Neural activity patterns of recent experiences are reactivated during sleep in structures critical for memory storage, including hippocampus and neocortex. This reactivation process is thought to aid memory consolidation. Although synaptic rearrangement dynamics following learning involve an interplay between slow-wave sleep (SWS) and rapid eye movement (REM) sleep, most physiological evidence implicates SWS directly following experience as a preferred window for reactivation. Here, we show that reactivation occurs in both REM and SWS and that coordination of REM and SWS activation on the same day is associated with rapid learning of a motor skill. We performed 6 h recordings from cells in rats' motor cortex as they were trained daily on a skilled reaching task. In addition to SWS following training, reactivation occurred in REM, primarily during the pre-task rest period, and REM and SWS reactivation occurred on the same day in rats that acquired the skill rapidly. Both pre-task REM and post-task SWS activation were coordinated with muscle activity during sleep, suggesting a functional role for reactivation in skill learning. Our results provide the first demonstration that reactivation in REM sleep occurs during motor skill learning and that coordinated reactivation in both sleep states on the same day, although at different times, is beneficial for skill learning. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.

Anatomical connectivity and lesion studies reveal distinct functional heterogeneity along the dorsal-ventral axis of the hippocampus. The immediate early gene Arc is known to be involved in neural plasticity and memory and can be used as a marker for cell activity that occurs, for example, when hippocampal place cells fire. We report here, that Arc is expressed in a greater proportion of cells in dorsal CA1, CA3, and dentate gyrus (DG), following spatial behavioral experiences compared to ventral hippocampal subregions (dorsal CA1 = 33%; ventral CA1 = 13%; dorsal CA3 = 23%; ventral CA3 = 8%; and dorsal DG = 2.5%; ventral DG = 1.2%). The technique used here to obtain estimates of numbers of behavior-driven cells across the dorsal-ventral axis, however, corresponds quite well with samples from available single unit recording studies. Several explanations for the two- to-threefold reduction in spatial behavior-driven cell activity in the ventral hippocampus can be offered. These include anatomical connectivity differences, differential gain of the self-motion signals that appear to alter the scale of place fields and the proportion of active cells, and possibly variations in the neuronal responses to non-spatial information within the hippocampus along its dorso-ventral axis.

The mechanisms governing how the hippocampus selects neurons to exhibit place fields are not well understood. A default assumption in some previous studies was the uniform random draw with replacement (URDWR) model, which, theoretically, maximizes spatial "pattern separation", and predicts a Poisson distribution of the numbers of place fields expressed by a given cell per unit area. The actual distribution of mean firing rates exhibited by a population of hippocampal neurons, however, is approximately exponential or log-normal in a given environment and these rates are somewhat correlated across multiple places, at least under some conditions. The advantage of neural activity-dependent immediate-early gene (IEG) analysis, as a proxy for electrophysiological recording, is the ability to obtain much larger samples of cells, even those whose activity is so sparse that they are overlooked in recording studies. Thus, a more accurate representation of the activation statistics can potentially be achieved. Some previous IEG studies that examined behavior-driven IEG expression in CA1 appear to support URDWR. There was, however, in some of the same studies, an under-recruitment of dentate gyrus granule cells, indicating a highly skewed excitability distribution, which is inconsistent with URDWR. Although it was suggested that this skewness might be related to increased excitability of recently generated granule cells, we show here that CA1, CA3, and subiculum also exhibit cumulative under-recruitment of neurons. Thus, a highly skewed excitability distribution is a general principle common to all major hippocampal subfields. Finally, a more detailed analysis of the frequency distributions of IEG intranuclear transcription foci suggests that a large fraction of hippocampal neurons is virtually silent, even during sleep. Whether the skewing of the excitability distribution is cell-intrinsic or a network phenomenon, and the degree to which this excitability is fixed or possibly time-varying are open questions for future studies. © 2016 Wiley Periodicals, Inc.