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Codebase for Between-subject prediction reveals a shared representational geometry in the rodent hippocampus (Chen et al. 2021, Current Biology)

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vandermeerlab/hc_hyperalign

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hc_hyperalign

The codebase of the paper: Between-subject prediction reveals a shared representational geometry in the rodent hippocampus. The main idea of this paper (which was started at 2018 MIND hackthon) is to reveal a shared relationship in ensemble hippocampal (place) cells activity between different experimental conditions (left and right running trials on a T-maze in this case) across subjects using hyperalignment.

Entry points

Clone and check out the hyperalignment branch of the vandermeerlab main codebase.

Before you try to do anything below, edit set_hyper_path for path setup (corresponds to your local path), and getTmazeDataPath and getAdrDataPath in utils/data folder for data setup.

Then execute set_hyper_path in your matlab command window.

Running Scripts

Each figure has a corresponding script in fig_scripts folder and data preparation script used in fig 2, supp. fig 2, fig 3 and supp. fig 3 is located at scripts/prepare_inputs.

Note that they might share the common scripts with only different parameter used (for flexibly testing different data input). For example, Q in figure 4 includes interneurons, so cfg_data.removeInterneurons = 0;, but figure 5 and so on excludes interneurons (cfg_data.removeInterneurons = 1;).

You should adjust the parameters before preparing the data input. (We might finalize the data input used then this is no longer required.)

Acknowledgement

The following tools/code were used in this paper. We thank all of their contributors.

shadedErrorBar: https://github.com/raacampbell/shadedErrorBar

hypertools: https://github.com/ContextLab/hypertools-matlab

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Codebase for Between-subject prediction reveals a shared representational geometry in the rodent hippocampus (Chen et al. 2021, Current Biology)

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