Identify Group Differences Research Articles

Investigating the perspective of Theory of Knowledge teachers in International Baccalaureate World Schools

As a part of the International Baccalaureate (IB) Diploma Programme (DP) students participate in the Theory of Knowledge (TOK) course. This research used a mixed methods design to investigate the perspective of TOK teachers in IB schools worldwide. To address the research questions, quantitative survey data were analyzed from 1,534 participants, and focus groups with 33 TOK teachers were conducted in Australia, The Netherlands, and the United States. Quantitative data were analyzed using descriptive statistics, t-tests, ANOVA, and linear trends analysis to identify group differences. Qualitative data were coded and analyzed using an inductive approach. Overwhelmingly, survey results indicated that teachers value the TOK course. Teachers ranked the main purposes of the TOK course as 1) to develop an awareness of how knowledge is constructed, critically examined, and renewed by individuals and communities and 2) to help students make connections among academic disciplines and among thoughts, feelings and actions. Teachers ranked the main benefits to students as 1) students better able to critically evaluate knowledge and 2) students better able to identify and reflect on personal assumptions. Teachers strongly agreed that teaching TOK has been a valuable professional development experience for them. Specifically, they indicated it enhanced their own critical thinking and developed their interdisciplinary understanding. Survey results and focus groups suggest the main challenges are 1) assessment, 2) time, and 3) administrative issues (scheduling and class size). Regarding implementation, approximately half of DP coordinators indicated that TOK implementation was different than other IB Diploma Programme aspects, specifically that teacher support and time were different.

Group-representative functional network estimation from multi-subject fMRI data via MRF-based image segmentation

Background and objectiveThere has been growing interest in using functional connectivity patterns, determined from fMRI data to characterize groups of individuals exhibiting common traits. However, the present challenge lies in efficient and accurate identification of distinct patterns observed consistently across multiple subjects. Existing approaches either impose strong assumptions, require aligning images before processing, or require data-intensive machine learning algorithms with manually labeled training datasets. In this paper, we propose a more principled and flexible approach to address this. MethodsOur approach redefines the problem of estimating the group-representative functional network as an image segmentation problem. After employing an improved clustering-based ICA scheme to pre-process the dataset of individual functional network images, we use a maximum a posteriori–Markov random field (MAP-MRF) framework to solve the image segmentation problem. In this framework, we propose a probabilistic model of the individual pixels of the fMRI data, with the model involving a latent group-representative functional network image. Given an observed dataset, we apply a novel and efficient variational Bayes algorithm to recover the associated latent group image. Our methodology seeks to overcome limitations in more traditional schemes by exploiting spatial relationships underlying the connectivity maps and accounting for uncertainty in the estimation process. ResultsWe validate our approach using synthetic, simulated and real data. First, we generate datasets from the proposed forward model with subject-specific binary masking and measurement noise, as well as from a variant of the model without measurement noise. We use both datasets to evaluate our model, along with two algorithms: coordinate-ascent algorithm and variational Bayes algorithm. We conclude that our proposed model with variational Bayes outperforms other competitors, even under model-misspecification. Using variational Bayes offers a significant improvement in performance, with almost no additional computational overhead. We next test our approach on simulated fMRI data. We show our approach is robust to initialization and can recover a solution close to the ground truth. Finally, we apply our proposed methodology along with baselines to a real dataset of fMRI recordings of individuals from two groups, a control group and a group suffering from depression, with recordings made while individuals were subjected to musical stimuli. Our methodology is able to identify group differences that are less clear under competing methods. ConclusionsOur model-based approach demonstrates the advantage of probabilistic models and modern algorithms that account for uncertainty in accurate identification of group-representative connectivity maps. The variational Bayes methodology yields highly accurate results without increasing the computational load compared to traditional methods. In addition, it is robust to model misspecification, and increases the ability to avoid local optima in the solution.

