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Randomized Controlled Trial
. 2014 Aug;17(8):1107-13.
doi: 10.1038/nn.3759. Epub 2014 Jul 6.

Reactivation of Emergent Task-Related Ensembles During Slow-Wave Sleep After Neuroprosthetic Learning

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Free PMC article
Randomized Controlled Trial

Reactivation of Emergent Task-Related Ensembles During Slow-Wave Sleep After Neuroprosthetic Learning

Tanuj Gulati et al. Nat Neurosci. .
Free PMC article

Abstract

Brain-machine interfaces can allow neural control over assistive devices. They also provide an important platform for studying neural plasticity. Recent studies have suggested that optimal engagement of learning is essential for robust neuroprosthetic control. However, little is known about the neural processes that may consolidate a neuroprosthetic skill. On the basis of the growing body of evidence linking slow-wave activity (SWA) during sleep to consolidation, we examined whether there is 'offline' processing after neuroprosthetic learning. Using a rodent model, we found that, after successful learning, task-related units specifically experienced increased locking and coherency to SWA during sleep. Moreover, spike-spike coherence among these units was substantially enhanced. These changes were not present with poor skill acquisition or after control awake periods, demonstrating the specificity of our observations to learning. Notably, the time spent in SWA predicted the performance gains. Thus, SWA appears to be involved in offline processing after neuroprosthetic learning.

Figures

Figure 1
Figure 1. Direct control of motor cortex units
a, Direct neural control of a feeding tube (θ = angular position). Each trial started with the tube at P1. b, Trial started with an audio tone cue and opening of the door. A successful trial required movement of the tube to P2 within 15 seconds. c, Change in task completion time as a function of trial number (line shows moving average of 20 trials). d, Comparison of time to trial completion and change in percentage of unsuccessful trials for ‘robust learning’ and ‘poor learning’ sessions. e, Angular position of the tube is shown from a single session (mean ± s.e.m.). Peri-event histogram (PETH) from early and late trials from a single session are shown in left and right panels respectively. trd task-related direct units, tri: task-related indirect units and tu: task-unrelated units. f, Comparison of the percentage of units that experienced a significant change in modulation depth. * = p < 0.001. g, Histogram of percentage change in modulation depth (MDchange) for each of the three category of units.
Figure 2
Figure 2. Changes in phase-locking and coherent spiking during SWS after learning
a, Examples of fifty raw LFP traces during SWSpre and SWSpost for a task-related direct neuron. Superimposed is the mean trace from an SWS epoch. Each trace was aligned to time of spike (dotted line). b, Filtered (0.3–3Hz) and unfiltered spike-triggered averages (STA) during SWS before and after successful acquisition of neuroprosthetic skill. c, Percent change in STA amplitude for each of the three categories of units in 15 sessions (mean ± s.e.m., * p < 0.001). d, Scatter plot showing relationship of depth of modulation during task performance to change in STA amplitude (R=0.85, Spearman correlation; p < 0.05). Color code represents each class of neuron. Dotted lines are the 0 values for the × and y-axes. e, Comparison of the power spectra from 10 minutes of SWSpre and SWSpost from a single experiment. Inset compares the power in the 0.3–3 Hz band for multiple experiments (n=15, normalized to SWSpre for each experiment).
Figure 3
Figure 3. Changes in spike-filed coherence (SFC) after learning
a, Example plot of SFC as a function of frequency before (blue) and after (red) skill acquisition for a direct pair. The lighter band is the jackknife error. The box highlights the 0.3–3Hz band. b, Task-unrelated SFC. c, Mean changes in SFC for the various categories of units. Lines marked by an ‘*’ indicate comparisons that showed significant differences (one-way ANOVA for overall, post hoc t-test with p < 0.001).
Figure 4
Figure 4. Changes in spike-spike coherence (SSC) after learning
a, Example plot of SSC as a function of frequency before (blue) and after (red) skill acquisition for a direct pair. The lighter band is the jackknife error. The box highlights the 0.3–3Hz band. Below are the respective cross-correlograms from SWSpre and SWSpost b, Spike-spike coherence of a task-unrelated pair. c, Mean changes in SSC for the various categories of neuron pairs. Lines above with an ‘*’ indicate comparisons that showed significant differences (one-way ANOVA for overall, post hoc t-test with p < 0.001).
Figure 5
Figure 5. Lack of increase in coherent spiking with poor learning and in control sleep
a, Plot of trial times versus trial number. Right panel shows the STA before and after. b, Mean changes in direct unit STA for robust learning (reproduced from Fig. 2c) and poor learning sessions. Also shown are units from ‘control awake’ periods. c, Changes in SSC for robust learning (reproduced from Fig. 2e) and poor learning for task-related pairs.
Figure 6
Figure 6. Changes in reactivation strength after learning
a, Peri-event firing rate modulation of units from a single session. Only task related units are shown and sorted by weights in the first principle component (PC). b, Correlation matrix eigenvalues calculated from activity during task performance (RL = Robust Learning; PL = Poor Learning). Dotted line is the signal threshold (λmax), defined as the theoretical upper bound for a randomized spike train. c, Reactivation strength during SWSpre and SWSpost for RL and PL. d, Mean population differences between SWSpre and SWSpost distributions of reactivation strengths for RL (n=15 sessions) and PL (n=4 sessions). * p < 0.05 logrank test. e, Event triggered average of reactivation strength centered on maximum delta wave negativity (time = 0) for SWSpost. * p < 0.01 t-test. f, Comparison of relative ratio of reactivation during baseline period and at time of maximum delta negativity (i.e. at time 0 in e). * p<0.001, t-test.
Figure 7
Figure 7. Continued task performance after sleep
a, Plot of time to task completion versus trial number. Conventions same as in Fig. 1c. Trace inset shows the STA from the respective sleep for a task-related neuron. STA scales are the same. b, Average time to reward at the end of first training session (Block1end) compared to the beginning of second session (Block2begin). * p<0.05 for all eight comparisons. c, Average trial time at the beginning of second session (Block2begin) compared to its end (Block2end). d, Relationship between mean change in STA amplitude for trd units and the improvement in performance. Also noted are the correlation coefficient and p value for the Spearman test. e, Relative changes in STA amplitude for trd and tri units between sleep1–2 and sleep2–3f, Relative change in SFC magnitude. g, Relative change in SSC magnitude.

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