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Aykan, D.

Publications and source records attributed to Aykan, D..

2 recordsLinked to original sources

Sharp wave-ripple clusters enhance hippocampal-neocortical engagement for memory consolidation

Hippocampal sharp wave-ripples (SPW-Rs), neocortical slow oscillations, and thalamocortical sleep spindles are hypothesized to provide a temporal framework for coordinated information transfer during memory consolidation. Hippocampal replay supports this process, yet replayed sequences often unfold across multiple SPW-Rs, suggesting that individual ripples may not constitute the fundamental unit of hippocampal output. Here, using large-scale electrophysiological recordings from the hippocampus and retrosplenial cortex, we show that hippocampal output is organized into clusters of SPW-Rs (cSPW-Rs) during UP states, which are often phase-locked to spindle troughs. Extending this approach with wide-field imaging and unsupervised latent-variable modeling, we found that cSPW-Rs enhanced segregation between the default mode and somatomotor networks and preferentially replayed spatially extended maze trajectories following learning. We propose that SPW-R clusters enable reverberating hippocampal-cortical spike exchange and the concatenation of sequential experiences, establishing ripple clusters as a previously unrecognized syntactic unit of hippocampal-neocortical dialogue.

neuroscience↗

Subspace communication in the hippocampal-retrosplenial axis

The capacity and flexibility of hippocampal circuits for transforming inputs into downstream outputs is fundamental for navigation and memory, yet the circuit-level mechanisms that allow this operation to adapt across experiences remain unknown. We approach this problem by performing large-scale (up to 1024-channel) recordings across the hippocampal-retrosplenial cortex (RSC) circuit in behaving mice, enabling simultaneous access to spiking activity in dentate gyrus (DG), CA3, CA2, CA1, RSC. Based on a linear dimensionality reduction technique known as partial canonical correlation analysis, we identify low-dimensional communication subspaces1 between two regions while accounting for measured third-area influences. These subspaces captured distinct input-output transformations in CA1, linking upstream (DG, CA3, and CA2) hippocampal activity to downstream cortical targets (RSC). Iintrinsic firing properties and anatomical location constrained subspace memberships--members were mapped to deep sublayers of the CA3-CA1-RSC axis during both spatial and non-spatial tasks. These subspaces could recombine overlapping neuronal pools to support distinct interareal interactions across changing experiences and brain states. Reactivation patterns of CA1-CA3 subspaces, but not those of CA1-RSC, during post-experience sleep correlated with replay, reflecting a plasticity-stability balance of the input-output transformation in the hippocampal-retrosplenial axis. Our data suggest a model in which hippocampal-neocortical communication reconfigures predetermined circuit motifs to flexibly encode experiences.

neuroscience↗