National Institutes of Health Toolbox Emotion Battery: Application of Summary Scores to Adults With Spinal Cord Injury, Traumatic Brain Injury, and Stroke

ObjectiveTo examine the validity of factor analytically based summary scores that were developed using the National Institutes of Health Toolbox Emotion Battery (NIHTB-EB); (ie, psychological well-being, social satisfaction, negative affect) normative sample in individuals with neurologic conditions. DesignCross-sectional, observational cohort. SettingCommunity. ParticipantsA total of 1036 English-speaking adults from the National Institutes of Health Toolbox (NIHTB) normative project and 604 community-dwelling adults with neurologic conditions including spinal cord injury (SCI n=209), traumatic brain injury (TBI n=184), and stroke (cerebrovascular accident [CVA] n=211) (N=1640). InterventionNot applicable. Main Outcome MeasuresThe NIHTB-EB. ResultsA series of univariate analyses comparing summary scores across the 4 groups (SCI, TBI, CVA, normative group) were conducted to identify group differences. Base rates (defined as >1 SD toward the problematic direction) were also identified. The normative group demonstrated better emotional functioning characterized by greater social satisfaction and psychological well-being (normative group > SCI, TBI, CVA; P’s <.0001), and less negative affect (normative group < SCI, P=.016; normative group < TBI, P<.001; normative group < CVA; P=.034) compared with each neurologic group. Using base rates to identify problematic emotions for the 3 summary scores, there were higher rates of problematic emotions on all 3 summary scores for the neurologic groups compared with the normative group. ConclusionsThe NIHTB-EB summary scores demonstrate an increased prevalence of problematic emotions among individuals with 3 neurologic conditions, and might be useful for identifying individuals with similar conditions and potentially in need of psychological support.

Gait stride-to-stride variability and foot clearance pattern analysis in Idiopathic Parkinson’s Disease and Vascular Parkinsonism

The literature on gait analysis in Vascular Parkinsonism (VaP), addressing issues such as variability, foot clearance patterns, and the effect of levodopa, is scarce. This study investigates whether spatiotemporal, foot clearance and stride-to-stride variability analysis can discriminate VaP, and responsiveness to levodopa.Fifteen healthy subjects, 15 Idiopathic Parkinson's Disease (IPD) patients and 15 VaP patients, were assessed in two phases: before (Off-state), and one hour after (On-state) the acute administration of a suprathreshold (1.5 times the usual) levodopa dose. Participants were asked to walk a 30-meter continuous course at a self-selected walking speed while wearing foot-worn inertial sensors. For each gait variable, mean, coefficient of variation (CV), and standard deviations SD1 and SD2 obtained by Poincaré analysis were calculated. General linear models (GLMs) were used to identify group differences. Patients were subject to neuropsychological evaluation (MoCA test) and Brain MRI.VaP patients presented lower mean stride velocity, stride length, lift-off and strike angle, and height of maximum toe (later swing) (p < .05), and higher %gait cycle in double support, with only the latter unresponsive to levodopa. VaP patients also presented higher CV, significantly reduced after levodopa. Yet, all VaP versus IPD differences lost significance when accounting for mean stride length as a covariate.In conclusion, VaP patients presented a unique gait with reduced degrees of foot clearance, probably correlated to vascular lesioning in dopaminergic/non-dopaminergic cortical and subcortical non-dopaminergic networks, still amenable to benefit from levodopa. The dependency of gait and foot clearance and variability deficits from stride length deserves future clarification.

Effects of Brain Parcellation on the Characterization of Topological Deterioration in Alzheimer's Disease.

Alzheimer's disease (AD) causes the progressive deterioration of neural connections, disrupting structural connectivity (SC) networks within the brain. Graph-based analyses of SC networks have shown that topological properties can reveal the course of AD propagation. Different whole-brain parcellation schemes have been developed to define the nodes of these SC networks, although it remains unclear which scheme can best describe the AD-related deterioration of SC networks. In this study, four whole-brain parcellation schemes with different numbers of parcels were used to define SC network nodes. SC networks were constructed based on high angular resolution diffusion imaging (HARDI) tractography for a mixed cohort that includes 20 normal controls (NC), 20 early mild cognitive impairment (EMCI), 20 late mild cognitive impairment (LMCI), and 20 AD patients, from the Alzheimer's Disease Neuroimaging Initiative. Parcellation schemes investigated in this study include the OASIS-TRT-20 (62 regions), AAL (116 regions), HCP-MMP (180 regions), and Gordon-rsfMRI (333 regions), which have all been widely used for the construction of brain structural or functional connectivity networks. Topological characteristics of the SC networks, including the network strength, global efficiency, clustering coefficient, rich-club, characteristic path length, k-core, rich-club coefficient, and modularity, were fully investigated at the network level. Statistical analyses were performed on these metrics using Kruskal-Wallis tests to examine the group differences that were apparent at different stages of AD progression. Results suggest that the HCP-MMP scheme is the most robust and sensitive to AD progression, while the OASIS-TRT-20 scheme is sensitive to group differences in network strength, global efficiency, k-core, and rich-club coefficient at k-levels from 18 and 39. With the exception of the rich-club and modularity coefficients, AAL could not significantly identify group differences on other topological metrics. Further, the Gordon-rsfMRI atlas only significantly differentiates the groups on network strength, characteristic path length, k-core, and rich-club coefficient. Results show that the topological examination of SC networks with different parcellation schemes can provide important complementary AD-related information and thus contribute to a more accurate and earlier diagnosis of AD.

