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BIOGRAPHY

I completed my Ph.D. in computational neuroscience at Freie Universität Berlin2011. My primary research interest areas are theoretical neuroscience and the stochastic analysis of neural network dynamics. My research seeks to answer how biological neural networks exhibit reliable spatiotemporal scales in the face of noisy processes that underlie the dynamics. My studies are based on statistical mechanics, the theory of stochastic systems, and the physics of non-linear dynamical systems.

PUBLICATIONS

Farkhooi F, Stannat W: Complete Mean-Field Theory for Dynamics of Binary Recurrent Networks, Physical Review Letters 119 (20), 208301.

Engelken R*, Farkhooi F*, Hansel D, van Vreeswijk C, Wolf F: A reanalysis of “Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons”, F1000Research 5.

Farkhooi F, van Vreeswijk C: Renewal approach to the analysis of the asynchronous state for coupled noisy oscillators, Physical review letters 115 (3), 038103.

Meckenhäuser G, Krämer S, Farkhooi F, Ronacher B, Nawrot MP: Neural representation of calling songs and their behavioral relevance in the grasshopper auditory system, Frontiers in systems neuroscience 8, 183.

Farkhooi F, Froese A, Muller E, Menzel R, Nawrot MP: Cellular adaptation facilitates sparse and reliable coding in sensory pathways, PLoS computational biology 9 (10), e1003251.

Farkhooi F, Muller E, Nawrot MP: Adaptation reduces variability of the neuronal population code, Physical Review E 83 (5), 050905.

Nawrot MP, Krofczik S, Farkhooi F, Menzel R: Fast dynamics of odor rate coding in the insect antennal lobe, arXiv preprint arXiv:1101.0271.

Farkhooi F, Strube-Bloss MF, Nawrot MP: Serial correlation in neural spike trains: experimental evidence, stochastic modeling, and single neuron variability, Physical Review E 79 (2), 021905.

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