Predicting functional impairments with lesion-derived disconnectome mapping: Validation in stroke patients with motor deficits.

Focal structural damage to white matter tracts can result in functional deficits in stroke patients. Traditional voxel-based lesion-symptom mapping is commonly used to localize brain structures linked to neurological deficits. Emerging evidence suggests that the impact of structural focal damage may extend beyond immediate lesion sites. In this study, we present a disconnectome mapping approach based on support vector regression (SVR) to identify brain structures and white matter pathways associated with functional deficits in stroke patients. For clinical validation, we utilized imaging data from 340 stroke patients exhibiting motor deficits. A disconnectome map was initially derived from lesions for each patient. Bootstrap sampling was then employed to balance the sample size between a minority group of patients exhibiting right or left motor deficits and those without deficits. Subsequently, SVR analysis was used to identify voxels associated with motor deficits (p < .005). Our disconnectome-based analysis significantly outperformed alternative lesion-symptom approaches in identifying major white matter pathways within the corticospinal tracts associated with upper-lower limb motor deficits. Bootstrapping significantly increased the sensitivity (80%-87%) for identifying patients with motor deficits, with a minimum lesion size of 32 and 235 mm3 for the right and left motor deficit, respectively. Overall, the lesion-based methods achieved lower sensitivities compared with those based on disconnection maps. The primary contribution of our approach lies in introducing a bootstrapped disconnectome-based mapping approach to identify lesion-derived white matter disconnections associated with functional deficits, particularly efficient in handling imbalanced data.

Flexible-center Hat Complete Electrode Model for EEG Forward Problem.

OBJECTIVE: This study aims to develop a more realistic electrode model by incorporating the non-uniform distribution of electrode contact conductance (ECC) and the shunting effects, to accurately solve EEG forward problem (FP). METHODS: Firstly, a hat function is introduced to construct a more realistic hat-shaped distribution (HD) for ECC. Secondly, this hat function is modified by applying two parameters - offset ratio and offset direction - to account for the variability in ECC's center and to develop the flexible-center HD (FCHD). Finally, by integrating this FCHD into the complete electrode model (CEM) with the shunting effects, a novel flexible-center hat complete electrode model (FCH-CEM) is proposed and used to solve FP. RESULTS: Simulation experiments using a realistic head model demonstrate the necessity of FCHCEM and its potential to improve the accuracy of the FP solution compared to current models, i.e., the point electrode model (PEM) and CEM. And compared to PEM, it has better performance under coarse mesh conditions (2 mm). Further experiments indicate the significance of considering shunting effects, as ignoring them results in larger errors than coarse mesh when the average contact conductance is large (). CONCLUSION: The proposed FCH-CEM has better accuracy and performance than PEM and complements CEM in finer meshes, making it necessary for coarse meshes. SIGNIFICANCE: This study proposes a novel model that enhances electrode modeling and FP accuracy, and provides new ideas and methods for future research.

Age-related differences in structural and resting-state functional brain network organization across the adult lifespan: A cross-sectional study.

We investigated age-related trends in the topology and hierarchical organization of brain structural and functional networks using diffusion-weighted imaging and resting-state fMRI data from a large cohort of healthy aging adults. At the cross-modal level, we explored age-related patterns in the RC involvement of different functional subsystems using a high-resolution functional parcellation. We further assessed age-related differences in the structure-function coupling as well as the network vulnerability to damage to rich club connectivity. Regardless of age, the structural and functional brain networks exhibited a rich club organization and small-world topology. In older individuals, we observed reduced integration and segregation within the frontal-occipital regions and the cerebellum along the brain's medial axis. Additionally, functional brain networks displayed decreased integration and increased segregation in the prefrontal, centrotemporal, and occipital regions, and the cerebellum. In older subjects, structural networks also exhibited decreased within-network and increased between-network RC connectivity. Furthermore, both within-network and between-network RC connectivity decreased in functional networks with age. An age-related decline in structure-function coupling was observed within sensory-motor, cognitive, and subcortical networks. The structural network exhibited greater vulnerability to damage to RC connectivity within the language-auditory, visual, and subcortical networks. Similarly, for functional networks, increased vulnerability was observed with damage to RC connectivity in the cerebellum, language-auditory, and sensory-motor networks. Overall, the network vulnerability decreased significantly in subjects older than 70 in both networks. Our findings underscore significant age-related differences in both brain functional and structural RC connectivity, with distinct patterns observed across the adult lifespan.

