David Dupret

The paper shows that brain regions use a shared ring manifold to represent time, with population activity evolving along a common trajectory to encode elapsed time through traversal speed modulation.

The paper shows that generative replay occurs in primary visual cortex during sleep, influenced by hippocampal activity, suggesting a mechanism for building hierarchical generative models for flexible behavior.

The paper identifies a slow-oscillatory architecture in the human medial temporal lobe that coordinates population activity during learning and facilitates offline reactivation and recall.

The paper shows that the scaling exponent of hippocampal activity during sleep/rest predicts spatial memory performance independently of reactivation.

The paper identifies two distinct hippocampal ripple types in mice during sleep/rest, showing they reorganize neuronal reactivation differently to integrate recent experiences and update prior memories.

The paper maps electrophysiological patterns along the hippocampal CA1-to-DG axis, identifying layer-specific activity signatures and firing motifs.

This study shows that dentate spikes (DSs) during sleep reactivate memory-related neuronal patterns, supporting flexible memory, and are distinct from sharp-wave ripples (SWRs) in their structure and function.

The paper shows that forming a robust memory restricts hippocampal coactivity, impairing flexible memory formation, and that optogenetic suppression during robust memory formation restores flexibility.

This paper develops an unsupervised method to classify dentate spikes into types 1 and 2 based on waveform features, showing high accuracy and revealing differences in DS characteristics between apoE3 and apoE4 mice.

The paper models hippocampal memory operations as a disk-drive system, showing spike sequences and replay dynamics align with disk-drive mechanics.

The paper shows that hippocampal activity predicts excitatory-inhibitory fluctuations in visual cortex during memory recall.

The paper develops a framework to analyze oscillatory waveform dynamics by isolating signals and quantifying cycle shape changes using instantaneous frequency, revealing variability in theta oscillations in mouse hippocampal recordings.

The paper investigates how neural coactivity encodes dynamic memory in mice, finding that contingency discrimination relies on emergent coactivity patterns rather than individual neuron tuning.