Publications

In this study we provide one of the first multi-variate methodology for investigating spike-LFP coupling, that allow us to connect neural activity to population dynamics. The method accompanied with large body of biophysical simulation, as well as analysis of prefrontal recurrent circuitry.

In this study, we probe the connection between the optimality discussed in the context of criticality hypothesis of the brain (that very much tied to neural dynamics), and the optimality discussed in theories of neural computations. We examine an efficient coding network for signatures of criticality and we find signatures of criticality emerging in a network that was designed based on criticality-agnostic principles merely by optimizing the coding performance. This suggests criticality and efficient coding might be intimately related.

Based on a large collection behavioral and neural data, we introduce a radically new perspective to the well-known phenomenon of perceptual multistability. We formulated the phenomenon as a value-based decision-making process that not only synergies with previous accounts, but also offers a more comprehensive treatment of computational and algorithmic facets of perceptual multistability.