Positioning rat using neuronal activity in hippocampus Tambet Matiisen Deep Learning for NLP seminar 25.01.2016

Place cells In year 2014 The Nobel Prize in Physiology or Medicine was given to John O’Keefe, May-Britt Moser and Edvard I. Moser for discovering “place cells” in a rat brain.

Dataset Rat recordings from University College London 1m x 1m arena for rat to run around. Number of spikes for 172 neurons. 20ms time resolution, 54100 measurements.

Features In total 5400 datapoints with 344 features. 1s (x,y) 1s (x,y) 200ms 200ms In total 5400 datapoints with 344 features.

Baseline Algorithm Train mean distance Validation mean distance Linear regression 13.27cm 20.85cm K nearest neighbors 0cm 24.05cm Random forest 2.47cm 16.02cm Extremely randomized trees 15.32cm Gradient boosted trees 1.45cm 15.30cm Linear SVM 13.04cm 21.09cm Polynomial SVM 14.25cm 18.77cm Radial basis SVM 0.16cm 15.66cm Used 4000/1400 train-test split and grid search for hyperparameter optimization.

Recurrent Neural Networks RNN Bi-directional RNN http://colah.github.io/posts/2015-09-NN-Types-FP/

Long Short-Term Memory http://colah.github.io/posts/2015-08-Understanding-LSTMs/

Reference Network Architecture 1 LSTM layer (+ linear fully connected layer), 1024 hidden nodes, dropout 0.5, sequence length 100, batch size 1, RMSProp, early stopping. 10.39cm validation error (5-fold crossvalidation).

Number of layers Hidden nodes Experiment Train mean distance Validation mean distance 1 layer 5.05cm 10.39cm 2 layers 5.63cm 10.61cm 3 layers 12.13cm 16.99cm Hidden nodes Experiment Train mean distance Validation mean distance Hidden 512 4.56cm 10.60cm Hidden 1024 5.05cm 10.39cm Hidden 2048 6.27cm 10.97cm

Dropout Experiment Train mean distance Validation mean distance 5.08cm 10.30cm Dropout 0.2 5.43cm 10.62cm Dropout 0.5 5.05cm 10.39cm

Sequence length Batch size Experiment Train mean distance Validation mean distance Seqlen 10 7.81cm 13.65cm Seqlen 100 5.05cm 10.39cm Seqlen 200 5.32cm 10.92cm Batch size Experiment Train mean distance Validation mean distance Batch size 1 5.05cm 10.39cm Batch size 5 4.59cm 10.50cm Batch size 10 4.94cm 10.87cm

Direction Optimization method Experiment Train mean distance Validation mean distance Reference 5.05cm 10.39cm Backwards 33.34cm 34.79cm Bi-directional 4.69cm 10.51cm Stateful 6.54cm 11.81cm Optimization method Experiment Train mean distance Validation mean distance RMSProp 5.05cm 10.39cm Adam 7.35cm 13.30cm Momentum ?

Do place cells code future or past?

Are errors caused by less data?

Are errors caused by rat speed or direction it is facing? Errors by speed Errors by angle

Are errors bigger at the start of sequence?

Latest results Experiment Train mean distance Validation mean distance LSTM 9-fold CV 5.24cm 10.19cm Bi-LSTM 9-fold CV 4.58cm 9.86cm LSTM 54-fold CV 8.42cm 9.84cm Bi-LSTM 54-fold CV 6.86cm 9.65cm

Thanks! Ardi Tampuu Sander Tanni Zurab Bzhalava Jaan Aru Raul Vicente