Ph.D. Thesis Dissertation: Statistical models of neural coding in motor cortex (pdf) Advisors: David Mumford, Michael J. Black   Computational Statistics, Functional Data Analysis Qi, K., Hu, G., and Wu, W., "Are made and missed different? An analysis of field goal attempts of professional basketball players via depth-based testing procedure", Annals of Applied Statistics, In Press. Ma, Y., Zhou, X., and Wu, W., "A stochastic process model for time warping functions", Computational Statistics and Data Analysis, vol. 194, 107941, 2024. (pdf) (software) Zhou, X. and Wu, W., "Statistical depth in spatial point process", Mathematics, vol. 12, no. 4, 595, 2024. (pdf) Mu, Y., Hu, G., and Wu, W., "Model-based statistical depth for bivariate functional data", Statistics and Its Interface, vol. 17, pp. 305-316, 2024. (pdf) Zhou. X, Ma, Y., and Wu, W., "Statistical depth for point process via the isometric log-ratio transformation", Computational Statistics and Data Analysis, vol. 187, 107813, 2023. (pdf) Zhao, W., Xu, Z., Mu, Y., Yang, Y., and Wu, W., "Model-based statistical depth with applications to functional data", Journal of Nonparametric Statistics, 1-44, 2023. (pdf) Wang, C., Chen, Y., Zhang, Y., Li, K., Lin, M., Pan, F., Wu, W., and Zhang, J., "A reinforcement learning approach for protein-ligand docking", BMC Bioinformatics, vol. 23, 368, 2022. (pdf) Xu, Z., Wang, C., and Wu, W., "A unified framework on defining depth for point process using function smoothing", Computational Statistics and Data Analysis , vol. 175, 107545, 2022. (pdf) Chen, Y., Ma, Y., and Wu, W., "Rank-based mixture models for temporal point processes", Frontiers in Applied Mathematics and Statistics , vol. 8, 852314, 2022. (pdf) Qi, K., Chen, Y., and and Wu, W., "Dirichlet depth for point process", Electronic Journal of Statistics , vol. 15, no. 1, 3574-3610, 2021. (pdf) Schluck, G., Wu, W., and Srivastava, A., "Intensity estimation of Poisson process with compositional noise", Frontiers in Applied Mathematics and Statistics , vol. 7, 1-19, 2021. (pdf) Ahn, K., Tucker, J. D., Wu, W., and Srivastava, A., "Regression models using shapes of functions as predictors'", Computational Statistics and Data Analysis , vol. 151, 107017, 2020. (pdf) Zhang, Y., Chen, Y., Wang, C., Lo, C., Liu, X., Wu, W., and Zhang, J., "ProDCoNN: a convolutional neural network method for protein design", Proteins: Sturcture, Function, and Bioinformatics, 1-11, 2020. (pdf) Schluck, G., Wu, W., Whyte, J., and Abbott, L., "Emergency department arrival times in Florida heart failure patients utilizing Fisher-Rao curve registration: A descriptive population-based study", Heart and Lung - The Journal of Acute and Critical Care, vol. 47, pp. 458-464, 2018. (pdf) (conference paper) Ahn, K., Tucker, J. D., Wu, W., and Srivastava, S., "Elastic handling of predictor phase in functional regression models", 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) , Salt Lake City, UT, June 18-22, 2018. (pdf) Cleveland, J., Zhao, W., and Wu, W., "Robust template estimation for functional data with phase variability using band depth", Computational Statistics and Data Analysis, vol. 125, pp. 10-26, 2018. (pdf) Wesolowski, S, Vera, D., and Wu, W., "SRSF shape analysis for sequencing data reveal new differentiating patterns", Computational Biology and Chemistry, vol. 70, pp. 56-64, 2017. (pdf) (conference paper) Cordova, J., Arghandeh, R., Zhou, Y., Wesolowski, S., Stifter, M., and Wu, W., "Shape-based data analysis for event classification in power systems", 2017 IEEE Manchester PowerTech, Manchester, UK, 2017. (pdf) Cleveland, J., Wu, W., and Srivastava, A., "Registration with