Artificial hibernation reveals synaptic engram architecture associated with memory retention
Data files
Jun 30, 2026 version files 32.15 MB
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Do_Cells_Matching.m
20.20 KB
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E1_Bayes_Decoder.m
16.45 KB
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Fig1.xlsx
211.05 KB
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Fig2.xlsx
32.68 KB
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Fig3.xlsx
24.49 KB
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Fig4.xlsx
55.36 KB
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Fig5_v2.xlsx
129.12 KB
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FigS1.xlsx
15.54 KB
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FigS2.csv
25.50 MB
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FigS6.xlsx
9.25 KB
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FigS7.xlsx
9.75 KB
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FigS8.xlsx
12.69 KB
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HIBER_N_v1.2.1_distrib.zip
6.09 MB
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IdentifyPlaceCells_opt4.m
19.75 KB
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README.md
10.30 KB
Abstract
Memories leave lasting physical changes at the synaptic level. Although stable, larger spines are thought to support memory, the high turnover of dendritic spines and the drifting of neuronal representations following memory formation suggest alternative possibilities. To elucidate the structural trace underlying memory retention, we utilize a mouse model of artificial hibernation. During hibernation, hippocampal neurons exhibited a substantial reduction in their activity and an extensive elimination of dendritic spines and synapses. Despite these changes, their memory and associated hippocampal neuronal representations remained intact. We found that a subset of spines characterized by synaptic contacts with multi-synaptic boutons is maintained during hibernation. These findings suggest that synaptic engram architecture, rather than larger spines per se, is resilient to network remodeling and associated with long-term memory retention.
Dataset DOI: 10.5061/dryad.m0cfxpphz
Description of the data and file structure
Overview
This repository contains the source data underlying the figures and representative MATLAB scripts used for data analysis in the manuscript.
The deposited files contain individual data points used to generate the statistical analyses and plots shown in the manuscript figures. Raw imaging data, electrophysiological recordings, and electron microscopy image stacks are not included in this repository because of their size. All numerical values used for statistical analyses and figure generation are provided.
Software Requirements
MATLAB version: MATLAB R2024b (MathWorks)
Required toolboxes:
- Statistics and Machine Learning Toolbox
- Signal Processing Toolbox
- Image Processing Toolbox
The scripts use relative file paths. Users should place the data files in the same directory as the scripts, or modify the input directory path accordingly.
File organization
Fig1.xlsx: Source data for Figure 1.
Fig2.xlsx: Source data for Figure 2.
Fig3.xlsx: Source data for Figure 3.
Fig4.xlsx: Source data for Figure 4.
Fig5_v2.xlsx: Source data for Figure 5.
FigS1.xlsx: Source data for Supplementary Figure S1.
FigS1.xlsx: Source data for Supplementary Figure S1.
FigS2.csv: Source data for Supplementary Figure S2.
FigS6.xlsx: Source data for Supplementary Figure S6.
FigS7.xlsx: Source data for Supplementary Figure S7.
FigS8.xlsx: Source data for Supplementary Figure S8.
E1_Bayes_Decoder.m: MATLAB script associated with Figure 2. Bayes decoding of animal trajectory from spike data.
Do_Cells_Matching.m: MATLAB script associated with Figure 4. Cell matching across sessions in Ca2+ imaging data.
IdentifyPlaceCells_opt4.m: Matlab script associated with Figure 4. Compute location-specific Ca2+ transients and run statistical analysis to identify place cells from Ca2+ imaging and behavior data.
HIBER_N_v1.2.zip: A zip file containing GUI software developed with C++. It runs on Windows and requires a FLIR C5 thermocamera.
Variable Definitions
General conventions used throughout the dataset:
- Animal: Unique identifier for each mouse.
- Cell: Unique identifier for each neuron.
- Synapse: Unique identifier for each synapse.
- Day: Experimental day.
- Treatment: Experimental condition.
- NoQIH: Control animals not subjected to QIH.
