Ila R Fiete

Ila Fiete is an Indian–American physicist and computational neuroscientist as well as a Professor in the Department of Brain and Cognitive Sciences within the McGovern Institute for Brain Research at the Massachusetts Institute of Technology. Fiete builds theoretical models and analyses neural data and to uncover how neural circuits perform computations and how the brain represents and manipulates information involved in memory and reasoning.

Early life and education Fiete was born in Mumbai, India. Her parents, Gopal Prasad and Indu Devi, moved to Michigan in 1992. She pursued her undergraduate studies at the University of Michigan, majoring in mathematics and physics. Fiete then moved to Boston to pursue her master's degree and graduate studies at Harvard University in the Department of Physics. and in physics by Daniel Fisher at Harvard. In her graduate degree, Fiete explored the principles of learning and coding in biological neural networks. Fiete is married to Greg Fiete, Professor of Physics at Northeastern University. Her brother Anoop Prasad, trained as a theoretical physicist, is Managing Director and Head of the Equities Group at D.E. Shaw & Co.

Fiete completed her graduate studies in 2003, and moved across the country to hold an appointment as a postdoctoral fellow at the Kavli Institute for Theoretical Physics at the University of California, Santa Barbara from 2004 until 2006.

Graduate Work - Coding in Biological Neural Circuits During her graduate studies, Fiete and her colleagues used linear networks of learning to show that sparse temporal neural codes minimize synaptic interference and facilitate learning in songbirds. Fiete then began to explore the computational principles underlying synaptic plasticity.

Grid Cells When Fiete started her postdoctoral research, she began to study the coding principles of cells in the brain that encode location. In 2006, Fiete and her colleagues described a framework to understand the computations of grid cells in the entorhinal cortex, and how they encode the positions of rats. This hypothesis is very different from others of how coding is performed in the brain, and this "arithmetic-friendly" numeral system highlights the ingenuity of neural codes. After serving on the faculty for 10 years and founding the Center for Theoretical and Computational Neuroscience there, in 2018 Fiete accepted an offer from the Massachusetts Institute of Technology and became an associate professor with tenure within the Department of Brain and Cognitive Sciences. Her lab uses numerical and theoretical modelling as well as raw neural data with which to test their models of brain computations. With inputs signifying the velocity and heading direction of the animal, continuous attractor models can generate triangular grid responses that encode updated estimates of location in two-dimensional spaces. They further show, with a proof of concept, that continuous attractor dynamics underlie the integration of velocity in grid cells. Their model, relying on low-dimensional continuous attractor dynamics, reliably characterized grid cell responses in short duration, familiar enclosures. In the beginning, their model depicts initially unstructured networks of neurons spiking to velocity and location inputs. Using the grid cell system, which Fiete had extensively probed and serves as a good system for testing computational models, Fiete showed that the "distribution of relative phase shifts" model has the potential to reveal highly detailed cortical circuit mechanisms from sparse neural recordings. This ring-like spatial representation of neural activity has been shown in flies to underlie head direction, and now, by Fiete, has been shown to represent head direction in mice - like an internal compass. Its shape and dimensionality represent the data in a more interpretable way. 2013 CNS Excellence Award for Teaching - College of Natural Sciences University of Texas at Austin 2013 Office of Naval Research Young Investigator 2010 Searle Scholar 2009 Alfred P. Sloan Foundation Fellow in Neuroscience