Grey Matter
grey matter
Seizure control by electrical stimulation: parameters and mechanisms
Seizure suppression by deep brain stimulation (DBS) applies high frequency stimulation (HFS) to grey matter to block seizures. In this presentation, I will present the results of a different method that employs low frequency stimulation (LFS) (1 to 10Hz) of white matter tracts to prevent seizures. The approach has been shown to be effective in the hippocampus by stimulating the ventral and dorsal hippocampal commissure in both animal and human studies respectively for mesial temporal lobe seizures. A similar stimulation paradigm has been shown to be effective at controlling focal cortical seizures in rats with corpus callosum stimulation. This stimulation targets the axons of the corpus callosum innervating the focal zone at low frequencies (5 to 10Hz) and has been shown to significantly reduce both seizure and spike frequency. The mechanisms of this suppression paradigm have been elucidated with in-vitro studies and involve the activation of two long-lasting inhibitory potentials GABAB and sAHP. LFS mechanisms are similar in both hippocampus and cortical brain slices. Additionally, the results show that LFS does not block seizures but rather decreases the excitability of the tissue to prevent seizures. Three methods of seizure suppression, LFS applied to fiber tracts, HFS applied to focal zone and stimulation of the anterior nucleus of the thalamus (ANT) were compared directly in the same animal in an in-vivo epilepsy model. The results indicate that LFS generated a significantly higher level of suppression, indicating LFS of white matter tract could be a useful addition as a stimulation paradigm for the treatment of epilepsy.
The role of CNS microglia in health and disease
Microglia are the resident CNS macrophages of the brain parenchyma. They have many and opposing roles in health and disease, ranging from inflammatory to anti-inflammatory and protective functions, depending on the developmental stage and the disease context. In Multiple Sclerosis, microglia are involved to important hallmarks of the disease, such as inflammation, demyelination, axonal damage and remyelination, however the exact mechanisms controlling their transformation towards a protective or devastating phenotype during the disease progression remains largely unknown until now. We wish to understand how brain microglia respond to demyelinating insults and how their behaviour changes in recovery. To do so we developed a novel histopathological analysis approach in 3D and a cell-based analysis tool that when applied in the cuprizone model of demyelination revealed region- and disease- dependent changes in microglial dynamics in the brain grey matter during demyelination and remyelination. We now use similar approaches with the aim to unravel sensitive changes in microglial dynamics during neuroinflammation in the EAE model. Furthermore, we employ constitutive knockout and tamoxifen-inducible gene-targeting approaches, immunological techniques, genetics and bioinformatics and currently seek to clarify the specific role of the brain resident microglial NF-κB molecular pathway versus other tissue macrophages in EAE.
Mapping Individual Trajectories of Structural and Cognitive Decline in Mild Cognitive Impairment
The US has an aging population. For the first time in US history, the number of older adults is projected to outnumber that of children by 2034. This combined with the fact that the prevalence of Alzheimer's Disease increases exponentially with age makes for a worrying combination. Mild cognitive impairment (MCI) is an intermediate stage of cognitive decline between being cognitively normal and having full-blown Dementia, with every third person with MCI progressing to dementia of the Alzheimer's Type (DAT). While there is no known way to reverse symptoms once they begin, early prediction of disease can help stall its progression and help with early financial planning. While grey matter volume loss in the Hippocampus and Entorhinal Cortex (EC) are characteristic biomarkers of DAT, little is known about the rates of decrease of these volumes within individuals in MCI state across time. We used longitudinal growth curve models to map individual trajectories of volume loss in subjects with MCI. We then looked at whether these rates of volume decrease could predict progression to DAT right in the MCI stage. Finally, we evaluated whether these rates of Hippocampal and EC volume loss were correlated with individual rates of decline of episodic memory, visuospatial ability, and executive function.
Dynamic structural neuroplasticity in the bilingual brain
Research on the effects of bilingualism on the structure of the brain has so far yielded variable patterns. Although it cannot be disputed that learning and using additional languages restructures the brain, the reported effects vary considerably, including both increases and reductions in grey matter volume and white matter diffusivity. This presentation reviews the available evidence and compares it to patterns from other domains of skill acquisition, culminating in the Dynamic Restructuring Model, a theory which synthesises the available evidence from the perspective of experience-based neuroplasticity. New corroborating evidence is also presented from healthy young and older bilinguals, and the presentation concludes with the implications of these effects for the ageing brain.
