DOI: 10.5061/dryad.m63xsj4f3
title: A contextual fear conditioning paradigm in head-fixed mice exploring virtual reality

description: Contextual fear conditioning is a classical laboratory task that tests
 associative memory formation and recall. Techniques such as multi-photon
 microscopy and holographic stimulation offer tremendous opportunities to
 understand the neural underpinnings of these memories. However, these
 techniques generally require animals to be head-fixed. There are few
 paradigms that test contextual fear conditioning in head-fixed mice, and
 none where the behavioral outcome following fear conditioning is freezing,
 the most common measure of fear in freely moving animals. To address this
 gap, we developed a contextual fear conditioning paradigm in head-fixed
 mice using virtual reality (VR) environments. We designed an apparatus to
 deliver tail shocks (unconditioned stimulus, US) while mice navigated a VR
 environment (conditioned stimulus, CS). The acquisition of contextual fear
 was tested when the mice were reintroduced to the shock-paired VR
 environment the following day. We tested three different variations of
 this paradigm and, in all of them, observed an increased conditioned fear
 response characterized by increased freezing behavior. This was especially
 prominent during the first trial in the shock-paired VR environment,
 compared to a neutral environment where the mice received no shocks. Our
 results demonstrate that head-fixed mice can be fear conditioned in VR,
 discriminate between a feared and neutral VR context, and display freezing
 as a conditioned response, similar to freely behaving animals.
 Furthermore, using a two-photon microscope, we imaged from large
 populations of hippocampal CA1 neurons before, during, and following
 contextual fear conditioning. Our findings reconfirmed those from the
 literature on freely moving animals, showing that CA1 place cells undergo
 remapping and show narrower place fields following fear conditioning. Our
 approach offers new opportunities to study the neural mechanisms
 underlying the formation, recall, and extinction of contextual fear
 memories. As the head-fixed preparation is compatible with multi-photon
 microscopy and holographic stimulation, it enables long-term tracking and
 manipulation of cells throughout distinct memory stages and provides
 subcellular resolution for investigating axonal, dendritic, and synaptic
 dynamics in real-time.
description: # A contextual fear conditioning paradigm in head-fixed mice exploring
 virtual reality Dataset DOI:
 [10.5061/dryad.m63xsj4f3](10.5061/dryad.m63xsj4f3) ## Description of the
 data and file structure Behavior Data: .pkl files contain behavior data
 across animals and sessions and are sorted by the version of the CFC
 Paradigm they correspond to (i.e. Paradigm 1, 2 or 3) Imaging Data: Folder
 contains mat files with extracted place cells and corresponding animal
 behavior sorted by animals. Files are divided by each session. Also
 consists of a csv file with parameters of extracted place cells. Scripts
 used to analyze data can be found
 in [https://github.com/seethakris/CFCMethodspaper](https://github.com/seethakris/CFCMethodspaper) ### Files and variables #### File: BehaviorData.zip Description: NaN indicates missing values. Data columns correspond to: 1. Animal: animal name 2. Behavior : running behavior of animals 3. Lap: frames corresponding to each lap 4. Paradigm: The session from which data has been curated 5. Shock: Type of shock administered 6. Laptime_bylap: Time taken in seconds to complete each lap 7. Avglaptime: Average lap time across all laps 8. Firstlap_time: Time taken to complete first lap 9. Numlaps: Total number of laps 10. Freezingpercent_bylap: Percentage of freezing by lap 11. Firstlapfreezing: Percentage of freezing in the very first lap 12. Averagefreezing: Average freezing across all laps 13. Freezingepoch_bylap: Number of freezing epochs per lap #### File: ImagingData.zip Description: Folders are sorted by mouse. Within each animal's dataset, .mat files with suffix *_beh* contains the running behavior of the animal. .mat files with suffix *_Placefields* contains extracted place cells. * The .mat files with suffix *_beh* is a structure with the following fields: Y_pos: position of the animal in VR. Shock: when shock was delivered during the CFC session Lick: lick signal collected from the lick sensor Velocity: velocity of the animal * The .mat files with suffix *_Placefields* is a structure with the following fields: Allbinned_F: A matrix where each column corresponds to an individual ROI and contains a cell array. Within each cell, rows represent lap numbers and columns represent spatial bins, storing the fluorescence data for that ROI across laps and space. E: A vector where each frame is assigned to a lap, based on the animal's behavior and position, indicating the lap number that each frame belongs to. PF_start_bins: A matrix where each column corresponds to an individual ROI. For ROIs identified as place cells, the entry contains the starting spatial bin of the place field. PF_end_bins: A matrix where each column corresponds to an individual ROI. For place cells, the entry specifies the ending spatial bin of the place field. PF_width: A matrix where each column corresponds to an individual ROI. For place cells, the value indicates the width (in spatial bins) of the place field. number_of_PFs: A matrix where each column corresponds to an individual ROI. For place cells, the entry indicates the number of identified place fields associated with that ROI. sig_PFs: A matrix where each column corresponds to an individual ROI. For ROIs with place fields, each entry is a cell array. Inside each cell, rows represent lap numbers and columns represent spatial bins, containing fluorescence data filtered to include only activity within the place field. sig_PFs_with_noise: Structured identically to sig_PFs, but the fluorescence data has not been filtered for noise. * .csv file contains parameters of each place field and consists of the following column names Task: Name of the task during which the data were collected CellNumber: Unique identifier for each recorded cell PlaceCellNumber: Index of the place field detected for that cell NumPlacecells: Total number of place fields assigned to that cell COM: A list of activity-weighted positions along a spatial axis, indicating the center of mass (COM) of firing in each spatial bin WeightedCOM: Weighted average position of firing, summarizing the COM vector into a single value Precision: A measure of how spatially confined the firing activity is; higher values suggest greater spatial specificity Precision_rising: A similar precision metric, potentially focused on the rising phase of the spatial firing field Width: Spatial width (in bins or units) of the place field FiringRatio: Ratio of in-field to out-of-field firing, indicating the selectivity of the place cell Firingintensity: Average or peak firing rate in the place field Reliability: Trial-to-trial consistency of spatial firing animalname: Identifier for the animal (e.g., NR22)