1. NATURE NEUROSCIENCE
Coordinated memory replay in the visual cortex and hippocampus during sleep
Daoyun Ji & Matthew A Wilson
Department of Brain and Cognitive Sciences and Department of Biology
Massachusetts Institute of Technology, USA
Xinjian Li

2. Matthew A Wilson
Department of Brain and Cognitive Sciences and Department of Biology,
Massachusetts Institute of Technology, Cambridge
Hippocampal in Learning and Memory
Their studies of learning and memory in awake, behaving animals have led to the exploration of the nature of sleep and its role in memory.

3. Electrophysiological evidence:
Background
The hippocampus is essential for episodic memory. Memory consolidation: active communication between the cortex and hippocampus. In hippocampus ,new memory transforms into long-term memory and stored in the cortex (Theory).
Electrophysiological evidence:
First, electroencephalogram (EEG) events between the cortex and hippocampus are correlated, suggesting the two areas are engaged in active interaction during sleep.
Second, cell pairs that are correlated during awake experience are also correlated during subsequent sleep within the hippocampus, within the cortex, and between the hippocampus and cortex (pairwise correlation).
theory of system memory consolidation
These results imply that the experience-related neuronal activity is, to some degree, reactivated during sleep.
However, the reactivation in these studies lacks the specificity presumably required for episodic memory.

4. Background
High-order replay (firing temporal is similar with task) has been observed in the hippocampus during slow-wave sleep (SWS) and rapid-eye-movement sleep.
However, whether high-order replay exists in the cortex remains unknown.
More importantly, the relationship between replay events in the cortex and hippocampus has not been studied.

5. Four Long-Evans rats (5–8 months old)
Background
Experimental design
Four Long-Evans rats (5–8 months old)
After about 2–3 weeks’ training, we implanted a microelectrode array containing 18 independently adjustable tetrodes. Six to eight tetrodes were assigned to the hippocampus and 10–12 tetrodes aimed at primary visual cortex
We reintroduced rats to the maze one week after the surgery and retrained them for about 10–15 d before the recording.
Figure Experimental design. During the RUN sessions, rats were trained to run an alternation task on a figure-8-shaped maze.

6. Firing patterns during SWS in the cortex and hippocampus
Results
Firing patterns during SWS in the cortex and hippocampus
Figure 2 Visual cortical and hippocampal spiking activities were organized as frames during SWS
(a) Cortical (CTX) and hippocampal (HP) frames during a 5-s SWS episode.
They refer to these active periods as frames
(b) Distributions of durations of frames and interframe silent periods in the cortex and hippocampus.
(c) Cortical EEG averages triggered by cortical frame start and end times.
d) Occurrence rate of hippocampal ripple events within hippocampal frames
(e) Average cross-correlogram between cortical and hippocampal frame start times and between their end times

7. High-order replay in the cortex and hippocampus
Results
High-order replay in the cortex and hippocampus
Figure 3 Visual cortical cells displayed localized firing fields.
(a) Firing rate maps of a cortical cell (CTX) and a hippocampal place cell (HP) on two consecutive recording days
(b) Consistent firing of the cortical cell and the hippocampal cell examined lap by lap on day 1 when the rat was running the leftright and rightleft trajectories
(c) Spatial information from cortical cells and hippocampal cells that were active on the maze.

8. High-order replay in the cortex and hippocampus
Results
High-order replay in the cortex and hippocampus
Figure 4. Sleep frames replayed multicell firing sequences during RUN in both the visual cortex and the hippocampus.
Cortical firing sequence during RUN and in a POST sleep frame
Hippocampal firing sequence during RUN and in a POST sleep frame

9. They then examined whether the observed numbers of replaying frames significantly deviated from those expected by chance, using two methods to evaluate the significance.
First, we computed the theoretical distribution of replaying frame numbers by assuming a binomial process in which every frame independently matches a template sequence at the same probability as the cutoff threshold. This distribution is referred to as chance distribution.
The second method tested the null hypothesis that a RUN template sequence is replayed with the same probability as any of its random shuffles. From the null hypothesis, a shuffle distribution of replaying frame number was obtained

10. High-order replay in the cortex and hippocampus
Results
High-order replay in the cortex and hippocampus
(a) Chance (dotted line) and shuffle (solid line) distributions of the number of replaying frames that were randomly generated for the visual cortex during PRE and POST.
(b) Same as a, but for
the hippocampus.
Figure 5 Frame replays occurred significantly more often than chance in POST in both the visual cortex and hippocampus.

11. Interaction between cortical and hippocampal replays
Results
(a) A cortical (CTX) and a hippocampal (HP) replaying frame that overlapped in time.
(b,c) Distributions of pair numbers produced by shuffling for overlapping cortical-hippocampal frame pairs that replayed the same (b) and different (c) trajectories in PRE and POST. Vertical gray lines, actual observed numbers.
(d) Dependence of the significance P values of the actual observed numbers on the matching probability threshold in PRE and POST.
Figure 6 Visual cortical and hippocampal frames that replayed the same trajectories tended to occur at the same time.

12. To provide further evidence that the replays in the hippocampus and the cortex were coordinated, they applied an interval analysis as follows. For a cell in a replaying frame in one area and a cell in one of its overlapping frames in the other area, they computed the temporal interval between their peak firing times in their corresponding frames, and compared it with the temporal interval between their peak firing times on a RUN trajectory.
Based on all cortical replaying frames for a trajectory, they first collected sleep intervals of all cell pairs with one cell in a cortical replaying frame and the other in one of its overlapping hippocampal frames, and their corresponding RUN intervals on the trajectory. We then examined whether the sleep intervals and the RUN intervals were correlated.

13. Interaction between cortical and hippocampal replays
Results
Interaction between cortical and hippocampal replays
(a) Time intervals between cortical and hippocampal cell pairs based on cortical replaying frames, compared with their corresponding RUN intervals on a trajectory. Solid line, linear regression
between the sleep and RUN intervals.
(b) Distribution of shuffling-produced correlation. Vertical line, actual observed correlation.
(c) P values of the actual
observed correlations based on cortical replaying frames for all trajectories. Trajectories represented by the same shape were from the same rat.
(d) Same as c, but based on hippocampal replaying frames.
Figure 7 Cortical and hippocampal frames co-replayed the same running trajectory as revealed by interval analysis.

14. Conclusions
Spiking patterns not only in the cortex but also in the hippocampus were organized into frames.
The multicell firing sequences evoked by awake experience were replayed during these frames in both regions.
Revents in the sensory cortex and hippocampus were coordinated to reflect the same experience.
These results imply simultaneous reactivation of coherent memory traces in the cortex and hippocampusduring sleep that may contribute to or reflect the result of the memory consolidation process.

15. Thanks you for your attention