Paper Info
Title
Connectome-based neurofeedback: A pilot study to improve sustained attention.
Abstract
Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback is a non-invasive, non-pharmacological therapeutic tool that may be useful for training behavior and alleviating clinical symptoms. Although previous work has used rt-fMRI to target brain activity in or functional connectivity between a small number of brain regions, there is growing evidence that symptoms and behavior emerge from interactions between a number of distinct brain areas. Here, we propose a new method for rt-fMRI, connectome-based neurofeedback, in which intermittent feedback is based on the strength of complex functional networks spanning hundreds of regions and thousands of functional connections. We first demonstrate the technical feasibility of calculating whole-brain functional connectivity in real-time and provide resources for implementing connectome-based neurofeedback. We next show that this approach can be used to provide accurate feedback about the strength of a previously defined connectome-based model of sustained attention, the saCPM, during task performance. Although, in our initial pilot sample, neurofeedback based on saCPM strength did not improve performance on out-of-scanner attention tasks, future work characterizing effects of network target, training duration, and amount of feedback on the efficacy of rt-fMRI can inform experimental or clinical trial designs.
Year
DOI
Venue
2020
10.1016/j.neuroimage.2020.116684
NeuroImage
Keywords
DocType
Volume
Real-time fMRI,Neurofeedback,Connectome-based predictive modeling,Functional connectivity,Attention
Journal
212
ISSN
Citations 
PageRank 
1053-8119
2
0.36
References 
Authors
0
7
Name
Order
Citations
PageRank
Dustin Scheinost128722.17
Tiffany W Hsu220.36
Emily W Avery320.70
Michelle Hampson417212.32
R Todd Constable584877.34
Marvin Chun613213.76
Monica D Rosenberg7544.60