Research Projects

Project 1

Cross-Species Interrogation of Thalamocortical Substrates for Hierarchical Reasoning and their Perturbations in Schizophrenia

Cognitive deficits are a prominent and debilitating feature of schizophrenia and remain largely resistant to current treatments in part because the circuit mechanisms that underlie these impairments are still poorly understood.  Progress has also been limited by marked patient heterogeneity and by the difficulty of developing tractable tasks that can isolate individual computations and link them back to their underlying neural substrates.  These challenges underscore the need for novel cross-species frameworks that can bridge clinically relevant behavioral variation in humans with mechanistically precise circuit perturbations in animals.  To address this, we developed a cross-species decision-making task in humans and animals, together with a computational model to dissect the latent processes that support hierarchical reasoning.

Using this framework, we aim to trace behavioral impairments in patients to specific algorithmic deficits, and then link those same algorithmic signatures to thalamocortical circuit-level perturbations in mice.  This work is motivated by converging evidence that interactions between the mediodorsal thalamus and prefrontal cortex support reasoning under uncertainty and that dysfunction in this same circuit is linked to executive deficits in schizophrenia (Mukherjee et al. 2021, Huang et al. 2024, Lam et al. 2025). By pairing computational phenotyping with task-engaged fMRI in humans and optogenetic inactivation in mice, we aim to identify the specific neural networks and circuits responsible for implementing these computations.  This translational cross-species framework provides a path toward identifying mechanistically grounded subtypes of cognitive impairment and ultimately toward more precise, subtype-informed treatment strategies in schizophrenia.  This work is done in collaboration with Neil Woodward’s group at Vanderbilt University.

Project 3

Frontal-hippocampal circuits for hierarchical planning

Flexible behavior in complex environments often requires hierarchical planning, where extended action sequences are organized around intermediate subgoals. We study how hippocampal-frontal cortical circuits support this computation across spatial and abstract domains. Our central hypothesis is that the hippocampus facilitates the discovery of useful subgoals from experience while frontal cortical circuits use those subgoals to guide hierarchical planning.

To test this idea, we combine mathematical theory, recurrent neural network models, and neural recordings during a hierarchical planning task. We have developed a multi-area circuit theory in which hippocampal replay supports subgoal discovery through a plasticity mechanism optimizing for a normative clustering objective. On the other hand, an orbitofrontal-anterior cingulate circuit performs hierarchical planning over these learned abstractions: orbitofrontal cortex computes subgoal values while anterior cingulate cortex selects action sequences that maximize future subgoal values. This framework generates experimentally testable predictions on how the frontal cortex and hippocampus interact during subgoal discovery, option selection, and flexible replanning. Our long-term goal is to establish a circuit-level theory of hierarchical planning that links neural dynamics to underlying computation.

Project 4

Top-Down Control of Adaptive Sleep Interruption

The sleeping brain trades off maintaining a state supporting homeostasis with interruptions to handle external contingencies. These interruptions are adaptive, yet little is known about their neural substrates. Taking note that human sleep interruption exhibits associative and contextual components, we develop analogous paradigms in mice and discover that these features rely on the amygdala and prefrontal cortex, respectively. Electrophysiological recordings in sleeping mice reveal a feedforward amygdala circuit for transforming conditioned cues to sleep interruption signals. This process is under top-down control by the prefrontal cortex, which allows sleep to go uninterrupted in neutral contexts. Overall, our work shows a prefrontal to amygdala pathway for adaptive sleep interruption, extending the notion of top-down executive control to decision making during sleep.

Project 5

Investigating frontal thalamocortical circuits in human cognitive flexibility

Published and ongoing work in our lab focusing on frontal thalamocortical circuits has shown their role in cognitive flexibility. This is congruent with work from multiple other laboratories in the field (e.g. Kellendonk, Mitchell, Saalmann, Wolff, among others). More recently, we have focused on the specific role of the mediodorsal thalamus (MD) in decisions involving multiple sources of uncertainty, with preliminary data suggesting a role in coupling error monitoring to task switching. However, to what degree these insights and mechanisms apply to the human brain is unknown. To address this issue, we developed a hierarchical decision-making task that requires individuals to integrate multiple sources of uncertainty and adapt their behavioral patterns based on feedback over time. Through the combined use of non-invasive functional MRI and computational modeling, we aim to better understand the interactions between MD, PFC, and other cortical and subcortical structures during the process of behavioral adaptation in uncertain environments. These insights into the neural mechanisms of cognitive flexibility hold significant promise for informing clinical interventions aimed at enhancing decision-making processes and adaptive behaviors in individuals with neurological and psychiatric conditions. (led by Mengxing Liu in collaboration with Kai Hwang’s lab, University of Iowa)