- QIH: Animals subjected to QIH.
- ANE: Animals subjected to anesthesia.
- CtxA: Training context.
- CtxB: Neutral context.
- Baseline: Pre-treatment recording period.
- Theta: Theta-band oscillatory power.
- lGamma: Low gamma oscillatory power.
- hGamma: High gamma oscillatory power.
- MeanFR: Mean firing rate (Hz).
- PeakFR: Peak firing rate (Hz).
- CSI: Complex spike index.
- SpatialInfo: Spatial information score (bits/spike).
- PFsize: Place field size.
- SynapseDensity: Synapse density (synapses/µm³).
- SynapseDistance: Distance between neighboring synapses (µm).
- SpineVolume: Spine volume (µm³).
- PSDArea: Postsynaptic density area (µm²).
- Vel: Running velocity (cm/s).
- Clustered Engram Synapse: Engram synapse located within a synaptic cluster as defined in the manuscript.
- Isolated Engram Synapse: Engram synapse not belonging to a cluster.
- MSB: Multi-synaptic bouton.
Description of each data file
Fig1.xlsx
Sheet A:
Time-binned body temperature measurements (Celsius degrees) shown in Fig. 1A. Each column represents an animal.
Sheet B:
Time-binned mean firing rates (Hz) shown in Fig. 1B. Each column represents a unit.
Sheet E:
Spectral power analyses for theta, low-gamma, and high-gamma bands. Each row represents a recording channel.
Sheet H:
Synaptic density measurements (um3) before, during, and after QIH. Each row represents an EM data volume.
Sheet J:
Morphological measurements including synapse density (/um3), synapse distance (um), spine volume (um3), and PSD area (um2). Each row represents a dendrite, a synaptic pair, spine, or PSD.
Fig2.xlsx
Sheet B:
Freezing scores (%) in Context A & B. Context discrimination index calculated from the freezing scores. Each column represents an animal.
Sheet D:
Percent correct choices during the spatial task. Each column represents an animal.
Sheet F:
Freezing scores (%) in Context A & B in the hippocampal lesion experiment. Each column represents an animal.
Sheet I:
Place-cell metrics including mean firing rate (MeanFR), peak firing rate (PeakFR), complex spike index (CSI), spatial information score (SpatialInfo), and place field size (PFsize). Each row represents a unit.
Fig3.xlsx
Sheet E:
Spine density across pre-QIH, QIH, and two post-QIH imaging sessions. Each row represents a dendrite.
Sheet F:
Differential fraction of spine loss between the two indicated states. Each row represents a dendrite.
Sheet G:
Differential fraction of newly-generated spines between the two indicated states. Each row represents a dendrite.
Sheet I:
Spine location similarity between the two indicated sessions. Each row represents a dendrite.
Sheet K:
Spine regrowth index comparing the observed values and the chance level. Each row represents a dendrite.
Sheet L:
Spine sizes of all observed spines (non-matched) or spines consistently observed (matched) across days. Each row represents a spine.
Sheet M:
Spine size correlations from matched spines. Each row represents a spine.
Sheet N:
Spine size similarity between Day 0-3 (left column) and 3-7 (right column). Each row represents a dendrite.
Fig4.xlsx
Sheet D:
Short-term PF stability (PF correlation) in the same context, pre-QIH (D1D2) or post-QIH (D10D11). Each row represents a cell.
Sheet E:
Population vector correlations between the different contexts, pre-QIH (ShortTerm) or post-QIH (LongTerm). Each row represents a cell.
Sheet F:
Long-term PF stability (PF correlation) in the same context, QIH (Group1) or without QIH (Group2). Each row represents a cell.
Fig5_v2.xlsx
Sheet A:
Time-binned mean firing rates (Hz) during anesthesia. Each column represents a unit.
Sheet B:
Spectral power analyses (theta, low gamma, high gamma, ripple) during anesthesia experiments.
