Most recent paper

Physical activity intensity is associated with cognition and functional connectivity in Parkinson's disease

Mon, 10/03/2022 - 18:00

Parkinsonism Relat Disord. 2022 Sep 24;104:7-14. doi: 10.1016/j.parkreldis.2022.09.005. Online ahead of print.

ABSTRACT

BACKGROUND: Cognitive impairment is common in Parkinson's disease (PD) and often leads to dementia, with no effective treatment. Aging studies suggest that physical activity (PA) intensity has a positive impact on cognition and enhanced functional connectivity may underlie these benefits. However, less is known in PD. This cross-sectional study examined the relationship between PA intensity, cognitive performance, and resting state functional connectivity in PD and whether PA intensity influences the relationship between functional connectivity and cognitive performance.

METHODS: 96 individuals with mild-moderate PD completed a comprehensive neuropsychological battery. Intensity of PA was objectively captured over a seven-day period using a wearable device (ActiGraph). Time spent in light and moderate intensity PA was determined based on standardized actigraphy cut points. Resting-state fMRI was assessed in a subset of 50 individuals to examine brain-wide functional connectivity.

RESULTS: Moderate intensity PA (MIPA), but not light PA, was associated with better global cognition, visuospatial function, memory, and executive function. Individuals who met the WHO recommendation of ≥150 min/week of MIPA demonstrated better global cognition, executive function, and visuospatial function. Resting-state functional connectivity associated with MIPA included a combination of brainstem, hippocampus, and regions in the frontal, cingulate, and parietal cortices, which showed higher connectivity across the brain in those achieving the WHO MIPA recommendation. Meeting this recommendation positively moderated the associations between identified functional connectivity and global cognition, visuospatial function, and language.

CONCLUSION: Encouraging MIPA, particularly the WHO recommendation of ≥150 min of MIPA/week, may represent an important prescription for PD cognition.

PMID:36191358 | DOI:10.1016/j.parkreldis.2022.09.005

Hippocampus and temporal pole functional connectivity is associated with age and individual differences in autobiographical memory

Mon, 10/03/2022 - 18:00

Proc Natl Acad Sci U S A. 2022 Oct 11;119(41):e2203039119. doi: 10.1073/pnas.2203039119. Epub 2022 Oct 3.

ABSTRACT

Recollection of one's personal past, or autobiographical memory (AM), varies across individuals and across the life span. This manifests in the amount of episodic content recalled during AM, which may reflect differences in associated functional brain networks. We take an individual differences approach to examine resting-state functional connectivity of temporal lobe regions known to coordinate AM content retrieval with the default network (anterior and posterior hippocampus, temporal pole) and test for associations with AM. Multiecho resting-state functional magnetic resonance imaging (fMRI) and autobiographical interviews were collected for 158 younger and 105 older healthy adults. Interviews were scored for internal (episodic) and external (semantic) details. Age group differences in connectivity profiles revealed that older adults had lower connectivity within anterior hippocampus, posterior hippocampus, and temporal pole but greater connectivity with regions across the default network compared with younger adults. This pattern was positively related to posterior hippocampal volumes in older adults, which were smaller than younger adult volumes. Connectivity associations with AM showed two significant patterns. The first dissociated connectivity related to internal vs. external AM across participants. Internal AM was related to anterior hippocampus and temporal pole connectivity with orbitofrontal cortex and connectivity within posterior hippocampus. External AM was related to temporal pole connectivity with regions across the lateral temporal cortex. In the second pattern, younger adults displayed temporal pole connectivity with regions throughout the default network associated with more detailed AMs overall. Our findings provide evidence for discrete ensembles of brain regions that scale with systematic variation in recollective styles across the healthy adult life span.

PMID:36191210 | DOI:10.1073/pnas.2203039119

Sustained upregulation of widespread hippocampal-neocortical coupling following memory encoding

Mon, 10/03/2022 - 18:00

Cereb Cortex. 2022 Oct 3:bhac384. doi: 10.1093/cercor/bhac384. Online ahead of print.

