Evidence map›Paper›PMID 25161613›Full record

ReviewFrontiers in systems neuroscience2014

Selective visual attention to drive cognitive brain-machine interfaces: from concepts to neurofeedback and rehabilitation applications.

Elaine Astrand, Claire Wardak, Suliann Ben Hamed

Abstract readReview
In one paragraph

Review in Frontiers in systems neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Trial
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  7. Dynamic and stable population coding of attentional instructions coexist in the prefrontal cortex.Proceedings of the National Academy of Sciences of the United States of America · 2022
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  17. Virtual reality and brain computer interface in neurorehabilitation.Proceedings (Baylor University. Medical Center) · 2016
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  19. Differential dynamics of spatial attention, position, and color coding within the parietofrontal network.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2015
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  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Elaine AstrandCNRS, Cognitive Neuroscience Center, UMR 5229, University of Lyon 1 Bron Cedex, France.
Claire WardakCNRS, Cognitive Neuroscience Center, UMR 5229, University of Lyon 1 Bron Cedex, France.
Suliann Ben HamedCNRS, Cognitive Neuroscience Center, UMR 5229, University of Lyon 1 Bron Cedex, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brain-machine interfaces (BMIs) using motor cortical activity to drive an external effector like a screen cursor or a robotic arm have seen enormous success and proven their great rehabilitation potential. An emerging parallel effort is now directed to BMIs controlled by endogenous cognitive activity, also called cognitive BMIs. While more challenging, this approach opens new dimensions to the rehabilitation of cognitive disorders. In the present work, we focus on BMIs driven by visuospatial attention signals and we provide a critical review of these studies in the light of the accumulated knowledge about the psychophysics, anatomy, and neurophysiology of visual spatial attention. Importantly, we provide a unique comparative overview of the several studies, ranging from non-invasive to invasive human and non-human primates studies, that decode attention-related information from ongoing neuronal activity. We discuss these studies in the light of the challenges attention-driven cognitive BMIs have to face. In a second part of the review, we discuss past and current attention-based neurofeedback studies, describing both the covert effects of neurofeedback onto neuronal activity and its overt behavioral effects. Importantly, we compare neurofeedback studies based on the amplitude of cortical activity to studies based on the enhancement of cortical information content. Last, we discuss several lines of future research and applications for attention-driven cognitive brain-computer interfaces (BCIs), including the rehabilitation of cognitive deficits, restored communication in locked-in patients, and open-field applications for enhanced cognition in normal subjects. The core motivation of this work is the key idea that the improvement of current cognitive BMIs for therapeutic and open field applications needs to be grounded in a proper interdisciplinary understanding of the physiology of the cognitive function of interest, be it spatial attention, working memory or any other cognitive signal.

Indexed as

brain–computer interfacesbrain–machine interfacescognitionfrontal eye fieldneural trainingneurofeedbackprefrontal cortexspatial attention

Identifiers

PMID25161613
PMCPMC4130369

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.