Assessment of executive function declines in presymptomatic and mildly symptomatic familial frontotemporal dementia: NIH-EXAMINER as a potential clinical trial endpoint

IntroductionIdentifying clinical measures that track disease in the earliest stages of frontotemporal lobar degeneration (FTLD) is important for clinical trials. Familial FTLD provides a unique paradigm to study early FTLD. Executive dysfunction is a clinically relevant hallmark of FTLD and may be a marker of disease progression. MethodsNinety-three mutation carriers with no symptoms or minimal/questionable symptoms (MAPT, n = 31; GRN, n = 28; C9orf72, n = 34; Clinical Dementia Rating scale plus NACC FTLD Module < 1) and 78 noncarriers enrolled through Advancing Research and Treatment in Frontotemporal Lobar Degeneration/Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects studies completed the Executive Abilities: Measures and Instruments for Neurobehavioral Evaluation and Research (NIH-EXAMINER) and the UDS neuropsychological battery. Linear mixed-effects models were used to identify group differences in cognition at baseline and longitudinally. We examined associations between cognition, clinical functioning, and magnetic resonance imaging volumes. ResultsNIH-EXAMINER scores detected baseline and differences in slopes between carriers and noncarriers, even in carriers with a baseline Clinical Dementia Rating scale plus NACC FTLD Module = 0. NIH-EXAMINER declines were associated with worsening clinical symptoms and brain volume loss. DiscussionThe NIH-EXAMINER is sensitive to cognitive changes in presymptomatic familial FTLD and is a promising surrogate endpoint.

Age interpretation in eulachon (Thaleichthys pacificus) as suggested by otolith microchemical signatures

Eulachon (Thaleichthys pacificus) are forage fish that play an important role in the ecosystem as prey for many species. Given their continuing population decline, determining accurate ages is necessary for age-structured stock assessments. This study employed microchemistry analysis to identify group differences and help interpret growth zone patterns on otolith surfaces. Specimens were collected off the coast of Oregon, in the coastal areas of Southeast Alaska, and in the southeastern Bering Sea. Laser-ablation inductively-coupled plasma mass spectrometry (LA-ICP-MS) was used to measure elemental ratios in the otoliths along a continuous track from the core to the proximoventral margin. Ba:Ca, Sr:Ca, Zn:Ca, and Mg:Ca signatures suggested that eulachon specimens from three geographic regions are different based on their elemental profiles. For the Oregon specimens, fluctuations in Ba:Ca and Zn:Ca signatures appeared consistent with otolith growth zones and most likely were the result of seasonal coastal upwelling events. Variations in Ba:Ca and Zn:Ca were useful as annual markers for eulachon otoliths from the Bering Sea. For the Southeast Alaska specimens, analysis of the Ba:Ca and Zn:Ca oscillations was not straightforward. Further work is needed to understand the link between otolith microchemistry, fish physiology, and regional environmental factors.

Effects of a Word-Problem Intervention on Word-Problem Language Features for Third-Grade Students with Mathematics Difficulty

Word problems require students to read a language-based problem, identify necessary information to answer a prompt, and perform calculation(s) to develop a problem solution. Solving word problems proves particularly challenging for students with mathematics difficulties because skill in reading, interpretation of language, and mathematics are required for word-problem proficiency. We examined whether two versions of a word-problem intervention increased students’ understanding of three word-problem language features: naming a superordinate category, identifying irrelevant information, and providing a word-problem label. At pre- and posttest, 145 3rd-grade students solved word problems and answered questions about word-problem language. Students who participated in the word-problem interventions demonstrated improvement on identifying irrelevant information and providing word-problem labels over students in the business-as-usual condition. We did not identify group differences related to naming a superordinate category. These results suggest the importance of explicit teaching of language comprehension features within word-problem intervention. Subscribe to LDMJ

Mild traumatic brain injury: The effect of age at trauma onset on brain structure integrity.

