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Brian D. DePasquale, Ph.D.

Affiliations: 
2009-2016 Center for Theoretical Neuroscience Columbia University, New York, NY 
 2016- Princeton Neuroscience Institute Princeton University, Princeton, NJ 
 2023- Biomedical Engineering Boston University, Boston, MA, United States 
Area:
Computation & Theory
Website:
http://www.princeton.edu/~briandd/
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"Brian DePasquale"
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Parents

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Ann M. Graybiel research assistant 2005-2009 MIT
Larry F. Abbott grad student 2009-2016 Columbia
Carlos D. Brody post-doc 2016-2022 Princeton
Jonathan Pillow post-doc 2016-2022 Princeton
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Publications

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DePasquale B, Brody CD, Pillow JW. (2024) Neural population dynamics underlying evidence accumulation in multiple rat brain regions. Elife. 13
Insanally MN, Albanna BF, Toth J, et al. (2024) Contributions of cortical neuron firing patterns, synaptic connectivity, and plasticity to task performance. Nature Communications. 15: 6023
Gupta D, DePasquale B, Kopec CD, et al. (2024) Trial-history biases in evidence accumulation can give rise to apparent lapses in decision-making. Nature Communications. 15: 662
Luo TZ, Kim TD, Gupta D, et al. (2023) Non-canonical attractor dynamics underlie perceptual decision-making. Biorxiv : the Preprint Server For Biology
Gupta D, DePasquale B, Kopec CD, et al. (2023) Trial-history biases in evidence accumulation can give rise to apparent lapses. Biorxiv : the Preprint Server For Biology
DePasquale B, Sussillo D, Abbott LF, et al. (2023) The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks. Neuron
Pinto L, Rajan K, DePasquale B, et al. (2019) Task-Dependent Changes in the Large-Scale Dynamics and Necessity of Cortical Regions. Neuron
Panichello MF, DePasquale B, Pillow JW, et al. (2019) Error-correcting dynamics in visual working memory. Nature Communications. 10: 3366
Insanally MN, Carcea I, Field RE, et al. (2019) Spike-timing-dependent ensemble encoding by non-classically responsive cortical neurons. Elife. 8
DePasquale B. (2019) Decision letter: Local online learning in recurrent networks with random feedback Elife
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