The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
Closed-loop training of attention with real-time brain imaging
Open accessAbstract
Lapses of attention can have negative consequences, including accidents and lost productivity. Here we used closed-loop neurofeedback to improve sustained attention abilities and reduce the frequency of lapses. During a sustained attention task, the focus of attention was monitored in real time with multivariate pattern analysis of whole-brain neuroimaging data. When indicators of an attentional lapse were detected in the brain, we gave human participants feedback by making the task more difficult. Behavioral performance improved after one training session, relative to control participants who received feedback from other participants' brains. This improvement was largest when feedback carried information from a frontoparietal attention network. A neural consequence of training was that the basal ganglia and ventral temporal cortex came to represent attentional states more distinctively. These findings suggest that attentional failures do not reflect an upper limit on cognitive potential and that attention can be trained with appropriate feedback about neural signals.
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Closed-loop brain training: the science of neurofeedback
Sitaram, R., Ros, T., Stoeckel, L., Haller, S., Scharnowski, F., Lewis-Peacock, J., Weiskopf, N., Blefari, M. L., Rana, M., Oblak, E., et al. (2017) · Nature Reviews Neuroscience · doi:10.1038/nrn.2016.164 · Cited by 1,306
A neuromarker of sustained attention from whole-brain functional connectivity
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Progress in Brain Computer Interface: Challenges and Opportunities
Saha, S., Mamun, K. A., Ahmed, K., Mostafa, R., Naik, G. R., Darvishi, S., Khandoker, A. H., & Baumert, M. (2021) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2021.578875 · Cited by 365
Neurofeedback with fMRI: A critical systematic review
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Mendoza, J. S., Pody, B. C., Lee, S., Kim, M., & McDonough, I. M. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.04.027 · Cited by 275
Metadata
- Authors
- deBettencourt, M. T., Cohen, J. D., Lee, R. F., Norman, K. A., & Turk-Browne, N. B.
- Venue
- Nature Neuroscience
- Published
- 2015-02-09
- Volume
- 18
- Issue
- 3
- Pages
- 470-475
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- OpenAlex
- W1980518572
- Cited by
- 324
- References
- 48
- FWCI
- 19.91
- Type
- journal article
- Language
- en
- Open access
- green
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- deBettencourt, M. T., Cohen, J. D., Lee, R. F., Norman, K. A., & Turk-Browne, N. B. (2015). Closed-loop training of attention with real-time brain imaging. Nature Neuroscience. https://doi.org/10.1038/nn.3940
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