this project is about using different machine learning techniques (Classic ML alghorithms, Deep learning, Ensemble learning, ...) in calcium imaganing data.
Data that we used in this project is for Allen Institute Calcium imagig dataset that is about V1,SST and VIP interneurons.
Learn more about data!
[this is our team project(Startgazzers) in NMA 2021 CN! hope you enjoy!]
- Numpy
- Matplotlib
- torch
- sklearn
we used ML techniques to find meaningfull relationship between different Neural activity and stimuluses (Novel or Familiar Pictures!)
so we have 3 different notebook:
- Predicting Novility vs familiarity based on VIP cells
- Predicting Novility vs familiarity based on SST cells
- Predicting Rewarded vs Not Rewarded trials based on SST and VIP cells
What about Our Machine learning techniques? we used :
- Logistic Regression
- Random Forest
- Linead Discrimination Analyze
- Deep Neural Network
- Ensemble Models