Neural activity prediction

This tutorial shows how to use the deep neural network encoding model to predict neural activity based on mouse orofacial behavior.

To process neural activity prediction using pose estimates extracted using the keypoint tracker:

  1. Load or process keypoints (see pose tracking tutorial).

  2. Select Neural activity from file menu.

  3. Click on Launch neural activity window.

  4. Select Load neural activity (2D-array stored in *.npy) and (optionally) timestamps for neural and behavioral data (1D-arrays stored in*.npy) then click Done.

  5. Once the neural data is loaded, click on Run neural predictions.

  6. Select Keypoints as input data and select one of the options for output of the model’s prediction, which can be Neural PCs or neural activity. CLick on Help button for more information.

  7. The predicted neural activity (*.npy) file will be saved in the selected output folder.

To predict neural activity using SVDs from Facemap:

  1. Load or process SVDs for the video. (see SVD tutorial).

  2. Follow steps 2-5 above.

Note: a linear model is used for prediction using SVDs.

Predicted neural activity will be plotted in the neural activity window. Toggle Highlight test data to highlight time segments not used for training i.e. test data. Further information about neural prediction, including variance explained can be found in the saved neural prediction file (*.npy).