Center of Excellence in Computational & Systems Neuroscience

Introduction
Theoretical and computational approaches to Neuroscience are becoming increasingly important in the arsenal of approaches used to explore the brain. Such approaches include modeling (mathematical and computational), the development of new mathematical and statistical methods for the analysis of huge data sets, and the development of new experimental techniques, motivated by theoretical considerations, such as the recording of large populations of neurons.

These developments are sure to play a crucial role in future brain research, both in advancing our understanding and in helping translational aspects of research, such as deep brain stimulation and the development of sensory or motor prostheses. The Center of Excellence in Computational & Systems Neuroscience at the Mount Sinai Friedman Brain Institute shall focus on the following programs.

Computational and mathematical modeling at multiple levels
Modeling is essential for interpreting experimental results and for planning new experiments. In neuroscience, it is important to support theoretical approaches at multiple levels.

Subcellular-level: Genetic/epigenetic network modeling is an important, emerging area with strong experimental representation in the Neuroscience and Neurology Departments. Our team includes:
Patrizia Casaccia MD, (Neuroscience)
Eric J. Nestler, MD, PhD (Neuroscience)
Stuart Sealfon, MD, (Neurology)

Mount Sinai holds a strong experimental interest in the area of biochemical signaling networks, such as the one underlying LTP/LTD. Our investigative team comprises:
Deanna L. Benson, PhD (Neuroscience)
Stuart Sealfon, MD, (Neurology)
George W. Huntley PhD (Neuroscience)
Eric J. Nestler, MD, PhD (Neuroscience)
Greg Phillips, PhD (Neuroscience)
Stephen R. Salton MD, PhD Neuroscience

Dr. Zhou leads research consisting of reaction-diffusion modeling of signaling molecules and ions, and effects on cell function.

Cellular-level: Cable and Hodgkin-Huxley modeling; compartment modeling based on accurately reconstructed cell morphologies, including spine morphology. Dependence of electrical signaling (impulse firing patterns) on morphology, Ca2+ diffusion, and ion channel densities/kinetics.
Vladimir Brezina, Ph.D., (Neuroscience)
Patrick R. Hof, M.D., (Neuroscience)
George W. Huntley PhD (Neuroscience)
John H. Morrison, Ph.D., (Neuroscience)
Eric J. Nestler, MD, PhD (Neuroscience)
Eric A. Sobie, Ph.D., (Pharmacology and Systems Therapeutics)
Hongyan (Jenny) Zou, M.D., Ph.D., (Neuroscience)

Circuit-level: Population dynamics and network changes in pathologies such as depression (Han, Russo), drug addiction (Nestler), or Alzheimer's disease (Gandy) are studied experimentally and through computational modeling. Modeling is currently conducted in the following labs.
Vladimir Brezina, Ph.D., (Neuroscience)
Ehud Kaplan, Ph.D., (Neuroscience)
Matthew L. Shapiro, Ph.D., (Neuroscience)
Klaudiusz Weiss, Ph.D., (Neuroscience)

Systems-Level: Visual system, vestibular system, stomato-gastric ganglion, central pattern generators (Brezina, Cohen, Copper, Kaplan, Weiss, Yakushin). Control systems and “Black Box” modeling (Cohen/Raphan, Brezina, Kaplan).
Vladimir Brezina, Ph.D., (Neuroscience)
Bernard Cohen, MD, (Neurology)
Elizabeth C. Cropper, Ph.D., (Neuroscience)
Ehud Kaplan, Ph.D., (Neuroscience)
Klaudiusz Weiss, Ph.D., (Neuroscience)
Sergei Yakushin, Ph.D., (Neurology)

Signal processing/image analysis
Signals that are recorded simultaneously from many neural sources (many electrodes, image pixels/voxels) provide new kinds of information, and the processing of such information has become an important area of intensive research, with implications for many disciplines. Mathematical, computational, and statistical approaches are essential for detecting tiny signals and functionally significant activity patterns buried in noisy records.

Imaging:

• Optical imaging (Ehud Kaplan, Ph.D., Lawrence Sirovich Ph.D., Hongyan (Jenny) Zou, M.D., Ph.D. / George W. Huntley PhD)
  
• fMRI (Cheuk Tang, PhD, Jin Fan, PhD)
  
• PET (Joseph Buxbaum, MSc, PhD)
  
• Ultrasound Imaging

Multi-electrode recordings:

Electrode arrays
Joseph Buxbaum, MSc, PhD, (Psychiatry)
Jin Fan, PhD, (Psychiatry)
Ehud Kaplan, Ph.D., (Neuroscience)
Matthew L. Shapiro, Ph.D., (Neuroscience)
Lawrence Sirovich Ph.D., (Pharmacology and Systems Therapeutics)
Cheuk Tang, PhD, (Radiology)
Hongyan (Jenny) Zou, M.D., Ph.D. / George W. Huntley PhD

Dynamics and Information in Neuronal Populations
Much of what we know about neuronal mechanisms comes from studies of individual neurons. However, every brain activity involves many neurons, and our knowledge of the dynamical interplay among neuronal populations within and between brain areas is sorely lacking.

It is only recently that we have been able to record the activity of large groups of neurons with electrodes or through imaging, as is done currently in the Kaplan and Shapiro labs. The analysis of the dynamics of such populations, and the decoding of the messages that this concerted activity represents, are emerging fields with great potential for both theoretical and translational advances, such as creating sensory or motor prostheses.