ABSTRACT

Systems consolidation of new experiences into lasting episodic memories involves hippocampal-neocortical interactions. Evidence of this process is already observed during early post-encoding rest periods, both as increased hippocampal coupling with task-relevant perceptual regions and reactivation of stimulus-specific patterns following intensive encoding tasks. We investigate the spatial and temporal characteristics of these hippocampally anchored post-encoding neocortical modulations. Eighty-nine adults participated in an experiment consisting of interleaved memory task- and resting-state periods. We observed increased post-encoding functional connectivity between hippocampus and individually localized neocortical regions responsive to stimuli encountered during memory encoding. Post-encoding modulations were manifested as a nearly system-wide upregulation in hippocampal coupling with all major functional networks. The configuration of these extensive modulations resembled hippocampal-neocortical interaction patterns estimated from active encoding operations, suggesting hippocampal post-encoding involvement exceeds perceptual aspects. Reinstatement of encoding patterns was not observed in resting-state scans collected 12 h later, nor when using other candidate seed regions. The similarity in hippocampal functional coupling between online memory encoding and offline post-encoding rest suggests reactivation in humans involves a spectrum of cognitive processes engaged during the experience of an event. There were no age effects, suggesting that upregulation of hippocampal-neocortical connectivity represents a general phenomenon seen across the adult lifespan.

PMID:36190442 | DOI:10.1093/cercor/bhac384

Genetic and environmental factors influencing neonatal resting-state functional connectivity

Mon, 10/03/2022 - 18:00

Cereb Cortex. 2022 Oct 3:bhac383. doi: 10.1093/cercor/bhac383. Online ahead of print.

ABSTRACT

Functional magnetic resonance imaging has been used to identify complex brain networks by examining the correlation of blood-oxygen-level-dependent signals between brain regions during the resting state. Many of the brain networks identified in adults are detectable at birth, but genetic and environmental influences governing connectivity within and between these networks in early infancy have yet to be explored. We investigated genetic influences on neonatal resting-state connectivity phenotypes by generating intraclass correlations and performing mixed effects modeling to estimate narrow-sense heritability on measures of within network and between-network connectivity in a large cohort of neonate twins. We also used backwards elimination regression and mixed linear modeling to identify specific demographic and medical history variables influencing within and between network connectivity in a large cohort of typically developing twins and singletons. Of the 36 connectivity phenotypes examined, only 6 showed narrow-sense heritability estimates greater than 0.10, with none being statistically significant. Demographic and obstetric history variables contributed to between- and within-network connectivity. Our results suggest that in early infancy, genetic factors minimally influence brain connectivity. However, specific demographic and medical history variables, such as gestational age at birth and maternal psychiatric history, may influence resting-state connectivity measures.

PMID:36190430 | DOI:10.1093/cercor/bhac383

Commentary: Aberrant dynamic functional connectivity of posterior cingulate cortex subregions in major depressive disorder with suicidal ideation

Mon, 10/03/2022 - 18:00

Front Neurosci. 2022 Sep 16;16:1012050. doi: 10.3389/fnins.2022.1012050. eCollection 2022.

NO ABSTRACT

PMID:36188483 | PMC:PMC9523315 | DOI:10.3389/fnins.2022.1012050

Altered synchronous neural activities in retinal vein occlusion patients: A resting-state fMRI study

Mon, 10/03/2022 - 18:00

Front Hum Neurosci. 2022 Sep 16;16:961972. doi: 10.3389/fnhum.2022.961972. eCollection 2022.

ABSTRACT

OBJECTIVE: Retinal vein occlusion (RVO) is the second most common retinal vascular disorder after diabetic retinopathy, which is the main cause of vision loss. Retinal vein occlusion might lead to macular edema, causing severe vision loss. Previous neuroimaging studies of patients with RVO demonstrated that RVO was accompanied by cerebral changes, and was related to stroke. The purpose of the study is to investigate synchronous neural activity changes in patients with RVO.

METHODS: A total of 50 patients with RVO and 48 healthy subjects with matched sex, age, and education were enrolled in the study. The ReHo method was applied to investigate synchronous neural activity changes in patients with RVO.

RESULTS: Compared with HC, patients with RVO showed increased ReHo values in the bilateral cerebellum_4_5. On the contrary, patients with RVO had decreased ReHo values in the bilateral middle occipital gyrus, right cerebelum_crus1, and right inferior temporal gyrus.

CONCLUSION: Our study demonstrated that patients with RVO were associated with abnormal synchronous neural activities in the cerebellum, middle occipital gyrus, and inferior temporal gyrus. These findings shed new insight into neural mechanisms of vision loss in patients with RVO.

PMID:36188177 | PMC:PMC9524247 | DOI:10.3389/fnhum.2022.961972

Dynamic functional connectivity estimation for neurofeedback emotion regulation paradigm with simultaneous EEG-fMRI analysis

Mon, 10/03/2022 - 18:00

Front Hum Neurosci. 2022 Sep 16;16:933538. doi: 10.3389/fnhum.2022.933538. eCollection 2022.