norm-invariant constraint and its application in signal estimation under compositional and additive noises", Journal of Nonparametric Statistics, vol. 28, pp. 338-359, 2016. (pdf) Rosenthal, M., Wu, W., Klassen, E., and Srivastava, A., "Spherical regression models using projective linear transformations", Journal of American Statistical Association, vol. 109, no. 508, pp. 1615- 1624, 2014. (pdf) Tucker, J. D., Wu, W., and Srivastava, A., "Analysis of signals under compositional noise with applications to SONAR data", IEEE Journal of Oceanic Engineering, vol.39, pp. 318-330, 2014. (pdf) Wu, W. and Srivastava, A., "Analysis of spike train data: alignment and comparisons using extended Fisher-Rao metric", Electronic Journal of Statistics, vol. 8, pp. 1776-1785, 2014. (pdf) Wu, W., Hatsopoulos, N., and Srivastava, A., "Introduction to neural spike train data for phase-amplitude analysis", Electronic Journal of Statistics, vol. 8, pp. 1759-1768, 2014. (pdf) Wu, W., Hatsopoulos, N., and Srivastava, A., "Analysis of spike train data: discussion of results", Electronic Journal of Statistics, vol. 8, pp. 1808-1810, 2014. (pdf) Tucker, J. D., Wu, W., and Srivastava, A., "Phase-amplitude separation of proteomics data using extended Fisher-Rao metric", Electronic Journal of Statistics, vol. 8, pp. 1724-1733, 2014. (pdf) (conference paper) Wu, W., Srivastava, A., Laborde, J., and Zhang, J., ``An efficient multiple protein structure comparison method and its application to structure clustering and outlier detection '', IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Shanghai, China, 2103. (pdf) Kurtek, S., Wu, W., and G. Christensen, and Srivastava, A., "Segmentation, alignment and statistical analysis of biosignals with application to disease classification", Journal of Applied Statistics, vol. 40, no. 6, pp. 1270-1288, 2013. (pdf) Tucker, J. D., Wu, W., and Srivastava, A. "Generative models for functional data using phase and amplitude separation", Computational Statistics and Data Analysis , vol. 61, pp. 50-66, 2013. (pdf) (conference paper) Tucker, J. D., Wu, W., and Srivastava, A. "Analysis of signals under compositional noise with applications to SONAR data", Oceans '12 MTS/IEEE Conference , Hampton Roads, VA, 2012. (pdf) (conference paper) Kurtek, S., Srivastava, A., and Wu, W. "Signal estimation under random time-warpings and nonlinear signal alignment", Neural Information Processing Systems (NIPS) , Granada, Spain, 2011. (pdf)   Computational Neuroscience (2006 - Present) Ma, Y. and Wu, W., "A novel point process model for neuronal spike trains", Frontiers in Applied Mathematics and Statistics, 10:1349665, 2024. (pdf) Simmons, C., Moseley, S., Ogg, J., Zhou, X., Johnson, M., Wu, W., Clark, B., and Wilber, A., "A thalamo-parietal cortex circuit is critical for place-action coordination", Hippocampus, vol. 33, no. 12, pp. 1252-1266, 2023 (pdf) Xu, Z., Zhou, X., Xu, Y. and Wu, W., "Removing nonlinear misalignment in neuronal spike trains using the Fisher-Rao registration framework", Journal of Neuroscience Methods, vol. 367, 109436, 2022. (pdf) Stimmell, A., Xu, Z., Moseley, S., Fernandez, D., Benthem, S., Dang, D., Santos-Molina, L., Anzalone, R., Carcia-Barbon, C., Rodrigue, S., Wu, W., and Wilber, A., "Tau pathology profile across a parietal-hippocampal brain network is associated with spatial reorientation learning and memory performance in the 3xTg-AD mouse", Frontiers in Aging, vol. 2, 1-10, 2021. (pdf) Schoepfer, K., Xu, Y., Wilber, A., Wu, W., and Kabbaj, M., "Sex differences and effects of estrous stage on hippocampal-prefrontal theta communications", Physiological Reports, vol. 8, no. 8, e14646, 