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Our lab's research is in theoretical neuroscience. Our broad interest is in understanding how large networks of neurons, e.g. those in the mammalian cerebral cortex, process sensory inputs and give rise to higher-level cognitive functions through their collective dynamics on multiple time scales. To shed light on the complexity of neurobiological phenomena we use mathematical models that capture a few core concepts or computational and dynamical principles. We also work on developing new statistical and computational tools for analyzing large, high-dimensional neurobiological and behavioral datasets. In pursuing these goals we use techniques from statistical physics, random matrix theory, machine learning and information theory. We collaborate with experimental labs here in the University of Oregon and elsewhere.

Current questions of interest include the following.

  • How do randomness and nonnormality in the connectivity structure of networks affect their dynamics?
  • How do the horizontal and feedback connections in sensory cortical areas shape their intrinsic dynamics, and how does this internal dynamics interact with incoming sensory inputs?
  • What is the role of recurrent connections in ubiquitous cortical computations like contextual modulation (how the response of neurons is affected by the sensory context of driving stimuli their receptive fields)? What is their role in shaping temporally stable perceptions given fast changing, ambiguous and noisy inputs?

We will approach these question from both the bottom-up/mechanistic level, but also from the top-down or normative level informed by the hypothesized computational goals of the system in question.


Google scholar profile


  1. Y. Ahmadian, F. Fumarola, and K. D. Miller (2015). Properties of networks with partially structured and partially random connectivity. Phys. Rev. E 91, 012820. [link]
  2. Y. Ahmadian, D. B. Rubin, and K. D. Miller (2013). Analysis of the stabilized supralinear network. Neural Computation, 25, 19942037. [link]
  3. M. Vidne, Y. Ahmadian, J. Shlens, J. Pillow, J. Kulkarni, A. Litke, E.J. Chichilnisky, E. Simoncelli, and L. Paninski (2012). Modeling the impact of common noise inputs on the network activity of retinal ganglion cells. Journal of Computational Neuroscience, 33(1), 97-121.
  4. X. Pitkow, Y. Ahmadian and K.D. Miller (2011). Learning unbelievable marginal probabilities. Advances in Neural Information Processing Systems (NIPS), 738-746. [link]
  5. Y. Ahmadian, A. Packer., R. Yuste, and L. Paninski (2011). Designing optimal stimuli to control neuronal spike timing. Journal of Neurophysiology, 106(2), 1038-1053. [link]
  6. A. D. Ramirez, Y. Ahmadian, J. Schumacher, D. Schneider, S. M. N. Woolley, and L. Paninski (2011). Incorporating naturalistic correlation structure improves spectrogram reconstruction from neuronal activity in the songbird auditory midbrain, Journal of Neuroscience, 31(10):3828-3842. [link]
  7. Y. Ahmadian, J. Pillow and L. Paninski (2011), Efficient Markov Chain Monte Carlo Methods for Decoding Neural Spike Trains, Neural Computation, 23(1), 46-96. [pdf]
  8. J. Pillow, Y. Ahmadian and L. Paninski (2010), Model-based decoding, information estimation, and change-point detection in multi-neuron spike trains, Neural Computation, 23(1), 1-45. [link]
  9. Edmund C. Lalor, Yashar Ahmadian, and Liam Paninski (2009), The relationship between optimal and biologically plausible decoding of stimulus velocity in the retina, JOSA A, Vol. 26, B25-B42. [link]
  10. L. Paninski, Y. Ahmadian, D.G. Ferreira, S. Koyama, K. Rahnama Rad, M. Vidne, J. Vogelstein and W. Wu (2009), A new look at state-space models for neural data, J. Comp. Neuro. Sci., 29, 107-126. [link]


  1. F. Fumarola, Y. Ahmadian, I. L. Aleiner and B. L. Altshuler, Negative echo in the density evolution of ultracold fermionic gases, Phys. Rev. Lett. 99, 020403 (2007). [link]
  2. Y. Ahmadian and I.L. Aleiner,Antilocalization in Coulomb blockade, Phys. Rev. B 73 073312 (2006). [link]
  3. Y. Ahmadian, G. Catelani and I.L. Aleiner, Spin related effects in transport properties of open quantum dots, Phys. Rev. B 72, 245315 (2005). [link]
  4. E. Henriksen, S. Syed, Y. Ahmadian, M. Manfra, K. Baldwin, A. Sergent, R. Molnar, and H. Stormer, Appl. Phys. Lett. 86, 252108 (2005). [link]
Page last modified on September 08, 2016, at 11:31 AM