Posts classified under: Computational and Systems Neuroscience

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.

Zili Liu, Ph.D.

Biography

Zili Liu studies visual perception — how people see and why they see the way they do (http://zililab.psych.ucla.edu). He joined UCLA’s Psychology Department in 2001. Dr. Liu received his Ph.D. in Cognitive and Linguistic Sciences, and his M.S. in Applied Mathematics, both from Brown University. He received his B.Sc. in Physics, from Beijing (Peking) University, China. He supports Rural China Education Foundation (http://www.ruralchina.org/)

Publications

A selected list of publications:

Lucy Cui and Zili Liu.   Synergy between Research on Ensemble Perception, Data Visualization, and Statistics Education: A Tutorial Review, Attention, Perception, & Psychophysics, 2020; (in press)(Special Issue on Ensemble Perception): .
Alan L.F. Lee, Zili Liu, Hongjing Lu.   Parts beget parts: Bootstrapping hierarchical object representations through visual statistical learning, Cognition, 2020; (in press): .
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Gennady Erlikhman, Gurjyot Singh, Tandra Ghose, Zili Liu   The effect of perceptual contour orientation uncertainty on the tilt aftereffect Vision Research, 2019; 158: 126-134.
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Yang (Mac) Xing, Zili Liu.   A Preference for Minimal Deformation Constrains the Perceived Depth of a Stereokinetic Stimulus Vision Research, 2018; 153: 53–59.
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Daniele Zavagno, Olga Daneyko, and Zili Liu.   The influence of physical illumination on lightness perception in simultaneous contrast displays i-Perception, 2018; 9(4): 1-22.
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Willey, C. and Liu, Z.   Long-term motor learning: Effects of varied and specific practice Vision Research, 2018; 152: 10-16.
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Jinfeng Huang; Ju Liang; Yifeng Zhou; Zili Liu   Transfer in motion discrimination learning was no greater in double training than in single training Journal of Vision, 2017; 17(6): 1-10.
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Hongjing Lu, Bosco S. Tjan, and Zili Liu   Human efficiency in detecting and discriminating biological motion Journal of Vision, 2017; 17(6): 1 — 14.
Jiawei Zhou, Zili Liu, Simon Clavagnier, Alexandre Reynaud, and Fang Hou.   Visual Plasticity in Adults, Neural Plasticity, 2017; 2017: 2.
Benjamin Thompson; Choi Deblieck; Allan D Wu; Marco Iacoboni; Zili Liu.   Psychophysical and rTMS evidence for the presence of motion opponency in human V5 Brain Stimulation, 2016; .
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Ju Liang, Yifeng Zhou, Zili Liu.   Examining the Standard Model of Signal Detection Theory in motion discrimination, Journal of Vision (Special Issue on Perceptual Learning), 2016; 16(9): doi:10.1167/16.7.9.
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Zili Liu, Xiaoyang Yang, Helene Intraub.   Boundary extension: Insights from Signal Detection Theory Journal of Vision, 2016; 16(8): 1–10.
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Jennifer Chang, Yifeng Zhou, Zili Liu.   Limited top-down influence from recognition to same-different matching of Chinese characters PLoS ONE, 2016; 11(6): e0156517. doi:10.1371/journal.pone.0156517.
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Ju Liang, Yifeng Zhou, Manfred Fahle, and Zili Liu   Limited Transfer of Long-Term Motion Perceptual Learning with Double Training Journal of Vision (Special Issue: Perceptual Learning), 2015; 15(1): 1 – 9.
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Ju Liang, Yifeng Zhou, Manfred Fahle, Zili Liu   Specificity of motion discrimination learning even with double training and staircase Journal of Vision (Special Issue: Perceptual Learning), 2015; 15(3): 1 – 10.
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Nihong Chen, Taiyong Bi, Tiangang Zhou, Sheng Li, Zili Liu, and Fang Fang.   Sharpened cortical tuning and enhanced cortico-cortical communication contribute to the long-term neural mechanisms of visual motion perceptual learning Neuro Image, 2015; 115: 17 — 29.
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Tandra Ghose, Zili Liu.   Generalization between canonical and non-canonical views in object recognition Journal of Vision, 2013; 13(1): 1–15.
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Xiaoxiao Wang, Yifeng Zhou, Zili Liu.   Transfer in motion perceptual learning depends on the difficulty of the training task Journal of Vision, 2013; 13((7):5): 1 — 9.
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Xuan Huang, Hongjing Lu, Yifeng Zhou, Zili Liu.   General and specific perceptual learning in radial speed discrimination Journal of Vision, 2011; 11(4, article 7): 1 — 11.