ABSTRACT

Joint Analysis of EEG and fMRI datasets can bring new insight into brain mechanisms. In this paper, we employed the recently introduced Correlated Coupled Tensor Matrix Factorization (CCMTF) method for analysis of the emotion regulation paradigm based on EEG frontal asymmetry neurofeedback in the alpha frequency band with simultaneous fMRI. CCMTF method assumes that the co-variations of the common dimension (temporal dimension) between EEG and fMRI are correlated and not necessarily identical. The results of the CCMTF method suggested that EEG and fMRI had similar covariations during the transition of brain activities from resting states to task (view and upregulation) states and these covariations followed an increasing trend. The fMRI shared spatial component showed activations in the limbic system, DLPFC, OFC, and VLPC regions, which were consistent with the previous studies and were linked to EEG frequency patterns in the range of 1-15 Hz with a correlation value close to 0.75. The estimated regions from the CCMTF method were then used as the candidate nodes for dynamic functional connectivity (dFC) analysis, in which the changes in connectivity from view to upregulation states were examined. The results of the dFC analysis were compared with a Normalized Mutual information (NMI) based approach in two different frequency ranges (1-15 and 15-40 Hz) as the NMI method was applied to the vectors of dFC nodes of EEG and fMRI data. The results of the two methods illustrated that the relation between EEG and fMRI datasets was mostly in the frequency range of 1-15 Hz. These relations were both in the brain activations and the dFCs between the two modalities. This paper suggests that the CCMTF method is a capable approach for extracting the shared information between EEG and fMRI data and can reveal new information about brain functions and their connectivity without solving the EEG inverse problem or analyzing different frequency bands.

PMID:36188168 | PMC:PMC9524189 | DOI:10.3389/fnhum.2022.933538

Aberrant dynamic minimal spanning tree parameters within default mode network in patients with autism spectrum disorder

Mon, 10/03/2022 - 18:00

Front Psychiatry. 2022 Sep 15;13:860348. doi: 10.3389/fpsyt.2022.860348. eCollection 2022.

ABSTRACT

The altered functional connectivity (FC) level and its temporal characteristics within certain cortical networks, such as the default mode network (DMN), could provide a possible explanatory framework for Autism spectrum disorder (ASD). In the current study, we hypothesized that the topographical organization along with its temporal dynamics of the autistic brain measured by temporal mean and variance of complex network measures, respectively, were significantly altered, which may further explain the autistic symptom severity in patients with ASD. To validate these hypotheses, the precise FCs between DMN regions at each time point were calculated using the resting-state functional magnetic resonance imaging (fMRI) datasets from the Autism Brain Imaging Data Exchange (ABIDE) project. Then, the minimal spanning tree (MST) technique was applied to construct a time-varying complex network of DMN. By analyzing the temporal mean and variance of MST parameters and their relationship with autistic symptom severity, we found that in persons with ASD, the information exchange efficiencies between cortical regions within DMN were significantly lower and more volatile compared with those in typical developing participants. Moreover, these alterations within DMN were closely associated with the autistic symptom severity of the ASD group.

PMID:36186871 | PMC:PMC9524021 | DOI:10.3389/fpsyt.2022.860348

Parenting and addictions: Current insights from human neuroscience

Mon, 10/03/2022 - 18:00

Curr Addict Rep. 2021 Sep;8(3):380-388. doi: 10.1007/s40429-021-00384-6. Epub 2021 Jul 9.

ABSTRACT

PURPOSE: A growing body of human research has documented associations between the maternal brain and maternal substance use and addictions. This neuroscience-informed approach affords the opportunity to unpack potential neurobiological mechanisms that may underscore challenges in maternal caregiving behavior among mothers with addictions and provide new directions for parenting interventions.

FINDINGS: Consistent with theoretical models of parenting and addictions, five studies evidence both hypo- and hyper-reactivity to infant affective cues across neuroimaging methods and tasks that incorporate both infant face and cry stimuli. Three structural and resting-state brain studies as a function of maternal substance use are also reported.

CONCLUSIONS: While human neuroimaging research converges in showing that maternal substance use is associated with differential reactivity to infant affective cues, further multi-level/multi-modal, longitudinal, and dimensional research is critically needed to advance this area of investigation.

