Omri Barak

PhD in Computational Neuroscience
Weizmann Institute of Science
Dissertation topic: Working Memory in Recurrent Neural Networks with Dynamic Synapses.

After his PhD, Omri spent time in New York doing postdoctoral research at Columbia University's Center for Theoretical Neuroscience. His research focused on studying the way populations of neurons represent cognitive tasks. Recordings from single neurons of animals performing cognitive tasks can show meaningful correlations to the task at hand, even though an entire network of neurons is responsible for the behavior. Using computational models of neural networks, Omri worked to tease apart the contribution of single cells from that of the population as a whole.
Omri has recently returned to Israel with his family and now holds a Senior Lecturer position in the Faculty of Medicine at the Technion.

A personal perspective:
In Omri's words: “ I enjoyed meeting the Azrieli Fellows, who come from diverse backgrounds. It was an opportunity to get a glimpse of fascinating research outside of my field.” 

Journals:

Barak O, Rigotti M. A simple derivation of a bound on the Perceptron margin using Singular Value Decomposition. Neural Computation. (In press)

Barak O, Tsodyks M, Romo R. 2010. Neuronal population coding of parametric working memory. J Neuroscience Jul 14; 30 (28): 9424-30.

• Melamed O, Barak O, Silberberg G, Markram H, Tsodyks M. 2008. Slow oscillations in neural networks with facilitating synapses. J Comput Neurosci Oct; 25 (2): 308-16. (Epub 2008 May 16)

• G. Mongillo*, O. Barak* & M. Tsodyks.  2008. Synaptic theory of working memory. Science Mar 14; 319 (5869): 1543-6 (* equal contribution).

O. Barak & M. Tsodyks. 2007. Persistent activity in neural networks with dynamic synapses. PLoS Comput Biol. Feb 23; 3 (2): 0323-0332.

• Mokeichev A., Okun M., Barak O., Katz Y., Ben-Shahar O., Lampl, I. 2007. Stochastic emergence of repeating cortical motifs in spontaneous membrane potential fluctuations in-vivo. Neuron Feb 1; 53 (3): 413-25.

O. Barak & M. Tsodyks. 2006. Recognition by Variance: Learning Rules for Spatiotemporal Patterns. Neural Computation 18 (10): 2343-58.

• Szwed M., Bagdasarian K., Blumenfeld B., Barak O., Derdikman D. and Ahissar E. 2006. Responses of trigeminal ganglion neurons to the radial distance of contact during active vibrissal touch. J Neurophysiol Feb; 95 (2): 791-802.