Neuroimaging determinants of cognitive impairment in the memory clinic: how important is the vascular burden?

While neurodegenerative and vascular neurocognitive disorder (NCD) often co-occur, the contribution of vascular lesions, especially stroke lesions identified on MRI, to global cognition in a real-life memory clinic population remains unclear. The main objective of this retrospective study was to determine NCD neuroimaging correlates: the GM atrophy pattern and vascular lesions (especially stroke lesion localization by voxel-based lesion-symptom mapping, VLSM) in a memory clinic. We included 336 patients with mild or major NCD who underwent cerebral MRI and a neuropsychological assessment. The GM atrophy pattern (obtained by voxel-based morphometry, VBM) and the stroke lesion localization (obtained by VLSM) associated with G5 z-score (a global cognitive score), were included as independent variables with other neuroimaging and clinical indices in a stepwise linear regression model. The mean age was 70.3 years and the mean MMSE score 21.3. On MRI, 75 patients had at least one stroke lesion. The G 5 z-score was associated with GM density in the pattern selected by the VBM analysis (R2 variation = 0.166, p < 0.001) and the presence of a stroke lesion in the region selected by the VSLM analysis (mainly in the right frontal region; R2 variation = 0.018, p = 0.008). The interaction between the two factors was insignificant (p = 0.374). In conclusion, in this first study combining VBM and VLSM analysis in a memory clinic, global cognition was associated with a specific GM atrophy pattern and the presence of a stroke lesion mainly in the right frontal region.

Assessing the effects of head modelling errors and measurement noise on EEG source localization accuracy in preterm newborns: A single-subject study.

The accuracy of electroencephalogram (EEG) source localization is compromised because of head modelling errors. In this study, we investigated the effect of inaccuracy in the conductivity of head tissues and head model structural deficiencies on the accuracy of EEG source analysis in premature neonates. A series of EEG forward and inverse simulations was performed by introducing structural deficiencies into the reference head models to generate test models, which were then used to investigate head modelling errors caused by cerebrospinal fluid (CSF) exclusion, lack of grey matter (GM)-white matter (WM) distinction, fontanel exclusion and inaccuracy in skull conductivity. The modelling errors were computed between forward and inverse solutions obtained using the reference and test models generated for each deficiency. Our results showed that the exclusion of CSF from the head model had a strong widespread effect on the accuracy of the EEG source localization with position errors lower than 4.17 mm. The GM and WM distinction also caused strong localization errors (up to 3.5 mm). The exclusion of fontanels from the head model also strongly affected the accuracy of the EEG source localization for sources located beneath the fontanels with a maximum localization error of 4.37 mm. Similarly, inaccuracies in the skull conductivity caused errors in EEG forward and inverse modelling in sources beneath cranial bones. Our results indicate that the accuracy of EEG source imaging in premature neonates can be largely improved by using head models, which include not only the brain, skull and scalp but also the CSF, GM, WM and fontanels.

Functional architecture of executive processes: Evidence from verbal fluency and lesion mapping in stroke patients.

