Itamar Kahn, PhD

  • Associate Professor of Neuroscience (in the Mortimer B. Zuckerman Mind Brain Behavior Institute)
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Overview

Education and Training

• BS, 1997 Mathematics and Computer Science, Ben-Gurion University, Israel

• PhD, 2005 Neuroscience, Massachusetts Institute of Technology

• Post-doctoral training, 2010 Harvard University

Academic Appointments

  • Associate Professor of Neuroscience (in the Mortimer B. Zuckerman Mind Brain Behavior Institute)

Gender

  • Male

Research

Over the past two decades the most important revolution in human brain research took place due to the availability of non-invasive imaging methods allowing to evaluate the structure and function of the brain. Structural imaging using magnetic resonance imaging (MRI) allows us to assess structural changes that occur as the brain develops when we are young and deteriorate as we age. When disease processes attack the brain, atrophy or other structural changes occurs at a rapid rate. MRI allows us to precisely assess these changes. Further, it is now possible to measure the activity of brain cells using functional MRI (fMRI). Brain cells compute and communicate using electrical signals. This activity requires oxygen, the brain’s energy source, and the intricate and precise supply of oxygen to the brain can be measured with fMRI, providing us a map of brain activity.

In the lab we seek to understand the relation between the brain’s structure and function in health and disease, with focus on the biology of learning and memory. We aspire to understand how brain structure and activity give rise to various aspects of behavior. To that end, we use fMRI in humans and mice to understand the basic principles of brain function as well as detect brain regions that are not working normally, follow them carefully and try novel first-in-class therapeutic approaches to alleviate brain disorders.

We measure activity in multiple brain systems simultaneously, looking at the interactions between regions of the brain. We attempt to characterize changes in activity that can be used to identify populations or individuals at risk. Namely, we look for changes that precede and predict diseases. In doing so we open a time window for prevention and/or early therapeutic intervention programs that may benefit people that seem to be on a trajectory to develop a brain disorder.

Lab website:

https://zuckermaninstitute.columbia.edu/itamar-kahn-phd

 

Selected Publications

1. Lichtman D.,  Bergmann E., Kavushansky A., Cohen N., Levy N. S., Levy A. P., and Kahn I. (2021). Structural and Functional Brain-wide Alterations in A350V IQSEC2 Mutant Mice Displaying Autistic-like Behavior. Translational Psychiatry 11:181, doi:10.1038/s41398-021-01289-8.

2. Bergmann E., Gofman X., Kavushansky A., and Kahn I. (2020). Individual variability in functional connectivity architecture of the mouse brain. Communications Biology 3:738, doi:10.1038/s42003-020-01472-5. 

3. Asleh J.*, Shofty B.*, Cohen N., Kavushansky A., Lopez-Juarez A., Constantini S., Ratner N., and Kahn I. (2020). Brain-wide structural and functional disruption in mice with oligodendrocyte-specific Nf1 deletion is rescued by inhibition of nitric oxide synthase. Proceedings of the National Academy of Sciences of the United States of America 117 (36):22506–22513, doi:10.1073/pnas.2008391117. *equal authorship 


4. Melozzi F.*, Bergmann E.*, Harris J. A., Kahn I.#, Jirsa V.#, and Bernard C.# (2019). Individual structural features constrain the mouse functional connectome. Proceedings of the National Academy of Sciences of the United States of America, 116 (52):26961–26969, doi:10.1073/pnas.1906694116. *equal authorship #equal senior authorship

5. Shofty B.*, Bergmann E.*, Zur G., Asleh J., Bosak N., Kavushansky A., Castellanos F. X., Ben-Sira L., Packer R. J., Vezina G., Constantini S., Acosta M. T., and Kahn I. (2019). Autism-associated Nf1 deficiency disrupts corticocortical and corticostriatal functional connectivity in human and mouse. Neurobiology of Disease (130), 104479, doi:10.1016/j.nbd.2019.104479. *equal authorship 

6. Amirav L., Berlin S., Olszakier S., Pahari S. K., & Kahn I. (2019). Multi-modal Nano Particle Labeling of Neurons. Frontiers in Neuroscience, doi: 10.3389/fnins.2019.00012. 

7. Pahari S., Olszakier S., Kahn I., & Amirav L. (2017). Magneto-Fluorescent Yolk-Shell Nanoparticles. Chemistry of Materials, 30, 3, 775–780, doi:10.1021/acs.chemmater.7b04253. 

8. Siman-Tov T., Bosak N., Sprecher E., Paz R., Eran A., Aharon-Peretz J., & Kahn I. (2016). Early Age-Related Functional Connectivity Decline in High-Order Cognitive Networks. Frontiers in Aging Neuroscience 8:330, doi:10.3389/fnagi.2016.00330. 

9. Bergmann E., Zur G., Bershadsky G., & Kahn I. (2016). The Organization of Mouse and Human Cortico-Hippocampal Networks Estimated by Intrinsic Functional Connectivity. Cerebral Cortex 26(12):4497–4512, doi:10.1093/cercor/bhw327. 

10. Gerraty R.T., Davidow J.Y., Wimmer, G.E., Kahn I., & Shohamy D. (2014). Transfer of Learning Relates to Intrinsic Connectivity between Hippocampus, Ventromedial Prefrontal Cortex, and Large-Scale Networks. Journal of Neuroscience 34(34): 11297–11303. 

11. Kahn I.*, Knoblich U.*, Desai M., Bernstein J., Graybiel A.M., Boyden E.S., Buckner R.L., & Moore C.I. (2013). Optogenetic Drive of Neocortical Pyramidal Neurons Generates fMRI Signals That Are Correlated with Spiking Activity. Brain Research 1511:33–45.*equal authorship 

12. Kahn I. & Shohamy D. (2013). Intrinsic Connectivity between the Hippocampus, Nucleus Accumbens and Ventral Tegmental Area in Humans. Hippocampus 23:187–192. 

13. Kahn I.*, Desai M.*, Knoblich U.*, Bernstein J., Henninger M., Graybiel A. M., Boyden E.S., Buckner R.L., & Moore C.I. (2011). Characterization of the Functional MRI Response Temporal Linearity via Optical Control of Neocortical Pyramidal Neurons. Journal of Neuroscience 31:15086-15091. *equal authorship 

14. Desai M.*, Kahn I.*, Knoblich U., Bernstein J., Atallah H., Yang A., Kopell, N., Buckner R.L., Graybiel A. M., Moore C. I., & Boyden E. S. (2011). Mapping Brain Networks in Awake Mice using Combined Optical Neural Control and fMRI. Journal of Neurophysiology 105: 1393–1405. *equal authorship

For a complete list of publications, please visit Google Scholar (link: https://scholar.google.com/citations?user=cHhK0DQAAAAJ&hl=en&oi=ao)