Deep learning-driven dyslexia detection model using multi-modality data.

Background: Dyslexia is a neurological disorder that affects an individual's language processing abilities. Early care and intervention can help dyslexic individuals succeed academically and socially. Recent developments in deep learning (DL) approaches motivate researchers to build dyslexia detection models (DDMs). DL approaches facilitate the integration of multi-modality data. However, there are few multi-modality-based DDMs. Methods: In this study, the authors built a DL-based DDM using multi-modality data. A squeeze and excitation (SE) integrated MobileNet V3 model, self-attention mechanisms (SA) based EfficientNet B7 model, and early stopping and SA-based Bi-directional long short-term memory (Bi-LSTM) models were developed to extract features from magnetic resonance imaging (MRI), functional MRI, and electroencephalography (EEG) data. In addition, the authors fine-tuned the LightGBM model using the Hyperband optimization technique to detect dyslexia using the extracted features. Three datasets containing FMRI, MRI, and EEG data were used to evaluate the performance of the proposed DDM. Results: The findings supported the significance of the proposed DDM in detecting dyslexia with limited computational resources. The proposed model outperformed the existing DDMs by producing an optimal accuracy of 98.9%, 98.6%, and 98.8% for the FMRI, MRI, and EEG datasets, respectively. Healthcare centers and educational institutions can benefit from the proposed model to identify dyslexia in the initial stages. The interpretability of the proposed model can be improved by integrating vision transformers-based feature extraction.

A quantitative comparison of atlas parcellations on the human superior temporal sulcus.

The superior temporal sulcus (STS) has a functional topography that has been difficult to characterize through traditional approaches. Automated atlas parcellations may be one solution while also being beneficial for both dimensional reduction and standardizing regions of interest, but they yield very different boundary definitions along the STS. Here we evaluate how well machine learning classifiers can correctly identify six social cognitive tasks from STS activation patterns dimensionally reduced using four popular atlases (Glasser et al., 2016; Gordon et al., 2016; Power et al., 2011 as projected onto the surface by Arslan et al., 2018; Schaefer et al., 2018). Functional data was summarized within each STS parcel in one of four ways, then subjected to leave-one-subject-out cross-validation SVM classification. We found that the classifiers could readily label conditions when data was parcellated using any of the four atlases, evidence that dimensional reduction to parcels did not compromise functional fingerprints. Mean activation for the social conditions was the most effective metric for classification in the right STS, whereas all the metrics classified equally well in the left STS. Interestingly, even atlases constructed from random parcellation schemes (null atlases) classified the conditions with high accuracy. We therefore conclude that the complex activation maps on the STS are readily differentiated at a coarse granular level, despite a strict topography having not yet been identified. Further work is required to identify what features have greatest potential to improve the utility of atlases in replacing functional localizers.

Loneliness and Resting-State Functional Brain Connectivity Among Older Adults: A Proportional Correlation.

OBJECTIVE: Loneliness reportedly increases the risk of dementia, especially Alzheimer's disease (AD). The authors' previous study demonstrated associations between loneliness and structural abnormalities observed in early-stage AD. The present study examined associations between the brain's functional characteristics and loneliness among older adults with concerns about cognitive decline. METHODS: This single-center study included 43 participants (13 with amnestic mild cognitive impairment and 30 with normal cognition). Participants were assessed with the revised University of California Los Angeles (UCLA) Loneliness Scale and underwent resting-state functional MRI. Functional images were preprocessed with the CONN toolbox. The selected seeds were within brain regions reportedly associated with loneliness. One-sample general linear model analysis was performed to examine regressions of UCLA Loneliness Scale scores and functional connectivity between the seeds and regions of interest. RESULTS: The revised UCLA Loneliness Scale scores were positively correlated with functional connectivity between the right hippocampus and left lateral parietal lobe and were negatively correlated with functional connectivity between the left amygdala and left frontal operculum and between the left amygdala and right supramarginal gyrus. Analyses were adjusted for age, sex, and education and scores on the Mini-Mental State Examination and Clinical Dementia Rating scale. CONCLUSIONS: Loneliness was associated with abnormal function of the hippocampus, parts of the parietal lobe and frontal cortex, and the amygdala. These findings may suggest a possible correlation between loneliness and neurological changes associated with dementia.

