Research

Our research focuses on the brain processes mediating learning and decision making in humans, and how they are disrupted in neuropsychiatric conditions such as substance use disorder. To complement this, we also study the neural mechanisms of olfaction, a sensory modality closely tied to motivation, behavior, and learning, and which is impacted in many neuropsychiatric disorders. To address these questions, we use a combination of behavioral methods, olfactory psychophysics, correlational brain imaging (i.e., functional magnetic resonance imaging, fMRI), causal neuromodulation methods (e.g., transcranial magnetic stimulation, TMS; transcranial ultrasound stimulation, TUS), and computational techniques (e.g., reinforcement learning, encoding models, machine learning).

A central goal of our work is to bridge animal models and clinical research in humans. This is critical to build a more comprehensive understanding of the basic brain processes underlying adaptive behavior, their disruption in neuropsychiatric conditions, and to facilitate the development of new treatments.

Current research projects in the lab can be divided into three areas.

Neural mechanisms of decision making

We study how prefrontal and subcortical brain networks including the medial prefrontal and orbitofrontal cortex, hippocampus and amygdala form and represent predictions about future rewards, and how these representations influence decision making. In particular, we focus on how these areas generate flexible predictions by representing models of the world and making inferences based on these models. By combining behavioral experiments with neuroimaging, neuromodulation and computational modeling, we seek to unravel the complex interactions between sensory inputs, cognitive processes and behavioral outputs, and how they are disrupted in disorders characterized by compulsive behaviors, such as substance use disorder.

Example publications

Kahnt T. Computationally informed interventions for targeting compulsive behaviors. Biological Psychiatry. 2023 Apr 15; 93(8):729-738.

Tegelbeckers J, Porter DB, Voss JL, Schoenbaum G, Kahnt T. Lateral orbitofrontal cortex integrates predictive information across multiple cues to guide behavior. Current Biology. 2023 Oct 23; 33(20):4496-4504.e5.

Wang F, Schoenbaum G, Kahnt T. Interactions between human orbitofrontal cortex and hippocampus support model-based inference. PLoS Biology. 2020 Jan 21; 18(1):e3000578.

Brain mechanisms of olfaction

Odors are uniquely powerful drivers of approach-avoidance behaviors. Our research aims to understand how odors are processed and represented in the brain, how odors influence learning and behavior, and how olfactory processing is modulated by internal and external states. We also study impairments in olfactory function in neuropsychiatric disorders and dementia. By combining olfactory psychophysics with functional MRI and pattern-based imaging data analysis, our research aims to understand the brain processes underlying olfactory perception and odor-guided behavior.

Example publications

Sagar V, Shanahan LK, Zelano CM, Gottfried JA, Kahnt T. High-precision mapping reveals the structure of odor coding in the human brain. Nature Neuroscience. 2023 Sep; 29(9):1595-1602.

Echevarria-Cooper SL, Zhou G, Zelano C, Pestilli F, Parrish TB, Kahnt T. Mapping the Microstructure and Striae of the Human Olfactory Tract with Diffusion MRI. Journal of Neuroscience. 2022 Jan 5; 42 (1):58-68.

Shanahan LK, Bhutani S, Kahnt T. Olfactory perceptual decision-making is biased by motivational state. PLoS Biology. 2021 Aug 26; 19(8):e3001374.

Midbrain dopamine and learning

Our research on reward learning focuses on how the dopaminergic system supports the formation of associations between predictive events and specific rewards. For this, we use a combination of behavioral learning experiments, neuroimaging, neuromodulation and computational modeling. Because dopamine is implicated in a variety of psychiatric disorders, this research is essential to better understanding these disorders and to identify novel targets for treatment.

Example publications

Kahnt T, Schoenbaum G. The curious case of dopaminergic prediction errors and learning associative information beyond value. Nature Reviews Neuroscience. 2025 Mar; 26(3):169-178.

Howard JD, Edmonds D, Schoenbaum G, Kahnt T. Distributed midbrain responses signal the content of positive identity prediction errors. Current Biology. 2024 Sep 23; 34(18):4240-4247.e4.

Liu Q, Zhao Y, Attanti S, Voss JL, Schoenbaum G, Kahnt T. Midbrain signaling of identity prediction errors depends on orbitofrontal cortex networks. Nature Communications. 2024 Feb 24; 15:1704.

Research

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