Bridging brain and cognition: A multilayer network analysis of brain structural covariance and general intelligence in a developmental sample of struggling learners
Network analytic methods that are ubiquitous in other areas, such as systems neuroscience, have recently been used to test network theories in psychology, including intelligence research. The network or mutualism theory of intelligence proposes that the statistical associations among cognitive abilities (e.g. specific abilities such as vocabulary or memory) stem from causal relations among them throughout development. In this study, we used network models (specifically LASSO) of cognitive abilities and brain structural covariance (grey and white matter) to simultaneously model brain-behavior relationships essential for general intelligence in a large (behavioral, N=805; cortical volume, N=246; fractional anisotropy, N=165), developmental (ages 5-18) cohort of struggling learners (CALM). We found that mostly positive, small partial correlations pervade both our cognitive and neural networks. Moreover, calculating node centrality (absolute strength and bridge strength) and using two separate community detection algorithms (Walktrap and Clique Percolation), we found convergent evidence that subsets of both cognitive and neural nodes play an intermediary role between brain and behavior. We discuss implications and possible avenues for future studies.
Cortical and subcortical grey matter micro-structure is associated with polygenic risk for schizophrenia
Background: Recent discovery of hundreds of common gene variants associated with schizophrenia has enabled polygenic risk scores (PRS) to be measured in the population. It is hypothesized that normal variation in genetic risk of schizophrenia should be associated with MRI changes in brain morphometry and tissue composition. Methods: We used the largest extant genome-wide association dataset (N = 69,369 cases and N = 236,642 healthy controls) to measure PRS for schizophrenia in a large sample of adults from the UK Biobank (Nmax = 29,878) who had multiple micro- and macro-structural MRI metrics measured at each of 180 cortical areas and seven subcortical structures. Linear mixed effect models were used to investigate associations between schizophrenia PRS and brain structure at global and regional scales, controlled for multiple comparisons. Results: Micro-structural phenotypes were more robustly associated with schizophrenia PRS than macro-structural phenotypes. Polygenic risk was significantly associated with reduced neurite density index (NDI) at global brain scale, at 149 cortical regions, and five subcortical structures. Other micro-structural parameters, e.g., fractional anisotropy, that were correlated with NDI were also significantly associated with schizophrenia PRS. Genetic effects on multiple MRI phenotypes were co-located in temporal, cingulate and prefrontal cortical areas, insula, and hippocampus. (Preprint: https://www.medrxiv.org/content/10.1101/2021.02.06.21251073v1)
Early constipation predicts faster dementia onset in Parkinson’s disease
Constipation is a common but not a universal feature in early PD, suggesting that gut involvement is heterogeneous and may be part of a distinct PD subtype with prognostic implications. We analysed data from the Parkinson’s Incidence Cohorts Collaboration, composed of incident community-based cohorts of PD patients assessed longitudinally over 8 years. Constipation was assessed with the MDS-UPDRS constipation item or a comparable categorical scale. Primary PD outcomes of interest were dementia, postural instability and death. PD patients were stratified according to constipation severity at diagnosis: none (n=313, 67.3%), minor (n=97, 20.9%) and major (n=55, 11.8%). Clinical progression to all 3 outcomes was more rapid in those with more severe constipation at baseline (Kaplan Meier survival analysis). Cox regression analysis, adjusting for relevant confounders, confirmed a significant relationship between constipation severity and progression to dementia, but not postural instability or death. Early constipation may predict an accelerated progression of neurodegenerative pathology. Conclusions: We show widespread cortical and subcortical grey matter micro-structure associations with schizophrenia PRS. Across all investigated phenotypes NDI, a measure of the density of myelinated axons and dendrites, showed the most robust associations with schizophrenia PRS. We interpret these results as indicative of reduced density of myelinated axons and dendritic arborization in large-scale cortico-subcortical networks mediating the genetic risk for schizophrenia.
Defining new multimodal neuroimaging marker for grey matter characterization
The human cortical ribbon varies during the lifespan, from childhood to senescence. To study the effects of genetic and environmental factors on these dynamics, one needs to measure specific phenotypes (cortical volume, surface area, thickness, new neuroimaging phenotypes such as intracortical myelination or multimodal ones based on their combination, or their asymmetries) that characterize the cerebral grey matter accurately
Misplaced and misconnected: circuit-level defects in malformations of cortical development
During histogenesis of the cerebral cortex, a proper laminar placement of defined numbers of specific cellular types is necessary to ensure proper functional connectivity patterns. There is a wide range of cortical malformations causing epilepsy and intellectual disability in humans, characterized with various degrees of neuronal misplacement, aberrant circuit organization or abnormal folding patterns. Although progress in human neurogenetics and brain imaging techniques have considerably advanced the identification of their causative genes, the pathophysiological mechanisms associated with defective cerebral cortex development remain poorly understood. In my presentation, I will outline some of our recent works in rodent models illustrating how misplaced neurons forming grey matter heterotopia, a cortical malformation subtype, interfere with the proper development of cortical circuits, and induce both local and distant circuitry changes associated with the subsequent emergence of epilepsy.
Coupling between global grey matter and fourth ventricle fMRI signals links with brain clearance in humans
FENS Forum 2024
Examining speech disfluency through the analysis of grey matter densities in 5-year-olds using voxel-based morphometry
FENS Forum 2024
The influence of the time of the day on the coupling between global grey matter BOLD and CSF flow signal in healthy humans: Preliminary results
FENS Forum 2024