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Zhou J, Tjan B S, Zhou Y, Liu Z   Better discrimination for illusory than for occluded perceptual completions Journal of Vision, 2008; 8(7(26)): 1-17.
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Zhou J, Gotch C, Zhou Y, Liu Z   Perceiving an object in its context — is the context cultural or perceptual? Journal of Vision, 2008; 8(12(2)): 1-5.
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Huang X, Lu H, Tjan BS, Zhou Y, Liu Z   Motion perceptual learning: When only task-relevant information is learned Journal of Vision, 2007; 7(10:14): 1-10.
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Hou F, Lu H, Zhou Y, Liu Z.   “Amodal completion impairs stereo acuity discrimination”, Vision Research, 2006; 46: 2061-2068.
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Lu H, Zavagno D, Liu Z.   “The glare effect does not give rise to a longer lasting afterimage”, Perception, 2006; 35: 701 — 707.
Thompson B, Liu Z.   Learning motion discrimination with suppressed and unsuppressed MT, Vision Research, 2006; 46: 2110-2121.
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Rokers B, Yuille A, Liu Z.   The perception of a stereokinetic stimulus, Vision Research, 2006; 46: 2375 — 2387.
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Lu H, Liu Z   Computing dynamic classification images from correlation maps Journal of Vision [electronic resource], 2006; 6: 475 — 483.
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Lu H, Tjan B S, Liu Z.   “Shape recognition alters sensitivity in stereoscopic depth discrimination” Journal of Vision [electronic resource], 2006; 6: 75–86.
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Tjan, B S Liu, Z.   Symmetry impedes symmetry discrimination Journal of vision [electronic resource], 2005; 5(10): 888-900.
Rokers B, Liu Z.   “On the minimal relative motion principle — lateral displacement of a contracting bar”, Journal of Mathematical Psychology, 2004; 48(4): 292-295.
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Liu Z.   “On the principle of minimal relative motion — the oscillating tilted bar” Journal of Mathematical Psychology, 2004; 48: 196-198.
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Lu, H Qian, N Liu, Z   Learning motion discrimination with suppressed MT Vision research. , 2004; 44(15): 1817-25.
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Liu, Z Kersten, D   Three-dimensional symmetric shapes are discriminated more efficiently than asymmetric ones Journal of the Optical Society of America. A, Optics, image science, and vision, 2003; 20(7): 1331-40.
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Liu Z.   “On the principle of minimal relative motion — the bar, the circle with a dot, and the ellipse” Journal of Vision [electronic resource], 2003; 3: 625–629.
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Matthews N, Liu Z, Qian N.   “The effect of orientation learning on contrast sensitivity” Vision Research, 2001; 41: 463-471.
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Liu, Z Weinshall, D   Mechanisms of generalization in perceptual learning Vision research, 2000; 40(1): 97-109.
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Liu Z.   “Learning a visual skill that generalizes across motion directions” Proceedings of the National Academy of Sciences USA, 1999; 96: 14085-14087.
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Matthews N, Liu Z, Geesaman B J, Qian N.   “Perceptual learning on orientation and direction discrimination” Vision Research, 1999; 39: 3692-3701.
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Liu, Z Jacobs, DW Basri, R   The role of convexity in perceptual completion: beyond good continuation Vision research. , 1999; 39(25): 4244-57.
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Liu, Z Kersten, D Knill, DC   Dissociating stimulus information from internal representation–a case study in object recognition Vision research, 1999; 39(3): 603-12.
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Liu, Z Kersten, D   2D observers for human 3D object recognition? Vision research. , 1998; 38(15-16): 2507-19.
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Liu, Z Vaina, LM   Simultaneous learning of motion discrimination in two directions Brain research. Cognitive brain research, 1998; 6(4): 347-9.
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Liu, Z   Viewpoint dependency in object representation and recognition Spatial vision, 1996; 9(4): 491-521.
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Liu, Z Knill, DC Kersten, D   Object classification for human and ideal observers Vision research, 1995; 35(4): 549-68.
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Zhang, S. W. Wang, X. Liu, Z. Srinivasan, M V.   Visual tracking of moving targets by freely flying honeybees Visual neuroscience, 1990; 4(4): 379-86.
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