Erlich Lab / Research

Erlich Lab Research Projects

  • Mapping decision-coding in the cortex of rats

The rat is a relatively understudied animal model for decision-making. But due to their size, cost and cognitive abilities they are a powerful model. During my postdoctoral work in Carlos Brody's lab I helped identify several key areas (e.g. the rat frontal orienting field and posterior parietal cortex) that show decision-related activity. However, the borders of these areas are unknown, and similar activity may be found elsewhere in the cortex. In my lab, we will further map out using electrophysiology and optogenetics the encoding of probability, value, effort, confidence and action across rodent cortex and examine the neural mechanism of competition or trade-off between factors (e.g. choosing a large effortful reward vs. a small easy reward).

  • Stress and decision-making

We all experience conflict between immediate rewards (a delicious pastry) and long-term goals (staying fit). One important variable in comparing immediate and future rewards is called the discounting factor: how much we undervalue future rewards. In humans, it has been shown that stress can increase the discounting factor, leading to more choices of immediate rewards. This phenomena can have serious social consequences. Those living in poverty experience significant stress that can perpetuate the cycle of poverty by driving decisions to be more steeply discounted (Haushofer & Fehr, 2014). One project in my lab will be the development of a rodent model of economic decision-making under stress to determine the neural mechanisms by which stress exacerbates discounting.

  • Reinforcement learning of deep networks (with Prof. Zheng Zhang)

The Deep Mind team (now at Google) has made recent progress in training neural networks with sparse reinforcement (as opposed to the more typical supervised learning algorithms). We are building on that work to develop an network model of a rat that will be trained on the same tasks that we use to train our real rat. This will be a test bed for our theories about learning, reinforcement, and neural mechanisms of cognition and will allow us to conduct experiments in silico, which we can then test in vivo.