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

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.

Keywords: ALFF; functional MRI; memory consolidation; resting-state fMRI; sleep deprivation; spatial learning.

Figure 1

Experimental Protocol. On Day 1, 50 participants were scanned in the resting state before (rsfMRI 1) and after (rsfMRI 2) out-of-scanner exploration of Level 1 of the virtual town, followed by fMRI Test 1 (immediate retrieval navigation test). Thirty-four participants then either slept normally (RS) or were sleep deprived (SD) during Night 1, and then slept normally on Nights 2 and 3. On Day 4, RS and SD participants were scanned in the resting state (rsfMRI 3) followed by fMRI Test 2 (delayed retrieval navigation test). Afterward, they were trained on an extended version (both Level 1 and 2) of the virtual town and then scanned a last time in the resting state (rsfMRI 4). Finally, participants were tested on the extended version of the virtual town outside of the MRI environment (Retrieval extended, not illustrated). Top left and right panels provide an aerial representation of the town map (not seen by participants who navigated from within the environment, see sample pictures) with Level 1 (left, day 1) and 2 (right, day 4) environments and navigation test targets A, B and C located on the 1^st level. At Day 4, Level 1 and 2 communicated through teleporters T1 and T2.

Figure 2

Higher FC in RS than SD participants between the right dorsal striatum (seed; left panel) and the middle frontal gyrus (target; right panel; cluster p^FWE = 0.001851) at Day 4 prior to relearning. Target clusters are visualised using the CONN toolbox glass display [46]. Seed areas are displayed on the mean MNI template (SPM12 software, Wellcome Department of Cognitive Neurology, London).

Figure 3

Higher seed-based FC in SD than RS participants between (left panel) left retrosplenial cortex (seed) and two frontal clusters (target left superior frontal gyrus and right middle frontal gyrus; cluster p^FWE > 0.00005) and (right panel) right entorhinal cortex (seed) and a right frontal gyrus cluster (target; cluster p^FWE < 0.002). Target clusters are visualised using the CONN toolbox glass display [46]. Seed areas are displayed on the mean MNI template (SPM12 software, Wellcome Department of Cognitive Neurology, London).