Jeff Gavornik, Ph.D.
All cognitive functions somehow emerge from the ongoing communication
between neurons in the brain. In a very real sense, each of us is
entirely defined by our unique neural anatomy. We know that the
connections between neurons are continuously modified by experience
over a lifetime and that neural structure determines how information is
represented and processed within the brain. Except in very limited ways
(often involving highly contrived laboratory conditions) we don't know
how brain structure actually relates to function or how experience
driven synaptic plasticity actually modifies the connections between
neurons. In other words, we don't know how the brain works. I'm trying
to figure it out.
I use a combination of computational and experimental
techniques to study how visual experience modifies visual processing
and perception. My goal is to understand how the cortex learns and
represents sequential relationships (for example, "B" follows "A"),
processes time and makes predictions. It may seem that these things are
unrelated. What, after all, does vision have to do with temporal
processing or sequences? The answer is quite a bit. When you look at a
baseball, you recognize the object because your brain knows that the
image projected on your retinas represents a baseball, and you can can
predict a ball's future location in space using motion cues gleaned
from the temporal sequence of retinal activation patterns that results
as it flies through the air. You weren't born with these abilities, you
learned them by looking at the world around you using the same cortical
mechanisms that underlie all learning and memory. I believe that
insights gained studying the early visual system will inform a general
understanding of how the brain works.
I am interested in neuroscience primarily because neuroscience
is really interesting. The brain is an incredibly complex, non-linear,
non-stationary stochastic, dynamic system. Through unsupervised
experience it can learn to recognize, predict and generate patterns
while maintaining robust I/O control of the body's sensory and effector
systems. I want to understand the principles by which biological neural
networks organize and processes information. Disease states that
disrupt neural function can be devastating; understanding how molecular
machinery creates and maintains brain function is absolutely necessary
to design effective medical interventions targeting all manner of
mental disorders and neurological dysfunctions. An algorithmic
understanding of the brain will also allow us to design neuromimetic
perception and control systems that actually work.
Shouval HZ, Agarwal A, Gavornik JP. (2013) Scaling of perceptual errors can predict the shape of neural tuning curves. Phys. Rev. Letters (in press).
Gavornik JP, Shouval HZ. (2010) A network of spiking neurons that can represent interval timing: mean field analysis. J. Comput. Neurosci. 30(2) 501-13.
Shouval HZ, Gavornik JP (2010) A single spiking neuron that can represent interval timing: analysis, plasticity and multi-stability. J. Comput. Neurosci. 30(2) 488-99.
Coleman J, Nahmani M, Gavornik JP,
Haslinger R, Heynen A, Bear MF and Erisir A. (2010) Rapid structural
remodeling of thalamocortical synapses parallels experience-dependent
functional plasticity in mouse primary visual cortex. J. Neurosci. 30(29) 9670-82.
Gavornik JP, Shuler MGH,
Loewenstein Y, Bear MF and Shouval, HZ (2009) Learning reward timing in
cortex through reward dependent expression of synaptic plasticity. Proc. Natl. Acad. Sci. U S A 106(16):6826-31.
Cai Y, Gavornik JP,
Cooper LN, Yeung LC, and Shouval HZ (2007) Effect of stochastic
synaptic and dendritic dynamics on synaptic plasticity in visual cortex
and hippocampus. J. Neurophysiol. 97:375-386.
K99/R00 Cortical mechanisms of learned spatial-temporal sequence coding (NIMH:1K99MH099654-01)
Education, Work, and Research Experience
HHMI Postdoctoral Associate in the Mark F. Bear Lab. The Picower Institute for Learning and
Memory, Massachusetts Institute of Technology, Cambridge, MA. (2009 – present)
Doctor of Philosophy in Electrical Engineering. The University of Texas at Austin, Austin, TX. (May 2009)
Researcher, Department of Neurobiology and Anatomy. The University of Texas Health Science Center. Houston, TX. (2006-2009)
Summer Program in Experimental & Computational Neurodynamics,
Center for Theoretical Biological Physics, The University of California
San Diego, La Jolla, CA. (August 2006)
Master of Electrical Engineering. Rice University. Houston, TX (May 2003)
Integrated Defense Systems, International Space Station
Hardware/Software Integration. The Boeing Company. Houston, TX.
Bachelor of Science, Electrical and Computer Engineering & History. Rice University. Houston, TX. (May 1999)
Internship, Satellite Communications Division. The MITRE Corp. Bedford, MA. (1998-1999)
Intern and Carl B. & Florence E. King Foundation Summer Program
Participant and Internship, Diagnostics Physics Department, MD Anderson
Cancer Center. Houston, TX. (1995~1998)
Internship, Anderson Lab. Air Force Office of Scientific Research. San Antonio TX. (1993-1995)
Chili, Done Right