I work on the theory and modeling of neural systems where the collective behavior is rich, but where underlying features such as single-neuron properties and local connectivity are constrained by experiment. My aims are to help (1) Elucidate the essential dynamical principles underlying emergent motor and sensorimotor function, (2) Understand principles of the encoding and decoding of neural information based on system function, and (3) Drive fruitful interactions between theory and experiment by generating non-trivial predictions for neural organization, activity, and synaptic plasticity. Ongoing and recent projects investigate:

• Navigation and idiothetic path integration in rats: dynamical modeling, precision and robustness
• Analysis of position codes in rat entorhinal cortex: properties and readouts
• Emergence of sequential neural activity (synaptic chains) in neural networks
• General rules for goal-directed (gradient) learning in recurrent networks
• Sensorimotor song learning in songbirds
• Sparse codes and learning in feedforward neural networks

 

• Y. Burak and I. R. Fiete. Accurate path integration in continuous attractor network models of grid cells. PLoS Comp. Biol. 5(2) (2009). (pdf)
   
• M. Murthy, I. R. Fiete, and G. Laurent. Testing odor response stereotypy in the Drosophila mushroom body. Neuron 59(6):1009-23 (2008). (link)
   
• I. R. Fiete and H. S. Seung. Neural network models of birdsong production, learning, and coding. In New Encyclopedia of Neuroscience. Eds L. Squire, T.Albright, F. Bloom, F.Gage, and N. Spitzer. Elsevier ( In Press, 2009). (pdf)
   
• P.E. Welinder, Y. Burak and I. R. Fiete. Grid cells: The position code, neural network models of activity, and the problem of learning. Hippocampus 18(12):1283-300 (2008).
   
• I. R. Fiete, Y. Burak and T. Brookings. What grid cells encode about rat position. J. Neuroscience 28, 6856-6871 (2008). (pdf)
  
        Related: T. Brookings, Y. Burak and I. R. Fiete. Triangular lattice neurons (grid cells) may encode rat position using an
        advanced numeral system. Preprint at: arxiv.org, q-bio.NC/0606005 (2006). (pdf)
   
• I. R. Fiete, M.S. Fee and H. S. Seung. Model of birdsong learning based on gradient estimation by dynamic perturbation of neural conductances. J. Neurophysiology 98, 2038-2057 (2007). (pdf)
   
• Y. Burak and I. R. Fiete. Do we understand the emergent dynamics of grid cell activity? J. Neuroscience 26, 9352-9354 (2006). (pdf)
   
• I. R. Fiete and H. S. Seung. Gradient learning in spiking neural networks by dynamic perturbation of conductances. Physical Review Letters 97, 048104 (2006). (pdf)
   
• I. R. Fiete, R.H.R Hahnloser, M.S. Fee and H. S. Seung. Temporal sparseness of the premotor drive is important for rapid learning in a neural network model of birdsong. J.Neurophysiology 92, 2274 (2004). (pdf)
   
• I. R. Fiete. Learning and coding in biological neural networks. Ph.D. Thesis, Harvard University (2004).
   
• S. Sullow, I.R. Prasad, M.C. Aronson et al. Metallization and magnetic order in EuB_6. Physical Review B 62, 11626 (2000). (pdf)
   
• S. Sullow, I.R. Prasad, S. Bogdanovich et al. Magnetotransport in the low carrier density ferromagnet EuB_6. J. Applied Physics 87, 5591 (2000). (pdf)
   
• S. Sullow, I.R. Prasad, M.C. Aronson et al. Magnetic order of EuB_6. Physical Review B 57, 5860 (1998). (pdf)
   

Sloan Fellow:             Alfred P. Sloan Foundation    (2009)
Assistant Professor:    Center for Learning and Memory, University of Texas at Austin (Fall 2008)
Broad Fellow:           Broad Fellows program in Brain Circuitry:, California Institute of Technology (Fall 2006- Fall 2008)
Postdoc:                    Kavli Institute for Theoretical Physics, UCSB (2004-2006)
Ph.D.                         Physics, Harvard University (Dec 2003)
M.A.                          Physics, Harvard University (2000)
B.S.                            Physics and Mathematics, University of Michigan (1997)

Ila Varma: Junior in Mathematics and Computer Science, Caltech.
Peter Welinder: Graduate student in Center for Neural Systems, Caltech.
Ni Ji: Graduate student in Brain and Cognitive Sciences, MIT.
Ted Brookings: Postdoctoral fellow at Volen Center, Brandeis.
Prashant Joshi: Postdoctoral fellow at FIAS, Frankfurt.
Sameet Sreenivasan: Postdoctoral fellow, UT Austin.