The functional organization and related anatomy of executive functions are still largely unknown and were examined in the present study using a verbal fluency task. The objective of this study was to determine the cognitive architecture of a fluency task and related voxelwise anatomy in the GRECogVASC cohort and fMRI based meta-analytical data. First, we proposed a model of verbal fluency in which two control processes, lexico-semantic strategic search process and attention process, interact with semantic and lexico-phonological output processes. This model was assessed by testing 404 patients and 775 controls for semantic and letter fluency, naming, and processing speed (Trail Making test part A). Regression (R2 = .276 and .3, P = .0001, both) and structural equation modeling (CFI: .88, RMSEA: .2, SRMR: .1) analyses supported this model. Second, voxelwise lesion-symptom mapping and disconnectome analyses demonstrated fluency to be associated with left lesions of the pars opercularis, lenticular nucleus, insula, temporopolar region, and a large number of tracts. In addition, a single dissociation showed specific association of letter fluency with the pars triangularis of F3. Disconnectome mapping showed the additional role of disconnection of left frontal gyri and thalamus. By contrast, these analyses did not identify voxels specifically associated with lexico-phonological search processes. Third, meta-analytic fMRI data (based on 72 studies) strikingly matched all structures identified by the lesion approach. These results support our modeling of the functional architecture of verbal fluency based on two control processes (strategic search and attention) operating on semantic and lexico-phonologic output processes. Multivariate analysis supports the prominent role of the temporopolar area (BA 38) in semantic fluency and the F3 triangularis area (BA 45) in letter fluency. Finally, the lack of voxels specifically dedicated to strategic search processes could be due to a distributed organization of executive functions warranting further studies.

Altered brain structural and functional connectivity in cannabis users.

Cannabis is one of the most used and commodified illicit substances worldwide, especially among young adults. The neurobiology mechanism of cannabis is yet to be identified particularly in youth. The purpose of this study was to concurrently measure alterations in brain structural and functional connectivity in cannabis users using resting-state functional magnetic resonance images (rs-fMRI) and diffusion-weighted images (DWI) from a group of 73 cannabis users (age 22-36, 19 female) in comparison with 73 healthy controls (age 22-36, 14 female) from Human Connectome Project (HCP). Several significant differences were observed in local structural/functional network measures (e.g. degree and clustering coefficient), being prominent in the insular and frontal opercular cortex and lateral/medial temporal cortex. The rich-club organization of structural networks revealed a normal trend, distributed within bilateral frontal, temporal and occipital regions. However, minor differences were found between the two groups in the superior and inferior temporal gyri. Functional rich-club nodes were mostly located within parietal and posterior areas, with minor differences between the groups found mainly in the centro-temporal and parietal regions. Regional network measures of structural/functional networks were associated with times used cannabis (TUC) in several regions. Although the structural/functional network in both groups showed small-world property, no differences between cannabis users and healthy controls were found regarding the global network measures, showing no association with cannabis use. After FDR correction, all of the significant associations between network measures and TUC were found to be insignificant, except for the association between degree and TUC within the presubiculum region. To recap, our findings revealed alterations in local topological properties of structural and functional networks in cannabis users, although their global brain network organization remained intact.

Poststroke apathy: Major role of cognitive, depressive and neurological disorders over imaging determinants.

Apathy occurs in approximately one third of people after stroke. Despite its frequency and functional consequences, the determinants of apathy have only been partially defined. The major difficulty lies in disentangling the reduction in activity due to apathy itself from those secondary to comorbidities, such as depression, sensorimotor deficits, and cognitive impairment. Here, we aimed to examine the prevalence of apathy, identify confounding sources of hypoactivity, and define its neuroimaging determinants using multivariate voxel lesion symptom-mapping (mVLSM) analyses. We assessed apathy in a subgroup (n = 325, mean age: 63.8 ± 10.5 years, 91.1% ischemic stroke) of the GRECogVASC cohort using the validated Behavioral Dysexecutive Syndrome Inventory, interpreted using GREFEX criteria, as well as confounding factors (depression, anxiety, severity of the neurological deficit, and gait disorders). mVLSM analysis was used to define neuroimaging determinants and was repeated after controlling for confounding factors. Apathy was present for 120 patients (36.9%, 95% CI: 31.7-42.2). Stepwise linear regression identified three factors associated with apathy: depressive symptoms (R2 = .3, p = .0001), cognitive impairment (R2 = .015, p = .02), and neurological deficit (R2 = .110, p = .0001). Accordingly, only 9 (7.5%) patients had apathy without a confounding factor, i.e., isolated apathy. In conventional VLSM analysis, apathy was associated with a large number of subcortical lesions that were no longer considered after controlling for confounding factors. Strategic site analysis identified five regions associated with isolated apathy: the F3 orbitalis pars, left amygdala, left thalamus, left pallidum, and mesencephalon. mVLSM analysis identified four strategic sites associated with apathy: the right corticospinal tract (R2 = .11; p = .0001), left frontostriatal tract (R2 = .11; p = .0001), left thalamus (R2 = .04; p = .0001), and left amygdala (R2 = .01; p = .013). These regions remained significant after controlling for confounding factors but explained a lower amount of variance. These findings indicate that poststroke apathy is more strongly associated with depression, neurological deficit, and cognitive impairment than with stroke lesions locations, at least using VLSM analysis.

