Initiation of sleep-dependent cortical-hippocampal correlations at wakefulness-sleep transition

Abstract

Sleep is involved in memory consolidation. Current theories propose that sleep-dependent memory consolidation requires active communication between the hippocampus and neocortex. Indeed, it is known that neuronal activities in the hippocampus and various neocortical areas are correlated during slow-wave sleep. However, transitioning from wakefulness to slow-wave sleep is a gradual process. How the hippocampal-cortical correlation is established during the wakefulness-sleep transition is unknown. By examining local field potentials and multiunit activities in the rat hippocampus and visual cortex, we show that the wakefulness-sleep transition is characterized by sharp-wave ripple events in the hippocampus and high-voltage spike-wave events in the cortex, both of which are accompanied by highly synchronized multiunit activities in the corresponding area. Hippocampal ripple events occur earlier than the cortical high-voltage spike-wave events, and hippocampal ripple incidence is attenuated by the onset of cortical high-voltage spike waves. This attenuation leads to a temporary weak correlation in the hippocampal-cortical multiunit activities, which eventually evolves to a strong correlation as the brain enters slow-wave sleep. The results suggest that the hippocampal-cortical correlation is established through a concerted, two-step state change that first synchronizes the neuronal firing within each brain area and then couples the synchronized activities between the two regions.

Keywords: high-voltage spike waves; hippocampus; memory consolidation; ripples; sleep.

Fig. 1.

Methods for behavioral state classification, high-voltage spike wave (HVS) and ripple event detection, and computing triggered multiunit activity (MUA) averages. A: an animal's behavior at every second of a 6-min time window was classified into wakefulness (Wake), rapid-eye-movement sleep (REM), slow-wave sleep (SWS), or intermediate (Int) states based on the electromyography (EMG) power, cortical delta power, hippocampal ripple power, and hippocampal theta-to-delta power ratio. Dashed lines: thresholds for state classification (see materials and methods for classification criteria). Two thresholds were defined for EMG, 1 for defining Wake state and 1 for REM. B: the animal's behavioral states during a 1-h session are displayed in a state space defined by EMG power, cortical delta power, and hippocampal theta-to-delta ratio. Each dot represents a state. Note that Wake, REM, and SWS states are well-separated along the 3 axes. C: cortical HVS and hippocampal ripple events were detected from band-pass filtered (6–12 Hz for HVS, 100–250 Hz for ripple) local-field potentials (LFPs). A detected event had at least 1 value below a “trough threshold.” The start and end times (black dots) of the event was determined by a “start threshold.” D: an example of computing the MUA average triggered by ripple trough times. MUA spikes recorded from all of the tetrodes in a brain area (each row of the MUA raster plot represents a tetrode) were counted in each time bin, smoothed, and then normalized (see materials and methods for details). For each detected ripple event i, we identified the time t_i of its most negative trough. The triggered MUA with a trigger range [−Δ Δ] was a segment of the normalized MUA within the time interval [t_i−Δ t_i+Δ]. The triggered MUA average was obtained by stacking the MUA segments triggered by all of the ripple events centered at time 0 and computing the mean value (thick line) and standard error (thin lines) at each time lag from 0.

Fig. 2.

Hippocampal (HP) and cortical (CTX) LFPs during the transitional period from wakefulness to SWS. A: classified behavioral states during a 15-min period when a rat transitioned from wakefulness to sustained SWS. B: EMG, CTX LFP, and HP LFP during the same time period. C: expanded view of the CTX and HP LFPs at the boxed time points (I–IV) in B. Arrows highlight a theta wave, 3 ripple events (at various time scales), an HVS event, and a delta wave. Note the HVS and ripple events during the transition from wakefulness to SWS.

Fig. 3.

Quantification of hippocampal ripple events during different behavioral stages. Mean incidence rate (A), mean frequency (B), and mean duration (C) of ripple events are plotted for the 20-s period before the 1st detected HVS event (Pre), the entire transitional period (Tran), and SWS following the transitional period.

Fig. 4.

HP ripples occurred earlier than CTX HVS events. A: CTX LFP, CTX MUA, HP MUA, and HP LFP (filtered within the ripple band) in an 11-s time window of a sleep session before the 1st HVS event. Arrow: onset of an HVS event. B: expanded view of the boxed area in A. Arrows: ripple events. Note the repetitive incidence of HP ripples and the synchronized activity of HP MUAs when ripples occurred. Also, note the low CTX LFP amplitude (compared with Fig. 2B) and continuous, nonpatterned nature of CTX MUA activity.

Fig. 5.

Absence of interaction in HP and CTX MUAs during the pre-HVS stage. A: average cross-correlogram between CTX and HP MUAs of all sleep sessions during the 20-s window before the 1st detected HVS event. Bin size: 10 ms. Note the absence of a peak. Thin gray lines: standard errors. B and C: HP (B) and CTX (C) MUA averages triggered by ripple trough times. Thin gray lines: standard errors. Note the peak in the average HP MUA but not the average CTX MUA.

Fig. 6.

HP ripple incidence and MUA were reduced during CTX HVS events. A: CTX LFP, CTX MUA, HP MUA, and HP LFP (filtered within ripple band) are shown in a 12-s time window. Solid line: HVS event. Dashed line: reduced HP MUA. Arrows: ripple events. Note the reduced HP MUA and the absence of ripples during a time window (dashed line) after the HVS onset. Also note the rebound HP MUA and ripples at the end of the HVS event. B and C: average ripple incidence rate (B) and average HP MUA (C) triggered by HVS event onset times. Thin gray lines: standard errors.

Fig. 7.

HP and CTX MUAs were weakly correlated within HVS events. A: CTX LFP, CTX MUA, HP MUA, and HP LFP (filtered within ripple band) in a 2-s time window within an HVS event. Arrow: ripple event. B: average cross-correlogram between CTX and HP MUAs within HVS events. C and D: average CTX MUA (C) and average HP MUA (D) triggered by the HVS trough times. Thin gray lines: standard errors.

Fig. 8.

HP and CTX MUAs were strongly correlated during the SWS after the transitional period. A: CTX LFP, CTX MUA, HP MUA, and HP LFP (filtered within ripple band) in a 4-s time window. Arrow: ripple event. B: average cross-correlogram between CTX and HP MUAs within SWS. C and D: average CTX MUA (C) and HP MUA (D) triggered by the troughs of ripple events. E: average cross-correlogram between HP ripple power and cortical spindle power during SWS. Thin gray lines: standard errors.