Mounting evidence suggests that mild traumatic brain injuries (mTBI) have long-term effects that interact with the aging process to precipitate cognitive decline. This line of research predicts that early exposure to brain trauma is particularly detrimental to long-term brain integrity. However, a second line of research into the effects of age at trauma onset predict that older brains are more vulnerable to the effects of mTBI than younger brains. We sought to determine whether patients who sustain a mTBI earlier in life fare better than patients who sustain a mTBI at an older age. We conducted a multi-cohort, case-control study, with participants randomly sampled from a population of patients with a history of mTBI. We recruited two cohorts of aging participants (N = 74, mean [SD] = 61.16 [6.41]) matched in age and education levels that differed in only one respect: age at mTBI onset. One cohort sustained their concussion in their early twenties (24.60 [6.34] y/o), the other in their early sixties (61.05 [4.90] y/o). Each mTBI cohort had its own matched control group. Participants underwent high-resolution MRI at 3 Tesla for T1 and diffusion-weighted images (DWI) acquisition. Images were processed and analyzed using Deformation-Based Morphometry and DWI Tract-Based Spatial Statistics to identify group differences in a 2 × 2 ANOVA design. Results showed a significant interaction on DWI measures of white matter integrity indicating larger anomalies in participants who sustained a mTBI at a younger age (F1,70, P < .05, FDR corrected). These findings suggest that mTBI initiates a lifelong neurodegeneration process that outweighs the risks associated with sustaining a mTBI at an older age. Implications are important for young athletes' populations exposed to the risk of mTBI in the practice of their sports and for retired athletes aging with a history of concussions sustained at a younger age.

Patterns of care for Multiple Sclerosis in a setting of universal care access: A cross-sectional study

BackgroundCurrent guidelines recommend regular neurological MS care in persons diagnosed with MS, but little is known about implementation of this recommendation or potential access barriers. This study examined disease-specific and sociodemographic differences between MS patients in Neurological Care (NeC), General Practitioner Care (GPC), or no Physician Care (NoPC) to identify group differences and characteristics that may suggest care access barriers. MethodsPatient-reported data were analyzed from 1038 Swiss Multiple Sclerosis Registry participants by means of multivariable regression to identify systematic differences across the three care groups. Assessments included comprehensive data on clinical, sociodemographic, and geographic factors. Results89% reported being in regular care by a neurologist (56% in private practices, 44% in hospitals), 5% were in GPC, and 6% reported No Physician Care (NoPC). Compared with the NeC group, patients not seeing a neurologist included two subgroups, one consisting of persons with a primary progressive MS (PPMS) and/or an extended MS history. The second subgroup included persons with a recent MS diagnosis within the last 2 years.Within the NeC group, the patients seen in private practices were of older age and more frequently female compared to those at clinics, but no differences were detected with regard to disability status, MS type, or treatment patterns. ConclusionsAccess to neurological care is high in Switzerland. Given the emerging paradigm for early treatment and new drugs for progressive MS, regular neurology visits should be promoted among patient groups currently less in neurological care such as persons with PPMS or recently diagnosed.

Developing a dynamic model of anomalous experiences and function in young people with or without psychosis: a cross-sectional and longitudinal study protocol

IntroductionAnomalous experiences are common within the general population, but the frequency and intensity is increased in young people with psychosis. Studies have demonstrated that perceptual biases towards noticing these phenomena...

Reduced local segregation of single-subject gray matter networks in adult PTSD.

To psychoradiologically investigate the topological organization of single-subject gray matter networks in patients with PTSD. Eighty-nine adult PTSD patients and 88 trauma-exposed controls (TEC) underwent a structural T1 magnetic resonance imaging scan. The single-subject brain structural networks were constructed based on gray matter similarity of 90 brain regions. The area under the curve (AUC) of each network metric was calculated and both global and nodal network properties were measured in graph theory analysis. We used nonparametric permutation tests to identify group differences in topological metrics. Relationships between brain network measures and clinical symptom severity were analyzed in the PTSD group. Compared with TEC, brain networks of PTSD patients were characterized by decreased clustering coefficient (Cp ) (p = .04) and local efficiency (Eloc ) (p = .04). Locally, patients with PTSD exhibited altered nodal centrality involving medial superior frontal (mSFG), inferior orbital frontal (iOFG), superior parietal (SPG), middle frontal (MFG), angular, and para-hippocampal gyri (p < .05, corrected). A negative correlation between the segregation (Cp ) of gray matter and functional networks was found in PTSD patients but not the TEC group. Analyses of topological brain gray matter networks indicate a more randomly organized brain network in PTSD. The reduced segregation in gray matter networks and its negative relation with increased segregation in the functional network indicate an inverse relation between gray matter and functional changes. The present psychoradiological findings may reflect a compensatory increase in functional network segregation following a loss of segregation in gray matter networks.

