Neurofisiologia hipocampal durante sessões de sono intercaladas por exploração espacial: Reverberação do passado ou predição do futuro?

• Autor(a) principal: Belchior, Hindiael Aeraf
• Data de Publicação: 2009
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFRN
• Texto Completo: https://repositorio.ufrn.br/jspui/handle/123456789/17278
• topic: Aprendizado espacial; Sono; Memória; Previsão de futuro; CNPQ::CIENCIAS HUMANAS::PSICOLOGIA::PSICOLOGIA FISIOLOGICA::PSICOBIOLOGIA

The ability to predict future rewards or threats is crucial for survival. Recent studies have addressed future event prediction by the hippocampus. Hippocampal neurons exhibit robust selectivity for spatial location. Thus, the activity of hippocampal neurons represents a cognitive map of space during navigation as well as during planning and recall. Spatial selectivity allows the hippocampus to be involved in the formation of spatial and episodic memories, including the sequential ordering of events. On the other hand, the discovery of reverberatory activity in multiple forebrain areas during slow wave and REM sleep underscored the role of sleep on the consolidation of recently acquired memory traces. To this date, there are no studies addressing whether neuronal activity in the hippocampus during sleep can predict regular environmental shifts. The aim of the present study was to investigate the activity of neuronal populations in the hippocampus during sleep sessions intercalated by spatial exploration periods, in which the location of reward changed in a predictable way. To this end, we performed the chronic implantation of 32-channel multielectrode arrays in the CA1 regions of the hippocampus in three male rats of the Wistar strain. In order to activate different neuronal subgroups at each cycle of the task, we exposed the animals to four spatial exploration sessions in a 4-arm elevated maze in which reward was delivered in a single arm per session. Reward location changed regularly at every session in a clockwise manner, traversing all the arms at the end of the daily recordings. Animals were recorded from 2-12 consecutive days. During spatial exploration of the 4-arm elevated maze, 67,5% of the recorded neurons showed firing rate differences across the maze arms. Furthermore, an average of 42% of the neurons showed increased correlation (R>0.3) between neuronal pairs in each arm. This allowed us to sort representative neuronal subgroups for each maze arm, and to analyze the activity of these subgroups across sleep sessions. We found that neuronal subgroups sorted by firing rate differences during spatial exploration sustained these differences across sleep sessions. This was not the case with neuronal subgroups sorted according to synchrony (correlation). In addition, the correlation levels between sleep sessions and waking patterns sampled in each arm were larger for the entire population of neurons than for the rate or synchrony subgroups. Neuronal activity during sleep of the entire neuronal population or subgroups did not show different correlations among the four arm mazes. On the other hand, we verified that neuronal activity during pre-exploration sleep sessions was significantly more similar to the activity patterns of the target arm than neuronal activity during pre-exploration sleep sessions. In other words, neuronal activity during sleep that precedes the task reflects more strongly the location of reward than neuronal activity during sleep that follows the task. Our results suggest that neuronal activity during sleep can predict regular environmental changes