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Coordinates activities of retrosplenial ensembles during resting-state encode spatial landmarks. Part 1 of 2

Citation

Chang, HaoRan et al. (2020), Coordinates activities of retrosplenial ensembles during resting-state encode spatial landmarks. Part 1 of 2, Dryad, Dataset, https://doi.org/10.5061/dryad.hhmgqnkd4

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 1 of 2 files

6bf7aa756c84131debb891492b135fb0  RSC036-2017_08_11-1.tar.gz
2dec4e464a9d7913adad91ddfdc6683a  RSC036-2017_08_11-2.tar.gz
7f17c720a65852c5949ce7895e65baad  RSC036-2017_08_11-3.tar.gz
5de257096d796d9c966bb5c3bf5c0fa5  RSC036-2017_08_21-1.tar.gz
386af8830b4981cd71cabcbf0c0cd463  RSC036-2017_08_21-2.tar.gz
6622a9d063a1d7787662d60493437311  RSC036-2017_08_21-3.tar.gz
d050cb9239b8e8aca5f077a6b44cd9e6  RSC036-2017_08_30-1.tar.gz
d25c75192e36d3f5629bf07c3be89b71  RSC036-2017_08_30-2.tar.gz
96511c599c7845f485d8f6dedd6fa765  RSC036-2017_08_30-3.tar.gz
d4c756ceb785857d2917c1cd29c187c7  RSC036-2017_09_04-1.tar.gz
cdd5f6f829cb5cf5d36103593cd252ce  RSC036-2017_09_04-2.tar.gz
2f00f78adab246e1bef5656455a5b379  RSC036-2017_09_04-3.tar.gz
a06b9e1a7826938f1c622d4c6f86f0b3  RSC036-2017_09_11-1.tar.gz
f5d60bbea30b4ad927d3a1d7f6b3cfda  RSC036-2017_09_11-2.tar.gz
2c53d299ea54283e7832f3d1415eec4f  RSC036-2017_09_11-3.tar.gz
6ce657f76c2967a21130095b5906d61d  RSC037-2017_08_11-1.tar.gz
129d294f020e19aa37148e15fa5f912f  RSC037-2017_08_11-2.tar.gz
528e5da1ab9db0b23ddd432d8766ad75  RSC037-2017_08_11-3.tar.gz
80819667fe07d71766ff54f8cc66001e  RSC037-2017_08_21-1.tar.gz
ae6068d3998ee91044e2baa5e141aeae  RSC037-2017_08_21-2.tar.gz
b6e2f47356fae82ccb1592b53c9a320a  RSC037-2017_08_21-3.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