations, ultimately hindering error processing.

PMID:36605414 | PMC:PMC9810366 | DOI:10.1162/netn_a_00241

Applying multilayer analysis to morphological, structural, and functional brain networks to identify relevant dysfunction patterns

Fri, 01/06/2023 - 11:00

Netw Neurosci. 2022 Jul 1;6(3):916-933. doi: 10.1162/netn_a_00258. eCollection 2022 Jul.

ABSTRACT

In recent years, research on network analysis applied to MRI data has advanced significantly. However, the majority of the studies are limited to single networks obtained from resting-state fMRI, diffusion MRI, or gray matter probability maps derived from T1 images. Although a limited number of previous studies have combined two of these networks, none have introduced a framework to combine morphological, structural, and functional brain connectivity networks. The aim of this study was to combine the morphological, structural, and functional information, thus defining a new multilayer network perspective. This has proved advantageous when jointly analyzing multiple types of relational data from the same objects simultaneously using graph- mining techniques. The main contribution of this research is the design, development, and validation of a framework that merges these three layers of information into one multilayer network that links and relates the integrity of white matter connections with gray matter probability maps and resting-state fMRI. To validate our framework, several metrics from graph theory are expanded and adapted to our specific domain characteristics. This proof of concept was applied to a cohort of people with multiple sclerosis, and results show that several brain regions with a synchronized connectivity deterioration could be identified.

PMID:36605412 | PMC:PMC9810367 | DOI:10.1162/netn_a_00258

Changes in Resting-State Neural Activity and Nerve Fibres in Ischaemic Stroke Patients with Hemiplegia

Thu, 01/05/2023 - 11:00

Brain Topogr. 2023 Jan 5. doi: 10.1007/s10548-022-00937-6. Online ahead of print.

ABSTRACT

Many neuroimaging studies have reported that stroke induces abnormal brain activity. However, little is known about resting-state networks (RSNs) and the corresponding white matter changes in stroke patients with hemiplegia. Here, we utilized functional magnetic resonance imaging (fMRI) to measure neural activity and related fibre tracts in 14 ischaemic stroke patients with hemiplegia and 12 healthy controls. Fractional amplitude of low-frequency fluctuations (fALFF) calculation and correlation analyses were used to assess the relationship between regional neural activity and movement scores. Tractography was performed using diffusion tensor imaging (DTI) data to analyse the fibres passing through the regions of interest. Compared with controls, stroke patients showed abnormal functional connectivity (FC) between some brain regions in the RSNs. The fALFF was increased in the contralesional parietal lobe, with the regional fALFF being correlated with behavioural scores in stroke patients. Additionally, the passage of fibres across regions with reduced FC in the RSNs was increased in stroke patients. This study suggests that structural remodelling of functionally relevant white matter tracts is probably an adaptive response that compensates for injury to the brain.

PMID:36604349 | DOI:10.1007/s10548-022-00937-6

Effects of bilateral sequential theta-burst stimulation on functional connectivity in treatment-resistant depression: First results

Thu, 01/05/2023 - 11:00

J Affect Disord. 2023 Jan 2:S0165-0327(22)01448-3. doi: 10.1016/j.jad.2022.12.088. Online ahead of print.

ABSTRACT

BACKGROUND: Previous studies suggest that transcranial magnetic stimulation exerts antidepressant effects by altering functional connectivity (FC). However, knowledge about this mechanism is still limited. Here, we aimed to investigate the effect of bilateral sequential theta-burst stimulation (TBS) on FC in treatment-resistant depression (TRD) in a sham-controlled longitudinal study.

METHODS: TRD patients (n = 20) underwent a three-week treatment of intermittent TBS of the left and continuous TBS of the right dorsolateral prefrontal cortex (DLPFC). Upon this trial's premature termination, 15 patients had received active TBS and five patients sham stimulation. Resting-state functional magnetic resonance imaging was performed at baseline and after treatment. FC (left and right DLPFC) was estimated for each participant, followed by group statistics (t-tests). Furthermore, depression scores were analyzed (linear mixed models analysis) and tested for correlation with FC.

RESULTS: Both groups exhibited reductions of depression scores, however, there was no significant main effect of group, or group and time. Anticorrelations between DLPFC and the subgenual cingulate cortex (sgACC) were observed for baseline FC, corresponding to changes in depression severity. Treatment did not significantly change DLPFC-sgACC connectivity, but significantly reduced FC between the left stimulation target and bilateral anterior insula.

