Dr Andrew Westbrook | Neuromodulation and cognitive effort
Cognitive Neurology Lecture
- Date: Sep 6, 2024
- Time: 01:00 PM - 02:00 PM (Local Time Germany)
- Speaker: Dr Andrew Westbrook
- Assistant Professor of Psychiatry, Center for Advanced Human Brain Imaging Research, Rutgers University
- Location: MPI for Human Cognitive and Brain Sciences
- Room: virtual
- Host: Department of Neurology
Novel stimuli can be learned by either of two mechanisms each with complementary strengths and weaknesses. Reinforcement learning is slow and incremental, but robust and stable over the long term. Working memory is fast and flexible but is susceptible to decay and is also effortful. But how does the brain mediate between these two mechanisms and how do we learn cognitive effort costs? In the first part of my talk, I will discuss evidence that striatal dopamine plays a role both in working memory and reinforcement learning. I will also discuss evidence that, as we have shown for effort-based decision-making, dopamine also plays a role in shaping how we learn about effort costs in the first place. In a study combining [18F]-DOPA PET imaging of dopamine synthesis capacity with dopamine transport blocker methylphenidate, the D2 agent sulpiride, and placebo, we find that striatal dopamine signaling increases our propensity to rely on costly working memory. We also find that, controlling for the contributions of working memory to the learning process, striatal dopamine signaling increases the rate of reinforcement learning. Finally, we find that while people treat rewards earned in the context of working memory demands to be less valuable when demands are higher, this effort-discounting effect is blunted by striatal dopamine signaling.
In the second part of this talk, I consider a novel hypothesis about the nature of effort costs. Namely, that subjective cognitive effort is a phenomenological readout of divergence from criticality in the brain. Brains at rest exhibit emergent properties indicative of a dynamical system near a critical point regulated by the balance of cortical excitation to inhibition. These properties are monotonically suppressed with increasing cognitive load, reflecting increasing divergence from criticality. Importantly, because criticality maximizes functional flexibility and information processing capacity, divergence implies computational costs. In my talk, I will discuss the rationale for the hypothesis linking subjective effort and criticality. I will also discuss a first study examining subjective cognitive effort and critical dynamics in EEG data while participants perform various levels of the N-back working memory task.