Inter-hemispheric functional connectivity changes with corpus callosum morphology in multiple sclerosis

From Genetics to Function: the Role of ABCA12 in Autism Neurobiology

ASD is a complex neurodevelopmental disorder with genetic, environmental, and molecular roots. Among the thousands of genes that have been associated with ASD, one critical factor has emerged as ABCA12, which plays an important role in lipid transport and metabolism. Traditionally, it has been related to skin disorders but has only recently been implicated in broader brain development and function. Some of the implicated effects include dysregulated lipid homeostasis, neuroinflammation, oxidative stress, and abnormalities in synaptic when the ABCA12 system is dysregulated. All the above processes are related to pathology in ASD. In this review, the emerging function of ABCA12 in autism neurobiology has been discussed; the core base is derived from in vivo models and preclinical studies. In vivo models such as mice and zebrafish that, in the previous studies had earlier shown impairments of ABCA12 which results in social deficiency behaviors but also perform repetitive actions. Based on the effects of the gene on molecular pathways, including neuronal signalling and membrane integrity, and identifying therapeutic approaches targeting ABCA12 or its downstream effects, preclinical studies have contributed to the integration of genetic, functional, and therapeutic perspectives for understanding the contribution of ABCA12 to ASD. These findings may unlock further investigations geared toward unravelling how lipid metabolism intricately influences neurodevelopment with regards to interventions available for use in ASD.

Feasibility of source-level motor imagery classification for people with multiple sclerosis

Objective.There is limited work investigating brain-computer interface (BCI) technology in people with multiple sclerosis (pwMS), a neurodegenerative disorder of the central nervous system. Present work is limited to recordings at the scalp, which may be significantly altered by changes within the cortex due to volume conduction. The recordings obtained from the sensors, therefore, combine disease-related alterations and task-relevant neural signals, as well as signals from other regions of the brain that are not relevant. The current study aims to unmix signals affected by multiple sclerosis (MS) progression and BCI task-relevant signals using estimated source activity to improve classification accuracy.Approach.Data was collected from eight participants with a range of MS severity and ten neurotypical participants. This dataset was used to report the classification accuracy of imagined movements of the hands and feet at the sensor-level and the source-level in the current study.K-means clustering of equivalent current dipoles was conducted to unmix temporally independent signals. The location of these dipoles was compared between MS and control groups and used for classification of imagined movement. Linear discriminant analysis classification was performed at each time-frequency point to highlight differences in frequency band delay.Main Results.Source-level signal acquisition significantly improved decoding accuracy of imagined movement vs rest and movement vs movement classification in pwMS and controls. There was no significant difference found in alpha (7-13 Hz) and beta (13-30 Hz) band classification delay between the neurotypical control and MS group, including imagery of limbs with weakness or paralysis.Significance.This study is the first to demonstrate the advantages of source-level analysis for BCI applications in pwMS. The results highlight the potential for enhanced clinical outcomes and emphasize the need for longitudinal studies to assess the impact of MS progression on BCI performance, which is crucial for effective clinical translation of BCI technology.

The corpus callosum in people with congenital adrenal hyperplasia (CAH)

Congenital Adrenal Hyperplasia (CAH) is a group of genetic disorders that affect the adrenal glands. CAH manifests in abnormal levels of cortisol and androgens and is accompanied by white matter alterations. However, no CAH study has specifically targeted the corpus callosum, the brain's largest white matter fiber tract. To bridge that gap in the literature, we investigated callosal morphology in 53 individuals with CAH and 53 matched controls (66 women, 40 men). In addition to calculating areas for seven callosal subsections, we estimated the callosal thickness at 100 equidistant points. All statistical analyses were conducted while co-varying for age and total brain volume and applying corrections for multiple comparisons. There were no significant effects of biological sex and no significant group-by-sex interactions. However, there was a significant effect of group, both for area measures and thickness estimates, indicating smaller dimensions within the callosal splenium and isthmus in people with CAH. Our findings corroborate previous studies highlighting white matter alterations in CAH and may suggest that callosal integrity is compromised due to potentially adverse effects of glucocorticoids, a standard treatment for both men and women with CAH.

