Research wish

I would like to understand the brain in a principled way (if possible). In other braches of science like physics and chemistry (and to some degree biology) a general principle often can capture the essence of the phenomena. I have been curious whether we can find such principles in neuroscience that will allow explaining important aspects of brain functions (e.g. what makes the brain computationally powerful and adaptive, how it encodes sensory information so efficiently). The “searching for principles” endeavor in neuroscience and perhaps broader in Biophysics led to a fundamental and quantitative understanding of some basics/fundamentals of brain function. This was (and still is) an intriguing window for me to understand the brain. What I’m still missing is cognition.

In the process of searching for missing pieces, l have developed an interest in understanding the principles which their failure leads to brain dysfunction. In other words, now I find it more interesting to understand the principles of brain function and dysfunction. In particular, I developed an interest in psychiatric disorders, as they are reminiscent of dysfunction of cognitive capabilities.

As far as I understand the field of Computational Psychiatry (CP), there are three main branches or approaches in this field. In the first branch, people try to model the dynamics of the pathological brain. These models are biologically plausible (of course up to some approximation) and they are usually close to implementation [referring to Marr’s third level of analysis]. In the second branch, people try to explain the behavior [typically] with normative models. I found them intriguing because they explicitly take into account the computation that brain presumably is doing. In the third branch, people try to extract meaningful patterns in different kinds of data collected from patients and healthy subjects. They typically use tools developed in machine learning.

I found all 3 approaches interesting, and in particular, I’m curious to develop models that have an explicit notion of impaired computation involved in a given psychiatric disorder and to be close to biological realism or at least the model should be able to provide some hints on the biological implementation (sort of establishing a bridge between branch 1 and 2).

Current and past research

Perhaps it was too much writing about scientific wishes, let me tell you a bit about the research I’ve done and been doing. Currently, I’m working on two computational neuroscience projects, I’m working toward establishing two bridges and I used to do NHP electrophysiology.

Bridge 1: I’m trying to establish a bridge between different scales by exploiting the cooperative neural activities. I’m mainly developing methods to explore the relationship between signals recorded in different modalities (that reflects activity in different scales), namely spikes, LFP, and BOLD. I should mention that I’m not trying to find transfer functions, for example, get spikes and give LFP back. I’m trying to exploit the cooperative dynamics of the network to find the temporal epochs that are likely to reflect interactions across scales.

Bridge 2: I’m trying to bridge computation and dynamics in a network of Leaky-Integrate and Fire (LIF) neurons. More specifically, I’m trying to explore if there are signatures of criticality in efficient coding networks. Criticality has a lot to do with network dynamics and efficient coding with computation (if you are curious to know more, check our recent abstract). If one finds a connection between these two, one might have a smoother way to establish the bridge between computation and dynamics in the network.

I have also spent a big portion of my PhD in understanding neural mechanisms involved in conscious visual perception. The involvement of PFC in visual awareness has been controversial [at least] since 2014, perhaps one of the papers which emphasize the discrepancy between results based on fMRI and NHP electrophysiology was our opinion paper. To help the resolution of this discrepancy we have done electrophysiology experiments with NHP performing binocular rivalry task. Check these 2 preprints to learn more about the results,