Figure 6 – Source Data and MATLAB Code (dmPFC firing, neural selectivity, and LDA decoding)
<p dir="ltr">This dataset contains the complete raw data and analysis code used to generate all panels of Figure 6, which examines dmPFC single-unit activity, directional selectivity, and population decoding in mice repeatedly treated with ketamine.</p><p><br></p...
محفوظ في:
| المؤلف الرئيسي: | |
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| منشور في: |
2025
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| الموضوعات: | |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
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| الملخص: | <p dir="ltr">This dataset contains the complete raw data and analysis code used to generate all panels of Figure 6, which examines dmPFC single-unit activity, directional selectivity, and population decoding in mice repeatedly treated with ketamine.</p><p><br></p><p dir="ltr">Included data:</p><p dir="ltr">- Spike timestamps and trial-aligned firing rates for dmPFC neurons recorded during the delayed Y-maze task (Panels 6b–e)</p><p dir="ltr">- auROC values and selectivity indices for left vs. right trials (Panels 6c–e)</p><p dir="ltr">- Cumulative probability distributions and summary statistics for selectivity index comparisons (Panels 6d–e)</p><p dir="ltr">- Raw LDA scores, ROC curves, and score distributions for correct vs. error trials across conditions (Panel 6f)</p><p dir="ltr">- Bootstrapped decoding accuracy values for leave-one-neuron-out classification (Panel 6g)</p><p dir="ltr">- Numerical values used for LDA-based delay-versus-fork discriminability, including SNR measurements and bootstrap distributions (Panel 6h)</p><p><br></p><p dir="ltr">Structure:</p><p dir="ltr">- Each worksheet or file corresponds to a specific panel </p><p dir="ltr">- MATLAB scripts and matrices for Panel 6h are included as separate files within the dataset.</p><p dir="ltr">- All values in this dataset represent unprocessed raw data directly used to generate the plots in Figure 6.</p><p dir="ltr">This dataset includes the raw numerical values for Figure 6, along with the MATLAB scripts used to compute the auROC and selectivity measures (panel f), the LDA decoding accuracy (panel g), and the delay-versus-fork SNR discriminability (panel h).</p><p><br></p> |
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