Research
We work on theoretical and computational problems in neuroscience and biophysics. In particular, we are interested in understanding how neural feature selectivity is influenced by, and to what extent is determined by, the statistics of real-world inputs. One of our long-term goals is to understand how invariant feature selectivity is achieved in cortex.
Research Topics
- Sensory Perception:
- Vision
- Audition
- Adaptation
- Optimal Neural Coding:
- Receptive field adaptation
- Multidimensional nonlinearities
- Error-correction
- Compensatory irregularities
- Computational Tools:
- Maximally Informative Dimensions
- Characterizing Feature Selectivity with Invariance
- Minimal models of nonlinear computations