Poststroke action slowing: Motor and attentional impairments and their imaging determinants. Evidence from lesion-symptom mapping, disconnection and fMRI activation studies.

BACKGROUND AND OBJECTIVES: Although action slowing is the main cognitive impairment in stroke survivors, its mechanisms and determinants are still poorly understood. The objectives of the present study were to determine the mechanisms of post-stroke action slowing (using validated, highly specific simple reaction time (SRT) and tapping tests) and identify its imaging determinants (using multivariate lesion-symptom mapping (mLSM)). METHODS: Action speed in the GRECogVASC cohort was assessed using finger tapping and SRT tests performed with both hands and analyzed using previously validated indices. Imaging determinants were identified using validated mLSM analyses and disconnection analysis and compared to those of an fMRI activation meta-analytic database. RESULTS: Both the tapping time and SRT were 10.7% slower for the 394 patients (p = 0.0001) than for the 786 controls, without a group × test interaction (p = 0.2). The intra-individual distribution curve was characterized by a rightward shift with an unaltered attentional peak. The mLSM analyses showed tapping to be associated with lesions in the frontostriatal tract (p = 0.0007). The SRT was associated with lesions in the frontostriatal tract (p = 0.04) and the orbital part of F3 (p = 0.0001). The SRT-tapping index was associated with lesions in the orbital part of F3 (p = 0.0001). All lesions were located in the right hemisphere only and were responsible for the disconnection of several structures involved in motor preparation, initiation, and speed. A comparison with fMRI activation meta-analytic data highlighted mostly the same regions, including the orbital part of F3, the ventral and dorsal parts of F1, and the premotor and cingulate regions in the right hemisphere. DISCUSSION: Our results confirm the marked impairment of action speed in stroke and show that the primary mechanism is motor slowing and that it is related to lesions in the right frontostriatal tract. A deficit in sustained alertness accounted for action slowing in the subgroup with lesions in the right orbital part of F3. Our SRT and mLSM results were in accordance with the fMRI activation data. Thus, stroke induces slowing in the broad network associated with SRT tasks by disrupting the frontostriatal tract and, to a lesser extent, other sites involved in attention.

Clinical and Imaging Determinants of Neurocognitive Disorders in Post-Acute COVID-19 Patients with Cognitive Complaints.