Sheet C:
Synaptic density measurements (um3) during anesthesia. Each row represents an EM data volume.
Sheet E:
Freezing scores (%) in Context A & B before (Pre) or after (Post) ANE.
Sheet I:
Quantification of total engram synapses, clustered engram synapses, and isolated engram synapses. Each row represents an image volume.
Sheet M:
Observed pre-synaptic partners in control synapses and eGRASP-identified synapses.
Sheet N:
Spine volumes (um3) of clustered engram synapses and other synapses on the same engram dendrites. Each row represents a spine.
FigS1.xlsx
Sheet C:
Spike amplitudes (mV) before or during QIH. Each row represents an unit.
Sheet D:
Spike waveform swing (mV) before or during QIH. Each row represents an unit.
Sheet E:
Spike width (usec) before or during QIH. Each row represents an unit.
FigS2.csv
Source data for Supplementary Figure S2. Each row represents a time bin.
Column definitions:
Vel
Running velocity (cm/s).
Treatment
Experimental condition.
Day
Recording day.
Animal
Unique animal identifier.
FigS6.xlsx
Clustered engram synapse density (/um3). Each row represents an image volume.
FigS7.xlsx
Sheet A:
Source data for Supplementary Figure S7A. MSB density measurements in QIH animals.
Sheet B:
Source data for Supplementary Figure S7B. Comparison of MSB frequency between clustered engram synapses and other engram synapses.
FigS8.xlsx
Sheet B:
Synaptic density measurements (um3) 5 days after anesthesia. Each row represents an EM data volume.
Sheet D:
Freezing scores (%) in Context A & B before (Pre) or after (Post) ANE, without CytoD injection.
Sheet F:
Spine density across pre-anesthesia, anesthesia, and post-anesthesia imaging sessions. Each row represents a dendrite.
Sheet G:
Spine location similarity between the two indicated sessions. Each row represents a dendrite.
Sheet H:
Spine regrowth index comparing the observed values and the chance level. Each row represents a dendrite.
About Hiber N
This software (HIBER_N_v1.2.1_distrib.zip) is the core acquisition application used for hibernation monitoring experiments.
It provides a multi-camera thermal imaging acquisition system capable of continuously monitoring animals throughout a recording session. For each monitored animal, the software:
- Acquires thermal images from infrared cameras
- Measures and records body temperature
- Tracks animal position
- On request, can estimate the animal's activity level over time
The system supports simultaneous acquisition from multiple thermal cameras.
Each camera can monitor up to three independent Regions of Interest (ROIs).
The software is designed for long-term, automated monitoring and data collection in hibernation studies.
Third-party runtime components
This application requires external runtime libraries. To ensure compatibility, use the following versions:
Qt: 5.11.2
OpenCV: 4.7.0
(MSVC 2017 64-bit)
- Extract the application package.
- Copy the required runtime files and plugins into the package.[ Maintain original directory structures and relative paths.]
- Launch the HIBER_N application.
Copy the files/folders from the local installation of the third-party software to the HIBER_N application as specified below.
QT RUNTIME
- Source: [Qt_Path]\5.11.2\msvc2017_64\bin
- Destination: [Application_Root]\
Required files
Qt5Core.dll
Qt5Gui.dll
Qt5Multimedia.dll
Qt5Network.dll
Qt5Svg.dll
Qt5Widgets.dll
d3dcompiler_47.dll
libEGL.dll
libGLESv2.dll
opengl32sw.dll
QT PLUGINS
- Destination: [Application_Root]\
- Folders (Copy entire directories):
audio\
bearer\
iconengines\
imageformats\
mediaservice\
platforms\
playlistformats\
styles\
OPENCV RUNTIME
- Source: [OpenCV_Path]\4.7.0\install\x64\vc15\bin
- Destination: [Application_Root]\
Required files
opencv_core470.dll
opencv_highgui470.dll
opencv_imgcodecs470.dll
opencv_imgproc470.dll
opencv_videoio470.dll