JEONG @ NIH - Research

One of the brain's remarkable abilities is to learn new behaviors and continuously reorganize them to adapt to dynamic environmental changes. Reinforcement learning serves as a prominent computational framework for understanding these processes. However, its implementation within the biological brain remains largely unknown.

My research focuses to understand how the brain’s neural circuits and molecular mechanisms enable reinforcement learning, a process essential for adaptive behaviors. Key questions driving my research include:

How rewards and errors are processed within the basal ganglia neural circuits.
How cortical dynamics contribute to optimizing behavioral structure and policy.
How previously learned behaviors are updated through neuromodulatory mechanisms, intracellular signaling, and genetic processes.

To address these questions, I employ in vivo calcium imaging to capture large-scale neural activity in freely behaving mice. In parallel, I develop advanced optical imaging systems and engineered protein technologies to probe intracellular signaling molecules and GPCR cascades in real time.

By integrating pharmacological approaches with single-cell RNA sequencing, my research seeks to elucidate the neural mechanisms underlying circuit dysfunctions and maladaptive behaviors at the levels of genes and proteins. This work holds the potential to identify novel therapeutic targets for neurological disorders such as addiction, depression, and motor dysfunction.

Neural Computation in the Cortex

The brains of humans and many other animals possess an extraordinary ability to flexibly organize complex and dynamic movement sequences through reinforcement learning. How do brain circuits compute behavioral information and regulate motor output during this process? My research explores the cortical circuits and neural dynamics involved in organizing motor behaviors. Using in-vivo optical imaging and computational techniques, I focus on decoding the neural network dynamics of cortical microcircuits that control action squence, reinforce motor learning, and enable flexible motor behaviors. In my most recent project (link), I use large-scale single-cell calcium imaging and opto/chemogenetic manipulations in freely behaving mice to decode the intricate dynamics of cortical interneuron networks that actively regulate movement sequences. These research directions aim to uncover the neural mechanisms underlying motor skill learning, motor refinement, and movement disorders.

Reward Processing Circuits in the Basal Ganglia

Neural substrates involved in reward processing and reinforcement learning (RL) are essential for biological organisms to acquire new skills, make decisions, and adapt to changing environments. I investigate how neural circuits in the basal ganglia encode reinforcement and error signals that drive learning and behavioral adaptation. Additionally, my research explores how pharmacological interventions and addictive drugs disrupt these processes.

Using in-vivo optical methods and animal behavior models, I examine how dopamine neuromodulation is differentially involved in reward-based learning and drug responses across striatal subregions (link). I also aim to investigate the mechanisms of intracellular signaling and neural circuit dysfunction associated with chronic exposure to psychoactive drugs, including addictive substances, selective receptor agonists, alcohol, and pain management drugs. In the long term, these approaches will enhance our understanding of the neural mechanisms underlying reward-based learning and offer new insights into pharmacological treatments for neurological disorders associated with basal ganglia circuits.

Imaging Molecules and Protein Interactions in Neurons

My research uses cutting-edge optical imaging and engineered protein technologies to detect signaling molecules in real-time. I develop novel genetically encoded biosensors and optical imaging systems to monitor in-vivo G protein coupled receptors (GPCRs) signaling cascades in behaving mice (link). For example, I measure intracellular second messenger such as cAMP using genetically engineered fluorescence proteins and fluorescence lifetime imaging microscopy (FLIM). These tools are crucial for elucidating the molecular and circuit-level mechanisms that underlie neuronal plasticity and gene expression, with the potential to provide new insights into the treatment of neurological and psychiatric disorders.