DOI: 10.5061/dryad.crjdfn31g
title: Data from: DG-CA3 circuitry mediates hippocampal representations of latent information

description: Survival in complex environments necessitates a flexible navigation system
 that incorporates memory of recent behavior and associations. Yet, how the
 hippocampal spatial circuit represents latent information independent of
 sensory inputs and future goals has not been determined. To address this,
 we imaged the activity of large ensembles in subregion CA1 via wide-field
 fluorescent microscopy during a novel behavioral paradigm. Our results
 demonstrated that latent information is represented through reliable
 firing rate changes during unconstrained navigation. We then hypothesized
 that the representation of latent information in CA1 is mediated by
 pattern separation/completion processes instantiated upstream within the
 dentate gyrus (DG) and CA3 subregions. Indeed, CA3 ensemble recordings
 revealed an analogous code for latent information. Moreover, selective
 chemogenetic inactivation of DG-CA3 circuitry completely and reversibly
 abolished the CA1 representation of latent information. These results
 reveal a causal and specific role of DG-CA3 circuitry in the maintenance
 of latent information within the hippocampus.  
description: <i>In vivo</i>
 calcium videos were recorded with a miniscope (v3; miniscope.org)
 containing a monochrome CMOS imaging sensor (MT9V032C12STM, ON
 Semiconductor) connected to a custom data acquisition (DAQ) box
 (miniscope.org) with a lightweight, flexible coaxial cable
 <sup>14</sup>. The DAQ was connected to a PC with a USB 3.0
 SuperSpeed cable and controlled with Miniscope custom acquisition software
 (miniscope.org). The outgoing excitation LED was set to between 3-6%,
 depending on the mouse to maximize signal quality with the minimum
 possible excitation light to mitigate the risk of photobleaching. Gain was
 adjusted to match the dynamic range of the recorded video to the
 fluctuations of the calcium signal for each recording to avoid saturation.
 Behavioral video data were recorded by a webcam mounted above the
 environment. Behavioral video recording parameters were adjusted such that
 only the red LED on the CMOS of the miniscope was visible. The DAQ
 simultaneously acquired behavioral and cellular imaging streams at 30 Hz
 as uncompressed avi files and all recorded frames were timestamped for
 post-hoc alignment. <b><i>           
 </i></b>All recording environments were constructed of a grey
 Lego base and black Lego bricks (Lego, Inc) according to the dimensions
 specified in the main text and supplemental figures. All external walls
 had a height of 22 cm; all internal walls had a height of 15 cm. All
 hallways were 5 cm wide; due to the width mice typically ran the length of
 the hallway rather than turning around in the hallway. During recording,
 the environment was dimly lit by a nearby computer screen, which served as
 directional cue. A white-noise generator was placed above the environment
 to mask uncontrolled ambient sounds. Each recording session lasted 20
 minutes, and only one session was recorded per day to avoid
 photobleaching. The mouse was always placed in the corner of the hallway
 at the start of the session and was allowed to explore the environment for
 15 to 30 s prior to data acquisition. Following each recording the
 environment was cleaned with disinfectant (Prevail).             For CA3 inactivation
 experiments, 5 mg/kg of clozapine-N-oxide (CNO + 0.7% DMSO) was injected
 Intraperitoneally 1 hr and 15 min prior to recording. This timepoint was
 chosen based on a separate experiment in which we monitored the time
 course of hippocampal theta power reduction during hm4di/CNO-mediated
 inhibition of the medial septum (data not shown). Mice were returned to
 their home cage between the injection and the start of the recording
 session. We conducted two separate control experiments to rule out the
 possibilities that our results could be explained by injection procedure,
 expression of hm4di-mcherry, or to non-specific effects of CNO itself. As
 our first within-animal control, we injected sterile saline instead of CNO
 and repeated the recording and analysis procedures (<b>Fig.
 4b-d</b>). The order of Saline and CNO recordings was interleaved
 within mouse, and whether the first recording session for a mouse followed
 a Saline or CNO injection was randomized. As a second control, to ensure
 that any differences between Saline and CNO sessions were attributable to
 the interaction between hm4di and CNO, and not an effect of CNO or its
 metabolites alone, CNO injection experiments were repeated in a second
 across-mouse control group which did not express hm4di (<b>Fig.
 4c-d</b>). Calcium imaging data were
 preprocessed prior to analyses via a pipeline of open source MATLAB
 (MathWorks) functions to correct for motion
 artifacts<sup>16</sup>, segment cells and extract
 transients<sup>17,18</sup>, and infer the likelihood of
 spiking events via deconvolution of the transient trace through a
 second-order autoregressive model<sup>19</sup>. The
 motion-corrected calcium imaging data were manually inspected to ensure
 that motion correction was effective and did not introduce additional
 artifacts. Following this preprocessing pipeline, the spatial footprints
 of all cells were manually verified to remove lens artifacts. Position
 data were inferred from this LED offline following recording using a
 custom written MATLAB (MathWorks) script and were manually corrected if
 needed. The experimenter manually segmented data recorded in the
 compartment and hallway, as well as the most recent entryway based on the
 recorded position data prior to all further analyses.
description: Each session is included as a separate .mat file containing the
 structures 'processed' and 'properties'. Most relevant
 fields are: processed.p = [x; y] position
 data  processed.trace = firing rates estimated via
 autoregressive deconvolution  processed.FiltTraces =
 dF/F traces prior to deconvolution processed.splithalf
 = various cell selection criteria processed.roi =
 coordinates for segmenting each entryway, the compartment, and the
 hallway