Farzad Farkhooi
Affiliations: | 2015- | Institut für Mathematik | Technische Universität Berlin, Berlin, Berlin, Germany |
Area:
Point process and spiking recurrent networkWebsite:
https://www.math.tu-berlin.de/fachgebiete_ag_stochfinanz/fg_mathematische_stochastik_stochastische_prozesse_in_den_neurowissenschaften/v_menue/mitarbeiter/farzad_farkhooi/farzad_farkhooi/Google:
"Farzad Farkhooi"Mean distance: 14.41 (cluster 17) | S | N | B | C | P |
Parents
Sign in to add mentor| Wilhelm Stannat | grad student | 2015- | TU Berlin | |
| Randolf Menzel | grad student | 2006-2009 | FU Berlin | |
| (Grad Student) | ||||
| Martin Paul Nawrot | grad student | 2007-2011 | FU Berlin | |
| Carl van Vreeswijk | post-doc | 2013-2015 | ||
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Publications
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| van Vreeswijk C, Farkhooi F. (2019) Fredholm theory for the mean first-passage time of integrate-and-fire oscillators with colored noise input. Physical Review. E. 100: 060402 |
| Farkhooi F, Stannat W. (2017) Complete Mean-Field Theory for Dynamics of Binary Recurrent Networks. Physical Review Letters. 119: 208301 |
| Engelken R, Farkhooi F, Hansel D, et al. (2016) A reanalysis of "Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons". F1000research. 5: 2043 |
| Farkhooi F, van Vreeswijk C. (2015) Renewal Approach to the Analysis of the Asynchronous State for Coupled Noisy Oscillators. Physical Review Letters. 115: 038103 |
| Meckenhäuser G, Krämer S, Farkhooi F, et al. (2014) 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, et al. (2013) Cellular adaptation facilitates sparse and reliable coding in sensory pathways. Plos Computational Biology. 9: e1003251 |
| Farkhooi F, Muller E, Nawrot MP. (2011) Adaptation reduces variability of the neuronal population code. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 83: 050905 |
| Farkhooi F, Strube-Bloss MF, Nawrot MP. (2009) Serial correlation in neural spike trains: experimental evidence, stochastic modeling, and single neuron variability. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 79: 021905 |