Understanding Episodic Memory Through Decoding EEG and Probabilistic Estimation of Brain Functional Connectivity Parameters
| Autor: | Mallampalli Kapardi, Kavitha Anandan |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
medicine.diagnostic_test
Functional connectivity Speech recognition 05 social sciences Electroencephalography 050105 experimental psychology Probabilistic estimation 03 medical and health sciences 0302 clinical medicine medicine 0501 psychology and cognitive sciences Psychology Episodic memory 030217 neurology & neurosurgery Decoding methods |
| Zdroj: | Advances in Computational Intelligence and Robotics |
| DOI: | 10.4018/978-1-7998-3038-2.ch008 |
| Popis: | Autobiographical events help us to analyze our own thoughts and behavior over a period of time. Analyzing the retrieval of memory helps in better understanding of the disorders. This chapter aims at analyzing the functional connectivity of young adults during a multiphase memory retrieval process. Subjects have been made to recall events in different phases of their life. EEG signals have been recorded while the subjects are performing their tasks. Inter-hemispherical coherence has been estimated from the processed EEG signals. As theta band posed higher power compared to all other bands, it was considered for further analysis. A mathematical function was formed for the processed theta wave to determine the coherence between various electrodes. The function generated a theta wave for every task and each wave was significant in its own way. The connectivity matrix was found to identify the active electrodes during retrieval of events. The results were validated by computing coherence separately for the same electrodes and for the same events. |
| Databáze: | OpenAIRE |
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