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  • Assistant Professor, Neural and Data Science Laboratory, Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research
  • Assistant Professor, Department of Molecular Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell

About the investigator

Dr. Theo Zanos is the head of the Neural and Data Science Lab and an assistant professor at the Feinstein Institutes for Medical Research and the Zucker School of Medicine at Hofstra/Northwell. He received his Bachelor of Engineering degree in electrical and computer engineering from the Aristotle University of Thessaloniki in Greece in 2004, his Master of Science and his Doctorate in biomedical engineering from the University of Southern California, Viterbi School of Engineering in 2006 and 2009 respectively. His thesis, supervised by Dr. Vasilis Marmarelis, focused on developing machine learning and system identification approaches for Multi-Input Multi-Output hippocampal neural circuits to be used for a cognitive neuroprosthesis platform. 

In 2009, Dr. Zanos was recruited as a postdoctoral fellow by Dr. Christopher Pack to work at the Montreal Neurological Institute (MNI), McGill, in Montreal, Canada, combining high-channel-count primate electrophysiology with machine-learning based neural data analysis methods to relate neural activity to behavior and cognition In 2016, Dr. Zanos joined the Institute of Bioelectronic Medicine at the Feinstein Institutes for Medical Research. 

Dr. Zanos has authored more than 20 peer-reviewed publications in journals like Neuron, PNAS, Journal of Neuroscience and others and his research has been featured in PBS, Scientific American and other media outlets. He and has been awarded the Excellence in Research Award in 2018, the Jean Timmins Award in 2012 and the Center of Excellence in Commercialization and Research Award in 2010.

Research focus

The goal of the Neural and Data Science Lab is to develop the algorithms that will power the next generation bioelectronic medicine devices to enable early diagnosis, assess disease severity and personalize and adapt therapies. Our ambition is to learn how the nervous system senses the state and affects the function of the immune, metabolic and cardiopulmonary systems. We want to use this knowledge to develop devices that are able to diagnose and treat various diseases and conditions by interacting with the nervous system. To achieve that, we combine neural and physiological signal processing, machine learning and neurophysiology. Current projects include decoding immune and metabolic states from vagal signals, closed-loop optimization of bioelectronic therapies, non-invasive bioelectronic analytics and machine learning and reinforcement learning applied in healthcare data.

Education

University of Southern California, Viterbi School of Engineering
Degree: PhD
2009
Field of study: Biomedical Engineering

University of Southern California, Viterbi School of Engineering
Degree: MSc
2006
Field of study: Biomedical Engineering

Aristotle University of Thessaloniki, Engineering School
Degree: BEng
2004
Field of study: Electrical and Computer Engineering

Lab members

Todd Levy, BS, MS
Electrical Engineer
Email[email protected]

Shubham Debnath, PhD
Postdoctoral Fellow
Emails[email protected]

Viktor Toth, MS
Research Associate
Email[email protected]

Honors & awards

  • 2018 Award of Excellence in Research, Feinstein Institutes for Medical Research
  • 2012 Jean Timmins Award, Montreal Neurological Institute
  • 2010 Center of Excellence in Commercialization and Research Award, McGill University
  • 2006 Fred Grodins Oral Presentation Award, University of Southern California
  • 2004 Senior Thesis Award, Aristotle University of Thessaloniki

