DOI: 10.5061/dryad.nk98sf7xx
title: Temporal cluster-based organisation of sleep spindles underlies motor memory consolidation

description: Sleep benefits motor memory consolidation, which is mediated by sleep
 spindle activity and associated memory reactivations during non-rapid eye
 movement (NREM) sleep. However, the particular role of NREM2 and NREM3
 sleep spindles and the mechanisms triggering this memory consolidation
 process remain unclear. Here, simultaneous electroencephalographic and
 functional magnetic resonance imaging (EEG-fMRI) recordings were collected
 during night-time sleep following the learning of a motor sequence task.
 Adopting a time-based clustering approach, we provide evidence that
 spindles iteratively occur within clustered and temporally organised
 patterns during both NREM2 and NREM3 sleep. However, the clustering of
 spindles in trains is related to motor memory consolidation during NREM2
 sleep only. Altogether, our findings suggest that spindles’ clustering and
 rhythmic occurrence during NREM2 sleep may serve as an intrinsic rhythmic
 sleep mechanism for the timed reactivation and subsequent consolidation of
 motor memories, through synchronised oscillatory activity within a
 subcortical-cortical network involved during learning.
description: Sleep EEG data were processed using the
 MATLAB R2019b software from The MathWorks (Natick, MA) and the open-source
 Brainstorm and EEGLAB softwares. The codes for the detection and
 clustering of sleep spindles are available at the following GitHub
 repositories: https://github.com/labdoyon/spindlesDetection and https://github.com/arnaudboutin/Spindle-clustering
description: Dataset related to the article Temporal cluster-based organisation of
 sleep spindles underlies motor memory consolidation \## Description of the
 experimental context and task In this study, participants were required to
 practice a motor sequence learning (MSL) task during training (14 blocks)
 and two retention sessions (1 block each) while lying supine in the MRI
 scanner. The MSL task required participants to perform an explicitly known
 5-element finger movement sequence as rapidly and accurately as possible
 using a response pad. Each practice block was composed of twelve
 repetitions of the motor sequence (i.e., 60 key presses per block).
 Participants underwent the training session about 30 minutes before going
 to sleep. They were then administered two delayed retention tests,
 performed 15 minutes (test) and 24 hours (retest) after the end of
 training. Each of the two retention tests consisted of only one practice
 block to minimise the effects of additional practice on the MSL task. \##
 Description of the data and file structure Dataset includes the changes in
 motor sequence performance from the delayed 15min test to the 24hr retest
 (in %), as a behavioural index of motor memory consolidation. The NREM2
 tab contains the information of all sleep spindle characteristics
 extracted at the Pz derivation during NREM2 sleep, including: *
 LengthTrain_N2: length of spindle trains (mean number of spindles per
 train) * ISI_N2: inter-spindle interval (in second) * ITI_N2: inter-train
 interval (in second) * GlobalDensity_N2: global density (number of
 spindles per minute) * LocalDensity_N2: local density (number of spindles
 within a spindle-centred sliding window of 60 seconds) * TotalSpindle_N2:
 total number of spindles * Ratio_N2: proportion of grouped over isolated
 spindles (in percentage) The NREM3 tab contains the information of all
 sleep spindle characteristics extracted at the Pz derivation during NREM3
 sleep, including similar metrics as detailed above. The iCoherence_N2 tab
 contains the information related to functional connectivity analysis
 between specific subcortical regions, by estimating the imaginary part of
 coherency: Putamen-Hippocampus coherence, Putamen-Thalamus coherence, and
 Hippocampus-Thalamus coherence (refers to the Figure 4 in the main
 manuscript). The sleep stages tab contains all the information related to
 time of sleep in the different stages, including: * WAKE * REM: Rapid Eye
 Movement * NREM1: Non-Rapid Eye Movement stage1 * NREM2: Non-Rapid Eye
 Movement stage2 * NREM3: Non-Rapid Eye Movement stage3 * Total Sleep Time
 \## Code/Software Sleep EEG data were processed using the MATLAB R2019b
 software from The MathWorks (Natick, MA) and the open-source Brainstorm
 and EEGLAB softwares. The codes for the detection and clustering of sleep
 spindles are available at the following GitHub repositories:
 and