2020. (pdf) Zhao, W., Xu, Z., Li, W., and Wu, W., "Modeling and analyzing neural signals with phase variability using the Fisher-Rao registration", Journal of Neuroscience Methods, vol. 346, 108954, 2020. (pdf) Meynadasy, M., Clancy, K., Simon, J., Wu, W., and Li, W., "Impaired early visual categorization of fear in social anxiety", Psychophysiology, 57, e13509, 2020. (pdf) Xu, Z., Wu, W., Winter, S., Mehlman, M., Butler, W., Simmons, C., Harvey, R., Berkowitz, L., Chen, Y., Taube, J., Wilber, A., and Clark, B., "A comparison of neural decoding methods and population coding across thalamo-cortical head direction cells", Frontiers in Neural Circuits, vol. 13, art. 75, 2019. (pdf) Wilber. A, Skelin, I., Wu, W., and McNaughton, B., "Laminar organization of encoding and memory reactivation in the parietal cortex", Neuron, vol. 95, pp. 1406-1419, 2017. (pdf) Liu, S. and Wu, W., "Generalized Mahalanobis depth in point process and its application in neural coding", Annals of Applied Statistics, vol. 11, pp. 992-1010, 2017. (pdf) Wesolowski, S., Contreras, R. J., and Wu, W., "A new framework for Euclidean summary statistics in neural spike train space", Annals of Applied Statistics, vol. 9, pp. 1278-1297, 2015. (pdf) Wu, W., Amarasingham, A., Chen, Z., and Kim, S., "Editorial: Modeling and analysis of neural spike trains", Computational Intelligence and Neuroscience , vol. 2014, Article ID 161203, 2014. (pdf) Wu, W., Mast, T., Ziembko, C., Breza, J., and Contreras, R. J., "Statistical analysis and decoding of neural activity in the rodent geniculate ganglion using a metric-based inference system", PLoS ONE, vol. 8, e65439, 2013. (pdf) Wu, W. and Srivastava, A., "Estimating summary statistics in the spike-train space", Journal of Computational Neuroscience, vol. 34, pp. 391-410, 2013. (pdf) Lawhern, V., Hatsopoulos, N. G., and Wu, W., "Coupling time decoding and trajectory decoding using a target-included model in the motor cortex", Neurocomputing, vol. 82, pp. 117-126, 2012. (pdf) (conference paper) Wu, W. and Srivastava, A., "Estimation of a mean template from spike-train data", 34th Annual Conference of IEEE EMBS, 2012. (pdf) Wu, W. and Srivastava, A., "An information-geometric framework for statistical inferences in the neural spike train space", Journal of Computational Neuroscience, vol. 31, pp. 725-748, 2011. (pdf) (software) Lawhern, V., Nikonov, A. A., Wu, W., and Contreras, R. J., "Spike rate and spike timing contributions to coding taste quality information in rat periphery", Frontiers in Integrative Neuroscience, vol. 5, art. 18, pp. 1-14, 2011. (pdf) Wu, W. and Srivastava, A., "Towards statistical summaries of spike train data", Journal of Neuroscience Methods, vol. 195, pp. 107-110, 2011. (pdf) Lawhern, V., Wu, W., Hatsopoulos, N. G., and Paninski, L., "Population decoding of motor cortical activity using a genralized linear model with hidden states", Journal of Neuroscience Methods , vol. 189, pp. 267-280, 2010. (pdf) Paninski, L., Ahmadian, Y., Ferreira, D., Koyama, S., Rahnama Rad, K., Vidne, M., Vogelstein, J., and Wu, W., "A new look at state-space models for neural data", Journal of Computational Neuroscience, vol. 29, pp. 107-126, 2010. (pdf) Wu, W., Kulkarni, J. E., Hatsopoulos, N. G., and Paninski, L., "Neural decoding of hand motion using a linear state-space model with hidden states", IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 17, pp. 370-378, 2009. (pdf) Wu, W. and Hatsopoulos, N., "Real-time decoding of non-stationary neural activity in motor cortex", IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 16, pp. 213-222, 2008. (pdf) (conference paper) Wu, W. and