Regional Brain Volume Changes in Alcohol-Dependent Individuals During Short-Term and Long-Term Abstinence.

Widespread brain atrophy in alcohol-dependent individuals (ALC) has been consistently documented in pathological and magnetic resonance imaging (MRI) studies. Longitudinal MRI studies have shown that the regional brain volume losses in ALC are partially reversible during abstinence from alcohol. The goal of this study was to determine volume reductions in cortical and subcortical regions functionally important to substance use behavior and their changes during short-term (1week to 1month) and long-term abstinence (1 to 7months) from alcohol. The regions of interest (ROIs) were as follows: anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), orbitofrontal cortex (OFC), insula, amygdala, and hippocampus. A total of 85 unique ALC were assessed at 1week (n=65), 1month (n=82), and 7months (n=36) of abstinence. In addition, 17 light/nondrinking healthy controls (CON) were assessed at baseline and follow-up over a 10-month interval. Regional brain volumes were derived from FreeSurfer. Cross-sectional statistical analyses using 1-way analysis of variance or Fisher's exact test were applied to identify group differences. Longitudinal statistical analyses using linear mixed models were applied to identify regional volume increases and nonlinear volume recovery trajectories. We demonstrated significant regional volume reductions in ACC, DLPFC, and hippocampus. Older age was associated with smaller DLPFC and OFC, and higher average monthly drinking over 1year prior to study was associated with smaller OFC. We also demonstrated significant volume increases of all ROIs except amygdala in ALC and significant nonlinear volume recovery trajectories of DLPFC, OFC, and insula. Results showed significant volume reductions in key regions of the executive control, salience, and emotion networks in ALC at entry into treatment and significant volume increases during short-term and long-term abstinence that were nonlinear over the entire abstinence period for the DLPFC, OFC, and insula. This gray matter plasticity during alcohol abstinence may have important neurobiological and neurocognitive implications in ALC, and it may contribute to an individual's ability to maintain abstinence from alcohol at different phases.

A comparative study to identify factors of caregiver burden between baby boomers and post baby boomers: a secondary analysis of a US online caregiver survey

BackgroundBaby boomers’ position in the caregiving context is shifting from caregiver to care recipient as the population ages. While the unique characteristics of baby boomer caregivers are well established in caregiving literature, there is limited information about the next caregiving group after the baby boomers. In this study, the sociodemographic and caregiving-related characteristics of the two generations are compared and specific factors contributing to caregiver burden between baby boomer and post baby boomer caregivers are identified.MethodsThis cross-sectional and correlational study used secondary analysis of data from the National Alliance for Caregiving and the American Association of Retired Persons. A structured online survey was conducted in 2014 with randomly selected samples (n = 1069) in the United States focusing on sociodemographics, caregiving-related characteristics, and burden of care. Descriptive statistics, multivariate linear regression analyses, and Steiger’s Z-test were used to identify group differences in multivariate factors related to caregiver burden in two generational groups.ResultsBaby boomers and post baby boomers experienced caregiver burden to a similar degree. Caregiving-related factors are more likely to increase burden of care than sociodemographics in both groups. Caregiving without choice and spending longer hours on caregiving tasks were common factors that increased the burden in both generational groups (all p values < 0.01). However, post baby boomer caregivers reported additional challenges, such as unemployment during caregiving, the dual responsibility of both adult and child care, and a family relationship with the care recipient.ConclusionsDue to the aging population of baby boomers, post baby boomers encounter different challenges related to caregiving burden, which is often considered an additional workload in their life course. Current policy and program tailored to baby boomers should be re-designed to meet the different needs of emerging caregivers. Specific vulnerable subgroups should have priority to receive the benefits of specific policies, such as those without choice and younger, working caregivers.

