Inhibitory plasticity supports replay generalization in the hippocampus

Memory consolidation assimilates recent experiences into long-term memory. This process requires the replay of learned sequences, though the content of these sequences remains controversial. Recent work has shown that the statistics of replay deviate from those of experience: stimuli that are experientially salient may be either recruited or suppressed from sharp-wave ripples. We find that this phenomenon can be explained parsimoniously and biologically plausibly by a Hebbian spike time-dependent plasticity rule at inhibitory synapses. Using models at three levels of abstraction--leaky integrate-and-fire, biophysically detailed, and abstract binary-we show that this rule enables efficient generalization. We make specific predictions about the consequences of intact and perturbed inhibitory dynamics for network dynamics and cognition. Finally, we use optogenetics to artificially implant nongeneralizable representations into the network, and find that these representations also accumulate..., , , # Inhibitory plasticity supports replay generalization in the hippocampus

[https://doi.org/10.5061/dryad.v15dv424t](https://doi.org/10.5061/dryad.v15dv424t)

Data associated with manuscript \"Inhibitory plasticity supports replay generalization in the hippocampus\" Nature Neuroscience 2024.

## Description of the data and file structure

Index of figure source data files.

1\. Figures in main text.

Figure 2.

\- Fig2b_place_sts_df.csv

Place cell spike times during online phase. Each column contains the spike times in seconds of the neuron gid specified in the first row.

\- Fig2b_cue_sts_df.csv

Place cell spike times during online phase. Each column contains the spike times in seconds of the neuron gid specified in the first row.

\- Fig2b_events_df.csv

Simulated cue events during online phase. Column event_times contains event times in seconds.

\- Fig2c_place_cell_norm_firing_rate.csv

Computed normalized firing rates in Hz for place cells during final lap of the online phase. Each...