The contribution of EEG to assess and treat motor disorders in multiple sclerosis

OBJECTIVE

Electroencephalography (EEG) can highlight significant changes in spontaneous electrical activity of the brain produced by altered brain network connectivity linked to inflammatory demyelinating lesions and neuronal loss occurring in multiple sclerosis (MS). In this review, we describe the main EEG findings reported in the literature to characterize motor network alteration in term of local activity or functional connectivity changes in patients with MS (pwMS).

METHODS

A comprehensive literature search was conducted to include articles with quantitative analyses of resting-state EEG recordings (spectrograms or advanced methods for assessing spatial and temporal dynamics, such as coherence, theory of graphs, recurrent quantification, microstates) or dynamic EEG recordings during a motor task, with or without connectivity analyses.

RESULTS

In this systematic review, we identified 26 original articles using EEG in the evaluation of MS-related motor disorders. Various resting or dynamic EEG parameters could serve as diagnostic biomarkers of motor control impairment to differentiate pwMS from healthy subjects or be related to a specific clinical condition (fatigue) or neuroradiological aspects (lesion load).

CONCLUSIONS

We highlight some key EEG patterns in pwMS at rest and during movement, both suggesting an alteration or disruption of brain connectivity, more specifically involving sensorimotor networks.

SIGNIFICANCE

Some of these EEG biomarkers of motor disturbance could be used to design future therapeutic strategies in MS based on neuromodulation approaches, or to predict the effects of motor training and rehabilitation in pwMS.

Effects on Corticospinal Tract Homology of Faremus Personalized Neuromodulation Relieving Fatigue in Multiple Sclerosis: A Proof-of-Concept Study

Objectives: Fatigue in multiple sclerosis (MS) is a frequent and invalidating symptom, which can be relieved by non-invasive neuromodulation, which presents only negligible side effects. A 5-day transcranial direct-current stimulation, 15 min per day, anodically targeting the somatosensory representation of the whole body against a larger occipital cathode was efficacious against MS fatigue (fatigue relief in multiple sclerosis, Faremus treatment). The present proof-of-concept study tested the working hypothesis that Faremus S1 neuromodulation modifies the homology of the dominant and non-dominant corticospinal (CST) circuit recruitment. Methods: CST homology was assessed via the Fréchet distance between the morphologies of motor potentials (MEPs) evoked by transcranial magnetic stimulation in the homologous left- and right-hand muscles of 10 fatigued MS patients before and after Faremus. Results: In the absence of any change in MEP features either as differences between the two body sides or as an effect of the treatment, Faremus changed in physiological direction the CST’s homology. Faremus effects on homology were more evident than recruitment changes within the dominant and non-dominant sides. Conclusions: The Faremus-related CST changes extend the relevance of the balance between hemispheric homologs to the homology between body sides. With this work, we contribute to the development of new network-sensitive measures that can provide new insights into the mechanisms of neuronal functional patterning underlying relevant symptoms.

Associations between corpus callosum damage, clinical disability, and surface-based homologous inter-hemispheric connectivity in multiple sclerosis

Axonal damage in the corpus callosum is prevalent in multiple sclerosis (MS). Although callosal damage is associated with disrupted functional connectivity between hemispheres, it is unclear how this relates to cognitive and physical disability. We investigated this phenomenon using advanced measures of microstructural integrity in the corpus callosum and surface-based homologous inter-hemispheric connectivity (sHIC) in the cortex. We found that sHIC was significantly decreased in primary motor, somatosensory, visual, and temporal cortical areas in a group of 36 participants with MS (29 relapsing-remitting, 4 secondary progressive MS, and 3 primary-progressive MS) compared with 42 healthy controls (cluster level, p < 0.05). In participants with MS, global sHIC correlated with fractional anisotropy and restricted volume fraction in the posterior segment of the corpus callosum (r = 0.426, p = 0.013; r = 0.399, p = 0.020, respectively). Lower sHIC, particularly in somatomotor and posterior cortical areas, was associated with cognitive impairment and higher disability scores on the Expanded Disability Status Scale (EDSS). We demonstrated that higher levels of sHIC attenuated the effects of posterior callosal damage on physical disability and cognitive dysfunction, as measured by the EDSS and Brief Visuospatial Memory Test-Revised (interaction effect, p < 0.05). We also observed a positive association between global sHIC and years of education (r = 0.402, p = 0.018), supporting the phenomenon of "brain reserve" in MS. Our data suggest that preserved sHIC helps prevent cognitive and physical decline in MS.

