Ph.D., Stanford University
Our group seeks to elucidate how large populations of neurons process information, from encoding sensory stimuli to guiding motor actions. Most neurophysiological studies to date involve studying one neuron at a time. Although one neuron can be informative about the sensory stimulus or motor action, it often doesn't tell the full story. While this provides the motivation for looking across a neural population, the heterogeneity of the activity of different neurons can be baffling.
We have two major aims:
(1) To develop and apply novel signal processing and machine learning algorithms to explain the high-dimensional structure and timecourse of neural population activity.
(2) To apply this knowledge to the design of next-generation biomedical devices that interface with large populations of neurons in increasingly sophisticated ways.
The work is at the intersection of signal processing / machine learning, biomedical engineering, and basic neuroscience.
- Churchland, MM, Yu, BM, Cunningham, JP, Sugrue, LP, Cohen, MR, Corrado, GS, Newsome, WT, Clark, AM, Hosseini, P, Scott, BB, Bradley, DC, Smith, MA, Kohn, A, Movshon, JA, Armstrong, KM, Moore, T, Chang, SW, Snyder, LH, Priebe, NJ, Finn, IM, Ferster, D, Ryu, SI, Santhanam, G, Sahani, M, Shenoy, KV: Stimulus onset quenches neural variability: a widespread cortical phenomenon. Nat Neurosci, 2010. In press.
- Santhanam, G, Yu, BM, Gilja, V, Ryu, SI, Afshar, A, Sahani, M, Shenoy, KV: Factor-analysis methods for higher-performance neural prostheses. J Neurophysiol 102: 1315-1330, 2009.
- Yu, BM, Cunningham, JP, Santhanam, G, Ryu, SI, Shenoy, KV, Sahani, M: Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity. J Neurophysiol 102: 614-635, 2009.
- Churchland, MM, Yu, BM, Sahani, M, Shenoy, KV: Techniques for extracting single-trial activity patterns from large-scale neural recordings. Curr Opin Neurobiol 17(5): 609-618, 2007.
- Yu, BM, Kemere, C, Santhanam, G, Afshar, A, Ryu, SI, Meng, TH, Sahani, M, Shenoy, KV: Mixture of trajectory models for neural decoding of goal-directed movements. J Neurophysiol 97: 3763-3780, 2007.
- Santhanam, G, Ryu, SI, Yu, BM, Afshar, A, Shenoy, KV: A high-performance brain-computer interface. Nature 442: 195-198, 2006.
- Churchland, MM, Yu, BM, Ryu, SI, Santhanam, G, Shenoy, KV: Neural variability in premotor cortex provides a signature of motor preparation. J Neurosci 26(14): 3697-3712, 2006.