PMID:36185758 | PMC:PMC9523670 | DOI:10.1007/s40429-021-00384-6

Adolescents with a concussion have altered brain network functional connectivity one month following injury when compared to adolescents with orthopedic injuries

Sat, 10/01/2022 - 18:00

Neuroimage Clin. 2022 Sep 27;36:103211. doi: 10.1016/j.nicl.2022.103211. Online ahead of print.

ABSTRACT

Concussion is a mild traumatic brain injury (mTBI) with increasing prevalence among children and adolescents. Functional connectivity (FC) within and between the default mode network (DMN), central executive network (CEN) and salience network (SN) has been shown to be altered post-concussion. Few studies have investigated connectivity within and between these 3 networks following a pediatric concussion. The present study explored whether within and between-network FC differs between a pediatric concussion and orthopedic injury (OI) group aged 10-18. Participants underwent a resting-state functional magnetic resonance imaging (rs-fMRI) scan at 4 weeks post-injury. One-way ANCOVA analyses were conducted between groups with the seed-based FC of the 3 networks. A total of 55 concussion and 27 OI participants were included in the analyses. Increased within-network FC of the CEN and decreased between-network FC of the DMN-CEN was found in the concussion group when compared to the OI group. Secondary analyses using spherical SN regions of interest revealed increased within-network FC of the SN and increased between-network FC of the DMN-SN and CEN-SN in the concussion group when compared to the OI group. This study identified differential connectivity patterns following a pediatric concussion as compared to an OI 4 weeks post-injury. These differences indicate potential adaptive brain mechanisms that may provide insight into recovery trajectories and appropriate timing of treatment within the first month following a concussion.

PMID:36182818 | DOI:10.1016/j.nicl.2022.103211

A synchronized multimodal neuroimaging dataset for studying brain language processing

Fri, 09/30/2022 - 18:00

Sci Data. 2022 Sep 30;9(1):590. doi: 10.1038/s41597-022-01708-5.

ABSTRACT

We present a synchronized multimodal neuroimaging dataset for studying brain language processing (SMN4Lang) that contains functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) data on the same 12 healthy volunteers while the volunteers listened to 6 hours of naturalistic stories, as well as high-resolution structural (T1, T2), diffusion MRI and resting-state fMRI data for each participant. We also provide rich linguistic annotations for the stimuli, including word frequencies, syntactic tree structures, time-aligned characters and words, and various types of word and character embeddings. Quality assessment indicators verify that this is a high-quality neuroimaging dataset. Such synchronized data is separately collected by the same group of participants first listening to story materials in fMRI and then in MEG which are well suited to studying the dynamic processing of language comprehension, such as the time and location of different linguistic features encoded in the brain. In addition, this dataset, comprising a large vocabulary from stories with various topics, can serve as a brain benchmark to evaluate and improve computational language models.

PMID:36180444 | DOI:10.1038/s41597-022-01708-5

Reliability and Sensitivity to Alterered Hemodynamics Measured with Resting-state fMRI Metrics: Comparison with <sup>123</sup>I-IMP SPECT

Fri, 09/30/2022 - 18:00

Neuroimage. 2022 Sep 27:119654. doi: 10.1016/j.neuroimage.2022.119654. Online ahead of print.

ABSTRACT

Blood oxygenation level-dependent (BOLD) contrast is sensitive to local hemodynamic changes and thus is applicable to imaging perfusion or vascular reactivity. However, knowledge about its measurement characteristics compared to reference standard perfusion imaging is limited. This study longitudinally evaluated perfusion in patients with steno-occlusive disease using resting-state functional MRI (rsfMRI) acquired before and within nine days of anterior circulation revascularization in patients with large cerebral artery steno-occlusive diseases. The reliability and sensitivity to longitudinal changes of rsfMRI temporal correlation (Rc) and time delay (TDc) relative to the cerebellar signal were examined voxel-wise in comparison with single-photon emission CT (SPECT) cerebral blood flow (CBF) using the within-subject standard deviation (Sw) and intraclass correlation coefficients (ICCs). For statistical comparisons, the standard deviation (SD) of longitudinal changes within the cerebellum, the number of voxels with significant changes in the left middle cerebral artery territory ipsilateral to surgery, and their average changes relative to the cerebellar SD were evaluated. The test-retest reliability of the fMRI metrics was also similarly evaluated using the human connectome project (HCP) healthy young adult dataset. The test-retest time interval was 31 ± 18 days. Test-retest reliability was significantly higher for SPECT (cerebellar SD: -2.59 ± 0.20) than for fMRI metrics (cerebellar SD: Rc, -2.34 ± 0.24, p = 0.04; TDc, -2.19 ± 0.21, p = 0.003). Sensitivity to postoperative changes, which was evaluated as the number of voxels, was significantly higher for fMRI TDc (8.78 ± 0.72) than for Rc (7.42 ± 1.48, p = 0.03) or SPECT CBF (6.88 ± 0.67, p < 0.001). The ratio between the average Rc, TDc, and SPECT CBF changes within the left MCA target region and cerebellar SD was also significantly higher for fMRI TDc (1.21 ± 0.79) than Rc (0.48 ± 0.94, p = 0.006) or SPECT CBF (0.23 ± 0.57, p = 0.001). The measurement variability of time delay was also larger than that of temporal correlation in HCP data within the cerebellum (t = -8.7, p < 0.001) or in the whole-brain (t = -27.4, p < 0.001) gray matter. These data suggest that fMRI time delay is more sensitive to the hemodynamic changes than SPECT CBF, although the reliability is lower. The implication for fMRI connectivity studies is that temporal correlation can be significantly decreased due to altered hemodynamics, even in cases with normal CBF.

