Extended Visual Sequence Learning Leaves a Local Trace in the Spontaneous EEG

• Published in: Frontiers in neuroscience Vol. 15; p. 707828
• Main Authors: Ricci, Serena, Tatti, Elisa, Nelson, Aaron B., Panday, Priya, Chen, Henry, Tononi, Giulio, Cirelli, Chiara, Ghilardi, M. Felice
• Format: Journal Article
• Language: English
• Published: Lausanne Frontiers Research Foundation 16.07.2021; Frontiers Media S.A
• Subjects: EEG; Electroencephalography; Experiments; Fatigue; homeostasis; Learning; Memory; Motor skill learning; Motor task performance; Neuroscience; resting state EEG; Sensorimotor integration; Short term memory; Visual discrimination learning; visual learning
• ISSN: 1662-453X; 1662-4548; 1662-453X
• DOI: 10.3389/fnins.2021.707828

We have previously demonstrated that, in rested subjects, extensive practice in a motor learning task increased both electroencephalographic (EEG) theta power in the areas involved in learning and improved the error rate in a motor test that shared similarities with the task. A nap normalized both EEG and performance changes. We now ascertain whether extensive visual declarative learning produces results similar to motor learning. Thus, during the morning, we recorded high-density EEG in well rested young healthy subjects that learned the order of different visual sequence task (VSEQ) for three one-hour blocks. Afterward, a group of subjects took a nap and another rested quietly. Between each VSEQ block, we recorded spontaneous EEG (sEEG) at rest and assessed performance in a motor test and a visual working memory test that shares similarities with VSEQ. We found that after the third block, VSEQ induced local theta power increases in the sEEG over a right temporo-parietal area that was engaged during the task. This local theta increase was preceded by increases in alpha and beta power over the same area and was paralleled by performance decline in the visual working memory test. Only after the nap, VSEQ learning rate improved and performance in the visual working memory test was restored, together with partial normalization of the local sEEG changes. These results suggest that intensive learning, like motor learning, produces local theta power increases, possibly reflecting local neuronal fatigue. Sleep may be necessary to resolve neuronal fatigue and its effects on learning and performance.