BACKGROUND: Neurocognitive disorders (NCDs) are a part of the post-acute coronavirus disease (COVID-19) syndrome. No study has specifically evaluated NCDs in post-acute COVID-19 patients with cognitive complaints or their MRI determinants. OBJECTIVE: To characterize NCDs in post-acute COVID-19 patients with cognitive complaints. The secondary objectives were to assess their clinical and MRI determinants. METHODS: We included 46 patients with a post-acute COVID-19 cognitive complaint referred to the Amiens University Hospital Memory Center. They underwent a neuropsychological assessment and 36 had cerebral MRI. The G3 overall summary score was the sum of the mean z scores for the executive function, language, and action speed domains. Neuropsychological profiles were compared in a general linear model. Clinical determinants were analyzed by stepwise linear regression. White matter hyperintensities (WMH) masks were analyzed using parcel-based WMH symptom mapping to identify the locations of WMHs associated with cognitive performance. RESULTS: Repeated ANOVA showed a group effect (p = 0.0001) due to overall lower performance for patients and a domain effect (p = 0.0001) due to a lower (p = 0.007) action speed score. The G3 overall summary score was significantly associated with solely the requirement for oxygen (R2 = 0.319, p = 0.031). WHMs were associated with the G3 overall summary score in the following structures, all right-sided (p < 0.01): superior frontal region, postcentral region, cingulum, cortico-spinal tract, inferior longitudinal fasciculus, internal capsule, and posterior segment of the arcuate fasciculus. CONCLUSION: Post-acute COVID-19 patients with cognitive complaints had NCD, with prominent action slowing, significantly associated with the acute phase oxygen requirement and a right-sided WMH structure pattern.

Brain Dynamics and Connectivity from Birth through Adolescence.

The human brain as a complex dynamic system undergoes significant structural and functional changes from birth to adulthood to engender neurocognitive functions [...].

Determinants of disability at 6 months after stroke: The GRECogVASC Study.

BACKGROUND AND PURPOSE: The aim of this study was to determine the contributions of background disorders responsible for participation restriction as indexed by a structured interview for the modified Rankin Scale (mRS-SI). METHODS: A subset of 256 patients was assessed at 6 months after stroke using the National Institutes of Health Stroke Scale (NIHSS), gait score, comprehensive cognitive battery (yielding a global cognitive Z-score), behavioral dysexecutive disorders (DDs), anxiety and depressive symptoms, epilepsy, and headache. Following bivariate analyses, determinants of participation restriction were selected using ordinal regression analysis with partial odds. RESULTS: Poststroke participation restriction (mRS-SI score > 1) was observed in 59% of the patients. In bivariate analyses, mRS-SI score was associated with prestroke mRS-SI score, 6-month NIHSS score, gait score, global cognitive Z-score, behavioral DDs, and presence of anxiety and depression (all: p = 0.0001; epilepsy: p =0.3; headache: p = 0.7). After logistic regression analysis, NIHSS score was associated with increasing mRS-SI score (p = 0.00001). Prestroke mRS-SI score (p = 0.00001), behavioral DDs (p = 0.0008) and global cognitive Z-score (p = 0.01) were associated with both mRS-SI score > 1 and mRS-SI score > 2. In addition, gait score was associated with mRS-SI score > 2 (p = 0.00001). This model classified 85% of mRS-SI scores correctly (p = 0.001). Structural equation modeling showed the contributions of gait limitation (standardized coefficient [SC]: 0.68; p = 0.01), prestroke mRS-SI (SC: 0.41; p = 0.01), severity of neurological impairment (SC: 0.16; p = 0.01), global cognitive Z-score (SC: -0.14; p = 0.05), and behavioral DDs (SC: 0.13; p = 0.01). CONCLUSION: These results provide a statistical model of weights of determinants responsible for poststroke participation restriction and highlight a new independent determinant: behavioral DDs.

Temporally dynamic neural correlates of drug cue reactivity, response inhibition, and methamphetamine-related response inhibition in people with methamphetamine use disorder.