Personalized, parcel-guided non-invasive transcranial magnetic stimulation for the treatment of post-concussive syndrome: safety and proof of concept.

OBJECTIVE: To determine the safety and proof of concept of a parcel-guided, repetitive Transcranial Magnetic Stimulation (rTMS) in patients who develop a heterogeneous array of symptoms, known collectively as post-concussive syndrome (PCS), following traumatic brain injury (TBI). METHODS: We performed a retrospective review of off-label, individualized, parcel-guided rTMS in 19 patients from December 2020 to May 2023. Patients had at least one instance of mild, moderate, or severe TBI and developed symptoms not present prior to injury. rTMS targets were identified based on machine learning connectomic software using functional connectivity anomaly matrices compared to healthy controls. EuroQol (EQ-5D), as a measurement of quality of life, and additional questionnaires dependent on individual's symptoms were submitted prior to, after, and during follow-up from rTMS. RESULTS: Nineteen patients showed improvement in EQ-5D and Rivermead Post Concussion Symptoms Questionnaires - 3 after treatment and follow-up. For nine patients who developed depression, five (55%) attained response and remission based on the Beck Depression Inventory after treatment. Eight of ten patients with anxiety had a clinically significant reduction in Generalized Anxiety Disorder-7 scores during follow-up. CONCLUSION: Parcel-guided rTMS is safe and may be effective in reducing PCS symptoms following TBI and should incite further controlled studies.

Assessment of objective visual function following idebenone administration in patients with leber hereditary optic neuropathy.

PURPOSE: To objectively assess visual function in Leber's Hereditary Optic Neuropathy (LHON) patients; this study evaluated pre- and post-idebenone treatment changes in primary visual cortical (V1) responses using functional magnetic resonance imaging (fMRI), given the challenges in subjective testing due to central retinal ganglion cell damage. STUDY DESIGN: A descriptive study involving four confirmed LHON patients. METHODS: Four patients received 900 mg/day of oral idebenone for 24 weeks. Baseline and post-treatment visual acuity, visual fields, and BOLD fMRI responses while passively viewed drifting contrast pattern visual stimuli were compared with self-reported symptoms. RESULTS: Post-idebenone, one patient showed positive trends across subjective tests, reported symptoms, and fMRI. Two patients had stable symptoms and fMRI responses; one improved on subjective tests, and another worsened slightly. Another patient improved in visual field tests despite worsening symptoms and fMRI trends. CONCLUSION: fMRI may offer a valuable objective measure of visual functions in LHON and appears to be more relevant in assessing symptoms. Further research with more participants is needed to ascertain fMRI's role in developing objective visual assessments and treatment evaluation.

Cerebral cortex functional reorganization in preschool children with congenital sensorineural hearing loss: a resting-state fMRI study.

