Search Results for author: Joshua I. Glaser

Found 5 papers, 1 papers with code

Deep learning approaches for neural decoding: from CNNs to LSTMs and spikes to fMRI

no code implementations19 May 2020 Jesse A. Livezey, Joshua I. Glaser

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.

EEG Image Segmentation +3

The Roles of Supervised Machine Learning in Systems Neuroscience

no code implementations21 May 2018 Joshua I. Glaser, Ari S. Benjamin, Roozbeh Farhoodi, Konrad P. Kording

Over the last several years, the use of machine learning (ML) in neuroscience has been rapidly increasing.

BIG-bench Machine Learning

Machine learning for neural decoding

1 code implementation2 Aug 2017 Joshua I. Glaser, Ari S. Benjamin, Raeed H. Chowdhury, Matthew G. Perich, Lee E. Miller, Konrad P. Kording

Despite rapid advances in machine learning tools, the majority of neural decoding approaches still use traditional methods.

BIG-bench Machine Learning Hippocampus

Physical Principles for Scalable Neural Recording

no code implementations24 Jun 2013 Adam H. Marblestone, Bradley M. Zamft, Yael G. Maguire, Mikhail G. Shapiro, Thaddeus R. Cybulski, Joshua I. Glaser, Dario Amodei, P. Benjamin Stranges, Reza Kalhor, David A. Dalrymple, Dongjin Seo, Elad Alon, Michel M. Maharbiz, Jose M. Carmena, Jan M. Rabaey, Edward S. Boyden, George M. Church, Konrad P. Kording

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

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