Cue-induced drug craving and disinhibition are two essential components of continued drug use and relapse in substance use disorders. While these phenomena develop and interact across time, the temporal dynamics of their underlying neural activity remain under-investigated. To explore these dynamics, an analysis of time-varying activation was applied to fMRI data from 62 men with methamphetamine use disorder in their first weeks of recovery in an abstinence-based treatment program. Using a mixed block-event, factorial cue-reactivity/Go-NoGo task and a sliding window across the task duration, dynamically-activated regions were identified in three linear mixed effects models (LMEs). Habituation to drug cues across time was observed in the superior temporal gyri, amygdalae, left hippocampus, and right precuneus, while response inhibition was associated with the sensitization of temporally-dynamic activations across many regions of the inhibitory frontoparietal network. Methamphetamine-related response inhibition was associated with temporally-dynamic activity in the parahippocampal gyri and right precuneus (corrected p-value < 0.001), which show a declining cue-reactivity contrast and an increasing response inhibition contrast. Overall, the declining craving-related activations (habituation) and increasing inhibition-associated activations (sensitization) during the task duration suggest the gradual recruitment of response inhibitory processes and a concurrent habituation to drug cues in areas with temporally-dynamic methamphetamine-related response inhibition. Furthermore, temporally dynamic cue-reactivity and response inhibition were correlated with behavioral and clinical measures such as the severity of methamphetamine use and craving, impulsivity and inhibitory task performance. This exploratory study demonstrates the time-variance of the neural activations undergirding cue-reactivity, response inhibition, and response inhibition during exposure to drug cues, and suggests a method to assess this dynamic interplay. Analyses that can capture temporal fluctuations in the neural substrates of drug cue-reactivity and response inhibition may prove useful for biomarker development by revealing the rate and pattern of sensitization and habituation processes, and may inform mixed cue-exposure intervention paradigms which could promote habituation to drug cues and sensitization in inhibitory control regions.

Disrupted Functional Rich-Club Organization of the Brain Networks in Children with Attention-Deficit/Hyperactivity Disorder, a Resting-State EEG Study.

Growing evidence indicates that disruptions in the brain's functional connectivity play an important role in the pathophysiology of ADHD. The present study investigates alterations in resting-state EEG source connectivity and rich-club organization in children with inattentive (ADHDI) and combined (ADHDC) ADHD compared with typically developing children (TD) under the eyes-closed condition. EEG source analysis was performed by eLORETA in different frequency bands. The lagged phase synchronization (LPS) and graph theoretical metrics were then used to examine group differences in the topological properties and rich-club organization of functional networks. Compared with the TD children, the ADHDI children were characterized by a widespread significant decrease in delta and beta LPS, as well as increased theta and alpha LPS in the left frontal and right occipital regions. The ADHDC children displayed significant increases in LPS in the central, temporal and posterior areas. Both ADHD groups showed small-worldness properties with significant increases and decreases in the network degree in the θ and ß bands, respectively. Both subtypes also displayed reduced levels of network segregation. Group differences in rich-club distribution were found in the central and posterior areas. Our findings suggest that resting-state EEG source connectivity analysis can better characterize alterations in the rich-club organization of functional brain networks in ADHD patients.

Morphological active contour model for automatic brain tumor extraction from multimodal magnetic resonance images.

BACKGROUND: Brain tumor extraction from magnetic resonance (MR) images is challenging due to variations in the location, shape, size and intensity of tumors. Manual delineation of brain tumors from MR images is time-consuming and prone to human errors. METHOD: In this paper, we present a method for automatic tumor extraction from multimodal MR images. Brain tumors are first detected using k-means clustering. A morphological region-based active contour model is then used for tumor extraction using an initial contour defined based on the boundary of the detected brain tumor regions. The contour evolution for tumor extraction was performed using successive application of morphological operators. In our model, a Gaussian distribution was used to model local image intensities. The spatial correlation between neighboring voxels was also modeled using Markov random field. RESULTS: The proposed method was evaluated on BraTS 2013 dataset including patients with high-grade and low-grade tumors. In comparison with other active contour based methods, the proposed method yielded better performance on tumor segmentation with mean Dice similarity coefficients of 0.9179 ( ±â€¯0.025) and 0.8910 ( ±â€¯0.042) obtained on high-grade and low-grade tumors, respectively. CONCLUSION: The proposed method achieved higher accuracies for brain tumor extraction in comparison to other contour-based methods.

Resting state dynamic functional connectivity in children with attention deficit/hyperactivity disorder.