CONCLUSIONS: Our data is compatible with previous reports on the relevance of anticorrelation between DLPFC and sgACC for treatment success. Furthermore, FC changes between left DLPFC and bilateral anterior insula highlight the effect of TBS on the salience network.

LIMITATIONS: Due to the limited sample size, results should be interpreted with caution and are of exploratory nature.

PMID:36603604 | DOI:10.1016/j.jad.2022.12.088

Cerebral perfusion alterations in patients with trigeminal neuralgia as measured by pseudo-continuous arterial spin labeling

Thu, 01/05/2023 - 11:00

Front Neurosci. 2022 Dec 16;16:1065411. doi: 10.3389/fnins.2022.1065411. eCollection 2022.

ABSTRACT

BACKGROUND: Accumulating evidence suggests that trigeminal neuralgia (TN) causes structural and functional alterations in the brain. However, only a few studies have focused on cerebral blood flow (CBF) changes in patients with TN. This study aimed to explore whether altered cerebral perfusion patterns exist in patients with TN and investigate the relationship between abnormal regional CBF (rCBF) and clinical characteristics of TN.

MATERIALS AND METHODS: This study included 28 patients with TN and 30 age- and sex-matched healthy controls (HCs) who underwent perfusion functional MRI (fMRI) of the brain using pseudo-continuous arterial spin labeling (pCASL) in the resting state. The regions of significantly altered CBF in patients with TN were detected using group comparison analyses. Then, the relationships between the clinical characteristics and abnormal rCBF were further investigated.

RESULTS: Compared to the control group, patients with TN exhibited increased rCBF, primarily in the thalamus, middle frontal gyrus (MFG), and left insula. Furthermore, the CBF values of the thalamus were negatively correlated with the pain intensity of TN and positively correlated with pain duration in patients with TN.

CONCLUSION: Primary alterations in rCBF in patients with TN occurred in different brain regions related to pain, which are involved in cognitive-affective interaction, pain perception, and pain modulation. These results indicate that non-invasive resting cerebral perfusion imaging may contribute complementary information to further understanding the neuropathological mechanism underlying TN.

PMID:36601595 | PMC:PMC9807247 | DOI:10.3389/fnins.2022.1065411

Confounds in neuroimaging: A clear case of sex as a confound in brain-based prediction

Thu, 01/05/2023 - 11:00

Front Neurol. 2022 Dec 19;13:960760. doi: 10.3389/fneur.2022.960760. eCollection 2022.

ABSTRACT

Muscle weakness is common in many neurological, neuromuscular, and musculoskeletal conditions. Muscle size only partially explains muscle strength as adaptions within the nervous system also contribute to strength. Brain-based biomarkers of neuromuscular function could provide diagnostic, prognostic, and predictive value in treating these disorders. Therefore, we sought to characterize and quantify the brain's contribution to strength by developing multimodal MRI pipelines to predict grip strength. However, the prediction of strength was not straightforward, and we present a case of sex being a clear confound in brain decoding analyses. While each MRI modality-structural MRI (i.e., gray matter morphometry), diffusion MRI (i.e., white matter fractional anisotropy), resting state functional MRI (i.e., functional connectivity), and task-evoked functional MRI (i.e., left or right hand motor task activation)-and a multimodal prediction pipeline demonstrated significant predictive power for strength (R 2 = 0.108-0.536, p ≤ 0.001), after correcting for sex, the predictive power was substantially reduced (R 2 = -0.038-0.075). Next, we flipped the analysis and demonstrated that each MRI modality and a multimodal prediction pipeline could significantly predict sex (accuracy = 68.0%-93.3%, AUC = 0.780-0.982, p < 0.001). However, correcting the brain features for strength reduced the accuracy for predicting sex (accuracy = 57.3%-69.3%, AUC = 0.615-0.780). Here we demonstrate the effects of sex-correlated confounds in brain-based predictive models across multiple brain MRI modalities for both regression and classification models. We discuss implications of confounds in predictive modeling and the development of brain-based MRI biomarkers, as well as possible strategies to overcome these barriers.

PMID:36601297 | PMC:PMC9806266 | DOI:10.3389/fneur.2022.960760

Atypical local brain connectivity in pediatric autism spectrum disorder? A coordinate-based meta-analysis of regional homogeneity studies

Wed, 01/04/2023 - 11:00

Eur Arch Psychiatry Clin Neurosci. 2023 Jan 4. doi: 10.1007/s00406-022-01541-2. Online ahead of print.

