Publications

Human electrophysiology and behavior

Sparse coding of ECoG signals identifies interpretable components for speech control in human sensorimotor cortex

Bouchard, K.E.*, Bujan, A.F., Chang, E.F., Sommer, F.T.; In press, IEEE, EMBC, Aug., 2017.

 

Spatial resolution dependence on spectral frequency in human electrocorticography.

Muller, L; Hamilton, L; Edwards, E; Bouchard, K; Chang, E.; J. Neural Engineering, Aug., 2016. (link)

 

Dynamic structure of neural variability in the cortical representation of speech sounds.
Dichter, B., Bouchard, K.E., Chang, E.F.; J. Neuroscience, July, 2016. (link)

 

High-resolution, non-invasive imaging of upper vocal tract articulators compatible with human brain recordings

Bouchard, K.E.*, Conant, D.*, Anumanchipalli, G., Dichter, B.; Johnson, K., Chang, E.F.; PLoS One. 2016 (Link)

 

Decoding speech from human ECoG with deep networks

Livesey, J.*, Anumanchipalli, G.K.*, Prabhat, Bouchard, K.E.** Chang, E.F.**; Submitted to NIPS; June, 2015.

 **: co-senior authors

 

Dynamic encoding of speech sequence probability in human temporal cortex

Leonard, M.K., Bouchard, K.E., Tang, C; Chang, E.F.; J. Neuroscience, May, 2015. (link)

 

Cortical control of vowel formants and co-articulation by human sensorimotor cortex

Bouchard, K.E., Chang, E.F.; J. Neuroscience, Sept., 2014. (link)

 

Neural decoding of spoken vowels from human sensory-motor cortex with high-density electrocorticography

Bouchard, K.E., Chang, E.F.; IEEE, EMBC, Aug., 2014. (link)

 

Speech map in the human ventral sensory-motor cortex.

Conant, D., Bouchard, K.E., Chang, E.F.; Curr. Opin. Neurobio. Feb., 2014. (link)

 

Functional organization of human sensorimotor cortex for speech articulation

Bouchard, K.E., Mesgarani, N., Johnson, K., Chang, E.F.; Nature Article, Feb., 2013. (link)

 

Birdsong electrophysiology and behavior 

Timing during transitions in Bengalese finch song: implications for motor sequencing.

Troyer, T.W.*; Brainard, M.S., Bouchard, K.E.*; Submitted to J. Neurophys.

 

Auditory-induced neural dynamics in sensory-motor circuitry predict learned temporal and sequential statistics of birdsong.

Bouchard KE, Brainard MS.; Proc Natl Acad Sci U S A.; Aug, 2016. (link)

An auditory-motor feedback loop with response adaptation contributes to generating repetitive vocalizations

Wittenback, J.*, Bouchard, K.E.*, Brainard, M.S., Jin, D.Z.; PLoS Comp. Bio.; July, 2015. [link]

*: co-first author

 

Neural encoding and integration of learned probabilistic sequences in avian sensory-motor circuitry

Bouchard, K.E., Brainard, M.S.; J. Neuroscience, Nov., 2013. [link]

 

 

Rodent behavior, electrophysiology and optogenetics

Identification of genetic factors that modify motor performance and body weight using Collaborative Cross mice.

Mao JH, Langley SA, Huang Y, Hang M, Bouchard K.E., Celniker SE, Brown JB, Jansson JK, Karpen GH, Snijders AM. Scientific Reports. Nov, 2015. (link)

 

Cannabinoid receptor 2 signaling in peripheral immune cells modulates disease onset and severity in mouse models of Huntington’s disease.

Bouchard, J.S., Truong, J., Bouchard, K.E., Dunkelberger, D., Desrayaud, S., Moussaoui, S., Tabrizi, S.J., Stella, N., Muchowski, P.J.; J. Neuroscience, Dec., 2012. (link)

 

Theory and Computation 

The Union of Intersections Method for Interpretable Data Driven Discovery and Prediction

Bouchard, K.E., Bujan, A.F., Roosta, F., Prabhat, Snijders, A., Mao, J-H., Chang, E.F., Mahoney, M., Bhattacharyya, S.; Under Review at PNAS/Statistics.(link)

 

UoI-NMFcluster: A Robust Non-negative Matrix Factorization Algorithm for Improved Parts-Based Decompositions from Noisy Data

Ubaru, S., Wu, K.J., Saad, Y., Bouchard, K.E.; Submitted to ICML.

 

Methods for Specifying Scientific Data Standards and Modeling Relationships with Applications to Neuroscience.

Rübel, O., Dougherty, M., Prabhat, Denes, P., Conant, D., Chang, E.F., Bouchard, K.E.; Front Neuroinform. 2016 Nov 4; (link)

 

High-Performance Computing in Neuroscience for Data-Driven Discovery, Integration, and Dissemination

Bouchard, K.E.*, et al., Neuron, Oct. 2016. (link)

 

Hierarchical spatio-temporal visual analysis of cluster evolution in electrocorticography data.

Murugesan, S., Bouchard, K. E., Chang, E. F., Dougherty, M., Hamann, B. and Weber, G. H.; Brain-KDD, Aug., 2016. (link)

 

Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity

Mururgesan, S., Bouchard, K.E., Brown, J.A., Hamann, B., Seeley, W.W., Trujillo, A., Weber, G. H.; IEEE TCBB; May, 2016. (link)

 

Usage Pattern-Driven Dynamic Data Layout Reorganization

Tang, H., Byna, S., Harenberg, S., Zou, X., Zhang, W., Wu, K., Dong, B., Rubel, O., Bouchard, K.E., Klasky, S., and Samatova, N.F.; IEEE/ACM CCGrid; 2016. (link)

 

BRAINformat: A Data Standardization Framework for Neuroscience Data

Rübel, O., Prabhat, Denes, P., Conant, D., Chang, E.F., Bouchard, K.E.; biorxiv, Aug., 2015. [link]

 

Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences

Bouchard, K.E., Ganguly, S., Brainard, M.S.; Front. in Comp. Neuro., July, 2015. [link]

 

Modeling neural activity at the ensemble level

Rapela, J., Kostuk, M., Rowat, P., Mullen, T., Chang, E.F., Bouchard, K.E.; arXiv.qbio.NC, May, 2015. [link]

 

Bootstrapped Adaptive Threshold Selection for Statistical Model Selection and Estimation

Bouchard, K.E.; arXiv.stat.ML; April, 2015. [link]

 

Control of network activity through neuronal response modulation

Swineheart, C., Bouchard, K.E., Partensky, P., Abbott, L. F.; Neurocomputing, 2003. [link]