Seoul National University · Connectome Laboratory

Understanding people through connections.

Why do people think, feel, and change differently? At the SNU Connectome Lab, led by Jiook Cha, we seek answers in the relationships among genes, brain, behavior, and environment. We study theories that could explain these relationships and predictive models that could apply to new people.

Our research questions

Everything Connects to Everything Else.

Leonardo da Vinci

MBBN Fig. 2A–C: model-estimated ADHD-related brain connectivity patterns shown in three views. — ADHD-related brain connectivity patterns estimated by MBBN (Fig. 2A–C, excerpt). These model analyses do not establish causal disease mechanisms. Bae et al., Communications Biology (2026) · CC BY 4.0

Our approach

What it means to study connections

A connectome maps connections within the brain. Our questions extend to how brain activity relates to a person’s experiences and circumstances. In developmental research, for example, we examine genetic variation and brain measurements alongside behavior, family relationships, school experience, and neighborhood conditions. This helps us ask what each observation reveals when read in relation to the others.

Bringing explanation and prediction together

We work with theoretical models that explain phenomena and AI models that learn predictive patterns from data. Our aim is to narrow the distance between predicting well and understanding why. Developing new tools goes together with examining the assumptions they carry.

Jiook Cha’s approach to research

Questions we pursue

How can AI trained on brain data help us understand and predict cognition, emotion, and behavior?
We build models around fMRI patterns across space and time and EEG channel configurations, examining how they learn information related to cognition, emotion and behavior.
How are genes, brain, behavior, and environment connected in development and mental health?
We analyze connections among genes, brain, behavior and environment in developmental data, studying the information in family history and predictions from combined measurements.
What possibilities does quantum computation open for representing and learning complex brain signals?
We compare ways to combine quantum circuits with classical models for brain-signal learning, examining computational requirements and constraints from noise.
How do feelings and remembered experiences relate to brain activity?
We use VR, experience reports and EEG to study mixed emotions, and test how emotional changes during recall can guide music and video generation.

People who see a question through

We set ambitious goals, identify what we need to learn, and learn from one another’s strengths. Working independently means examining our assumptions, considering other explanations, and bringing research to a form that others can examine and build on.

AI expands what we can read, build, and test. Turning that possibility into better questions and more complete research remains our responsibility.

People