PMID:36180009 | DOI:10.1016/j.neuroimage.2022.119654

Partly recovery and compensation in anterior cingulate cortex after SSRI treatment-evidence from multi-voxel pattern analysis over resting state fMRI in depression

Fri, 09/30/2022 - 18:00

J Affect Disord. 2022 Sep 27:S0165-0327(22)01077-1. doi: 10.1016/j.jad.2022.09.071. Online ahead of print.

ABSTRACT

BACKGROUND: Anterior cingulate cortex (ACC) plays an essential role in the pathophysiology of major depressive disorder (MDD) and its treatment. However, it's still unclear whether the effects of disease and antidepressant treatment on ACC perform diversely in neural mechanisms.

METHODS: Fifty-nine MDD patients completed resting-state fMRI scanning twice at baseline and after 12-week selective serotonin reuptake inhibitor (SSRI) treatment, respectively in acute state and remission state. Fifty-nine demographically matched healthy controls were enrolled. Using fractional amplitude of low-frequency fluctuation (fALFF) in ACC as features, we performed multi-voxel pattern analysis over pretreatment MDD patients vs health control (HC), and over pretreatment MDD patients vs posttreatment MDD patients.

RESULTS: Discriminative regions in ACC for MDD impairment and changes after antidepressants were obtained. The intersection set and difference set were calculated to form ACC subregions of recovered, unrecovered and compensative, respectively. The recovered ACC subregion mainly distributed in rostral ACC (80 %) and the other two subregions had nearly equal distribution over dorsal ACC and rostral ACC. Furthermore, only the compensative subregion had significant changed functional connectivity with cingulo-opercular control network (CON) after antidepressant treatment.

LIMITATIONS: The number of subjects was relatively small. The results need to be validated with larger sample sizes and multisite data.

CONCLUSIONS: This finding suggested that the local function of ACC was partly recovered on regulating emotion after antidepressant by detecting the common subregional targets of depression impairment and antidepressive effect. Besides, changed fALFF in the compensative ACC subregion and its connectivity with CON may partly compensate for the cognition deficits.

PMID:36179779 | DOI:10.1016/j.jad.2022.09.071

Functional connectivity dynamics reflect disability and multi-domain clinical impairment in patients with relapsing-remitting multiple sclerosis

Fri, 09/30/2022 - 18:00

Neuroimage Clin. 2022 Sep 16;36:103203. doi: 10.1016/j.nicl.2022.103203. Online ahead of print.

ABSTRACT

BACKGROUND & AIM: Multiple sclerosis (MS) is an autoimmune disease of the central nervous system associated with deficits in cognitive and motor functioning. While structural brain changes such as demyelination are an early hallmark of the disease, a characteristic profile of functional brain alterations in early MS is lacking. Functional neuroimaging studies at various disease stages have revealed complex and heterogeneous patterns of aberrant functional connectivity (FC) in MS, with previous studies largely being limited to a static account of FC. Thus, it remains unclear how time-resolved FC relates to variance in clinical disability status in early MS. We here aimed to characterize brain network organization in early MS patients with time-resolved FC analysis and to explore the relationship between disability status, multi-domain clinical outcomes and altered network dynamics.