ABSTRACT

Despite decades of massive neuroimaging research, the comprehensive characterization of short-range functional connectivity in autism spectrum disorder (ASD) remains a major challenge for scientific advances and clinical translation. From the theoretical point of view, it has been suggested a generalized local over-connectivity that would characterize ASD. This stance is known as the general local over-connectivity theory. However, there is little empirical evidence supporting such hypothesis, especially with regard to pediatric individuals with ASD (age [Formula: see text] 18 years old). To explore this issue, we performed a coordinate-based meta-analysis of regional homogeneity studies to identify significant changes of local connectivity. Our analyses revealed local functional under-connectivity patterns in the bilateral posterior cingulate cortex and superior frontal gyrus (key components of the default mode network) and in the bilateral paracentral lobule (a part of the sensorimotor network). We also performed a functional association analysis of the identified areas, whose dysfunction is clinically consistent with the well-known deficits affecting individuals with ASD. Importantly, we did not find relevant clusters of local hyper-connectivity, which is contrary to the hypothesis that ASD may be characterized by generalized local over-connectivity. If confirmed, our result will provide a valuable insight into the understanding of the complex ASD pathophysiology.

PMID:36599959 | DOI:10.1007/s00406-022-01541-2

Altered functional connectivity of anterior cingulate cortex in chronic insomnia: A resting-state fMRI study

Wed, 01/04/2023 - 11:00

Sleep Med. 2022 Dec 5;102:46-51. doi: 10.1016/j.sleep.2022.11.036. Online ahead of print.

ABSTRACT

The aim of our present study was to explore the connectivity pattern change between the anterior cingulate cortex (ACC) and the voxels from the whole brain in chronic insomnia (CI). With region of interest (ROI)-based functional connectivity, a two-sample t-test was performed on individual FC correlation maps from two groups based on the resting-state fMRI data acquired from 57 CI patients and 46 healthy controls (GRF correction, voxel-level P < 0.001 and cluster-level P < 0.001). A correlation analysis was performed to evaluate the relationship between the clinical features and the abnormal FC. Compared to the healthy controls, the CI patients show increased connectivity between the ACC and the right middle frontal gyrus, with decreased connectivity between the ACC and the bilateral precuneus gyrus. Correlation analysis indicated that the decreased connectivity showed positive correlations with Self-Rating Anxiety Scale (SAS) scores. Our study shows the alterations of CI patients in the level of functional integration and may indicate the dysfunction of communication within brain regions of the default mode network (DMN). These changes and their correlation with negative emotions may provide additional evidence to understand the possible neural mechanisms of CI.

PMID:36599195 | DOI:10.1016/j.sleep.2022.11.036

Implementation of Automated Pipeline for Resting-State fMRI Analysis with PACS Integration

Tue, 01/03/2023 - 11:00

J Digit Imaging. 2023 Jan 3. doi: 10.1007/s10278-022-00758-w. Online ahead of print.

ABSTRACT

In recent years, the quantity and complexity of medical imaging acquisition and processing have increased tremendously. The explosion in volume and need for advanced imaging analysis have led to the creation of numerous software programs, which have begun to be incorporated into clinical practice for indications such as automated stroke assessment, brain tumor perfusion processing, and hippocampal volume analysis. Despite these advances, there remains a need for specialized, custom-built software for advanced algorithms and new areas of research that is not widely available or adequately integrated in these "out-of-the-box" solutions. The purpose of this paper is to describe the implementation of an image-processing pipeline that is versatile and simple to create, which allows for rapid prototyping of image analysis algorithms and subsequent testing in a clinical environment. This pipeline uses a combination of Orthanc server, custom MATLAB code, and publicly available FMRIB Software Library and RestNeuMap tools to automatically receive and analyze resting-state functional MRI data collected from a custom filter on the MR scanner output. The processed files are then sent directly to Picture Archiving and Communications System (PACS) without the need for user input. This initial experience can serve as a framework for those interested in simple implementation of an automated pipeline customized to clinical needs.

PMID:36596936 | DOI:10.1007/s10278-022-00758-w

Pulvinar Response Profiles and Connectivity Patterns to Object Domains

Tue, 01/03/2023 - 11:00

J Neurosci. 2023 Jan 3:JN-RM-0613-22. doi: 10.1523/JNEUROSCI.0613-22.2022. Online ahead of print.

