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Dryad

Data from: Time or distance: flexible coding of Hippocampal cells

Cite this dataset

Abramson, Shai et al. (2024). Data from: Time or distance: flexible coding of Hippocampal cells [Dataset]. Dryad. https://doi.org/10.5061/dryad.ngf1vhhxp

Abstract

Analysis of neuronal activity in the hippocampus of behaving animals has revealed cells acting as "Time Cells," which exhibit selective spiking patterns at specific time intervals since a triggering event, and "Distance Cells," which encode the traversal of specific distances. Other neurons exhibit a combination of these features, alongside place selectivity. This study aims to investigate how the task performed by animals during recording sessions influences the formation of these representations. The data used here was originally curated in a treadmill running study conducted by Kraus et al. (2013) in which rats were trained to run at different velocities. The rats were recorded in two trial contexts: a "fixed time" condition, where the animal ran on the treadmill for a predetermined duration before proceeding, and a "fixed distance" condition, where the animal ran a specific distance on the treadmill. Our findings indicate that the type of experimental condition significantly influenced the encoding of hippocampal cells. Specifically, distance-encoding cells dominated in fixed-distance experiments, whereas time-encoding cells dominated in fixed-time experiments. These results underscore the flexible coding capabilities of the hippocampus, which are shaped by over-representation of salient variables associated with reward conditions.

Data used in Absramson et al., 2023, "Time or distance: flexible coding of Hippocampal cells",  originally curated by Kraus et al., Neuron, 78(6), 1090-1101, 2013.

README: Recording and analysis of 6 animals during treadmill runs in fixed-time and fixed-distance trials

The original Kraus et al data *.mat files are named by the respective animal and trial date and contains trials data. For example, bk45-0826 contains the data from animal number 45 from a trial conducted by August 26th. The cells classification analysis results are at ResultsSummary.xls

Description of the data and file structure

BKnn-mmdd.mat contains each trail data (nn is the animal number, mmdd is the month and day of the experiment)

The important data structure items are :

neurons : contains the time stamps of the events for each recorded neuron
alltreadmill : contains the start time, stop time, velocity and period of each run in the trial

ResultsSummary.xls contains the cells count in of each cell type in the fixed-distance and fixed-time experiments per the 3 metrics defined in the paper : CellType, Fit and P-Value :

The rows display the results for each of the following analyses :

- By onset, until treadmill stops + 5 secs, with 100mSec time bins
- By onset, until 16 sec from treadmill start, with 100mSec time bins
- By peak firing, until treadmill stops + 5 secs, with 100mSec time bins
- By peak, until 16 sec from treadmill start, with 100mSec time bins

Methods

Data originally curated in Kraus et al., Neuron, 78(6), 1090-1101, 2013

Usage notes

Matlab

Funding

Israel Science Foundation, Award: 2655/18

Israel Science Foundation, Award: 2183/21

German-Israeli Foundation for Scientific Research and Development, Award: GIF I-1477-421.13/2018

United States-Israel Binational Science Foundation, Award: NIMH-BSF CRCNS BSF:2019807, NIMH:R01 MH125544-01