Jacob Reimer

The paper develops inception loops to identify Most Exciting Images for V1 neurons in mice, finding that these images outperform linear model stimuli and reveal complex spatial features.

A deep recurrent encoding model predicts spiking of thousands of mouse V1 neurons during natural video and carries over to noise stimuli when only its last layer is retrained.

The paper demonstrates the use of Semliki Forest virus to deliver channelrhodopsin into locust optic lobe neurons, enabling optogenetic manipulation and activation of medullary neurons and their postsynaptic targets.

The paper benchmarks spike rate inference algorithms for two-photon calcium imaging data and finds that top-performing algorithms show high correlation despite diverse approaches.

The paper benchmarks spike rate inference algorithms using calcium imaging data and introduces a supervised learning method that outperforms existing techniques across diverse datasets.

DataJoint is an open-source toolbox for managing large scientific datasets using MATLAB or Python, enabling flexible data manipulation and processing.