Individual variability in the nonlinear development of the corpus callosum during infancy and toddlerhood: a longitudinal MRI analysis

The human brain spends several years bootstrapping itself through intrinsic and extrinsic modulation, thus gradually developing both spatial organization and functions. Based on previous studies on developmental patterns and inter-individual variability of the corpus callosum (CC), we hypothesized that inherent variations of CC shape among infants emerge, depending on the position within the CC, along the developmental timeline. Here we used longitudinal magnetic resonance imaging data from infancy to toddlerhood and investigated the area, thickness, and shape of the midsagittal plane of the CC by applying multilevel modeling. The shape characteristics were extracted using the Procrustes method. We found nonlinearity, region-dependency, and inter-individual variability, as well as intra-individual consistencies, in CC development. Overall, the growth rate is faster in the first year than in the second year, and the trajectory differs between infants; the direction of CC formation in individual infants was determined within six months and maintained to two years. The anterior and posterior subregions increase in area and thickness faster than other subregions. Moreover, we clarified that the growth rate of the middle part of the CC is faster in the second year than in the first year in some individuals. Since the division of regions exhibiting different tendencies coincides with previously reported divisions based on the diameter of axons that make up the region, our results suggest that subregion-dependent individual variability occurs due to the increase in the diameter of the axon caliber, myelination partly due to experience and axon elimination during the early developmental period.

The brain network organization during sleep onset after deprivation

OBJECTIVE

Aim of the present study is to investigate the alterations of brain networks derived from EEG analysis in pre- and post-sleep onset conditions after 40 h of sleep deprivation (SD) compared to sleep onset after normal sleep in 39 healthy subjects.

METHODS

Functional connectivity analysis was made on electroencelographic (EEG) cortical sources of current density and small world (SW) index was evaluated in the EEG frequency bands (delta, theta, alpha, sigma and beta).

RESULTS

Comparing pre- vs. post-sleep onset conditions after a night of SD a significant decrease of SW in delta and theta bands in post-sleep onset condition was found together with an increase of SW in sigma band. Comparing pre-sleep onset after sleep SD versus pre-sleep onset after a night of normal sleep a decreased of SW index in beta band in pre-sleep onset in SD compared to pre-sleep onset in normal sleep was evidenced.

CONCLUSIONS

Brain functional network architecture is influenced by the SD in different ways. Brain networks topology during wake resting state needs to be further explored to reveal SD-related changes in order to prevent possible negative effects of SD on behaviour and brain function during wakefulness.

SIGNIFICANCE

The SW modulations as revealed by the current study could be used as an index of an altered balance between brain integration and segregation processes after SD.

Detection of functional connectivity in the brain during visuo-guided grip force tracking tasks: A functional near-infrared spectroscopy study