METHODS: Resting-state functional MRI (rs-fMRI) data were acquired from 101 MS patients and 101 age- and sex-matched healthy controls (HC). Based on the Expanded Disability Status Score (EDSS), patients were split into two sub-groups: patients without clinical disability (EDSS ≤ 1, n = 36) and patients with mild to moderate levels of disability (EDSS ≥ 2, n = 39). Five dynamic FC states were extracted from whole-brain rs-fMRI data. Group differences in static and dynamic FC strength, across-state overall connectivity, dwell time, transition frequency, modularity, and global connectivity were assessed. Patients' impairment was quantified as custom clinical outcome z-scores (higher: worse) for the domains depressive symptoms, fatigue, motor, vision, cognition, total brain atrophy, and lesion load. Correlation analyses between functional measures and clinical outcomes were performed with Spearman partial correlation analyses controlling for age.

RESULTS: Patients with mild to moderate levels of disability exhibited a more widespread spatiotemporal pattern of altered FC and spent more time in a high-connectivity, low-occurrence state compared to patients without disability and HCs. Worse symptoms in all clinical outcome domains were positively associated with EDSS scores. Furthermore, depressive symptom severity was positively related to functional dynamics as measured by state-specific global connectivity and default mode network connectivity with attention networks, while fatigue and motor impairment were related to reduced frontoparietal network connectivity with the basal ganglia.

CONCLUSIONS: Despite comparably low impairment levels in early MS, we identified distinct connectivity alterations between patients with mild to moderate disability and those without disability, and these changes were sensitive to clinical outcomes in multiple domains. Furthermore, time-resolved analysis uncovered alterations in network dynamics and clinical correlations that remained undetected with conventional static analyses, showing that accounting for temporal dynamics helps disentangle the relationship between functional alterations, disability status, and symptoms in early MS.

PMID:36179389 | DOI:10.1016/j.nicl.2022.103203

Altered dynamic functional connectivity in rectal cancer patients with and without chemotherapy: A resting-state fMRI study

Fri, 09/30/2022 - 18:00

Int J Neurosci. 2022 Sep 30:1-18. doi: 10.1080/00207454.2022.2130295. Online ahead of print.

ABSTRACT

Purpose: Understanding the mechanism of brain functional alterations in rectal cancer (RC) patients is of great significance to improve the prognosis and quality of life of patients. Additionally, the influence of chemotherapy on brain function in RC patients is still unclear. In this study, we aimed to investigate the alterations of brain functional network dynamics in RC patients and explore the effects of chemotherapy on temporal dynamics of dynamic functional connectivity (DFC).Methods: The group spatial independent component analysis and sliding window method were applied to investigate abnormalities of DFC based on resting-state functional magnetic resonance imaging of 18 RC patients without chemotherapy (RC_NC), 21 RC patients with chemotherapy (RC_C), and 33 healthy controls (HC). Then, the Spearman correlation between aberrant properties and clinical measures was calculated.Results: Two discrete states were identified. Compared to HC, RC_NC exhibited increased mean dwell time and fractional windows in state 2 and decreased transition numbers between the two states. Notably, three temporal properties in RC_C showed an intermediate trend in comparison with RC_NC and HC. Furthermore, RC_C also demonstrated abnormal intra- and inter-network connections, involving the visual (VIS), default mode, and cognitive control networks, and most connections related to VIS were correlated with the severity of anxiety and depression.Conclusions: Our study suggested that abnormal DFC patterns could be manifested in RC patients and chemotherapy would further correct abnormalities of network dynamics, which may provide new insights into the brain functional alterations in patients with RC from the time-varying connectivity perspective.

PMID:36178032 | DOI:10.1080/00207454.2022.2130295

Reliability of multi-site UK Biobank MRI brain phenotypes for the assessment of neuropsychiatric complications of SARS-CoV-2 infection: The COVID-CNS travelling heads study

Thu, 09/29/2022 - 18:00

PLoS One. 2022 Sep 29;17(9):e0273704. doi: 10.1371/journal.pone.0273704. eCollection 2022.