Purpose: How cortical functional reorganization occurs after hearing loss in preschool children with congenital sensorineural hearing loss (CSNHL) is poorly understood. Therefore, we used resting-state functional MRI (rs-fMRI) to explore the characteristics of cortical reorganization in these patents. Methods: Sixty-three preschool children with CSNHL and 32 healthy controls (HCs) were recruited, and the Categories of Auditory Performance (CAP) scores were determined at the 6-month follow-up after cochlear implantation (CI). First, rs-fMRI data were preprocessed, and amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) were calculated. Second, whole-brain functional connectivity (FC) analysis was performed using bilateral primary auditory cortex as seed points. Finally, Spearman correlation analysis was performed between the differential ALFF, ReHo and FC values and the CAP score. Results: ALFF analysis showed that preschool children with CSNHL had lower ALFF values in the bilateral prefrontal cortex and superior temporal gyrus than HCs, but higher ALFF values in the bilateral thalamus and calcarine gyrus. And correlation analysis showed that some abnormal brain regions were weak negatively correlated with CAP score (p < 0.05). The ReHo values in the bilateral superior temporal gyrus, part of the prefrontal cortex and left insular gyrus were lower, whereas ReHo values in the bilateral thalamus, right caudate nucleus and right precentral gyrus were higher, in children with CSNHL than HCs. However, there was no correlation between ReHo values and the CAP scores (p < 0.05). Using primary auditory cortex (PAC) as seed-based FC further analysis revealed enhanced FC in the visual cortex, proprioceptive cortex and motor cortex. And there were weak negative correlations between the FC values in the bilateral superior temporal gyrus, occipital lobe, left postcentral gyrus and right thalamus were weakly negatively correlated and the CAP score (p < 0.05). Conclusion: After auditory deprivation in preschool children with CSNHL, the local functions of auditory cortex, visual cortex, prefrontal cortex and somatic motor cortex are changed, and the prefrontal cortex plays a regulatory role in this process. There is functional reorganization or compensation between children's hearing and these areas, which may not be conducive to auditory language recovery after CI in deaf children.

Comparative imaging study of patients with persistent olfactory dysfunction due to mild COVID-19 using structural and functional MRI.

INTRODUCTION: Persistent post-COVID olfactory dysfunction continues to be studied due to the controversy in its pathophysiology and neuroimaging. MATERIALS AND METHODS: The patients had confirmed mild COVID-19 infection with olfactory dysfunction of more than one month of evolution and they were compared to controls with normal olfaction, assessed using the Sniffin' Sticks Olfactory Test and underwent brain, magnetic resonance imaging (MRI) of the olfactory bulb and olfactory function. RESULTS: A total of 8 patients and 2 controls participated. The average age of the patients was 34.5 years (SD 8.5), and that of the controls was 28.5 (SD 2.1). The average score in the patients' olfactory test was 7.9 points (SD 2.2). In brain and olfactory bulb MRI tests, no morphological differences were found. When evaluated by functional MRI, none of the patients activated the entorhinal area in comparison to the controls, who did show activation at this level. Activation of secondary olfactory areas in cases and controls were as follows: orbitofrontal (25% vs 100%), basal ganglia (25% vs 50%) and insula (38% vs 0%) respectively. CONCLUSIONS: There were no observed morphological changes in the brain MRI. Unlike the controls, none of the patients activated the entorhinal cortex in the olfactory functional MRI.

Cerebellar functional connectivity relates to lower urinary tract function: A 7 Tesla study.

OBJECTIVES: The objective of this study is to explore the functional connectivity (FC) of the cerebellum during the storage phase of micturition, through detecting spontaneous blood-oxygen-level dependent signal between the cerebellum and different brain regions using a high-resolution 7 Tesla magnetic resonance imaging (MRI) scanner. MATERIALS AND METHODS: We recruited healthy individuals with no reported history of neurological disease or lower urinary tract (LUT) symptoms. Participants were asked to drink 500 mL of water and then empty their bladders before entering the MRI scanner. They underwent a T1-weighted anatomical scan, followed by an initial (8 min) empty bladder resting state functional MRI (rs-fMRI) acquisition. Once subjects felt the desire to void, a second rs-fMRI scan was obtained, this time with a full bladder state. We established a priori cerebellar regions of interest from the literature to perform seed-to-voxel analysis using nonparametric statistics based on the Threshold Free Cluster Enhancement method and utilized a voxel threshold of p < 0.05. RESULTS: Twenty individuals (10 male and 10 female) with a median age of 25 years (IQR [3.5]) participated in the study. We placed 31 different 4-mm spherical seeds throughout the cerebellum and assessed their FC with the remainder of the brain. Three of these (left cerebellar tonsil, right posterolateral lobe, right posterior lobe) showed significant differences in connectivity when comparing scans conducted with a full bladder to those with an empty bladder. Additionally, we observed sex differences in FC, with connectivity being higher in women during the empty bladder condition. CONCLUSION: Our initial findings reveal, for the first time, that the connectivity of the cerebellar network is modulated by bladder filling and is associated with LUT function. Unraveling the cerebellum's role in bladder function lays the foundation for a more comprehensive understanding of urinary pathologies affecting this area.

