Date: October 25, 2023
Place: Seminar Room, SC 106
Processing and representation of decision variables across interacting brain regions in a complex spatial task.
Decisions in naturalistic environments take place in dynamic, temporally extended, and topologically complex environments. A broad range of research into neural and behavioral correlates of decision making suggests that the brain contains multiple
competing systems to generate adaptive strategies for different situations and contexts. This raises two questions:
1) how does different neural circuitry represent structurally different environments, and
2) how do interactions between brain regions change to promote adaptive behaviors in differently complex environments.
We have sought to answer these questions by simultaneously recording from the rodent medial prefrontal cortex, hippocampus, and dorsolateral striatum—all regions implicated in different decision making paradigms, namely deliberative and procedural, respectively—during a freely-behaving left/right/alternate foraging task. Furthermore, to isolate the role of medial prefrontal cortex as the hub for high-level strategy setting, we chemogentically inhibited dorsal prefrontal cortex. Our work suggests that deliberative and habitual decision-making is highly modulated by the environment the animal is in, with more complex environments requiring longer deliberative periods—through prefrontal-hippocampal interactions—and more detailed environmental representations. Moreover, neural signatures associated with procedural decision-making suggests that environment topology influences goal and subgoal representations, further buttressing the idea of modeling decision-making as a hierarchical process. Together these findings aim to elucidate how the activity, and interactions between interconnected brain regions accommodate computational demands of different levels of task complexity.
Ugurcan Mugan is a postdoctoral researcher at the University of Minnesota department of neuroscience working with Dr. David Redish. She completed her undergraduate degree in Electrical and Electronics Engineering at Bilkent University, Turkey, and
thereafter pursued a PhD in Biomedical Engineering at Northwestern University with a focus in computational and evolutionary neuroscience. In her postdoctoral work she studied how the representations of decision variables change with task demands across interconnected brain regions using electrophysiology and chemogenetics in freely behaving animals. She is currently looking at the contributions of genetically distinct neuron types in information relay between prefrontal cortex and hippocampus in a variably complex spatial working memory task using electrophysiology and dual color optogenetics.