ABSTRACT

INTRODUCTION: Magnetic resonance imaging (MRI) of the brain could be a key diagnostic and research tool for understanding the neuropsychiatric complications of COVID-19. For maximum impact, multi-modal MRI protocols will be needed to measure the effects of SARS-CoV-2 infection on the brain by diverse potentially pathogenic mechanisms, and with high reliability across multiple sites and scanner manufacturers. Here we describe the development of such a protocol, based upon the UK Biobank, and its validation with a travelling heads study. A multi-modal brain MRI protocol comprising sequences for T1-weighted MRI, T2-FLAIR, diffusion MRI (dMRI), resting-state functional MRI (fMRI), susceptibility-weighted imaging (swMRI), and arterial spin labelling (ASL), was defined in close approximation to prior UK Biobank (UKB) and C-MORE protocols for Siemens 3T systems. We iteratively defined a comparable set of sequences for General Electric (GE) 3T systems. To assess multi-site feasibility and between-site variability of this protocol, N = 8 healthy participants were each scanned at 4 UK sites: 3 using Siemens PRISMA scanners (Cambridge, Liverpool, Oxford) and 1 using a GE scanner (King's College London). Over 2,000 Imaging Derived Phenotypes (IDPs), measuring both data quality and regional image properties of interest, were automatically estimated by customised UKB image processing pipelines (S2 File). Components of variance and intra-class correlations (ICCs) were estimated for each IDP by linear mixed effects models and benchmarked by comparison to repeated measurements of the same IDPs from UKB participants. Intra-class correlations for many IDPs indicated good-to-excellent between-site reliability. Considering only data from the Siemens sites, between-site reliability generally matched the high levels of test-retest reliability of the same IDPs estimated in repeated, within-site, within-subject scans from UK Biobank. Inclusion of the GE site resulted in good-to-excellent reliability for many IDPs, although there were significant between-site differences in mean and scaling, and reduced ICCs, for some classes of IDP, especially T1 contrast and some dMRI-derived measures. We also identified high reliability of quantitative susceptibility mapping (QSM) IDPs derived from swMRI images, multi-network ICA-based IDPs from resting-state fMRI, and olfactory bulb structure IDPs from T1, T2-FLAIR and dMRI data.

CONCLUSION: These results give confidence that large, multi-site MRI datasets can be collected reliably at different sites across the diverse range of MRI modalities and IDPs that could be mechanistically informative in COVID brain research. We discuss limitations of the study and strategies for further harmonisation of data collected from sites using scanners supplied by different manufacturers. These acquisition and analysis protocols are now in use for MRI assessments of post-COVID patients (N = 700) as part of the ongoing COVID-CNS study.

PMID:36173949 | DOI:10.1371/journal.pone.0273704

Grouped Spherical Data Modeling Through Hierarchical Nonparametric Bayesian Models and Its Application to fMRI Data Analysis

Thu, 09/29/2022 - 18:00

IEEE Trans Neural Netw Learn Syst. 2022 Sep 29;PP. doi: 10.1109/TNNLS.2022.3208202. Online ahead of print.

ABSTRACT

Recently, spherical data (i.e., L2 normalized vectors) modeling has become a promising research topic in various real-world applications (such as gene expression data analysis, document categorization, and gesture recognition). In this work, we propose a hierarchical nonparametric Bayesian model based on von Mises-Fisher (VMF) distributions for modeling spherical data that involve multiple groups, where each observation within a group is sampled from a VMF mixture model with an infinite number of components allowing them to be shared across groups. Our model is formulated by employing a hierarchical nonparametric Bayesian framework known as the hierarchical Pitman-Yor (HPY) process mixture model, which possesses a power-law nature over the distribution of the components and is particularly useful for data distributions with heavy tails and skewness. To learn the proposed HPY process mixture model with VMF distributions, we systematically develop a closed-form optimization algorithm based on variational Bayes (VB). The merits of the proposed hierarchical Bayesian nonparametric model for modeling grouped spherical data are demonstrated through experiments on both synthetic data and a real-world application about resting-state functional magnetic resonance imaging (fMRI) data analysis.

PMID:36173782 | DOI:10.1109/TNNLS.2022.3208202

Investigating the Influence of Autism Spectrum Traits on Face Processing Mechanisms in Developmental Prosopagnosia

Thu, 09/29/2022 - 18:00

J Autism Dev Disord. 2022 Sep 29. doi: 10.1007/s10803-022-05705-w. Online ahead of print.

ABSTRACT

Autism traits are common exclusionary criteria in developmental prosopagnosia (DP) studies. We investigated whether autism traits produce qualitatively different face processing in 43 DPs with high vs. low autism quotient (AQ) scores. Compared to controls (n = 27), face memory and perception were similarly deficient in the high- and low-AQ DPs, with the high-AQ DP group additionally showing deficient face emotion recognition. Task-based fMRI revealed reduced occipito-temporal face selectivity in both groups, with high-AQ DPs additionally demonstrating decreased posterior superior temporal sulcus selectivity. Resting-state fMRI showed similar reduced face-selective network connectivity in both DP groups compared with controls. Together, this demonstrates that high- and low-AQ DP groups have very similar face processing deficits, with additional facial emotion deficits in high-AQ DPs.

