Evidence map›Paper›PMID 29247807›Full record

ArticleNeuroImage2018

Real-time decoding of covert attention in higher-order visual areas.

Jinendra Ekanayake, Chloe Hutton, Gerard Ridgway, Frank Scharnowski, Nikolaus Weiskopf, Geraint Rees

Abstract read
In one paragraph

Article in NeuroImage, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

6 authors.

Jinendra EkanayakeWellcome Trust Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom; Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom; Institute of Cognitive Neuroscience, University College London, London, United Kingdom. Electronic address: j.ekanayake@ucl.ac.uk.
Chloe HuttonSiemens Molecular Imaging, Oxford, United Kingdom.
Gerard RidgwayUniversity of Oxford, Headington, United Kingdom.
Frank ScharnowskiPsychiatric University Hospital, University of Zürich, Lenggstrasse 31, 8032 Zürich, Switzerland; Neuroscience Center Zürich, University of Zürich and Swiss Federal Institute of Technology, Winterthurerstr. 190, 8057 Zürich, Switzerland; Zürich Center for Integrative Human Physiology (ZIHP), University of Zürich, Winterthurerstr. 190, 8057 Zürich, Switzerland.
Nikolaus WeiskopfWellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Geraint ReesWellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom; Institute of Cognitive Neuroscience, University College London, London, United Kingdom.

Funding

Medical Research Council MR/J014257/1Medical Research Council MR/J014257/2
6 · The paper itself

Abstract

Brain-computer-interfaces (BCI) provide a means of using human brain activations to control devices for communication. Until now this has only been demonstrated in primary motor and sensory brain regions, using surgical implants or non-invasive neuroimaging techniques. Here, we provide proof-of-principle for the use of higher-order brain regions involved in complex cognitive processes such as attention. Using realtime fMRI, we implemented an online 'winner-takes-all approach' with quadrant-specific parameter estimates, to achieve single-block classification of brain activations. These were linked to the covert allocation of attention to real-world images presented at 4-quadrant locations. Accuracies in three target regions were significantly above chance, with individual decoding accuracies reaching upto 70%. By utilising higher order mental processes, 'cognitive BCIs' access varied and therefore more versatile information, potentially providing a platform for communication in patients who are unable to speak or move due to brain injury.

Indexed as

Brain-Computer InterfacesAdultAttentionCerebral CortexEye Movement MeasurementsFemaleFunctional NeuroimagingHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMalePattern Recognition, VisualProof of Concept StudySpace PerceptionYoung Adult

Identifiers

PMID29247807
PMCPMC5864512

What OpenQuestion holds

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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.