Attention-based CNN-BiLSTM for sleep state classification of spatiotemporal wide-field calcium imaging data-Reference-Cited by-同舟云学术

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Attention-based CNN-BiLSTM for sleep state classification of spatiotemporal wide-field calcium imaging data

Published:2024-11 Issue: Volume:411 Page:110250
ISSN:0165-0270
Container-title:Journal of Neuroscience Methods
language:en
Short-container-title:Journal of Neuroscience Methods

Author:

Zhang Xiaohui,Landsness Eric C.,Miao Hanyang,Chen Wei,Tang Michelle J.,Brier Lindsey M.,Culver Joseph P.,Lee Jin-Moo,Anastasio Mark A.

Funder

American Academy of Sleep Medicine Foundation

National Institute on Aging

American Heart Association Inc

National Institutes of Health

National Institute of Neurological Disorders and Stroke

Publisher

Elsevier BV

Reference58 articles.

1. Global representations of goal-directed behavior in distinct cell types of mouse neocortex;Allen;Neuron,2017

2. Bahdanau, Dzmitry, Kyunghyun Cho, and Yoshua Bengio. 2016. Neural Machine Translation by Jointly Learning to Align and Translate. arXiv. 〈https://doi.org/10.48550/arXiv.1409.0473〉.

3. Longitudinal monitoring of mesoscopic cortical activity in a mouse model of microinfarcts reveals dissociations with behavioral and motor function;Balbi;J. Cereb. Blood Flow. Metab.,2019

4. Robust, Automated Sleep Scoring by a Compact Neural Network with Distributional Shift Correction;Barger;PLOS ONE,2019

5. Measurement Error in Visually Scored Electrophysiological Data: Respiration during Sleep;Bliwise;J. Neurosci. Methods,1984

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