The functional connectivity (FC) between multiple brain regions during tasks is currently gradually being explored with functional near-infrared spectroscopy (fNIRS). However, the FC present during grip force tracking tasks performed under visual feedback remains unclear. In the present study, we used fNIRS to measure brain activity during resting states and grip force tracking tasks at 25%, 50%, and 75% of maximum voluntary contraction (MVC) in 11 healthy subjects, and the activity was measured from four target brain regions: the left prefrontal cortex (lPFC), right prefrontal cortex (rPFC), left sensorimotor cortex (lSMC), and right sensorimotor cortex (rSMC). We determined the FC between these regions utilizing three different methods: Pearson's correlation method, partial correlation method, and a pairwise maximum entropy model (MEM). The results showed that the FC of lSMC-rSMC and lPFC-rPFC (interhemispheric homologous pairs) were significantly stronger than those of other brain region pairs. Moreover, FC of lPFC-rPFC was strengthened during the 75% MVC task compared to the other task states and the resting states. The FC of lSMC-lPFC and rSMC-rPFC (intrahemispheric region pairs) strengthened with a higher task load. The results provided new insights into the FC between brain regions during visuo-guided grip force tracking tasks.

Both Stationary and Dynamic Functional Interhemispheric Connectivity Are Strongly Associated With Performance on Cognitive Tests in Multiple Sclerosis

Although functional connectivity has been extensively studied in MS, robust estimates of both stationary (static connectivity at the time) and dynamic (connectivity variation across time) functional connectivity has not been commonly evaluated and neither has its association to cognition. In this study, we focused on interhemispheric connections as previous research has shown links between anatomical homologous connections and cognition. We examined functional interhemispheric connectivity (IC) in MS during resting-state functional MRI using both stationary and dynamic strategies and related connectivity measures to processing speed performance. Twenty-five patients with relapsing-remitting MS and 41 controls were recruited. Stationary functional IC was assessed between homologous Regions of Interest (ROIs) using correlation. For dynamic IC, a sliding window approach was used to quantify changes between homologous ROIs across time. We related IC measures to cognitive performance with correlation and regression. Compared to control subjects, MS demonstrated increased IC across homologous regions, which accurately predicted performance on the symbol digit modalities test (SDMT) (R ² = 0.96) and paced auditory serial addition test (PASAT) (R ² = 0.59). Dynamic measures were not different between the 2 groups, but dynamic IC was related to PASAT scores. The associations between stationary/dynamic connectivity and cognitive tests demonstrated that different aspects of functional IC were associated with cognitive processes. Processing speed measured in SDMT was associated with static interhemispheric connections and better PASAT performance, which requires working memory, sustain attention, and processing speed, was more related to rigid IC, underlining the neurophysiological mechanism of cognition in MS.

Transcallosal Control of Bilateral Actions

The corpus callosum is an important neural structure for controlling and coordinating bilateral movements of the upper limbs; however, there remains a substantial lack of knowledge regarding its association with lower limb control. We argue that transcallosal structure is an integral neural mechanism underlying control of the lower limbs and callosal degradation is a key contributor to mobility declines.

Fatigue in multiple sclerosis: Does the functional or structural damage prevail?

Fatigue in multiple sclerosis (MS) is a highly invalidating symptom, lacking efficacious drugs. This topical review aims at assessing the signs in the literature of functional versus structural damage prevalence at the origin of MS fatigue by focusing on papers that assessed the two counterparts in the same patients, paying attention that the fatigue levels do not correlate with clinical severity. We summarize and discuss evidence of increased levels of fatigue occurring together with the alterations of functional connectivity at multiple levels, in the absence of any relationship with lesion load and local atrophy of the involved structures. Specifically, neuronal communication mainly altered in the corticomuscular synchronizations, between hemispheric homologs and in the resting-state networks involved in emotion (cingulate cortex) and effort-reward balance (striatum and inferior parietal lobule). Finally, given the functional prevalence in neuronal network alterations at the origin of fatigue in MS, we highlight the relevance of developing treatments aiming at compensating the neuronal electric communication dysfunctions.

