Oscillatory dynamics of active learning in the human brain

Abstract

Comunicació presentada al 2019 Conference on Cognitive Computational Neuroscience, celebrada a Berlin (Alemanya) del 13 al 16 de setembre de 2019.

While the benefits of self-directed learning on human memory are well-acknowledged, little is known on its underlying neurophysiological substrate. Here, we investigated the key signatures of volitional learning in the brain as assessed by representational similarity analysis applied to human intracranial EEG (iEEG) data. Epilepsy patients performed an episodic memory task during virtual navigation which tests differences in recognition memory for self-directed versus passive learning. Consistent with previous literature, higher recognition accuracy was observed for items studied in active as opposed to passive movement conditions at the behavioral level. In addition, we demonstrate a critical role of hippocampal low-frequency oscillations for active learning. This is observed in 1) increased hippocampal 2-6Hz power for active versus passive information sampling and 2) significantly greater encoding-retrieval similarity (ERS) for volitional as compared to passive conditions in the first second after cue onset at retrieval. Follow-up analyses will address the contribution of activity at different frequencies for item-specific ERS and volitional versus passive learning. Together, these results offer a first perspective on the key oscillatory mechanisms underlying volitional learning in the human brain.

The research leading to these results has received funding from the ERC grant agreement n° 341196 (CDAC).