ABSTRACT

Distributed cortical regions show differential responses to visual objects belonging to different domains varying by animacy (e.g., animals vs tools), yet it remains unclear whether this is an organization principle also applying to the subcortical structures. Combining multiple fMRI activation experiments (two main experiments and six validation datasets; 12 females and 9 males in the main Experiment 1; 10 females and 10 males in the main Experiment 2), resting-state functional connectivity, and task-based dynamic causal modeling analysis in human subjects, we found that visual processing of images of animals and tools elicited different patterns of response in the pulvinar, with robust left lateralization for tools, and distinct, bilateral (with rightward tendency) clusters for animals. Such domain-preferring activity distribution in the pulvinar was associated with the magnitude with which the voxels were intrinsically connected with the corresponding domain-preferring regions in the cortex. The pulvinar-to-right-amygdala path showed a one-way shortcut supporting the perception of animals, and the modulation connection from pulvinar to parietal showed an advantage to the perception of tools. These results incorporate the subcortical regions into the object processing network and highlight that domain organization appears to be an overarching principle across various processing stages in the brain.Significance Statement:Viewing objects belonging to different domains elicited different cortical regions, but whether the domain organization applied to the subcortical structures (e.g., pulvinar) was unknown. Multiple fMRI activation experiments revealed that object pictures belonging to different domains elicited differential patterns of response in the pulvinar, with robust left lateralization for tool pictures, and distinct, bilateral (with rightward tendency) clusters for animals. Combining the resting-state functional connectivity and dynamic causal modeling analysis on task-based fMRI data, we found domain-preferring activity distribution in the pulvinar aligned with that in cortical regions. These results highlight the need for coherent visual theories that explain the mechanisms underlying the domain organization across various processing stages.

PMID:36596697 | DOI:10.1523/JNEUROSCI.0613-22.2022

Altered regional homogeneity and its association with cognitive function in adolescents with borderline personality disorder

Tue, 01/03/2023 - 11:00

J Psychiatry Neurosci. 2023 Jan 3;48(1):E1-E10. doi: 10.1503/jpn.220144. Print 2023 Jan-Feb.

ABSTRACT

BACKGROUND: Adolescents with borderline personality disorder often have cognitive impairment, but the underlying mechanism for this is not clear. This study was aimed at assessing alterations in regional homogeneity using resting-state functional MRI (fMRI) in adolescents with borderline personality disorder, and evaluating the associations between regional homogeneity and cognitive testing scores.

METHODS: We enrolled 50 adolescents with borderline personality disorder (age 12-17 years) and 21 age- and sex-matched healthy controls. We performed regional homogeneity and seed-based functional connectivity analysis for both groups. We also performed correlative analysis for regional homogeneity and cognitive testing scores.

RESULTS: Compared with healthy controls, adolescents with borderline personality disorder had reduced regional homogeneity values in the frontal cortex (including the left inferior orbitofrontal cortex and the bilateral superior frontal cortex) as well as in the left precuneus in the default mode network. Adolescents with borderline personality disorder also had higher regional homogeneity values in several cortical regions: the right middle temporal gyrus, the right cuneus, the right precentral gyrus and the left middle occipital gyrus. Regional homogeneity values in the left middle occipital gyrus, left inferior orbitofrontal cortex and right superior frontal gyrus were associated with cognitive testing scores in adolescents with borderline personality disorder. We also found increased functional connectivity between the left middle occipital gyrus and right superior frontal gyrus in adolescents with borderline personality disorder.

LIMITATIONS: This study had a modest sample size, with a possible case selection bias for patients with more severe illness. This cohort also included patients with comorbidities or taking psychotropic medications, which may have confounded study results.

CONCLUSION: Alterations in regional homogeneity and functional connectivity in brain regions that involve the limbic-cortical circuit could be neural correlates for cognitive impairment in adolescents with borderline personality disorder.

PMID:36596589 | DOI:10.1503/jpn.220144

Altered connectivity of default mode and executive control networks among female patients with persistent post-concussion symptoms

Tue, 01/03/2023 - 11:00

Brain Inj. 2023 Jan 3:1-12. doi: 10.1080/02699052.2022.2163290. Online ahead of print.

ABSTRACT

OBJECTIVE: To examine the roles of the default mode network (DMN) and executive control network (ECN) in prolonged recovery after mild traumatic brain injury (mTBI), and relationships with indices of white matter microstructural injury.