Lack of Accurate Self-appraisal is Equally Likely in MCI from Parkinson's Disease and Alzheimer's Disease.

How accurate are mild cognitive impairment (MCI) patients in assessing their cognitive and functional deficit is often unclear to the clinician. The accuracy of patient self-appraisal in Parkinson's disease-MCI (PD-MCI) has received less attention than amnestic MCI (a-MCI) often associated with Alzheimer's disease. We evaluated if PD-MCI patients demonstrate accurate self-appraisal of their cognitive deficits compared to patients with amnestic a-MCI or non-amnestic MCI (na-MCI). This cross-sectional cohort study included, 30 PD-MCI, 33 a-MCI, and 17 na-MCI patients. Self-appraisal was assessed by comparing responses of caregivers and patients on a validated self-rating questionnaire of cognitive and functional impairments. All patients completed a full neuropsychological evaluation and depression screening measure. Univariate ANOVA, regression, and correlational analyses were employed to identify group differences in self-appraisal scores and relationships between cognitive and functional impairment, depression measures, and self-appraisal scores. Self-appraisal scores for PD-MCI did not differ significantly from a-MCI and na-MCI. In the PD-MCI group, higher depression scores were associated with lower self-appraisal scores (i.e, patients assessed cognition as worse than caregivers). In a stepwise regression model with self-appraisal scores as the dependent variable, only the depression score was significant predictor among PD-MCI and accounted for 50% of the variance. Our findings suggest that impaired patient self-appraisal is equally likely to occur in PD-MCI as in a-MCI and na-MCI patients. Among PD-MCI, depression was the strongest predictor of impaired patient self-appraisal. Impaired insight into cognitive impairment and depression should be considered in both care and research with PD patients.

Depression is associated with dimensional and categorical effects on white matter pathways.

Diffusion tensor imaging (DTI) studies report reduced fractional anisotropy (FA) in major depressive disorder (MDD). However, whether FA covaries with key depressive symptoms, such as anhedonia, is unclear. Magnetic resonance imaging data were acquired from 38 unmedicated adults with MDD and 52 healthy controls. DTI metrics were extracted from regions of interest that have consistently shown reduced FA in MDD. Analyses focused first on identifying group differences, and then determining whether reduced FA in depressed adults was related to individual differences in anhedonia and depressive severity. To establish specificity to depression, these analyses controlled for symptoms of anxiety. Relative to controls, depressed adults showed reduced FA in the genu of the corpus callosum, the anterior limb of the internal capsule (ALIC), the cingulum bundle near the anterior cingulate cortex, and the uncinate fasciculus (UF). In the depressed group, anhedonia negatively correlated with FA in the genu, cingulum, and UF, but positively correlated with radial diffusivity (RD)-a metric previously linked to demyelination-in the genu and ALIC. Depressive severity positively correlated with RD in the ALIC. These relationships remained significant after accounting for anxiety. Anhedonia was positively correlated with reduced FA and increased RD in white matter pathways that connect regions critical for value coding, representing stimulus-reward associations, and guiding value-based action selection. Thus, a cardinal symptom of MDD-anhedonia-was lawfully related to abnormalities in reward network connectivity.

Disrupted functional network integrity and flexibility after stroke: Relation to motor impairments

Previous studies investigating brain activation present during upper limb movement after stroke have greatly detailed activity alterations in the ipsi- and contralesional primary motor cortices (M1). Despite considerable interest in M1, investigations into the integration and coordination of large-scale functional networks subserving motor, sensory, and cognitive control after stroke remain scarce. The purpose of this study was to assess non-static functional connectivity within whole-brain networks involved in the production of isometric, visually-paced hand grips. Seventeen stroke patients and 24 healthy controls underwent functional MRI while performing a series of 50 isometric hand grips with their affected hand (stroke patients) or dominant hand (control subjects). We used task-based multivariate functional connectivity to derive spatial and temporal information of whole-brain networks specifically underlying hand movement. This technique has the advantage of extracting within-network commonalities across groups and identifying connectivity differences between these groups. We further used a nonparametric statistical approach to identify group differences in regional activity within these task-specific networks and assess whether such alterations were related to the degree of motor impairment in stroke patients. Our whole-brain multivariate analysis revealed group differences in two networks: (1) a motor network, including pre- and postcentral gyri, dorsal and ventral premotor cortices, as well as supplementary motor area, in which stroke patients showed reduced task-related activation compared to controls, and (2) a default-mode network (DMN), including the posterior cingulate cortex, precuneus, and medial prefrontal cortex, in which patients showed less deactivation than controls. Within-network group differences revealed decreased activity in ipsilesional primary sensorimotor cortex in stroke patients, which also positively correlated with lower levels of motor impairment. Moreover, the temporal information extracted from the functional networks revealed that stroke patients did not show a reciprocal DMN deactivation peak following activation of their motor network. This finding suggests that allocation of functional resources to motor areas during hand movement may impair their ability to efficiently switch from one network to another. Taken together, our study expands our understanding of functional reorganization during motor recovery after a stroke, and suggests that modulation of ipsilesional sensorimotor activity may increase the integrity of a whole-brain motor network, contribute to better motor performance, and optimize network flexibility.

