Yashar Ahmadian

Affiliations: 
2007-2010 Statistics Columbia University, New York, NY 
 2011-2014 Neuroscience Columbia University, New York, NY 
 2015- Biology University of Oregon, Eugene, OR, United States 
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"Yashar Ahmadian"
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Publications

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Hennequin G, Ahmadian Y, Rubin DB, et al. (2018) The Dynamical Regime of Sensory Cortex: Stable Dynamics around a Single Stimulus-Tuned Attractor Account for Patterns of Noise Variability. Neuron. 98: 846-860.e5
Ahmadian Y, Fumarola F, Miller KD. (2015) Properties of networks with partially structured and partially random connectivity. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 91: 012820
Ahmadian Y, Fumarola F, Miller KD. (2015) Properties of networks with partially structured and partially random connectivity Physical Review E - Statistical, Nonlinear, and Soft Matter Physics. 91
Ahmadian Y, Rubin DB, Miller KD. (2013) Analysis of the stabilized supralinear network. Neural Computation. 25: 1994-2037
Vidne M, Ahmadian Y, Shlens J, et al. (2012) Modeling the impact of common noise inputs on the network activity of retinal ganglion cells. Journal of Computational Neuroscience. 33: 97-121
Pitkow X, Ahmadian Y, Miller KD. (2011) Learning unbelievable probabilities. Advances in Neural Information Processing Systems. 24: 738-746
Ahmadian Y, Packer AM, Yuste R, et al. (2011) Designing optimal stimuli to control neuronal spike timing. Journal of Neurophysiology. 106: 1038-53
Ramirez AD, Ahmadian Y, Schumacher J, et al. (2011) Incorporating naturalistic correlation structure improves spectrogram reconstruction from neuronal activity in the songbird auditory midbrain. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 31: 3828-42
Ahmadian Y, Pillow JW, Paninski L. (2011) Efficient Markov chain Monte Carlo methods for decoding neural spike trains. Neural Computation. 23: 46-96
Pillow JW, Ahmadian Y, Paninski L. (2011) Model-based decoding, information estimation, and change-point detection techniques for multineuron spike trains. Neural Computation. 23: 1-45
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