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Found 5 papers, 1 papers with code
Machine learning for neural decoding
Despite rapid advances in machine learning tools, the majority of neural decoding approaches still use traditional methods.
The Roles of Supervised Machine Learning in Systems Neuroscience
Over the last several years, the use of machine learning (ML) in neuroscience has been rapidly increasing.
Puzzle Imaging: Using Large-scale Dimensionality Reduction Algorithms for Localization
Current high-resolution imaging techniques require an intact sample that preserves spatial relationships.
Physical Principles for Scalable Neural Recording
Simultaneously measuring the activities of all neurons in a mammalian brain at millisecond resolution is a challenge beyond the limits of existing techniques in neuroscience.
Neurons and Cognition Biological Physics
Deep learning approaches for neural decoding: from CNNs to LSTMs and spikes to fMRI
Deep learning has been shown to be a useful tool for improving the accuracy and flexibility of neural decoding across a wide range of tasks, and we point out areas for future scientific development.
