Análise Espectral de Alta Ordem no Domínio do Tempo Para o Estudo da Plasticidade Neural Frente a Tarefa de Aprendizagem Associativa em Ratos

Abstract

This paper presents the use of high-order spectral analysis in the time domain for identifying changes in the mesencephalic neural network after an associative learning task in rats. It has been demonstrated that during auditory fear conditioning tasks, the evoked potentials in the inferior colliculus exhibit an oscillation at the same frequency as the modulating frequency of the sound stimulus used. Upon auditory fear conditioned memory consolidation, the power at this frequency increased significantly compared to the stimulus applied before the task, among other changes. The paper discusses the advantages and disadvantages of using high-order spectral analysis in the time domain compared to traditional techniques for identifying attributes related to neural plasticity, such as increases in phase synchrony and power. Additionally, it highlights that high-order spectral analysis in the time domain can provide useful information on possible nonlinearities and frequency coupling during the analysis. The article provides an overview of the mathematical fundamentals of each technique and emphasizes the potential of highorder spectral analysis in the time domain as a valuable tool for analyzing electrophysiological recordings. This information can be valuable for understanding the complex dynamics of neural networks and identifying the underlying mechanisms of neural plasticity.