Attention deficit/hyperactivity disorder (ADHD) is characterized by inattention, hyperactivity and impulsivity. In this study, we investigated group differences in dynamic functional connectivity (dFC) between 113 children with inattentive (46 ADHDI) and combined (67 ADHDC) ADHD and 76 typically developing (TD) children using resting-state functional MRI data. For dynamic connectivity analysis, the data were first decomposed into 100 independent components, among which 88 were classified into eight well-known resting-state networks (RSNs). Three discrete FC states were then identified using k-means clustering and used to estimate transition probabilities between states in both patient and control groups using a hidden Markov model. Our results showed state-dependent alterations in intra and inter-network connectivity in both ADHD subtypes in comparison with TD. Spending less time than healthy controls in state 1, both ADHDIand ADHDCwere characterized with weaker intra-hemispheric connectivity with functional asymmetries. In this state, ADHDIfurther showed weaker inter-hemispheric connectivity. The patients spent more time in state 2, exhibiting characteristic abnormalities in corticosubcortical and corticocerebellar connectivity. In state 3, a less frequently state observed across the ADHD and TD children, ADHDCwas differentiated from ADHDIby significant alterations in FC between bilateral temporal regions and other brain areas in comparison with TD. Across all three states, several strategic brain regions, mostly bilateral, exhibited significant alterations in both static functional connectivity (sFC) and dFC in the ADHD groups compared to TD, including inferior, middle and superior temporal gyri, middle frontal gyri, insula, anterior cingulum cortex, precuneus, calcarine, fusiform, superior motor area, and cerebellum. Our results show distributed abnormalities in sFC and dFC between different large-scale RSNs including cortical and subcortical regions in both ADHD subtypes compared to TD. Our findings show that the dynamic changes in brain FC can better explain the underlying pathophysiology of ADHD such as deficits in visual cognition, attention, memory and emotion processing, and cognitive and motor control.

Effect of Multishell Diffusion MRI Acquisition Strategy and Parcellation Scale on Rich-Club Organization of Human Brain Structural Networks.

The majority of network studies of human brain structural connectivity are based on single-shell diffusion-weighted imaging (DWI) data. Recent advances in imaging hardware and software capabilities have made it possible to acquire multishell (b-values) high-quality data required for better characterization of white-matter crossing-fiber microstructures. The purpose of this study was to investigate the extent to which brain structural organization and network topology are affected by the choice of diffusion magnetic resonance imaging (MRI) acquisition strategy and parcellation scale. We performed graph-theoretical network analysis using DWI data from 35 Human Connectome Project subjects. Our study compared four single-shell (b = 1000, 3000, 5000, 10,000 s/mm2) and multishell sampling schemes and six parcellation scales (68, 200, 400, 600, 800, 1000 nodes) using five graph metrics, including small-worldness, clustering coefficient, characteristic path length, modularity and global efficiency. Rich-club analysis was also performed to explore the rich-club organization of brain structural networks. Our results showed that the parcellation scale and imaging protocol have significant effects on the network attributes, with the parcellation scale having a substantially larger effect. Regardless of the parcellation scale, the brain structural networks exhibited a rich-club organization with similar cortical distributions across the parcellation scales involving at least 400 nodes. Compared to single b-value diffusion acquisitions, the deterministic tractography using multishell diffusion imaging data consisting of shells with b-values higher than 5000 s/mm2 resulted in significantly improved fiber-tracking results at the locations where fiber bundles cross each other. Brain structural networks constructed using the multishell acquisition scheme including high b-values also exhibited significantly shorter characteristic path lengths, higher global efficiency and lower modularity. Our results showed that both parcellation scale and sampling protocol can significantly impact the rich-club organization of brain structural networks. Therefore, caution should be taken concerning the reproducibility of connectivity results with regard to the parcellation scale and sampling scheme.

Multi-scale structural rich-club organization of the brain in full-term newborns: a combined DWI and fMRI study.

