Transdiagnostic Connectome-Based Prediction of Craving
Kathleen A Garrison1, Rajita Sinha1, Marc N Potenza1
1Department of Psychiatry (Garrison, Sinha, Potenza), Child Study Center (Sinha, Potenza, Scheinost), n.; Department of Neuroscience (Sinha, Potenza), Wu Tsai Institute (Potenza, Scheinost), Department of Biomedical Engineering (Gao, Liang, Scheinost), and Department of Statistics and Data Science (Scheinost), Yale University, New Haven, Conn.; Connecticut Mental Health Center, New Haven, Conn. (Potenza); Connecticut Council on Problem Gambling, Hartford, Conn. (Potenza).
Researchers identified a common "craving network" in the brain using connectome-based predictive modeling. This network helps predict craving across various substance use disorders and in healthy individuals.
Area of Science:
- Neuroscience
- Addiction Research
- Psychiatry
Background:
- Craving is a core component of addictive disorders and a key factor in motivated behavior.
- Understanding the neural basis of craving is crucial for developing transdiagnostic treatments for addiction.
Purpose of the Study:
- To identify a transdiagnostic neural network associated with craving.
- To predict self-reported craving using functional connectivity data.
- To validate the generalizability of the identified
Main Methods:
- Connectome-based predictive modeling (CPM) was applied to functional connectivity data from 274 participants.
- Brain activity during guided imagery (appetitive, stress, neutral) was used to predict craving.
- The
Main Results:
- CPM successfully predicted craving, revealing a transdiagnostic
Conclusions:
- A common neural network for craving was identified, applicable across individuals with and without substance use disorders.
- This
