- Ph.D. in Molecular Biology and Neuroscience, Princeton University, 2012.
- B.S. in Biology, California Institute of Technology (Caltech), 2006.
I am an Assistant Professor in the Biology department at UW, supported by the Washington Research Foundation (WRF)
through the new UW Institute of Neuroengineering (UWIN).
I am also a Data Science Fellow of the UW eScience Institute and a faculty member of the Graduate Program in Neuroscience.
I consider myself primarily a computational neuroscientist interested in how networks of neurons
compute and also how computational methods help us understand meausurements from neurons.
I am also broadly interested in visualizing, manipulating,
and understanding complex, dynamic data, particularly from biologically relevant systems.
Previously, I was a postdoc at UW working with Nathan Kutz
in the Applied Math department and Tom Daniel in the Biology department.
I learned a lot about computational techniques that exploit inherent sparsity in complex data;
my collaborators and I continue to develop data-driven, low-dimensional dynamic models for biological and engineered systems.
I grew up in Maryland (MBHS) and was an undergrad at Caltech, where I majored in biology.
Afterwards, I went to Princeton and studied neuroscience with Carlos Brody.
In Carlos's lab, I trained rodents to perform decision-making tasks and developed computational models to help us understand mechanisms underlying their behavior.
I also did some experimental work in electrophysiology, neuropharmacology, and human psychophysics.
- Understanding complex data by exploiting sparsity
- Sparse sensor placement for classification
- Computational and systems neuroscience
- Accumulation of information for decision-making
- N. X. R. Wang, J. D. Olson, J. G. Ojemann, R. P. N. Rao, B. W. Brunton (2015),
Unsupervised decoding of long-term, naturalistic human neural recordings with automated video and audio annotations;
Submitted; arXiv preprint.
- S. L. Brunton, B. W. Brunton, J. L. Proctor, J. N. Kutz (2015),
Koopman observable subspaces and finite linear representations of nonlinear dynamical systems for control;
Submitted; arXiv preprint.
- B. W. Brunton, J. A. Johnson, J. G. Ojemann, J. N. Kutz (2016),
Extracting spatial-temporal coherent patterns in large-scale neural recordings using dynamic mode decomposition.
J Neuroscience Methods 258, 1--15;
earlier arXiv version.
- C. D. Kopec, J. C. Erlich, B. W. Brunton, K. Deisseroth, C. D. Brody (2015),
Cortical and subcortical contributions to short-term memory for orienting movements.
Neuron 88 (2), 367-377.
- T. D. Hanks, C. D. Kopec, B. W. Brunton, C. A. Duan, J. C. Erlich, C. D. Brody (2015),
Distinct relationships of parietal and prefrontal cortices to evidence accumulation.
Nature 520, 220-223.
- J. C. Erlich, B. W. Brunton, C. A. Duan, T. D. Hanks, C. D. Brody (2014),
Distinct behavioral effects of prefrontal and pareital cortex inactivations on an accumulation of evidence task in the rat.
- J. L. Proctor, S. L. Brunton, B. W. Brunton, J. N. Kutz (2014),
Exploiting sparsity and equation-free architecture in complex systems.
European Physical Journal Special Topics 223, 2665-2684.
- B. W. Brunton, S. L. Brunton, J. L. Proctor, J. N. Kutz (2013),
Optimal sensor placement and enhanced sparsity for classification;
In Review; arXiv preprint.
- B. W. Brunton, M. M. Botvinick, C. D. Brody (2013),
Rats and humans can optimally accumulate evidence for decision-making.
Science 340 (6128), 95-98.
- J. Kubanek, L. H. Snyder, B. W. Brunton, C. D. Brody, G. Schalk (2013),
A low-frequeny oscillatory neural signal in humans encodes a developing decision variable.
NeuroImage 83, 795-808.
- A. E. Granstedt, B. W. Brunton, L. W. Enquist (2013),
Imaging the transport dynamics of single alphaherpesvirus particles in intact peripheral nervous system explants from infected mice.
- K. C. Huang, R. Mukhopadhyay, B. Wen, Z. Gitai, N. S. Wingreen (2008) ,
Cell shape and cell-wall organization in Gram-negative bacteria.
Proceedings of the National Academy of Sciences 105(49), 19282-19287.
- Biology 300 (with Bill Moody), Intro to Neuroscience (Spring 2016)
- MOOC: Data Science for Biologists (with Steve Brunton and Nathan Kutz, on edX Winter 2016)
- Biology 419/519, Data Science for Biologists (Winter 2016)
- Biology 419/519, Data Science for Biologists (Spring 2015)
My husband Steve Brunton and I met when we
were undergrads and have migrated together ever since. We live in Seattle with our two kids and our dog Mordecai.