METHODS: Seventeen mTBI patients with persistent symptoms were imaged an average of 21.5 months post-injury, along with 23 healthy controls. Resting-state functional magnetic resonance imaging (rs-fMRI) was used to evaluate functional connectivity (FC) of the DMN and ECN. Diffusion tensor imaging (DTI) quantified fractional anisotropy, along with mean, axial and radial diffusivity of white matter tracts.

RESULTS: Compared to controls, patients with mTBI had increased functional connectivity of the DMN and ECN to brain regions implicated in salience and frontoparietal networks, and increased white matter diffusivity within the cerebrum and brainstem. Among the patients, FC was correlated with better neurocognitive test scores, while diffusivity was correlated with more severe self-reported symptoms. The FC and diffusivity values within abnormal brain regions were not significantly correlated.

CONCLUSION: For female mTBI patients with prolonged symptoms, hyper-connectivity may represent a compensatory response that helps to mitigate the effects of mTBI on cognition. These effects are unrelated to indices of microstructural injury, which are correlated with symptom severity, suggesting that rs-fMRI and DTI may capture distinct aspects of pathophysiology.

PMID:36594665 | DOI:10.1080/02699052.2022.2163290

Distinct profiles of functional connectivity density aberrance in Alzheimer's disease and mild cognitive impairment

Mon, 01/02/2023 - 11:00

Front Psychiatry. 2022 Dec 15;13:1079149. doi: 10.3389/fpsyt.2022.1079149. eCollection 2022.

ABSTRACT

INTRODUCTION: Investigating the neuroimaging changes from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is of great significance. However, the details about the distinct functional characteristics of AD and MCI remain unknown.

METHODS: In this study, we investigated distinct profiles of functional connectivity density (FCD) differences between AD and MCI compared with the normal population, aiming to depict the progressive brain changes from MCI to AD. As a data-driven method, FCD measures the profiles of FC for the given voxel at different scales. Resting-state functional magnetic resonance imaging (fMRI) images were obtained from patients with AD and MCI and matched healthy controls (HCs). One-way ANCOVA was used to investigate (global, long-range, and local) FCD differences among the three groups followed by post-hoc analysis controlling age, sex, and head motion.

RESULTS: The three groups exhibited significant global FCD differences in the superior frontal gyrus. The post-hoc results further showed that patients with AD had a significant increase in global FCD values than those with MCI and HCs. Patients with MCI exhibited an increased trend compared with HCs. We further identified brain regions contributing to the observed global FCD differences by conducting seed-based FC analysis. We also identified that the observed global FCD differences were the additive effects of altered FC between the superior frontal gyrus and the posterior default model network.

DISCUSSION: These results depicted the global information communication capability impairment in AD and MCI providing a new insight into the progressive brain changes from MCI to AD.

PMID:36590612 | PMC:PMC9797864 | DOI:10.3389/fpsyt.2022.1079149

Multi-band network fusion for Alzheimer's disease identification with functional MRI

Mon, 01/02/2023 - 11:00

Front Psychiatry. 2022 Dec 15;13:1070198. doi: 10.3389/fpsyt.2022.1070198. eCollection 2022.

ABSTRACT

INTRODUCTION: The analysis of functional brain networks (FBNs) has become a promising and powerful tool for auxiliary diagnosis of brain diseases, such as Alzheimer's disease (AD) and its prodromal stage. Previous studies usually estimate FBNs using full band Blood Oxygen Level Dependent (BOLD) signal. However, a single band is not sufficient to capture the diagnostic and prognostic information contained in multiple frequency bands.

METHOD: To address this issue, we propose a novel multi-band network fusion framework (MBNF) to combine the various information (e.g., the diversification of structural features) of multi-band FBNs. We first decompose the BOLD signal adaptively into two frequency bands named high-frequency band and low-frequency band by the ensemble empirical mode decomposition (EEMD). Then the similarity network fusion (SNF) is performed to blend two networks constructed by two frequency bands together into a multi-band fusion network. In addition, we extract the features of the fused network towards a better classification performance.

RESULT: To verify the validity of the scheme, we conduct our MBNF method on the public ADNI database for identifying subjects with AD/MCI from normal controls.

DISCUSSION: Experimental results demonstrate that the proposed scheme extracts rich multi-band network features and biomarker information, and also achieves better classification accuracy.

PMID:36590604 | PMC:PMC9798220 | DOI:10.3389/fpsyt.2022.1070198

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