TY - JOUR T1 - Deepinsight: a general framework for interpreting wide-band neural activity JF - bioRxiv DO - 10.1101/871848 SP - 871848 AU - Markus Frey AU - Sander Tanni AU - Catherine Perrodin AU - Alice O’Leary AU - Matthias Nau AU - Jack Kelly AU - Andrea Banino AU - Christian F. Doeller AU - Caswell Barry Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/12/11/871848.abstract N2 - Rapid progress in technologies such as calcium imaging and electrophysiology has seen a dramatic increase in the size and extent of neural recordings, yet their interpretation still depends on time-intensive manual operations. Decoding provides a means to infer the information content of such recordings but typically requires highly processed data and prior knowledge of variables. Here, we developed DeepInsight - a deep-learning-framework able to decode sensory and behavioural variables directly from wide-band neural data. The network requires little user input and generalizes across stimuli, behaviours, brain regions, and recording techniques. Critically, once trained, it can be analysed to determine elements of the neural code that are informative about a given variable. We validated this approach using data from rodent auditory cortex and hippocampus, identifying a novel representation of head direction encoded by CA1 interneurons. Thus, we present a robust, user-friendly tool for characterising and decoding neural recordings in an automated way. Code is available at https://github.com/CYHSM/DeepInsight. ER -