Hatsopoulos, N., "Target-included model and hybrid decoding of stereotyped hand movement in the motor cortex", The second IEEE RAS / EMBS International Conference on Biomedical Robotics and Biomechatronics, Scottsdale, AZ, October 19-22, 2008. (pdf) Wu, W. and Hatsopoulos, N., "Coordinate system representations of movement direction in the premotor cortex", Experimental Brain Research, vol. 176, pp. 652-657, 2007. (pdf) Chi, Z., Wu W., Haga Z., Hatsopoulos, N., and Margoliash D., "Identifying neuronal activity pattern: patching local temporal information", Journal of Neurophysiology vol. 97, pp. 1221-1235, 2007. (pdf) Wu, W. and Hatsopoulos, N., "Evidence against a single coordinate system representation in the motor cortex ", Experimental Brain Research, vol. 175, pp. 197-210, 2006. (pdf) Wu,W., Gao, Y., Bienenstock, E., Donoghue, J. P., and Black, M. J., "Bayesian population decoding of motor cortical activity using a Kalman filter", Neural Computation, vol. 18, pp. 80-118, 2006. (pdf)   Birdsong Production Ross, M., Flores, D., Bertram, R., Johnson, F., Wu, W., and Hyson, R., "Experience-dependent intrinsic plasticity during auditory learning", Journal of Neuroscience, vol. 39, pp. 1206-1221, 2019. (pdf) Shaughnessy, D., Hyson, R., Bertram, R., Wu, W., and Johnson, F., "Female zebra finches do not sing yet share neural pathways necessary for singing in males", Journal of Comparative Neurology, vol. 527, pp. 843-855, 2019. (pdf) Galvis, D., Wu, W., Hyson, R., Johnson, F., and Bertram, R., "Interhemispheric dominance switching in a neural network model for birdsong", Journal of Neurophysiology, vol. 120, pp. 1186-1197, 2018. (pdf) Galvis, D., Wu, W., Hyson, R., Johnson, F., and Bertram, R., "A recurrent network model can explain the effects of targeted partial ablation of HVC on zebra finch song", Journal of Neurophysiology, vol. 118, pp. 677-692, 2017. (pdf) Elliott, K., Wu, W., Bertram, R., Hyson, R., and Johnson, F., "Orthogonal topography in the parallel input architecture of songbird HVC", Journal of Comparative Neurology, vol. 525, no. 9, 2133-2151, 2017. (pdf) Basista, M., Elliott, K., Wu, W., Hyson, R., Bertram, R., and Johnson, F., "Independent premotor encoding of the sequence and structure of birdsong syllables in avian cortex", Journal of Neuroscience, vol. 34, no. 50, pp. 16821-16834, 2014. (pdf) Bertram, R., Daou, A., Hyson, R., Johnson, F., and Wu, W.,"Two neural streams, one voice: pathways for theme and variation in the songbird brain", Neuroscience, vol. 277, pp. 806-817, 2014. (pdf) Elliott, K. C., Wu, W., Bertram, R., and Johnson, F., "Disconnection of a basal ganglia circuit in juvenile songbirds attenuates the spectral differentiation of song syllables", Developmental Neurobiology, vol. 74, pp. 574-590, 2014. (pdf) Daou, A., Johnson, F., Wu, W., and Bertram, R., "A computational tool for automated large-scale analysis and measurement of bird-song syntax", Journal of Neuroscience Methods, vol. 210, no. 2, pp. 147-160, 2012. (pdf) Thompson, J. A., Basista, M., Wu, W., Bertram, R., and Johnson, F., "Dual pre-motor contribution to songbird syllable variation", Journal of Neuroscience, vol. 31, no. 1, pp. 322-330, 2011. (pdf) Wu, W., Thompson, J. A., Bertram, R., and Johnson, F., "A statistical method for quantifying songbird phonology and syntax", Journal of Neuroscience Methods, vol. 174, no. 1, pp. 147-154, 2008. (pdf) (software) Thompson, J. A., Wu, W., Bertram, R., and Johnson, F., "Auditory-dependent vocal recovery in adult male zebra finches is facilitated by lesion of a forebrain pathway that includes the basal ganglia", Journal of Neuroscience, vol. 27, no. 45, pp. 12308-12320, 2007. (pdf)