Publications

  1. E.B. Masi, T. Levy, T. Tsaava, C.E. Bouton, K.J. Tracey, S.C. Chavan, T.P. Zanos (2019) Identification of hypoglycemia-specific neural signals by decoding murine vagus nerve activity, Bioelectronic Medicine 2019:5-9
  2. T.P. Zanos. (2019) Recording and Decoding of Vagal Neural Signals Related to Changes in Physiological Parameters and Biomarkers of Disease. Cold Spring Harbor Perspectives in Medicine, doi:10.1101/cshperspect.a034157
  3. T.P. Zanos, H. A. Silverman, T. Levy, T. Tsaava, E. Battinelli, P.W. Lorraine, J. M. Ashe, S. S. Chavan, K. J. Tracey, C. B. Bouton, “Identification of cytokine-specific sensory neural signals by decoding murine vagus nerve activity”, Proceedings of the National Academy of Sciences 115: E4843–E4852 (2018)
  4. M.R. Krause, T.P. Zanos, B.A. Csorba, P.K. Pilly, J. Choe, M.E. Phillips, A. Datta, C.C. Pack, “Transcranial direct current stimulation facilitates associative learning and alters functional connectivity in the primate brain”, Current Biology, 27, 1–11 (2017)
  5. C. Li, H.S. Sohal, F. Li, T.P. Zanos, L. Goldman, R.K. Narayan, C.E. Bouton, “A new 3D self-adaptive nerve electrode for high density peripheral nerve stimulation and recording”, 19thInternational Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS), Kaohsiung, pp. 51-54 (2017)
  6. T.P. Zanos, P.J. Mineault, D. Guitton, C.C. Pack, “Mechanisms of Saccadic Suppression in primate cortical area V4”, Journal of Neuroscience, 36, 9227-9239 (2016)
  7.  A. Datta, M. Krause, P. Pilly, J. Choe, T. P. Zanos, C. Thomas, C. C. Pack, “Experimental and modeling evidence for optimized transcranial electrical stimulation in primates”, IEEE Eng in Medicine and Biology Society Conference, Orlando, FL, in press (2016)
  1. T. P. Zanos, P. J. Minaeult, K. T. Nasiotis, D. Guitton, C. C. Pack, “A sensorimotor role for traveling waves in visual cortex”, Neuron, 85, 1-13. (2015) – Journal Cover Story
  2. P. J. Mineault, T. P. Zanos, C. C. Pack, “Local Field Potentials reflect multiple spatial scales in V4”, Frontiers in Computational Neuroscience, 7:21. (2013)
  3. S. Zanos, T. P. Zanos, V. Z. Marmarelis, G. A. Ojemann, E. E. Fetz, “Relationships between spike-free local field potentials and spike timing in human temporal cortex”, Journal of Neurophysiology, Vol. 107(7), pp. 1808-21 (2012)
  4. T. P. Zanos, P. J. Minaeult, C. C. Pack, “Removal of Spurious Correlations between Spikes and Local Field Potentials”, Journal of Neurophysiology, Vol. 105, pp. 474-486. (2011)
  5. T. P. Zanos, P. J. Mineault, J. A. Monteon, C. C. Pack, “Functional Connectivity during surround suppression in macaque area V4”, IEEE Eng in Medicine and Biology Society Conference, Boston, MA, pp. 3342-3345 (2011)
  6. T. P. Zanos, V. Z. Marmarelis, R. E. Hampson, T. W. Berger, S. A. Deadwyler, “Boolean Modeling of Neural Systems with Point-Process Inputs and Outputs. Part II: Application to the Hippocampus”, Annals of Biomedical Engineering, Vol. 37 (8), pp. 1668-1682. (2009)
  7. V. Z. Marmarelis, T. P. Zanos, T. W. Berger, “Boolean Modeling of Neural Systems with Point-Process Inputs and Outputs. Part I: Theory and Simulations”, Annals of Biomedical Engineering, Vol. 37 (8), pp. 1654-1667. (2009)
  8. T. P. Zanos, S. H. Courellis, T. W. Berger, R. E. Hampson, S. A. Deadwyler, V. Z. Marmarelis, “Nonlinear Modeling of Causal Interrelationships in Neuronal Ensembles”, IEEE Trans. on Neural Systems and Rehabilitation Engineering, Vol. 15 (4), pp. 336-352. (2008) – Journal Cover Story
  9. T. P. Zanos, R. E. Hampson, S. A. Deadwyler, T. W. Berger, V. Z. Marmarelis, “Functional Connectivity through Nonlinear Modeling: An Application to the Rat Hippocampus”, IEEE Engineering in Medicine and Biology Society Conference, Vancouver, Canada, pp. 5522-5525 (2008)
  10. T. P. Zanos, S. H. Courellis, R. E. Hampson, S. A. Deadwyler, V. Z. Marmarelis, T. W. Berger, “A multi-input modeling approach to quantify hippocampal nonlinear dynamic transformations”, IEEE Engineering in Medicine and Biology Society Conference, New York, NY, pp. 4967-4970 (2006)
  11. V. Z. Marmarelis, T. P. Zanos, S. H. Courellis, T. W. Berger, “Boolean Modeling of Neural Systems with Point-Process Inputs and Outputs”, IEEE Eng in Medicine and Biology Society Conference, New York, NY, pp. 2114-2117 (2006)
  12. S. H. Courellis, T. P. Zanos, M. C. Hsiao, R. E. Hampson, S. A. Deadwyler, V. Z. Marmarelis, T. W. Berger, “Modeling Hippocampal Nonlinear Dynamic Transformations with Principal Dynamic Modes”, IEEE Engineering in Medicine and Biology Society Conference, New York, NY, pp. 2300-2303 (2006)
  13. M. Hsiao, C. H. Chan, V. Srinivasan, A. Ahuja, G. Erinjippurath, T. P. Zanos, G. Gholmieh, D. Song, J. D. Wills, J. LaCross, S. H. Courelis, A. R. Tanguay, J. J. Granacki, V. Z. Marmarelis, T. W. Berger, “VLSI Implementation of a nonlinear neuronal model: A “Neural Prosthesis” to restore hippocampal trisynaptic dynamics, IEEE Engineering in Medicine and Biology Society Conference, New York, NY, pp. 4396-4399 (2006)
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