A contextual fear conditioning paradigm in head-fixed mice exploring virtual reality
Data files
Jul 01, 2025 version files 136.06 MB
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BehaviorData.zip
85.40 MB
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ImagingData.zip
50.66 MB
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README.md
4.71 KB
Abstract
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.
Dataset DOI: 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
Files and variables
File: BehaviorData.zip
Description: NaN indicates missing values. Data columns correspond to:
- Animal: animal name
- Behavior : running behavior of animals
- Lap: frames corresponding to each lap
- Paradigm: The session from which data has been curated
- Shock: Type of shock administered
- Laptime_bylap: Time taken in seconds to complete each lap
- Avglaptime: Average lap time across all laps
- Firstlap_time: Time taken to complete first lap
- Numlaps: Total number of laps
- Freezingpercent_bylap: Percentage of freezing by lap
- Firstlapfreezing: Percentage of freezing in the very first lap
- Averagefreezing: Average freezing across all laps
- 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)
