Sharp-wave ripples as a signature of hippocampal-prefrontal reactivation for memory during sleep and waking states

Abstract

It is widely believed that memories that are encoded and retrieved during waking behavior are consolidated during sleep. Recent studies on the interactions between the hippocampus and the prefrontal cortex have greatly advanced our understanding of the physiological bases of these memory processes. Although hippocampal-prefrontal network activity differs in many aspects during waking and sleep states, here we review evidence that hippocampal sharp-wave ripples (SWRs) emerge as a common neurophysiological pattern in both states, facilitating communication between these two regions via coordinated reactivation of stored memory information. We further consider whether sleep and awake reactivation mediate similar memory processes or have different mnemonic functions, and the mechanistic role of this cross-regional dialogue in learning and memory. Finally, we provide an integrated view of how these two forms of reactivation might work together to support spatial learning and memory.

Keywords: Consolidation; Hippocampus; Memory; Prefrontal cortex; Reactivation; Sharp-wave ripples (SWRs).

Figure 1. Hippocampal-prefrontal coordination during sleep SWRs

(A) Distinct hippocampal-prefrontal activity patterns during NREM and REM sleep. Simultaneously recoded spiking activity from the hippocampal area CA1(black ticks) and PFC (blue ticks) is shown along with corresponding CA1 LFP traces (red line: theta-delta ratio; green line, ripple-filter LFP). REM sleep (red shading) is accompanied by enhanced theta (6-12 Hz) power (characterized by theta-delta ratio), and theta-modulated firing of CA1 pyramidal cells (horizontal stripes in the raster plot). In NREM sleep (grey shading), large-amplitude ripples (green line) were observed, coincident with population synchrony of CA1 spikes (note the vertical stripes in the raster plot). Top panel shows an expanded view of a representative CA1 synchronous reactivation event during sleep SWRs (orange shading). (B) Hippocampal-prefrontal oscillatory coupling during NREM sleep. Example traces of simultaneously acquired LFPs from two CA1 (top) and two PFC tetrodes (bottom) in NREM stage are shown. Note that CA1 ripples (green) are closely followed by delta waves (1-4 Hz; orange) and spindles (12-18 Hz; red). (C-E) Coordinated hippocampal-prefrontal reactivation during sleep SWRs. The coordinated reactivation of hippocampal-prefrontal ensembles can be measured using reactivation strength (Peyrache et al., 2009; Peyrache et al., 2010). This method uses principle components analysis (PCA) to detect neuronal ensembles, within which spiking activity is strongly co-activated among individual neurons of the ensemble during behavioral tasks. The contributions of single neurons to the co-activation are measured as their corresponding PC weights (D; color-coded to highlight neurons with high weights). The reactivation strength (RS) measures the correlation between the activity patterns during behavior characterized by PC weights and those during SWRs. If this synchronous activation of the detected ensembles during behavior is also strongly reactivated during sleep periods, the RS will have a high value. The RS of a representative CA1-PFC ensemble during sleep is shown in C. Notably, the RS is higher during post-task sleep (bottom) than pre-task sleep (top), suggesting enhanced reactivation after experience and learning. Also, the increase of RS during post-task sleep is prominent during NREM sleep (grey shadings), but not REM sleep (red shadings), suggesting stronger CA1-PFC reactivation in NREM stage. (E) The peaks of RS (top) represent synchronous events of CA1-PFC ensembles (bottom), which occurred predominantly during SWRs (same color code used in D). Panels adapted from Tang et al. (2017).

Figure 2. Hippocampal-prefrontal network oscillatory patterns differ during awake and sleep SWRs

(A-B) SWR-triggered power spectrograms in CA1 (A) and PFC (B) during pre-task NREM sleep (left), wake (middle), and post-task NREM sleep (right). The spectrograms were Z-scored by the average power of each frequency in a given session. Note that there is enhanced delta (1-4 Hz) and spindle (12-18 Hz) power in the CA1 and PFC during sleep SWRs, but not during awake SWRs. (C-D) Averaged cross-correlograms of CA1 ripple power versus PFC spindle (C) and delta (D) power. Note that there is stronger spindle-ripple and delta-ripple coupling during NREM sleep (purple) than waking (black). In addition, consistent with previous studies (Siapas and Wilson, 1998; Phillips et al., 2012), there is an asymmetry between positive and negative time lags in sleep correlograms, indicating an overall tendency for ripples to precede spindle-ripple/delta-ripple episodes. Panels adapted from Tang et al. (2017).

Figure 3. The functional roles of hippocampal-prefrontal reactivation across sleep-waking cycles

In spatial learning tasks, animals learn by trial and error that particular sequences of locations (paths) will be rewarded (left top). As animals traverse the environment, many hippocampal neurons (blue triangles) selectively respond to certain locations in the environment (i.e., place fields, represented by blue ellipses). Upon reward receipt, awake SWRs occur at the reward location (left; SWRs shown in green), which serve as a potential neural mechanism to linking spatial experience encoded by hippocampal ensembles with rewards and outcomes encoded by PFC ensembles (red triangles; left bottom). When animals perform the same task in a different environment (middle), different action-outcome associations (green and red triangles) form in the hippocampal-prefrontal network during awake SWRs. During subsequent sleep SWRs (right), repeated hippocampal-prefrontal reactivation strengthens memory traces. These sleep SWRs are further coupled with prefrontal delta waves (orange line) and spindles (red line), which allows active systems consolidation and local cortical processes. During these processes, the overlapping prefrontal memory traces form connections with each other, creating an integrated representation (red triangles and connecting lines).