Roozbeh Farhoodi


(312) 721-4271
RIC 1479


Roozbeh is fourth-year Ph.D. student at Sharif University of Technology, working on applied mathematics and neuroscience and joined the lab from October 2015 as a visiting scholar. His backgrounds in mathematics are stochastic analysis, probability and computational topology.

Ongoing projects

- Localization and classification of neurons with high-density electrode arrays

E.L. Dyer, R. Farhoodi, M. Azar, and K.P. K├Ârding

Electrical recordings have been the primary means by which neuroscientists have studied the function of neural systems. However, multi-electrode arrays are usually assumed to provide little information about the location and morphology of neurons. With recent advances in the design of high-density electrode arrays, this begs the question of whether electrical recordings can be converted into multi-dimensional images of neural activity. By imaging, we mean that we can obtain a picture of a neuron that provides a glimpse into the location and shape of neurons and time-varying activity. As such, the possibility of electrical imaging methods will open up a broad range of new applications for electrical recording.

- Emergent of Cross Frequency in network of neurons

R. Farhoodi, A.H.Abbasian, M. Fotouhi

It is widely known that cross frequency couplings in brain activity may result from interacting physiological processes. Among these couplings the phase amplitude couplings is by far the most studied as for example, the theta-gamma rhythm in the hippocampus .Although a common starting point is the observed spectral correlations based on the recorded neural activity there is as yet no consensus on the exact mechanism of such dynamical interactions. In this project we search for a rigorous mathematical formulation to link properties of a network of neurons to its nested oscillations