Literature DB >> 17626211

Direct instrumental conditioning of neural activity using functional magnetic resonance imaging-derived reward feedback.

Signe Bray1, Shinsuke Shimojo, John P O'Doherty.   

Abstract

Successful learning is often contingent on feedback. In instrumental conditioning, an animal or human learns to perform specific responses to obtain reward. Instrumental conditioning is often used by behavioral psychologists to train an animal (or human) to produce a desired behavior. Shaping involves reinforcing those behaviors, which in a stepwise manner are successively closer to the desired behavior until the desired behavior is reached. Here, we aimed to extend this traditional approach to directly shape neural activity instead of overt behavior. To achieve this, we scanned 22 human subjects with functional magnetic resonance imaging and performed image processing in parallel with acquisition. We delineated regions of interest (ROIs) in finger and toe motor/somatosensory regions and used an instrumental shaping procedure to induce a regionally specific increase in activity by providing an explicit monetary reward to reinforce neural activity in the target areas. After training, we found a significant and regionally specific increase in activity in the ROI being rewarded (finger or toe) and a decrease in activity in the nonrewarded region. This demonstrates that instrumental conditioning procedures can be used to directly shape neural activity, even without the production of an overt behavioral response. This procedure offers an important alternative to traditional biofeedback-based approaches and may be useful in the development of future therapies for stroke and other brain disorders.

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Year:  2007        PMID: 17626211      PMCID: PMC6672599          DOI: 10.1523/JNEUROSCI.2118-07.2007

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  58 in total

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Authors:  Ranganatha Sitaram; Tomas Ros; Luke Stoeckel; Sven Haller; Frank Scharnowski; Jarrod Lewis-Peacock; Nikolaus Weiskopf; Maria Laura Blefari; Mohit Rana; Ethan Oblak; Niels Birbaumer; James Sulzer
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Review 5.  Real-time fMRI neurofeedback: progress and challenges.

Authors:  J Sulzer; S Haller; F Scharnowski; N Weiskopf; N Birbaumer; M L Blefari; A B Bruehl; L G Cohen; R C DeCharms; R Gassert; R Goebel; U Herwig; S LaConte; D Linden; A Luft; E Seifritz; R Sitaram
Journal:  Neuroimage       Date:  2013-03-27       Impact factor: 6.556

6.  Covert neurofeedback without awareness shapes cortical network spontaneous connectivity.

Authors:  Michal Ramot; Shany Grossman; Doron Friedman; Rafael Malach
Journal:  Proc Natl Acad Sci U S A       Date:  2016-04-11       Impact factor: 11.205

7.  How feedback, motor imagery, and reward influence brain self-regulation using real-time fMRI.

Authors:  Pradyumna Sepulveda; Ranganatha Sitaram; Mohit Rana; Cristian Montalba; Cristian Tejos; Sergio Ruiz
Journal:  Hum Brain Mapp       Date:  2016-06-06       Impact factor: 5.038

8.  Improving visual perception through neurofeedback.

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Journal:  J Neurosci       Date:  2012-12-05       Impact factor: 6.167

9.  Visuomotor discordance during visually-guided hand movement in virtual reality modulates sensorimotor cortical activity in healthy and hemiparetic subjects.

Authors:  Eugene Tunik; Soha Saleh; Sergei V Adamovich
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2013-01-09       Impact factor: 3.802

Review 10.  Sensorimotor training in virtual reality: a review.

Authors:  Sergei V Adamovich; Gerard G Fluet; Eugene Tunik; Alma S Merians
Journal:  NeuroRehabilitation       Date:  2009       Impact factor: 2.138

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