Combined structural and functional patterns discriminating upper limb motor disability in multiple sclerosis using multivariate approaches

A structural or functional pattern of neuroplasticity that could systematically discriminate between people with impaired and preserved motor performance could help us to understand the brain networks contributing to preservation or compensation of behavior in multiple sclerosis (MS). This study aimed to (1) investigate whether a machine learning-based technique could accurately classify MS participants into groups defined by upper extremity function (i.e. motor function preserved (MP) vs. motor function impaired (MI)) based on their regional grey matter measures (GMM, cortical thickness and deep grey matter volume) and inter-regional functional connection (FC), (2) investigate which features (GMM, FC, or GMM + FC) could classify groups more accurately, and (3) identify the multivariate patterns of GMM and FCs that are most discriminative between MP and MI participants, and between each of these groups and the healthy controls (HCs). With 26 MP, 25 MI, and 21 HCs (age and sex matched) underwent T1-weighted and resting-state functional MRI at 3 T, we applied support vector machine (SVM) based classification to learn discriminant functions indicating regions in which GMM or between which FCs were most discriminative between groups. This study demonstrates that there exist structural and FC patterns sufficient for correct classification of upper limb motor ability of people with MS. The classifier with GMM + FC features yielded the highest accuracy of 85.61 % (p < 0.001) to distinguish between the MS groups using leave-one-out cross-validation. It suggests that a machine-learning approach combining structural and functional features is useful for identifying the specific neural substrates that are necessary and sufficient to preserve motor function among people with MS.

How changes in brain activity and connectivity are associated with motor performance in people with MS

People with multiple sclerosis (MS) exhibit pronounced changes in brain structure, activity, and connectivity. While considerable work has begun to elucidate how these neural changes contribute to behavior, the heterogeneity of symptoms and diagnoses makes interpretation of findings and application to clinical practice challenging. In particular, whether MS related changes in brain activity or brain connectivity protect against or contribute to worsening motor symptoms is unclear. With the recent emergence of neuromodulatory techniques that can alter neural activity in specific brain regions, it is critical to establish whether localized brain activation patterns are contributing to (i.e. maladaptive) or protecting against (i.e. adaptive) progression of motor symptoms. In this manuscript, we consolidate recent findings regarding changes in supraspinal structure and activity in people with MS and how these changes may contribute to motor performance. Furthermore, we discuss a hypothesis suggesting that increased neural activity during movement may be either adaptive or maladaptive depending on where in the brain this increase is observed. Specifically, we outline preliminary evidence suggesting sensorimotor cortex activity in the ipsilateral cortices may be maladaptive in people with MS. We also discuss future work that could supply data to support or refute this hypothesis, thus improving our understanding of this important topic.

Learned control of inter-hemispheric connectivity: Effects on bimanual motor performance

Bimanual movements involve the interactions between both primary motor cortices. These interactions are assumed to involve phase-locked oscillatory brain activity referred to as inter-hemispheric functional coupling. So far, inter-hemispheric functional coupling has been investigated as a function of motor performance. These studies report mostly a negative correlation between the performance in motor tasks and the strength of functional coupling. However, correlation might not reflect a causal relationship. To overcome this limitation, we opted for an alternative approach by manipulating the strength of inter-hemispheric functional coupling and assessing bimanual motor performance as a dependent variable. We hypothesize that an increase/decrease of functional coupling deteriorates/facilitates motor performance in an out-of-phase bimanual finger-tapping task. Healthy individuals were trained to volitionally regulate functional coupling in an operant conditioning paradigm using real-time magnetoencephalography neurofeedback. During operant conditioning, two discriminative stimuli were associated with upregulation and downregulation of functional coupling. Effects of training were assessed by comparing motor performance prior to (pre-test) and after the training (post-test). Participants receiving contingent feedback learned to upregulate and downregulate functional coupling. Comparing motor performance, as indexed by the ratio of tapping speed for upregulation versus downregulation trials, no change was found in the control group between pre- and post-test. In contrast, the group receiving contingent feedback evidenced a significant decrease of the ratio implicating lower tapping speed with stronger functional coupling. Results point toward a causal role of inter-hemispheric functional coupling for the performance in bimanual tasks. Hum Brain Mapp 38:4353-4369, 2017. © 2017 Wiley Periodicals, Inc.

