Interpreting wide-band neural activity using convolutional neural networks.

ABSTRACT: Rapid progress in technologies such as calcium imaging and electrophysiology has seen a dramatic increase in the size and extent of neural recordings. Even so, interpretation of this data requires considerable knowledge about the nature of the representation and often depends on manual operations. Decoding provides a means to infer the information content of such recordings but typically requires highly processed data and prior knowledge of the encoding scheme. Here, we developed a deep-learning framework able to decode sensory and behavioral variables directly from wide-band neural data. The network requires little user input and generalizes across stimuli, behaviors, brain regions, and recording techniques. Once trained, it can be analyzed to determine elements of the neural code that ar

SUBMITTER: Frey M 

PROVIDER: S-EPMC8328518 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature