1. Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training
- Author
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Tetsuya Suhara, Yasumasa Okamoto, Maro G. Machizawa, Takashi Nakano, Naho Ichikawa, Makiko Yamada, Shigeto Yamawaki, Haruki Nishimura, Junichiro Yoshimoto, Go Okada, Atsuo Yoshino, and Masahiro Takamura
- Subjects
Adult ,Male ,Brain activity and meditation ,Prediction of neurofeedback aptitude, Resting-state functional connectivity ,Cognitive Neuroscience ,media_common.quotation_subject ,Rest ,Datasets as Topic ,Neurosciences. Biological psychiatry. Neuropsychiatry ,Gyrus Cinguli ,Functional brain ,Neurofeedback with functional MRI ,Text mining ,Predictive Value of Tests ,Cortex (anatomy) ,Parietal Lobe ,medicine ,Connectome ,Humans ,Generalization to independent test data ,media_common ,Partial least square regression ,Depressive Disorder, Major ,Resting state fMRI ,business.industry ,Regression analysis ,Middle Aged ,Neurofeedback ,medicine.disease ,Magnetic Resonance Imaging ,Healthy Volunteers ,medicine.anatomical_structure ,Neurology ,Posterior cingulate ,Major depressive disorder ,Aptitude ,Female ,business ,Neuroscience ,RC321-571 - Abstract
Neurofeedback (NF) aptitude, which refers to an individual's ability to change brain activity through NF training, has been reported to vary significantly from person to person. The prediction of individual NF aptitudes is critical in clinical applications to screen patients suitable for NF treatment. In the present study, we extracted the resting-state functional brain connectivity (FC) markers of NF aptitude, independent of NF-targeting brain regions. We combined the data from fMRI-NF studies targeting four different brain regions at two independent sites (obtained from 59 healthy adults and six patients with major depressive disorder) to collect resting-state fMRI data associated with aptitude scores in subsequent fMRI-NF training. We then trained the multiple regression models to predict the individual NF aptitude scores from the resting-state fMRI data using a discovery dataset from one site and identified six resting-state FCs that predicted NF aptitude. Subsequently, the reproducibility of the prediction model was validated using independent test data from another site. The identified FC model revealed that the posterior cingulate cortex was the functional hub among the brain regions and formed predictive resting-state FCs, suggesting that NF aptitude may be involved in the attentional mode-orientation modulation system's characteristics in task-free resting-state brain activity.
- Published
- 2021