The Transdiagnostic Connectome Project: a richly phenotyped open dataset for advancing the study of brain-behavior relationships in psychiatry.

An important aim in psychiatry is the establishment of valid and reliable associations linking profiles of brain functioning to clinically relevant symptoms and behaviors across patient populations. To advance progress in this area, we introduce an open dataset containing behavioral and neuroimaging data from 241 individuals aged 18 to 70, comprising 148 individuals meeting diagnostic criteria for a broad range of psychiatric illnesses and a healthy comparison group of 93 individuals. These data include high-resolution anatomical scans, multiple resting-state, and task-based functional MRI runs. Additionally, participants completed over 50 psychological and cognitive assessments. Here, we detail available behavioral data as well as raw and processed MRI derivatives. Associations between data processing and quality metrics, such as head motion, are reported. Processed data exhibit classic task activation effects and canonical functional network organization. Overall, we provide a comprehensive and analysis-ready transdiagnostic dataset, which we hope will accelerate the identification of illness-relevant features of brain functioning, enabling future discoveries in basic and clinical neuroscience.

Cerebello-Parietal Functional Connectivity in Amnestic Mild Cognitive Impairment.

The role of the cerebellum in amnestic mild cognitive impairment (aMCI), typically a prodromal stage of Alzheimer's disease, is not fully understood. We studied the lobule-specific cerebello-cerebral connectivity in 15 cognitively normal and 16 aMCI using resting-state functional MRI. Our analysis revealed weaker connectivity between the cognitive cerebellar lobules and parietal lobe in aMCI. However, stronger connectivity was observed in the cognitive cerebellar lobules with certain brain regions, including the precuneus cortex, posterior cingulate gyrus, and caudate nucleus in participants with worse cognition. Leveraging these measurable changes in cerebello-parietal functional networks in aMCI could offer avenues for future therapeutic interventions.

Contribution of changes in the spinal cord and brain to the onset and progression of hand clumsiness symptoms in cervical spondylotic myelopathy.

OBJECTIVE: Cervical spondylotic myelopathy (CSM) stands as the most prevalent form of spinal cord injury, frequently prompting various changes in both the brain and spinal cord. However, the precise nature of these changes within the brains and spinal cords of CSM patients experiencing hand clumsiness (HCL) symptoms has remained elusive. The authors aimed to scrutinize these alterations and explore potential links between these changes and the onset of HCL symptoms. METHODS: Using the modified Japanese Orthopaedic Association (mJOA) scale, the authors classified CSM patients into two groups: those without HCL and those with HCL. The authors performed voxel-wise z-score transformation amplitude of low-frequency fluctuations (zALFF) and resting-state functional connectivity (FC) evaluations in the brain. Additionally, they used the Spinal Cord Toolbox to calculate the fractional anisotropy (FA) of spinal cord tracts. The analysis also encompassed an examination of the correlation of these measures with improvements in mJOA scores. RESULTS: Significant disparities in zALFF values surfaced in the right calcarine, right cuneus, right precuneus, right middle occipital gyrus (MOG), right superior occipital gyrus (SOG), and right superior parietal gyrus (SPG) between healthy controls (HC), patients without HCL, and patients with HCL, primarily within the visual cortex. In the patient group, patients with HCL displayed reduced FC between the right calcarine, right MOG, right SOG, right SPG, right SFG, bilateral MFG, and left median cingulate and paracingulate gyri when compared with patients without HCL. Moreover, significant differences in FA values of the corticospinal tract (CST) and reticulospinal tract (REST) at the C2 level emerged among HC, patients without HCL, and patients with HCL. Notably, zALFF, FC, and FA values in specific brain regions and spinal cord tracts exhibited correlations with mJOA upper-extremity scores. Additionally, FA values of the CST and REST correlated with zALFF values in the right calcarine, right MOG, right SOG, and right SPG. CONCLUSIONS: Alterations within brain regions associated with the visual cortex, the fronto-parietal-occipital attention network, and spinal cord pathways appear to play a substantial role in the emergence and progression of HCL symptoms. Furthermore, the existence of a potential connection between the spinal cord and the brain suggests that this link might be related to the clinical symptoms of CSM.

