Watson Lab

Cortical circuits and Psychiatry

Brendon Watson M.D., Ph.D.

University of Michigan

Seeking: One highly qualified postdoctoral fellow

We seek a postdoctoral fellow to perform combined behavior and electrophysiology in rodents chronically in their homecages, with the goal of determining electrophysiologic correlates of stress and antidepressant treatment.

Our lab expertise is in electrophysiology and brain network function. In this project, we combine that with a novel system we have developed to record from animals over weeks in their homecages. This recording system classifies behavior at sub-second resolution while allowing multi-region electrophysiologic recordings simultaneously. In this study we will use this powerful system to study the effects of chronic stress on the electrophysiology of limbic system circuitry. We will also study how subsequent ketamine acts on those same circuits to potentially reverse stress effects.

We seek experimentalists with a PhD and expertise in in vivo electrophysiology and behavior with an interest in the neurobiology of mood-related circuits. Coding experience is preferred. We will work in collaboration with the machine learning group of Dr. Ivaylo Dinov.

We are at the University of Michigan in Ann Arbor, in the department of psychiatry and this project will be NIH funded. Positions will begin as early as July 1, 2021 and are funded for 1 year at the standard NIH postdoctoral fellow payscale with option to extend if it is mutually agreeable to both lab director and fellow.

The Watson Lab is committed to making neuroscience a more open and inclusive field, so we strongly encourage applications from individuals with non-traditional backgrounds or from underrepresented groups.

Interested applicants please reply to brendonw@umich.edu, Please include CV, letter of intent/summary of background and copies of published articles relevant to your application.

Focus: Brain and cortical network dynamics

Basic function in normal brain and role in psychiatric disease

We use electrophysiology and optogenetics to observe and manipulate dozens of neurons simultaneously in both head-fixed and freely-behaving rodents in order to answer questions aimed both at fundamental neurobiological understanding of the cortical states and dynamics as well as the role of cortex in disease.

We use an approach informed by an understanding of neuronal microcircuit dynamics, macrocircuit connectivity and organism-level behavior to connect between the level of single neurons, networks of those neurons and animal behavior.

See further details in Research section.

Recent work

We propose that the neocortical populations have a constant "backbone" element to their sequence as well as a proportion of neurons with maleable timing. These stable and maleable aspects may have differential roles. The stable firing sequence may play a role in network homeostasis while the variable element may related to information "coding".

Why and how is the field of rodent ketamine research yielding such variable results. How can we interpret that variance?

Only stressed mice show antidepressant-like response to ketamine. Unestressed ones actually show an opposite response. See Paul Fitzgerald and Jessica Yen's paper here: Link

How neuronal activity changes during sleep and wake: An integrative and statistically-controlled re-analysis of data from neocortex and hippocampus

What we know about how antidepressants work at an electrophysiologic level

A minutes-timescale rhythm of the brain that dictates brain function and performance: What do we know about it already?

Might gamma oscillations be biomarkers for depression? What is the current state of the field in both patients and rodent models.

How field potential oscillations and neuronal firing rates are correlated time in the frontal cortex in rodent recordings.

Review article putting forward novel ideas about the role of learning rules in sculpting activity of cortical neuronal populations over wake-sleep cycles

Cortical neuronal firing rates are dynamically modulated over sleep wake cycles without novel learning tasks.