Posts classified under: Computational and Systems Neuroscience

Neil Harris, Ph.D.

Biography

Professor Harris directs NEIL lab with over 25 years of experience with rodent CNS injury models and in particular using MRI and PET to assess structure and function. He received his B.Sc. in Biology/Neuroscience from University of Portsmouth in 1988, and his Ph.D. in Physiology from King’s College London in 1991. Dr. Harris’s early focus of research addressed the question of optimal timing for intervention after the diagnosis of infantile hydrocephalus. Prior to joining University of California Los Angeles (UCLA), Dr. Harris received training in multimodality imaging techniques, including PET, structural MRI, fMRI, DTI, and Glucose/blood-flow autoradiography at Kings college University of London, University of Florida McKnight Brain Institute, the Royal College of Surgeons unit of Biophysics in the Institute of Child Health, and University of Cambridge Department of Neurosurgery. Subsequently, Dr. Harris conducted studies to address forebrain ischemic stroke looking at the potential use of non-invasive biomarkers to determine salvageable areas of brain. The studies were cited amongst primary reported findings on biophysical mechanism of the change in water diffusion after stroke. Dr. Harris currently resides as Professor in Residence of UCLA Department of Neurosurgery where he primarily conducts investigations on Traumatic Brain Injury and is the scientific director of UCLA 7T animal imaging core.

Keith Holyoak, Ph.D.

Biography

Combining behavioral studies of normal cognition, computational modeling, and neuropsychological and neuroimaging studies, to understand the role of the prefrontal cortex in human thinking Keith J. Holyoak conducts research in human reasoning and problem solving. Much of his work is concerned with the role of analogy in thinking. One of the major themes of this work is the way in which analogy serves as a psychological mechanism for learning and transfer of knowledge. In his book Mental Leaps with Paul Thagard, he presents a general theory of analogical thinking that includes analysis of how the capacity to use analogy evolved in primates, how it develops in children, and how it is used to reason in domains ranging from law and politics to science. Other related reserach, in collaboration with Dan Simon, deals with complex decision-making in fields such as the law. Holyoaks research combines studies of thinking in normal adults with neuropsychological studies of how thinking in brain-damaged individuals. This work, in collaboration with Barbara Knowlton and others, is investigating the role of prefrontal cortex in complex human reasoning. In addition to experimental work, Holyoak works with John Hummel to develop computational models of human thinking based on neural-network models. These models use neural synchrony to preform dynamic variable binding, and thereby represent and maniputlate symbolic knowledge. The overall goal is to understand the neural basis for human thought.

Jonathan Kao, Ph.D.

Biography

Dr. Jonathan Kao is an Assistant Professor in the Department of Electrical Engineering. He received his Ph.D. in 2016 in Electrical Engineering from Stanford University working with Dr. Krishna Shenoy, where he developed algorithms for brain-machine interfaces. He continued his post-doctoral research in the same lab, using statistical and machine learning techniques to analyze the dynamics of neural populations. His lab is interested in computational techniques to elucidate computational mechanisms in neural populations as well as designing algorithms for neural prostheses.

Publications

A selected list of publications:

O’Shea Daniel J, Trautmann Eric, Chandrasekaran Chandramouli, Stavisky Sergey, Kao Jonathan C, Sahani Maneesh, Ryu Stephen, Deisseroth Karl, Shenoy Krishna V   The need for calcium imaging in nonhuman primates: New motor neuroscience and brain-machine interfaces Experimental neurology, 2016; .
Kao Jonathan C, Nuyujukian Paul, Ryu Stephen I, Shenoy Krishna V   A high-performance neural prosthesis incorporating discrete state selection with hidden Markov models IEEE transactions on bio-medical engineering, 2016; .
Kao Jonathan C, Ryu Stephen I, Shenoy Krishna V   Leveraging historical knowledge of neural dynamics to rescue decoder performance as neural channels are lost: “Decoder hysteresis” Conference proceedings : … Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2015; 2015: 1061-6.
Kao Jonathan C, Nuyujukian Paul, Ryu Stephen I, Churchland Mark M, Cunningham John P, Shenoy Krishna V   Single-trial dynamics of motor cortex and their applications to brain-machine interfaces Nature communications, 2015; 6: 7759.
Stavisky Sergey D, Kao Jonathan C, Nuyujukian Paul, Ryu Stephen I, Shenoy Krishna V   A high performing brain-machine interface driven by low-frequency local field potentials alone and together with spikes Journal of neural engineering, 2015; 12(3): 036009.
Even-Chen Nir, Stavisky Sergey D, Kao Jonathan C, Ryu Stephen I, Shenoy Krishna V   Auto-deleting brain machine interface: Error detection using spiking neural activity in the motor cortex Conference proceedings : … Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2015; 2015(3): 71-5.
Nuyujukian Paul, Fan Joline M, Kao Jonathan C, Ryu Stephen I, Shenoy Krishna V   A high-performance keyboard neural prosthesis enabled by task optimization IEEE transactions on bio-medical engineering, 2015; 62(1): 21-9.
Nuyujukian Paul, Kao Jonathan C, Fan Joline M, Stavisky Sergey D, Ryu Stephen I, Shenoy Krishna V   Performance sustaining intracortical neural prostheses Journal of neural engineering, 2014; 11(6): 066003.
Stavisky Sergey D, Kao Jonathan C, Nuyujukian Paul, Ryu Stephen I, Shenoy Krishna V   Hybrid decoding of both spikes and low-frequency local field potentials for brain-machine interfaces Conference proceedings : … Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2014; 2014(1): 3041-4.
Fan Joline M, Nuyujukian Paul, Kao Jonathan C, Chestek Cynthia A, Ryu Stephen I, Shenoy Krishna V   Intention estimation in brain-machine interfaces Journal of neural engineering, 2014; 11(1): 016004.
Kao Jonathan C, Nuyujukian Paul, Stavisky Sergey, Ryu Stephen I, Ganguli Surya, Shenoy Krishna V   Investigating the role of firing-rate normalization and dimensionality reduction in brain-machine interface robustness Conference proceedings : … Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2013; 2013(1): 293-8.
Gilja Vikash, Nuyujukian Paul, Chestek Cindy A, Cunningham John P, Yu Byron M, Fan Joline M, Churchland Mark M, Kaufman Matthew T, Kao Jonathan C, Ryu Stephen I, Shenoy Krishna V   A high-performance neural prosthesis enabled by control algorithm design Nature neuroscience, 2012; 15(12): 1752-7.
Sussillo David, Nuyujukian Paul, Fan Joline M, Kao Jonathan C, Stavisky Sergey D, Ryu Stephen, Shenoy Krishna   A recurrent neural network for closed-loop intracortical brain-machine interface decoders Journal of neural engineering, 2012; 9(2): 026027.

Alicia Izquierdo, Ph.D.

Publications

A selected list of publications:

González VV, Zhang Y, Ashikyan SA, Rickard A, Yassine I, Romero-Sosa JL, Blaisdell AP, Izquierdo A (2024). A special role for anterior cingulate cortex, but not orbitofrontal cortex or basolateral amygdala, in choices involving information. Cerebral Cortex 34(4): bhae135.

Aguirre CG, Woo JH, Romero-Sosa JL, Rivera ZM, Tejada AN, Munier JJ, Perez J, Goldfarb M, Das K, Gomez M, Ye T, Pannu J, Evans K, O’Neill PR, Spigelman I, Soltani A, Izquierdo A (2024). Dissociable contributions of basolateral amygdala and ventrolateral orbitofrontal cortex to flexible learning under uncertaintyThe Journal of Neuroscience 44(2): e0622232023.

Ye T, Romero-Sosa JL, Rickard A, Aguirre CG, Wikenheiser AM, Blair HT, Izquierdo A (2023). Theta oscillations in anterior cingulate cortex and orbitofrontal cortex differentially modulate accuracy and speed in flexible reward learningOxford Open Neuroscience 2: kvad005.

Hart EE, Blair GJ, O’Dell TJ, Blair HT, Izquierdo A (2020). Chemogenetic modulation and single-photon calcium imaging in anterior cingulate cortex reveal a mechanism for effort-based decisionsThe Journal of Neuroscience 40 (29) 5628-5643.

Stolyarova A, Rakhshan M, Hart EE, O’Dell TJ, Peters MAK, Lau H, Soltani A, Izquierdo A (2019). Contributions of anterior cingulate cortex and basolateral amygdala to decision confidence and learning under uncertaintyNature Communications 10: 4704.

Soltani A and Izquierdo A (2019). Adaptive learning under expected and unexpected uncertaintyNat Rev Neurosci doi: 10.1038/s41583-019-0180-y.