The relative brain signal variability increases in the behavioral variant of frontotemporal dementia and Alzheimer's disease but not in schizophrenia.

Overlapping symptoms between Alzheimer's disease (AD), behavioral variant of frontotemporal dementia (bvFTD), and schizophrenia (SZ) can lead to misdiagnosis and delays in appropriate treatment, especially in cases of early-onset dementia. To determine the potential of brain signal variability as a diagnostic tool, we assessed the coefficient of variation of the BOLD signal (CVBOLD) in 234 participants spanning bvFTD (n = 53), AD (n = 17), SZ (n = 23), and controls (n = 141). All underwent functional and structural MRI scans. Data unveiled a notable increase in CVBOLD in bvFTD patients across both datasets (local and international, p < 0.05), revealing an association with clinical scores (CDR and MMSE, r = 0.46 and r = -0.48, p < 0.0001). While SZ and control group demonstrated no significant differences, a comparative analysis between AD and bvFTD patients spotlighted elevated CVBOLD in the frontopolar cortices for the latter (p < 0.05). Furthermore, CVBOLD not only presented excellent diagnostic accuracy for bvFTD (AUC 0.78-0.95) but also showcased longitudinal repeatability. During a one-year follow-up, the CVBOLD levels increased by an average of 35% in the bvFTD group, compared to a 2% increase in the control group (p < 0.05). Our findings suggest that CVBOLD holds promise as a biomarker for bvFTD, offering potential for monitoring disease progression and differentiating bvFTD from AD and SZ.

Disrupted dynamic brain functional connectivity in male cocaine use disorder: Hyperconnectivity, strongly-connected state tendency, and links to impulsivity and borderline traits.

Cocaine use is a major public health problem with serious negative consequences at both the individual and societal levels. Cocaine use disorder (CUD) is associated with cognitive and emotional impairments, often manifesting as alterations in brain functional connectivity (FC). This study employed resting-state functional magnetic resonance imaging (rs-fMRI) to examine dynamic FC in 38 male participants with CUD and 31 matched healthy controls. Using group spatial independent component analysis (group ICA) combined with sliding window approach, we identified two recurring distinct connectivity states: the strongly-connected state (state 1) and weakly-connected state (state 2). CUD patients exhibited significant increased mean dwell and fraction time in state 1, and increased transitions from state 2 to state 1, demonstrated significant strongly-connected state tendency. Our analysis revealed abnormal FC patterns that are state-dependent and state-shared in CUD patients. This study observed hyperconnectivity within the default mode network (DMN) and between DMN and other networks, which varied depending on the state. Furthermore, after adjustment for multiple comparisons, we found significant correlations between these altered dynamic FCs and clinical measures of impulsivity and borderline personality disorder. The disrupted FC and repetitive effects of precuneus and angular gyrus across correlations suggested that they might be the important hub of neural circuits related behaviorally and mentally in CUD. In summary, our study highlighted the potential of these disrupted FC as neuroimaging biomarkers and therapeutic targets, and provided new insights into the understanding of the neurophysiologic mechanisms of CUD.

The Concussion, Exercise, and Brain Networks (ConExNet) study: a cohort study aimed at understanding the effects of sub-maximal aerobic exercise on resting state functional brain activity in pediatric concussion.

