Epilepsy affects over 50 million people worldwide. Drug-resistant epilepsy (DRE) accounts for up to a third of these cases, and neuro-inflammation is thought to play a role in such cases. Despite being a long-debated issue in the field of DRE, the mechanisms underlying neuroinflammation have yet to be fully elucidated. The pro-inflammatory microenvironment within the brain tissue of people with DRE has been probed using single-cell multimodal transcriptomics. Evidence suggests that inflammatory cells and pro-inflammatory cytokines in the nervous system can lead to extensive biochemical changes, such as connexin hemichannel excitability and disruption of neurotransmitter homeostasis. The presence of inflammation may give rise to neuronal network abnormalities that suppress endogenous antiepileptic systems. We focus on the role of neuroinflammation and brain network anomalies in DRE from multiple perspectives to identify critical points for clinical application. We hope to provide an insightful overview to advance the quest for better DRE treatments.
Humans ; Drug Resistant Epilepsy/metabolism* ; Neuroinflammatory Diseases/immunology* ; Animals ; Brain/pathology* ; Nerve Net/pathology*

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

In this study, we systematically tested the hypothesis that during the critical developmental period of adolescence, on a macro scale, the concentrations of major excitatory and inhibitory neurotransmitters (glutamate/glutamine and γ‑aminobutyric acid [GABA]) in the dorsal and ventral lateral prefrontal cortex are associated with the brain's functional connectivity and an individual's psychopathology. Neurotransmitters were measured via magnetic resonance spectroscopy while functional connectivity was measured with resting-state fMRI (n = 121). Seed-based and network-based analyses revealed associations of neurotransmitter concentrations and functional connectivities between regions/networks that are connected to prefrontal cortices via structural connections that are thought to be under dynamic development during adolescence. These regions tend to be boundary areas between functional networks. Furthermore, several connectivities were found to be associated with individual's levels of internalizing psychopathology. These findings provide insights into specific neurochemical mechanisms underlying the brain's macroscale functional organization, its development during adolescence, and its potential associations with symptoms associated with internalizing psychopathology.
Humans ; Adolescent ; Glutamic Acid/metabolism* ; Prefrontal Cortex/diagnostic imaging* ; Male ; Glutamine/metabolism* ; Female ; gamma-Aminobutyric Acid/metabolism* ; Magnetic Resonance Imaging ; Magnetic Resonance Spectroscopy ; Nerve Net/metabolism* ; Neural Pathways ; Connectome

Exploring the transition from inter-ictal to ictal epileptiform discharges (IDs) and how GABA receptor-mediated action affects the onset of IDs will enrich our understanding of epileptogenesis and epilepsy treatment. We used Mg-free artificial cerebrospinal fluid (ACSF) to induce epileptiform discharges in juvenile mouse hippocampal slices and used a micro-electrode array to record the discharges. After the slices were exposed to Mg-free ACSF for 10 min-20 min, synchronous recurrent seizure-like events were recorded across the slices, and each event evolved from inter-ictal epileptiform discharges (IIDs) to pre-ictal epileptiform discharges (PIDs), and then to IDs. During the transition from IIDs to PIDs, the duration of discharges increased and the inter-discharge interval decreased. After adding 3 μmol/L of the GABA receptor agonist muscimol, PIDs and IDs disappeared, and IIDs remained. Further, the application of 10 μmol/L muscimol abolished all the epileptiform discharges. When the GABA receptor antagonist bicuculline was applied at 10 μmol/L, IIDs and PIDs disappeared, and IDs remained at decreased intervals. These results indicated that there are dynamic changes in the hippocampal network preceding the onset of IDs, and GABA receptor activity suppresses the transition from IIDs to IDs in juvenile mouse hippocampus.
Animals ; Animals, Newborn ; Bicuculline ; pharmacology ; Disease Models, Animal ; Epilepsy ; pathology ; GABA-A Receptor Agonists ; pharmacology ; GABA-A Receptor Antagonists ; therapeutic use ; Hippocampus ; drug effects ; metabolism ; physiopathology ; In Vitro Techniques ; Magnesium ; metabolism ; pharmacology ; Male ; Membrane Potentials ; drug effects ; Mice ; Mice, Inbred C57BL ; Muscimol ; pharmacology ; Nerve Net ; drug effects ; Receptors, GABA-A ; metabolism

OBJECTIVETo establish a brain functional network of the whole brain based on glucose metabolism, and to evaluate the cost and efficiency of the functional network.

METHODS18F-FDG PET of 148 healthy volunteers (30-59 years, n = 148) was performed in a resting state. Images were registered to atlas by using the statistical parametric mapping (SPM) software. The functional connectivity between 90 cortical and sub-cortical regions was estimated by correlation analysis.

RESULTSGlucose metabolism brain functional networks had global efficiency greater than the lattice but less than the random graph, and local efficiency greater than random but less than lattice. This characteristically small-world behavior of the brain network was most consistently seen for low-cost to medium-cost networks. The small world regime was Cost-[0.0512, 0.5406]. The cost efficiency of the networks typically had a maximum positive value when the cost was 0.23.

CONCLUSIONSGlucose metabolism brain functional networks have economical small-world properties. It is feasible to analyze the functional characteristics of human brain by study 18F-FDG PET images. This paper provides a new method for studies on brain function.

Adult ; Brain ; metabolism ; physiology ; Brain Mapping ; Female ; Fluorodeoxyglucose F18 ; Glucose ; metabolism ; Humans ; Male ; Middle Aged ; Models, Neurological ; Nerve Net ; Positron-Emission Tomography ; methods