RESUMO
Alcohol use is a leading risk factor for substantial health loss, disability, and death. Thus, there is a general interest in developing computational tools to classify electroencephalographic (EEG) signals in alcoholism, but there are a limited number of studies on convolutional neural network (CNN) classification of alcoholism using topographic EEG signals. We produced an original dataset recorded from Brazilian subjects performing a language recognition task. Then, we transformed the Event-Related Potentials (ERPs) into topographic maps by using the ERP's statistical parameters across time, and used a CNN network to classify the topographic dataset. We tested the effect of the size of the dataset in the accuracy of the CNNs and proposed a data augmentation approach to increase the size of the topographic dataset to improve the accuracies. Our results encourage the use of CNNs to classify abnormal topographic EEG patterns associated with alcohol abuse.
Assuntos
Alcoolismo , Humanos , Alcoolismo/diagnóstico , Redes Neurais de Computação , Eletroencefalografia/métodos , Potenciais EvocadosRESUMO
Mirror neurons fire action potentials both when the agent performs a certain behavior and watches someone performing a similar action. Here, we present an original mirror neuron model based on the spike-timing-dependent plasticity (STDP) between two morpho-electrical models of neocortical pyramidal neurons. Both neurons fired spontaneously with basal firing rate that follows a Poisson distribution, and the STDP between them was modeled by the triplet algorithm. Our simulation results demonstrated that STDP is sufficient for the rise of mirror neuron function between the pairs of neocortical neurons. This is a proof of concept that pairs of neocortical neurons associating sensory inputs to motor outputs could operate like mirror neurons. In addition, we used the mirror neuron model to investigate whether channelopathies associated with autism spectrum disorder could impair the modeled mirror function. Our simulation results showed that impaired hyperpolarization-activated cationic currents (Ih) affected the mirror function between the pairs of neocortical neurons coupled by STDP.
Assuntos
Potenciais de Ação/fisiologia , Transtorno do Espectro Autista/fisiopatologia , Canalopatias/fisiopatologia , Neurônios-Espelho/fisiologia , Modelos Neurológicos , Neocórtex/fisiopatologia , Plasticidade Neuronal/fisiologia , Animais , Simulação por Computador , Canais Iônicos/metabolismo , Atividade Motora/fisiologia , Percepção/fisiologia , Estudo de Prova de Conceito , Células Piramidais/fisiologiaRESUMO
Frequently, a common chemical entity triggers opposite cellular processes, which implies that the components of signalling networks must detect signals not only through their chemical natures, but also through their dynamic properties. To gain insights on the mechanisms of discrimination of the dynamic properties of cellular signals, we developed a computational stochastic model and investigated how three calcium ion (Ca(2+))-dependent enzymes (adenylyl cyclase (AC), phosphodiesterase 1 (PDE1), and calcineurin (CaN)) differentially detect Ca(2+) transients in a hippocampal dendritic spine. The balance among AC, PDE1 and CaN might determine the occurrence of opposite Ca(2+)-induced forms of synaptic plasticity, long-term potentiation (LTP) and long-term depression (LTD). CaN is essential for LTD. AC and PDE1 regulate, indirectly, protein kinase A, which counteracts CaN during LTP. Stimulations of AC, PDE1 and CaN with artificial and physiological Ca(2+) signals demonstrated that AC and CaN have Ca(2+) requirements modulated dynamically by different properties of the signals used to stimulate them, because their interactions with Ca(2+) often occur under kinetic control. Contrarily, PDE1 responds to the immediate amplitude of different Ca(2+) transients and usually with the same Ca(2+) requirements observed under steady state. Therefore, AC, PDE1 and CaN decode different dynamic properties of Ca(2+) signals.
Assuntos
Adenilil Ciclases/metabolismo , Calcineurina/metabolismo , Sinalização do Cálcio/fisiologia , Cálcio/metabolismo , Simulação por Computador , Nucleotídeo Cíclico Fosfodiesterase do Tipo 1/metabolismo , Espinhas Dendríticas/fisiologia , Hipocampo/fisiologia , Potenciação de Longa Duração/fisiologia , Depressão Sináptica de Longo Prazo/fisiologia , Modelos Químicos , Modelos Neurológicos , Proteínas do Tecido Nervoso/metabolismo , Soluções Tampão , Proteínas Quinases Dependentes de AMP Cíclico/metabolismo , Cinética , Receptores de N-Metil-D-Aspartato/metabolismo , Processos Estocásticos , TermodinâmicaRESUMO
This work consists of a computational study of the electrical responses of three classes of granule cells of the olfactory bulb to synaptic activation in different dendritic locations. The constructed models were based on morphologically detailed compartmental reconstructions of three granule cell classes of the olfactory bulb with active dendrites described by Bhalla and Bower (1993, pp. 1948-1965) and dendritic spine distributions described by Woolf et al. (1991, pp. 1837-1854). The computational studies with the model neurons showed that different quantities of spines have to be activated in each dendritic region to induce an action potential, which always was originated in the active terminal dendrites, independently of the location of the stimuli, and the morphology of the dendritic tree. These model predictions might have important computational implications in the context of olfactory bulb circuits.
RESUMO
This work describes a biophysical model of the initial stages of vertebrate olfactory system containing structures representing the olfactory epithelium and bulb. Its main novelty is the introduction of gap junctions connecting neurons both in the epithelium and bulb, and of biologically detailed dendrodendritic synapses between granule and mitral cells in the bulb. The model was used to simulate the effect of an odor presentation on the neural activity pattern in the epithelium and bulb. During the time for which an odor is presented with a constant concentration, there are spatiotemporal patterns in the epithelium and bulb generated by the couplings due to the gap junctions and/or dendrodendritic synapses. A study varying the strength of the gap junction coupling shows that the spatiotemporal patterns, both in the epithelium and bulb, are dependent of the coupling strength. It is also shown that the olfactory bulb's spatiotemporal pattern depends on the existence of the dendrodendritic connections between mitral and granule cells. If these spatiotemporal patterns really exist in the early processing stages of the olfactory system they may be used for odor coding and the gap junctions and dendrodendritic synapses might have a role on it.