BACKGROUND: Recent scientific evidence has challenged the traditional "rest-is-best" approach for concussion management. It is now thought that "exercise-is-medicine" for concussion, owing to dozens of studies which demonstrate that sub-maximal, graded aerobic exercise can reduce symptom burden and time to symptom resolution. However, the primary neuropathology of concussion is altered functional brain activity. To date, no studies have examined the effects of sub-maximal aerobic exercise on resting state functional brain activity in pediatric concussion. In addition, although exercise is now more widely prescribed following concussion, its cardiopulmonary response is not yet well understood in this population. Our study has two main goals. The first is to understand whether there are exercise-induced resting state functional brain activity differences in children with concussion vs. healthy controls. The second is to profile the physiological response to exercise and understand whether it differs between groups. METHODS: We will perform a single-center, controlled, prospective cohort study of pediatric concussion at a large, urban children's hospital and academic center. Children with sport-related concussion (aged 12-17 years) will be recruited within 4-weeks of injury by our clinical study team members. Key inclusion criteria include: medical clearance to exercise, no prior concussion or neurological history, and no implants that would preclude MRI. Age- and sex-matched healthy controls will be required to meet the same inclusion criteria and will be recruited through the community. The study will be performed over two visits separated by 24-48 h. Visit 1 involves exercise testing (following the current clinical standard for concussion) and breath-by-breath gas collection using a metabolic cart. Visit 2 involves two functional MRI (fMRI) scans interspersed by 10-minutes of treadmill walking at an intensity calibrated to Visit 1 findings. To address sub-objectives, all participants will be asked to self-report symptoms daily and wear a waist-worn tri-axial accelerometer for 28-days after Visit 2. DISCUSSION: Our study will advance the growing exercise-concussion field by helping us understand whether exercise impacts outcomes beyond symptoms in pediatric concussion. We will also be able to profile the cardiopulmonary response to exercise, which may allow for further understanding (and eventual optimization) of exercise in concussion management. TRIAL REGISTRATION: Not applicable.

Comparative analysis of brain language templates with primary language areas detected from presurgical fMRI of brain tumor patients.

INTRODUCTION: Functional brain templates are often used in the analysis of clinical functional MRI (fMRI) studies. However, these templates are mostly built based on anatomy or fMRI of healthy subjects, which have not been fully vetted in clinical cohorts. Our aim was to evaluate language templates by comparing with primary language areas (PLAs) detected from presurgical fMRI of brain tumor patients. METHODS: Four language templates (A-D) based on anatomy, task-based fMRI, resting-state fMRI, and meta-analysis, respectively, were compared with PLAs detected by fMRI with word generation and sentence completion paradigms. For each template, the fraction of PLA activations enclosed by the template (positive inclusion fraction, [PIF]), the fraction of activations within the template but that did not belong to PLAs (false inclusion fraction, [FIF]), and their Dice similarity coefficient (DSC) with PLA activations were calculated. RESULTS: For anterior PLAs, Template A had the greatest PIF (median, 0.95), whereas Template D had both the lowest FIF (median, 0.074), and the highest DSC (median, 0.30), which were all significant compared to other templates. For posterior PLAs, Templates B and D had similar PIF (median, 0.91 and 0.90, respectively) and DSC (both medians, 0.059), which were all significantly higher than that of Template C. Templates B and C had significantly lower FIF (median, 0.061 and 0.054, respectively) compared to Template D. CONCLUSION: This study demonstrated significant differences between language templates in their inclusiveness of and spatial agreement with the PLAs detected in the presurgical fMRI of the patient cohort. These findings may help guide the selection of language templates tailored to their applications in clinical fMRI studies.

Motor network dynamic resting state fMRI connectivity of neurotypical children in regions affected by cerebral palsy.

