Repo for analysing dimensionality of spontaneous and evoked activity, and encoding of stimuli in the layers of the visual cortex, using dimensionality reduction, logistic and linear regression. This is a work in progress!
Using data from Stringer et al. : https://pubmed.ncbi.nlm.nih.gov/31000656/
- the analysis of spontaneous and evoked activity in visual cortex of mice
- the prediction of stimuli from responses to infer the amount of information held in each cortical layer
Modules contain functions for analysing cortical data Accompanying ipynotebooks demonstrate how to use the modules
'admin_functions.py' - useful administrative functions
'cortex_layer_dim.ipynb' - analysing the dimensionality of each cortical layer in spont and evoked activity
'cortex_layer_minidomains.ipynb' - assessing the presence of minidomains that share orientation preferences
'cortex_layer_orient_linreg.ipynb' - using linear regression to predict stimulus orientation from activity
'cortex_layer_orient_logreg.ipynb' - using logistic regression to predict stimulus orientation from activity
'cortex_layer_orient_PCpred.ipynb' - using PCs to predict stimulus orientation from activity