Objective.Our understanding of early brain development is limited due to rapid changes in white matter pathways after birth. In this study, we introduced a multi-scale cross-modal approach to investigate the rich club (RC) organization and topology of the structural brain networks in 40 healthy neonates using diffusion-weighted imaging and resting-state fMRI data.Approach.A group independent component analysis was first performed to identify eight resting state networks (RSNs) used as functional modules. A groupwise whole-brain functional parcellation was also performed at five scales comprising 100-900 parcels. The distribution of RC nodes was then investigated within and between the RSNs. We further assessed the distribution of short and long-range RC, feeder and local connections across different parcellation scales.Main results.Sharing the scale-free characteristic of small-worldness, the neonatal structural brain networks exhibited an RC organization at different nodal scales (NSs). The subcortical, sensory-motor and default mode networks were found to be strongly involved in the RC organization of the structural brain networks, especially in the zones where the RSNs overlapped, with an average cross-scale proportion of 45.9%, 28.5% and 10.5%, respectively. A large proportion of the connector hubs were found to be RC members for the coarsest (73%) to finest (92%) NSs. Our results revealed a prominent involvement of cortico-subcortical and cortico-cerebellar white matter pathways in the RC organization of the neonatal brain. Regardless of the NS, the majority (more than 65.2%) of the inter-RSN connections were long distance RC or feeder with an average physical connection of 105.5 and 97.4 mm, respectively. Several key RC regions were identified, including the insula and cingulate gyri, middle and superior temporal gyri, hippocampus and parahippocampus, fusiform gyrus, precuneus, superior frontal and precentral gyri, calcarine fissure and lingual gyrus.Significance.Our results emphasize the importance of the multi-scale connectivity analysis in assessing the cross-scale reproducibility of the connectivity results concerning the global and local topological properties of the brain networks. Our findings may improve our understanding of the early brain development.

Sexual Dimorphisms and Asymmetries of the Thalamo-Cortical Pathways and Subcortical Grey Matter of Term Born Healthy Neonates: An Investigation with Diffusion Tensor MRI.

Diffusion-tensor-MRI was performed on 28 term born neonates. For each hemisphere, we quantified separately the axial and the radial diffusion (AD, RD), the apparent diffusion coefficient (ADC) and the fractional anisotropy (FA) of the thalamo-cortical pathway (THC) and four structures: thalamus (TH), putamen (PT), caudate nucleus (CN) and globus-pallidus (GP). There was no significant difference between boys and girls in either the left or in the right hemispheric THC, TH, GP, CN and PT. In the combined group (boys + girls) significant left greater than right symmetry was observed in the THC (AD, RD and ADC), and TH (AD, ADC). Within the same group, we reported left greater than right asymmetry in the PT (FA), CN (RD and ADC). Different findings were recorded when we split the group of neonates by gender. Girls exhibited right > left AD, RD and ADC in the THC and left > right FA in the PT. In the group of boys, we observed right > left RD and ADC. We also reported left > right FA in the PT and left > right RD in the CN. These results provide insights into normal asymmetric development of sensory-motor networks within boys and girls.

Sleep Spindle Characteristics in Obstructive Sleep Apnea Syndrome (OSAS).

Background: We compared the density and duration of sleep spindles topographically in stage 2 and 3 of non-rapid eye movement sleep (N2 and N3) among adults diagnosed with Obstructive Sleep Apnea Syndrome (OSAS) and healthy controls. Materials and Methods: Thirty-one individuals with OSAS (mean age: 48.50 years) and 23 healthy controls took part in the study. All participants underwent a whole night polysomnography. Additionally, those with OSAS were divided into mild, moderate and severe cases of OSAS. Results: For N2, sleep spindle density did not significantly differ between participants with and without OSAS, or among those with mild, moderate and severe OSAS. For N3, post-hoc analyses revealed significantly higher spindle densities in healthy controls and individuals with mild OSAS than in those with moderate or severe OSAS. Last, in N2 a higher AHI was associated with a shorter sleep spindle duration. Conclusion: OSAS is associated with a significantly lower spindle density in N3 and a shorter spindle duration in N2. Our results also revealed that, in contrast to moderate and severe OSAS, the sleep spindle characteristics of individuals with mild OSAS were very similar to those of healthy controls.