Background: Normative childhood motor network resting-state fMRI effective connectivity is undefined, yet necessary for translatable dynamic resting-state-network-informed evaluation in pediatric cerebral palsy. Methods: Cross-spectral dynamic causal modeling of resting-state-fMRI was investigated in 50 neurotypically developing 5- to 13-year-old children. Fully connected six-node network models per hemisphere included primary motor cortex, striatum, subthalamic nucleus, globus pallidus internus, thalamus, and contralateral cerebellum. Parametric Empirical Bayes with exhaustive Bayesian model reduction and Bayesian modeling averaging informed the model; Purdue Pegboard Test scores of hand motor behavior were the covariate at the group level to determine the effective-connectivity-functional behavior relationship. Results: Although both hemispheres exhibited similar effective connectivity of motor cortico-basal ganglia-cerebellar networks, magnitudes were slightly greater on the right, except for left-sided connections of the striatum which were more numerous and of opposite polarity. Inter-nodal motor network effective connectivity remained consistent and robust across subjects. Age had a greater impact on connections to the contralateral cerebellum, bilaterally. Motor behavior, however, affected different connections in each hemisphere, exerting a more prominent effect on the left modulatory connections to the subthalamic nucleus, contralateral cerebellum, primary motor cortex, and thalamus. Discussion: This study revealed a consistent pattern of directed resting-state effective connectivity in healthy children aged 5-13 years within the motor network, encompassing cortical, subcortical, and cerebellar regions, correlated with motor skill proficiency. Both hemispheres exhibited similar effective connectivity within motor cortico-basal ganglia-cerebellar networks reflecting inter-nodal signal direction predicted by other modalities, mainly differing from task-dependent studies due to network differences at rest. Notably, age-related changes were more pronounced in connections to the contralateral cerebellum. Conversely, motor behavior distinctly impacted connections in each hemisphere, emphasizing its role in modulating left sided connections to the subthalamic nucleus, contralateral cerebellum, primary motor cortex, and thalamus. Motor network effective connectivity was correlated with motor behavior, validating its physiological significance. This study is the first to evaluate a normative effective connectivity model for the pediatric motor network using resting-state functional MRI correlating with behavior and serves as a foundation for identifying abnormal findings and optimizing targeted interventions like deep brain stimulation, potentially influencing future therapeutic approaches for children with movement disorders.

A machine learning approach for potential Super-Agers identification using neuronal functional connectivity networks.

INTRODUCTION: Aging is often associated with cognitive decline. Understanding neural factors that distinguish adults in midlife with superior cognitive abilities (Positive-Agers) may offer insight into how the aging brain achieves resilience. The goals of this study are to (1) introduce an optimal labeling mechanism to distinguish between Positive-Agers and Cognitive Decliners, and (2) identify Positive-Agers using neuronal functional connectivity networks data and demographics. METHODS: In this study, principal component analysis initially created latent cognitive trajectories groups. A hybrid algorithm of machine learning and optimization was then designed to predict latent groups using neuronal functional connectivity networks derived from resting state functional magnetic resonance imaging. Specifically, the Optimal Labeling with Bayesian Optimization (OLBO) algorithm used an unsupervised approach, iterating a logistic regression function with Bayesian posterior updating. This study encompassed 6369 adults from the UK Biobank cohort. RESULTS: OLBO outperformed baseline models, achieving an area under the curve of 88% when distinguishing between Positive-Agers and cognitive decliners. DISCUSSION: OLBO may be a novel algorithm that distinguishes cognitive trajectories with a high degree of accuracy in cognitively unimpaired adults. Highlights: Design an algorithm to distinguish between a Positive-Ager and a Cognitive-Decliner.Introduce a mathematical definition for cognitive classes based on cognitive tests.Accurate Positive-Ager identification using rsfMRI and demographic data (AUC = 0.88).Posterior default mode network has the highest impact on Positive-Aging odds ratio.

Leveraging the adolescent brain cognitive development study to improve behavioral prediction from neuroimaging in smaller replication samples.

