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README.txt
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+-------------------------------------------------------------------------+
| Geometric transformation of cognitive maps for generalization |
| across hippocampal-prefrontal circuits |
+-------------------------------------------------------------------------+
README.txt
Copyright (C) 2023, Wenbo Tang, version 1.0
All rights reserved.
BRIEF
=====
Code accompanying the paper: Tang, W., Shin, J. D. & Jadhav, S. P. (2023). Geometric transformation of cognitive maps for generalization across hippocampal-prefrontal circuits. Cell Reports.
GETTING STARTED
===============
Launch MATLAB and cd into the directory containing the code (e.g. '/CellRep_2023/').
Time-filter framework: Jadhav Lab (Brandeis University) and Frank Lab (UCSF)
Other files in the directory (with all sub-folders) needed in path for running the time-filter framework and other analysis:
\usrlocal\
\Src_Matlab\
\Sleep_Code\
Toolboxes required:
- Libsvm (version 3.12; https://www.csie.ntu.edu.tw/~cjlin/libsvm/)
- Uniform Manifold Approximation and Projection (UMAP) (version 4.1; https://www.mathworks.com/matlabcentral/fileexchange/71902-uniform-manifold-approximation-and-projection-umap)
- MatPlotLib (version 2.1.3; https://www.mathworks.com/matlabcentral/fileexchange/62729-matplotlib-perceptually-uniform-colormaps)
These codes were originally created in the MATLAB 2017a. All main scripts have plotting functions built-in to generate the figures shown in the paper.
FILES and FOLDERS
=================
./Figure1
cal_behavperform.m : main script for calculating performance for each animal
behavperform_gather.m : main script for generating statistics of performance in Figure 1
./Figure1/Performance_files
subfolder containing all performance files generated by cal_behavperform.m
./Figure2
Plot_linearRateMaps_allcells.m : script for plotting the sorted linearized rate maps in Figure 2
cal_PVsimilarity.m : compute PV similarity across environments
decoding_position_novelfamiliar_batch.m : main script for decoding animal's current position using rate maps
decoding_position_novelfamiliar_templateN2_batch.m : main script for decoding animal's current position using rate maps from N’
decoding_position_novelfamiliar_trial_batch.m : main script for get decoding error of animal's current position using rate maps from N' in a trial-by-trial basis
cal_confusionMat_novelfamiliar.m : script for plotting the confusion matrix in Figure 2
./Figure2/Decodepos
subfolder containing all decoding results generated by decoding_position_novelfamiliar_batch.m and decoding_position_novelfamiliar_templateN2_batch.m
./Figure3
cal_SI.m : main script for calculating trajectory selectivity index
Plot_linfields_sortedbySI.m : script for plotting plotting all linearized rate maps sorted by trajectory selectivity index in Figure 3
cal_UMAP.m : main script for UMAP transformation of neuronal population activity
cal_UMAP_TrajPhase_vs_Spatial_distance.m : main script for calculating the distance of neural states of the same spatial location vs. the same trajectory phase on UMAP neural manifolds
cal_UMAP_INSeq_distance.m : main script for calculating INSeq vs. OUTSeq trajectory distance based on UMAP manifolds of neural population activity
cal_UMAP_FNdistance_shuffle.m : main script for calculating the distance of neural states between N' and shuffled neural manifolds
cal_UMAP_FNdistance.m : main script for calculating the distance of neural states between N' and F neural manifolds, and comparing to the shuffles
./Figure3/Supplemental :
subfolder containing supplemental analysis related to Figure 3
cal_path_equivalence.m : main script for calculating path-equivalent coefficient
cal_PV_TrajPhase_vs_Spatial_distance.m : main script for calculating the distance of neural states of the same spatial location vs. the same trajectory phase in the original state space
cal_PV_INSeq_distance.m : main script for calculating INSeq vs. OUTSeq trajectory distance in the original state space
cal_PV_FNdistance_shuffle.m : main script for calculating the distance of neural states between N' and shuffled neural activity in the original state space
cal_PV_FNdistance.m : main script for calculating the distance of neural states between N' and F neural activity in the original state space, and comparing to the shuffles
./Figure3/SingleTrial_ratemaps :
subfolder containing all files for single-trial firing rates
./Figure4
cal_all_dichotomies.m : main script for getting all dichotomies (clusters) in Figure 4
CCGP_trajPhase.m : main script for CCGP of trajectory phases using linear SVMs
CCGP_taskSeq.m : main script for CCGP of task sequences using linear SVMs
CCGP_environment.m : main script for CCGP of different environments using linear SVMs
decoding_CCGP_linearSVM_simple.m: helper function that computers CCGP using linear SVMs, and tests significance using trial-label shuffles
./Figure4/Supplemental :
subfolder containing supplemental analysis related to Figure 4
decoding_dichotomy_main.m : main script for decoding all dichotomies using 4-fold cross-validation
decoding_dichotomy_linearSVM.m: helper function that computers decoding accuracy using linear SVMs, and tests significance using trial-label shuffles
CITING OUR WORK
===============
If you find the code useful, please cite the code source and the paper:
Tang, W., Shin, J. D. & Jadhav, S. P. (2023). Geometric transformation of cognitive maps for generalization across hippocampal-prefrontal circuits. Cell Reports.
CONTACT
=======
Bug reports, comments and questions are appreciated.
Please write to:
Wenbo Tang <wenbo.tang07@gmail.com>