Contact ZIPS organizers at [email protected] for the Zoom link.

Deconstructing the neural circuits of stress-susceptibility and stress-resiliency in mice
Featuring Kristin Anderson (Dumitriu Lab)

Preventable mental and physical illnesses, such as depression, rank amongst the most disruptive disorders worldwide. While stressful events often lead to depression, not all individuals are susceptible and some remain resilient even when facing severe stress. We aim to understand what mediates this stress-susceptibility and resiliency. To tackle this, we use rodent models of social stressors to uncover any preexisting neurocircuit differences that are present prior to stress exposure and how such differences may lead to the individual variability seen following stress. In concordance with the movement towards ‘circuit psychiatry’, we are also developing an open-science platform, MouseCircuits.org.

Motion estimation and registration of Neuropixel data
Featuring Erdem Varol (Paninski Lab)

Multi-electrode arrays are essential electrophysiological tools for studying the voltage signal of individual neurons across arbitrary regions of the brain. Chronic recordings of neural activity using these devices may experience the shifting of the probe due to movement, breathing, or blood flow of animals, resulting in poorly localized voltage readings. Recently, highly dense probes, termed Neuropixels, with hundreds of regularly spaced electrodes have been introduced, allowing to record the neural voltages in a manner resembling image pixels. We utilize this platform to introduce a technique to register the signal that may have been subjected to motion. Our technique involves representing the signal as time-binned spatial-histograms whose relative displacements are estimated using a template-free decentralized approach. We study the performance of our registration technique over a template-based approach and show that our decentralized technique is more sensitive towards capturing subtle as well as large amounts of motion. Furthermore, we demonstrate that our proposed registration technique improves the yield of spike detection and sorting.