Machine Learning in Neuroscience

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Sharif University of Technology

Sharif University of Technology

Mackenzie W Mathis

Harvard University

Shahid Beheshti University

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In recent years, machine learning and artificial intelligence algorithms have been utilized in solving many fascinating problems in different fields of science, including neuroscience. In this Research Topic, we are seeking to bring together researchers from machine learning and computational neuroscience and to stimulate collaboration between researchers in these fields. More specifically, this collection of articles is intended to cover recent directions and activities in the field of machine learning, especially the recent paradigm of deep learning, in neuroscience dedicated to analysis, diagnosis, and modeling of the neural mechanisms of brain functions.

We welcome submissions of original research papers from systems/cognitive and computational neuroscience, to neuroimaging and neural signal processing. Original research and reviews, as well as theoretical work, methods, and modeling articles are welcomed. The research work includes experimental studies using state-of-the-art in electrophysiology and neuroimaging as well as experimentally-based computational or theoretical work and biologically inspired neural networks.

In recent years, machine learning and artificial intelligence algorithms have been utilized in solving many fascinating problems in different fields of science, including neuroscience. In this Research Topic, we are seeking to bring together researchers from machine learning and computational neuroscience and to stimulate collaboration between researchers in these fields. More specifically, this collection of articles is intended to cover recent directions and activities in the field of machine learning, especially the recent paradigm of deep learning, in neuroscience dedicated to analysis, diagnosis, and modeling of the neural mechanisms of brain functions.

We welcome submissions of original research papers from systems/cognitive and computational neuroscience, to neuroimaging and neural signal processing. Original research and reviews, as well as theoretical work, methods, and modeling articles are welcomed. The research work includes experimental studies using state-of-the-art in electrophysiology and neuroimaging as well as experimentally-based computational or theoretical work and biologically inspired neural networks.

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Editors

Sharif University of Technology

Sharif University of Technology

Mackenzie W Mathis

Harvard University

Shahid Beheshti University

Impact

281,711 Total views

212,500 Article views

50,422 Article downloads

18,789 Topic views

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Frontiers in Neuroscience

Brain Imaging Methods, Neural Technology, Systems Biology Archive

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Systems Biology Archive

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