Brain Parenchymal Fraction in Healthy Adults-A Systematic Review of the Literature

Brain atrophy is an important feature of many neurodegenerative disorders. It can be described in terms of change in the brain parenchymal fraction (BPF). In order to interpret the BPF in disease, knowledge on the BPF in healthy individuals is required. The aim of this study was to establish a normal range of values for the BPF of healthy individuals via a systematic review of the literature. The databases PubMed and Scopus were searched and 95 articles, including a total of 9269 individuals, were identified including the required data. We present values of BPF from healthy individuals stratified by age and post-processing method. The mean BPF correlated with mean age and there were significant differences in age-adjusted mean BPF between methods. This study contributes to increased knowledge about BPF in healthy individuals, which may assist in the interpretation of BPF in the setting of disease. We highlight the differences between post-processing methods and the need for a consensus gold standard.

Disrupted topological organization of structural and functional brain connectomes in clinically isolated syndrome and multiple sclerosis

The brain connectome of multiple sclerosis (MS) has been investigated by several previous studies; however, it is still unknown how the network changes in clinically isolated syndrome (CIS), the earliest stage of MS, and how network alterations on a functional level relate to the structural level in MS disease. Here, we investigated the topological alterations of both the structural and functional connectomes in 41 CIS and 32 MS patients, compared to 35 healthy controls, by combining diffusion tensor imaging and resting-state functional MRI with graph analysis approaches. We found that the structural connectome showed a deviation from the optimal pattern as early as the CIS stage, while the functional connectome only showed local changes in MS patients, not in CIS. When comparing two patient groups, the changes appear more severe in MS. Importantly, the disruptions of structural and functional connectomes in patients occurred in the same direction and locally correlated in sensorimotor component. Finally, the extent of structural network changes was correlated with several clinical variables in MS patients. Together, the results suggested early disruption of the structural brain connectome in CIS patients and provided a new perspective for investigating the relationship of the structural and functional alterations in MS.

A surface-based technique for mapping homotopic interhemispheric connectivity: Development, characterization, and clinical application

The functional organization of the human brain consists of a high degree of connectivity between interhemispheric homologous regions. The degree of homotopic organization is known to vary across the cortex and homotopic connectivity is high in regions that share cross-hemisphere structural connections or are activated by common input streams (e.g., the visual system). Damage to one or both regions, as well as damage to the connections between homotopic regions, could disrupt this functional organization. Here were introduce and test a computationally efficient technique, surface-based homotopic interhermispheric connectivity (sHIC), that leverages surface-based registration and processing techniques in an attempt to improve the spatial specificity and accuracy of cortical interhemispheric connectivity estimated with resting state functional connectivity. This technique is shown to be reliable both within and across subjects. sHIC is also characterized in a dataset of nearly 1000 subjects. We confirm previous results showing increased interhemispheric connectivity in primary sensory regions, and reveal a novel rostro-caudal functionally defined network level pattern of sHIC across the brain. In addition, we demonstrate a structural-functional relationship between sHIC and atrophy of the corpus callosum in multiple sclerosis (r = 0.2979, p = 0.0461). sHIC presents as a sensitive and reliable measure of cortical homotopy that may prove useful as a biomarker in neurologic disease. Hum Brain Mapp 37:2849-2868, 2016. © 2016 Wiley Periodicals, Inc.

Unraveling the secrets of white matter--bridging the gap between cellular, animal and human imaging studies

The CNS white matter makes up about half of the human brain, and with advances in human imaging it is increasingly becoming clear that changes in the white matter play a major role in shaping human behavior and learning. However, the mechanisms underlying these white matter changes remain poorly understood. Within this special issue of Neuroscience on white matter, recent advances in our knowledge of the function of white matter, from the molecular level to human imaging, are reviewed. Collaboration between fields is essential to understand the function of the white matter, but due to differences in methods and field-specific 'language', communication is often hindered. In this review, we try to address this hindrance by introducing the methods and providing a basic background to myelin biology and human imaging as a prelude to the other reviews within this special issue.