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Coordinates activities of retrosplenial ensembles during resting-state encode spatial landmarks. Part 2 of 2

Citation

Chang, HaoRan et al. (2020), Coordinates activities of retrosplenial ensembles during resting-state encode spatial landmarks. Part 2 of 2, Dryad, Dataset, https://doi.org/10.5061/dryad.jh9w0vt7q

Abstract

The brain likely uses off-line periods to consolidate recent memories. One hypothesis holds that the hippocampal output provides a unique, global linking or 'index' code for each memory, and that this code is stored in the cortex in association with locally encoded attributes of each memory. Activation of the index code is hypothesized to evoke coordinated memory trace reactivation thus facilitating consolidation. Retrosplenial cortex (RSC) is a major recipient of hippocampal outflow and we have described populations of neurons there with sparse and orthogonal coding characteristics that resemble hippocampal 'place' cells, and whose expression depends on an intact hippocampus. Using two-photon Ca2+ imaging, we recorded ensembles of neurons in the RSC during periods of immobility before and after active running on a familiar linear treadmill track. Synchronous bursting of distinct groups of neurons occurred during rest both prior to and after running. In the second rest epoch, these patterns were associated with the locations of tactile landmarks and reward. Complementing established views on the functions of the RSC, our findings indicate that the structure is involved with processing landmark information during rest.

Methods

This dataset includes imaging data collected from three Thy1-GCaMP6s transgenic mice in the Retrosplenial Cortex (RSC). Imaging data were acquired using a Thorlabs Bergamo II multiphoton microscope. Tissue was excited by a Ti:Sapphire laser (Coherent) tuned to an excitatory wavelength of 920 nm. Beam focusing and light collection were achieved by a 16X water immersion objective (Nikon, NA 0.8, 80-120 mW output power measured at the sample). Beam-scanning was conducted by Galvo-Resonant mirrors. Emitted fluorescent lights were detected by a GaAsP photomultiplier tube (Hamamatsu) and digitized to a resolution of 800x800 pixels at a sampling rate of 19 Hz. We collected an 835x835 um window over layers II-III of the agranular RSC at depths between 100 and 200 um (imaging windows centred at -1.8 to -2.5 mm AP, 0.5 mm ML).

Usage Notes

Dataset divided into two DOIs due to large file size. See Related Resources for a link to the additional part.

The original size of the files was 560 GB. The files were archived using tar and compressed using pigz.

The folder structure is as follows: 1. animal ID, 2. date of recording, 3. session number. In folder 2 resides abf files generated from Clampex for individual recordings. Channel 1 contains frame pulses corresponding to the start and the end of rasterization of each individual recorded frame. Channels 2 and 3 correspond to outputs A and B respectively of the optical rotary encoder used in detecting the position of the animal over the treadmill belt. Finally, channel 5 contains the readout for the delivery of reward, which also serves to signal the start of a new lap. In folder 3 are raw imaging files along with xml files, which hold the experimental parameters, generated by the ThorImage software.

Part 2 of 2 files

d9c381900f55511f10aa02cef78741e6  RSC037-2017_08_30-1.tar.gz
3226b62d02b78ed1c2427d0134a5f69d  RSC037-2017_08_30-2.tar.gz
c7ea8a5482bdd21eb5e03acb048c6b40  RSC037-2017_08_30-3.tar.gz
376afa8acf97ab5efc3657b78fe76416  RSC037-2017_09_06-1.tar.gz
7f10bdcdbabc14d3670a0d39188b098c  RSC037-2017_09_06-2.tar.gz
a040b935359d797e9b4d2d8355a6eb10  RSC037-2017_09_06-3.tar.gz
1395cb4a80cdb10dfda1d7b8371dde70  RSC037-2017_09_11-1.tar.gz
3efd74a56e22974bdcb6d40c57d113c1  RSC037-2017_09_11-2.tar.gz
aab7efabc4e7770da7acbbb254b4405d  RSC037-2017_09_11-3.tar.gz
34a5341f17cbc24cbc604fcb238a37c5  RSC037-2017_09_18-1.tar.gz
34af40bf61a8e005dc8527eb735a80b9  RSC037-2017_09_18-2.tar.gz
9aa05e2c203b08b5f6ea9cef1b275799  RSC037-2017_09_18-3.tar.gz
66fcf6f9a4f741e7e055166ff5ca70a9  RSC038-2017_09_13-1.tar.gz
9f268d3b8203fa40218a21b5a410641b  RSC038-2017_09_13-2.tar.gz
457c5825459d6574c5cba563be34fe4d  RSC038-2017_09_13-3.tar.gz
78692b1a5ab31df37cf77014c5acd33a  RSC038-2017_11_02-1.tar.gz
243dfc026bd373da0e43c46454349bf1  RSC038-2017_11_02-2.tar.gz
88d123cab0e7cf51762407f1ee324a1c  RSC038-2017_11_02-3.tar.gz

Funding

Natural Sciences and Engineering Research Council of Canada, Award: 1631465

Canadian Institutes of Health Research, Award: PJT 156040

Defense Advanced Research Projects Agency, Award: HR0011-18-2-0021