Astrocytes facilitate gabazine-evoked electrophysiological hyperactivity and distinct biochemical responses in mature neuronal cultures

Gamma-aminobutyric acid (GABA) is the principal inhibitory neurotransmitter in the adult brain that binds to GABA receptors and hyperpolarizes the postsynaptic neuron. Gabazine acts as a competitive antagonist to type A GABA receptors (GABAAR), thereby causing diminished neuronal hyperpolarization and GABAAR-mediated inhibition. However, the biochemical effects and the potential regulatory role of astrocytes in this process remain poorly understood. To address this, we investigated the neuronal responses of gabazine in rat cortical cultures containing varying ratios of neurons and astrocytes. Electrophysiological characterization was performed utilizing microelectrode arrays (MEAs) with topologically controlled microcircuit cultures that enabled control of neuronal network growth. Biochemical analysis of the cultures was performed using traditional dissociated cultures on coverslips. Our study indicates that, upon gabazine stimulation, astrocyte-rich neuronal cultures exhibit elevated electrophysiological activity and tyrosine phosphorylation of tropomyosin receptor kinase B (TrkB; receptor for brain-derived neurotrophic factor), along with distinct cytokine secretion profiles. Notably, neurons lacking proper astrocytic support were found to experience synapse loss and decreased mitogen-activated protein kinase (MAPK) phosphorylation. Furthermore, astrocytes contributed to neuronal viability, morphology, vascular endothelial growth factor (VEGF) secretion, and overall neuronal network functionality, highlighting the multifunctional role of astrocytes. (Figure presented.)Peer reviewe

Epileptic EEG Signal Classification with ANFIS Based on Harmony Search Method

In this paper, the Adaptive Neuro-Fuzzy Inference System (ANFIS) is used for the classification of the epileptic electroencephalogram (EEG) signals. The ANFIS combines the adaptation capability of the neural networks and the fuzzy logic-based qualitative approach together. A given input/output data set is deployed to construct a fuzzy inference system, whose membership function parameters are trained using a back propagation algorithm in combination with a least squares method. However, the training method sometimes may lead to local optima. We here propose a new strategy of hybrid training algorithm based on the fusion of the ANFIS and Harmony Search (HS), HS-ANFIS, which is adopted to tune all the parameters of the ANFIS. The validity of our method is verified by numerical experiments. ? 2012 IEEE.EI

Automatic objective thresholding to detect neuronal action potentials

In this paper, we introduce a fully objective method to set thresholds (THs) for neuronal action potential spike detection from extracellular field potential signals. Although several more sophisticated methods exist, thresholding is still the most used spike detection method. In general, it is employed by setting a TH as per convention or operator decision, and without considering either the undetected or spurious spikes. Here, we demonstrate with both simulations and real microelectrode measurement data that our method can fully automatically and objectively yield THs comparable to those set by an expert operator. A Matlab function implementation of the method is described, and provided freely in Matlab Central File Exchange.acceptedVersionPeer reviewe