Plexon Research Spotlight

Steve W. C. Chang, Ph.D.

Assistant Professor, Yale University

Steve Chang Yale


What type of neuroscience research do you do and what got you interested in this research? 

I found social cognition fascinating as it demands contingent and dynamic computations, not only with respect to ourselves but also with respect to other complex individuals. Our primary research goal is to better understand the neural mechanisms underlying social behaviors.

We approach this question from multiple angles, including spiking and local field potential recordings, and neuropharmacological manipulations, frequently during real-life social interactions. Several research projects in the lab focuses on how decision variables with respect to self and other are computed in the prefrontal and amygdala circuits. Another growing line of inquiry investigates how the prefrontal cortex and the amygdala represent fascinating dynamics underlying social gaze interactions. 

What challenges did you encounter along the way, and how did you overcome these challenges?

In studying the neurobiological mechanisms underlying social interactions in a laboratory, it is important to ensure that what you study captures, as best it can within obvious limitations, the core neural processes that are used in real-life settings.

Accommodating this, especially when it comes to electrophysiology, requires an intricate balance between experimental control and ecological validity. Our solution has been to implement behavioral paradigms involving another individual that can be quantified and modeled while minimizing experimental confounds.

What new technique do you think will have the greatest impact on neuroscience research and how do you plan to apply this to your research?

Because of my interests in contingent and dynamic social behaviors and inter-regional communications in the brain in general, neurobiological techniques that are geared to providing reliable signals from multiple brain areas that can be coupled with high resolution behavioral monitoring will be extremely valuable. In particular, I am very much looking forward to learning more about the similarities and differences in neuronal dynamics underlying higher-order cognition across task-confined versus task-free situations.

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