A Riemannian Framework for Longitudinal Analysis of Resting-State Functional Connectivity.

Even though the number of longitudinal resting-state-fMRI studies is increasing, accurately characterizing the changes in functional connectivity across visits is a largely unexplored topic. To improve characterization, we design a Riemannian framework that represents the functional connectivity pattern of a subject at a visit as a point on a Riemannian manifold. Geodesic regression across the 'sample' points of a subject on that manifold then defines the longitudinal trajectory of their connectivity pattern. To identify group differences specific to regions of interest (ROI), we map the resulting trajectories of all subjects to a common tangent space via the Lie group action. We account for the uncertainty in choosing the common tangent space by proposing a test procedure based on the theory of latent p-values. Unlike existing methods, our proposed approach identifies sex differences across 246 subjects, each of them being characterized by three rs-fMRI scans.

Cerebral changes and disrupted gray matter cortical networks in asymptomatic older adults at risk for Alzheimer's disease

The diagnostic value of cerebrospinal fluid (CSF) biomarkers is well established in Alzheimer's disease, but our current knowledge about how abnormal CSF levels affect cerebral integrity, at local and network levels, is incomplete in asymptomatic older adults. Here, we have collected CSF samples and performed structural magnetic resonance imaging scans in cognitively normal elderly as part of a cross-sectional multicenter study (SIGNAL project). To identify group differences in cortical thickness, white matter volume, and properties of structural networks, participants were split into controls (N = 20), positive amyloid-β (Aβ1–42+) (N = 19), and positive phosphorylated tau (N = 18). The Aβ1–42+ group exhibited thickening of middle temporal regions, while positive phosphorylated tau individuals showed thinning in the superior parietal and orbitofrontal cortices. Subjects with abnormal CSF biomarkers further showed regional white matter atrophy and more segregated cortical networks, the Aβ1–42+ group showing heightened isolation of cingulate and temporal cortices. Collectively, these findings highlight the relevance of combining structural brain imaging and connectomics for in vivo tracking of Alzheimer's disease lesions in asymptomatic stages.

Graph-based analysis of brain connectivity in schizophrenia

The present study evaluated brain connectivity using electroencephalography (EEG) data from 14 patients with schizophrenia and 14 healthy controls. Phase-Locking Value (PLV), Phase-Lag Index (PLI) and Directed Transfer Function (DTF) were calculated for the original EEG data and following current source density (CSD) transformation, re-referencing using the average reference electrode (AVERAGE) and reference electrode standardization techniques (REST). The statistical analysis of adjacency matrices was carried out using indices based on graph theory. Both CSD and REST reduced the influence of volume conducted currents. The largest group differences in connectivity were observed for the alpha band. Schizophrenic patients showed reduced connectivity strength, as well as a lower clustering coefficient and shorter characteristic path length for both measures of phase synchronization following CSD transformation or REST re-referencing. Reduced synchronization was accompanied by increased directional flow from the occipital region for the alpha band. Following the REST re-referencing, the sources of alpha activity were located at parietal rather than occipital derivations. The results of PLV and DTF demonstrated group differences in fronto-posterior asymmetry following CSD transformation, while for PLI the differences were significant only using REST. The only analysis that identified group differences in inter-hemispheric asymmetry was DTF calculated for REST. Our results suggest that a comparison of different connectivity measures using graph-based indices for each frequency band, separately, may be a useful tool in the study of disconnectivity disorders such as schizophrenia.