NeuroscienceMolecular PsychiatryPeer-reviewed
Clinical Response to Neurofeedback in Major Depression Relates to Subtypes of Whole-Brain Activation Patterns During Training
Masaya Misaki, Kymberly D. Young, Aki Tsuchiyagaito…·Salvador Martin Guinjoan
Author
Kymberly D. Young
University of PittsburghORCID 0000-0001-5133-2142Unclaimed ORCID profile · follow to get notified of new preprints
Biology Disciplines
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2020-2024 · peak 2/yrCo-Author Collaboration Network
10 top collaborators · 36 mutual co-author linksFocal author (center)Selected co-authorORCID co-authorUnlinked name
Curved chords = mutual co-authorship5 papers
Recent·Most cited
- NeuroscienceBrain Imaging and BehaviorPeer-reviewed
Cingulate prediction of response to antidepressant and cognitive behavioral therapies for depression: Theory, meta-analysis, and empirical application
Marlene V. Strege, Greg J. Siegle, John A. Richey…·Kymberly D. Young
The paper identifies neural predictors of response to antidepressants and cognitive behavioral therapy in depression using meta-analysis and empirical data.
- NeuroscienceTranslational PsychiatryPeer-reviewed
Importance of test-retest reliability for promoting fMRI based screening and intervention in major depressive disorder
Laurie Compère, Greg J. Siegle, Kymberly D. Young
This paper highlights the importance of test-retest reliability in fMRI studies for major depressive disorder to improve clinical applications like neurofeedback and outcome evaluation.
- NeurosciencebioRxivPreprint
Determinants of Real-Time fMRI Neurofeedback Performance and Improvement: a Machine Learning Mega-Analysis
Amelie Haugg, Fabian M. Renz, Andrew A. Nicholson…·David Steyrl
This study uses machine learning to analyze 608 participants and identifies two factors improving neurofeedback performance: pre-training no-feedback runs and training patients over healthy participants.
- NeuroscienceHuman Brain MappingPeer-reviewed
Can we predict real-time fMRI neurofeedback learning success from pre-training brain activity?
Amelie Haugg, Ronald Sladky, Stavros Skouras…·Frank Scharnowski
This study investigates whether pre-training brain activity can predict success in real-time fMRI neurofeedback learning across 24 studies and 401 participants, finding a weak correlation but no consistent predictors.