Post-Training Sleep Modulates Topographical Relearning-Dependent Resting State Activity.

Michele Deantoni,Evelyne Balteau,Philippe Peigneux,Thomas Villemonteix,Christina Schmidt

doi:10.3390/brainsci11040476

Abstract

Continuation of experience-dependent neural activity during offline sleep and wakefulness episodes is a critical component of memory consolidation. Using functional magnetic resonance imaging (fMRI), offline consolidation effects have been evidenced probing behavioural and neurophysiological changes during memory retrieval, i.e., in the context of task practice. Resting state fMRI (rsfMRI) further allows investigating the offline evolution of recently learned information without the confounds of online task-related effects. We used rsfMRI to investigate sleep-related changes in seed-based resting functional connectivity (FC) and amplitude of low frequency fluctuations (ALFF) after spatial navigation learning and relearning. On Day 1, offline resting state activity was measured immediately before and after topographical learning in a virtual town. On Day 4, it was measured again before and after relearning in an extended version of the town. Navigation-related activity was also recorded during target retrieval, i.e., online. Participants spent the first post-training night under regular sleep (RS) or sleep deprivation (SD) conditions. Results evidence FC and ALFF changes in task-related neural networks, indicating the continuation of navigation-related activity in the resting state. Although post-training sleep did not modulate behavioural performance, connectivity analyses evidenced increased FC after post-training SD between navigation-related brain structures during relearning in the extended environment. These results suggest that memory traces were less efficiently consolidated after post-learning SD, eventually resulting in the use of compensatory brain resources to link previously stored spatial elements with the newly presented information.

Highlights

Evidence ranging from cell recordings in rodents to human behavioural and neuroimaging data show that sleep participates in the long-term consolidation of recently acquired information [1] in various memory domains [2,3]
We previously showed using functional magnetic resonance imaging (fMRI) that novel topographical learning modulates hippocampal responses at wake during a subsequent, unrelated attentional task, suggesting that modulated brain activity during post-training wakefulness contributes to memory consolidation by shaping and reinforcing the functional connections between learning-related cerebral structures and other brain regions [29]
We investigated Resting state fMRI (rsfMRI) activity and connectivity changes immediately after spatial navigation learning, at delayed retrieval 4 days later modulated by regular sleep (RS) versus total sleep deprivation (SD) on the first post-learning night, and after a relearning episode in an extended environment encompassing the initial environment

Summary

Introduction

Evidence ranging from cell recordings in rodents to human behavioural and neuroimaging data show that sleep participates in the long-term consolidation of recently acquired information [1] in various memory domains [2,3]. Sleep supports the consolidation of spatial memory [4,5,6], the cognitive system responsible for recording information about one’s environment and spatial orientation. Spatial and episodic declarative memory share similar neuroanatomical foundations in human beings and animals [7]. This makes spatial memory an attractive paradigm to study the effects of sleep, with unique opportunities for translational inferences. Non-invasive neuroimaging studies have consistently shown that spatial navigation is subtended by a distributed brain network encompassing the hippocampus, the dorsal striatum, the precuneus and the entorhinal, parahippocampal, retrosplenial and frontal cortices [8,9]. Human and animal studies investigating the role of hippocampal and striatal areas in place-based vs. response-based navigation strategies suggest that these two systems initially compete with each other during the acquisition phase, and become more integrated and interdependent after extended training [12,13]

Methods

Results

Conclusion