PMID:36173532 | DOI:10.1007/s10803-022-05705-w

Ayu-Characterization of healthy aging from neuroimaging data with deep learning and rsfMRI

Thu, 09/29/2022 - 18:00

Front Comput Neurosci. 2022 Sep 12;16:940922. doi: 10.3389/fncom.2022.940922. eCollection 2022.

ABSTRACT

Estimating brain age and establishing functional biomarkers that are prescient of cognitive declines resulting from aging and different neurological diseases are still open research problems. Functional measures such as functional connectivity are gaining interest as potentially more subtle markers of neurodegeneration. However, brain functions are also affected by "normal" brain aging. More information is needed on how functional connectivity relates to aging, particularly in the absence of neurodegenerative disorders. Resting-state fMRI enables us to investigate functional brain networks and can potentially help us understand the processes of development as well as aging in terms of how functional connectivity (FC) matures during the early years and declines during the late years. We propose models for estimation of the chronological age of a healthy person from the resting state brain activation (rsfMRI). In this work, we utilized a dataset (N = 638, age-range 20-88) comprising rsfMRI images from the Cambridge Centre for Aging and Neuroscience (Cam-CAN) repository of a healthy population. We propose an age prediction pipeline Ayu which consists of data preprocessing, feature selection, and an attention-based model for deep learning architecture for brain age assessment. We extracted features from the static functional connectivity (sFC) to predict the subject's age and classified them into different age groups (young, middle, middle, and old ages). To the best of our knowledge, a classification accuracy of 72.619 % and a mean absolute error of 6.797, and an r 2 of 0.754 reported by our Ayu pipeline establish competitive benchmark results as compared to the state-of-the-art-approach. Furthermore, it is vital to identify how different functional regions of the brain are correlated. We also analyzed how functional regions contribute differently across ages by applying attention-based networks and integrated gradients. We obtained well-known resting-state networks using the attention model, which maps to within the default mode network, visual network, ventral attention network, limbic network, frontoparietal network, and somatosensory network connected to aging. Our analysis of fMRI data in healthy elderly Age groups revealed that dynamic FC tends to slow down and becomes less complex and more random with increasing age.

PMID:36172055 | PMC:PMC9511020 | DOI:10.3389/fncom.2022.940922

Functional network alterations in young brain tumor patients with radiotherapy-induced memory impairments and vascular injury

Thu, 09/29/2022 - 18:00

Front Neurol. 2022 Sep 12;13:921984. doi: 10.3389/fneur.2022.921984. eCollection 2022.

ABSTRACT

BACKGROUND: Cognitive impairment and cerebral microbleeds (CMBs) are long-term side-effects of cranial radiation therapy (RT). Previously we showed that memory function is disrupted in young patients and that the rate of cognitive decline correlates with CMB development. However, vascular injury alone cannot explain RT-induced cognitive decline. Here we use resting-state functional MRI (rsfMRI) to further investigate the complex mechanisms underlying memory impairment after RT.

METHODS: Nineteen young patients previously treated with or without focal or whole-brain RT for a brain tumor underwent cognitive testing followed by 7T rsfMRI and susceptibility-weighted imaging for CMB detection. Global brain modularity and efficiency, and rsfMRI signal variability within the dorsal attention, salience, and frontoparietal networks were computed. We evaluated whether MR metrics could distinguish age- and sex-matched controls (N = 19) from patients and differentiate patients based on RT exposure and aggressiveness. We also related MR metrics with memory performance, CMB burden, and risk factors for cognitive decline after RT.

RESULTS: Compared to controls, patients exhibited widespread hyperconnectivity, similar modularity, and significantly increased efficiency (p < 0.001) and network variability (p < 0.001). The most abnormal values were detected in patients treated with high dose whole-brain RT, having supratentorial tumors, and who did not undergo RT but had hydrocephalus. MR metrics and memory performance were correlated (R = 0.34-0.53), though MR metrics were more strongly related to risk factors for cognitive worsening and CMB burden with evidence of functional recovery.

CONCLUSIONS: MR metrics describing brain connectivity and variability represent promising candidate imaging biomarkers for monitoring of long-term cognitive side-effects after RT.

PMID:36172034 | PMC:PMC9511024 | DOI:10.3389/fneur.2022.921984