Neuroimaging is a popular method to map brain structural and functional patterns to complex human traits. Recently published observations cast doubt upon these prospects, particularly for prediction of cognitive traits from structural and resting state functional magnetic resonance imaging (MRI). We leverage baseline data from thousands of children in the Adolescent Brain Cognitive DevelopmentSM Study to inform the replication sample size required with univariate and multivariate methods across different imaging modalities to detect reproducible brain-behavior associations. We demonstrate that by applying multivariate methods to high-dimensional brain imaging data, we can capture lower dimensional patterns of structural and functional brain architecture that correlate robustly with cognitive phenotypes and are reproducible with only 41 individuals in the replication sample for working memory-related functional MRI, and ~ 100 subjects for structural and resting state MRI. Even with 100 random re-samplings of 100 subjects in discovery, prediction can be adequately powered with 66 subjects in replication for multivariate prediction of cognition with working memory task functional MRI. These results point to an important role for neuroimaging in translational neurodevelopmental research and showcase how findings in large samples can inform reproducible brain-behavior associations in small sample sizes that are at the heart of many research programs and grants.

Sleep and physical activity measures are associated with resting-state network segregation in non-demented older adults.

Greater physical activity and better sleep are associated with reduced risk of cognitive decline and dementia among older adults, but little is known about their combined associations with measures of brain function and neuropathology. This study investigated potential independent and interactive cross-sectional relationships between actigraphy-estimated total volume of physical activity (TVPA) and sleep patterns [i.e., total sleep time (TST), sleep efficiency (SE)] with resting-state functional magnetic resonance imaging (rs-fMRI) measures of large scale network connectivity and positron emission tomography (PET) measures of amyloid-ß. Participants were 135 non-demented older adults from the BIOCARD study (116 cognitively normal and 19 with mild cognitive impairment; mean age = 70.0 years). Using multiple linear regression analyses, we assessed the association between TVPA, TST, and SE with connectivity within the default-mode, salience, and fronto-parietal control networks, and with network modularity, a measure of network segregation. Higher TVPA and SE were independently associated with greater network modularity, although the positive relationship of SE with modularity was only present in amyloid-negative individuals. Additionally, higher TVPA was associated with greater connectivity within the default-mode network, while greater SE was related to greater connectivity within the salience network. In contrast, longer TST was associated with lower network modularity, particularly among amyloid-positive individuals, suggesting a relationship between longer sleep duration and greater network disorganization. Physical activity and sleep measures were not associated with amyloid positivity. These data suggest that greater physical activity levels and more efficient sleep may promote more segregated and potentially resilient functional networks and increase functional connectivity within specific large-scale networks and that the relationship between sleep and functional networks connectivity may depend on amyloid status.

A 32-Month Follow-Up Study of the Effect of APOE ε4 on the Whole Brain Connection in Young Healthy Individuals.

APOE ε4 is risk for cognitive decline even in normal aging, but its effect on the whole-brain functional connectivity (FC) among time in young adults remain elusive. This study aimed to validate the time-by-APOE ε4 interaction on brain FC of this specific population. Longitudinal changes in neuropsychological assessments and resting-state functional magnetic resonance imaging in 26 ε4 carriers and 26 matched non-ε4 carriers were measured for about 3 years. Whole-brain FC was calculated, and a full factorial design was used to compare the difference among groups. Two-sample t test was used for post-hoc analysis. Pearson's correlation analysis was conducted to investigate the relationships between FC and cognitive tests. Of 26 specially appointed ROIs, left superior temporal gyrus (TG) was most sensitive to the effect of time-by-gene interaction. Specifically, the alteration of FC was distributed between the left TG and right TG with GRF correction (voxel-P < 0.001, cluster-P < 0.05), and decreased in ε4 carriers while increased in non-ε4. The main effect of gene showed ε4 carriers has lower FC between left TG and right middle frontal gyrus as compared with non-ε4 both at baseline and follow-up study; ε4 carriers has lower FC between left TG and right supramarginal as compared with non-ε4 at baseline, but no difference in follow-up study. The time-by-APOE ε4 interaction on brain FC was demonstrated at a young age, and left TG was the earliest affected brain regions. The young adult ε4 carriers experience decreased FC among time in the absence overt clinical symptoms.