Evidence map›Paper›PMID 28098561›Full record

ArticleJournal of neural engineering2017

Decoding of intended saccade direction in an oculomotor brain-computer interface.

Nan Jia, Scott L Brincat, Andrés F Salazar-Gómez, Mikhail Panko, Frank H Guenther, Earl K Miller

Abstract read
In one paragraph

Article in Journal of neural engineering, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. In vivo ephaptic coupling allows memory network formation.Cerebral cortex (New York, N.Y. : 1991) · 2023
    Article
  3. Review
  4. Article
  5. Persistent Spiking Activity Underlies Working Memory.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2018
    Article
  6. Article
  7. 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.

Nan JiaCenter for Computational Neuroscience and Neural Technology, Boston University, 677 Beacon Street, Boston, MA 02215, United States of America.
Scott L BrincatThe Picower Institute for Learning and Memory, Massachusetts Institute of Technology, 77 Massachusetts Avenue, MIT Building 46-6241, Cambridge, MA 02139, United States of America.
Andrés F Salazar-GómezCenter for Computational Neuroscience and Neural Technology, Boston University, 677 Beacon Street, Boston, MA 02215, United States of America.
Mikhail PankoCenter for Computational Neuroscience and Neural Technology, Boston University, 677 Beacon Street, Boston, MA 02215, United States of America.
Frank H GuentherCenter for Computational Neuroscience and Neural Technology, Boston University, 677 Beacon Street, Boston, MA 02215, United States of America.
Earl K MillerThe Picower Institute for Learning and Memory, Massachusetts Institute of Technology, 77 Massachusetts Avenue, MIT Building 46-6241, Cambridge, MA 02139, United States of America.

Funding

Cortical Circuits for Attention and DecisionsR37MH087027 · NIMH · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI MILLER, EARL K · 2010 to 2019
$4.7M
Integrative Functions of the Prefrontal CortexR01NS035145 · NINDS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI MILLER, EARL K · 2002 to 2011
$3.7M
NIMH NIH HHS R37 MH087027NINDS NIH HHS R01 NS035145
6 · The paper itself

Abstract

objectiveTo date, invasive brain-computer interface (BCI) research has largely focused on replacing lost limb functions using signals from the hand/arm areas of motor cortex. However, the oculomotor system may be better suited to BCI applications involving rapid serial selection from spatial targets, such as choosing from a set of possible words displayed on a computer screen in an augmentative and alternative communication (AAC) application. Here we aimed to demonstrate the feasibility of a BCI utilizing the oculomotor system. APPROACH: We developed a chronic intracortical BCI in monkeys to decode intended saccadic eye movement direction using activity from multiple frontal cortical areas. MAIN

resultsIntended saccade direction could be decoded in real time with high accuracy, particularly at contralateral locations. Accurate decoding was evident even at the beginning of the BCI session; no extensive BCI experience was necessary. High-frequency (80-500 Hz) local field potential magnitude provided the best performance, even over spiking activity, thus simplifying future BCI applications. Most of the information came from the frontal and supplementary eye fields, with relatively little contribution from dorsolateral prefrontal cortex. SIGNIFICANCE: Our results support the feasibility of high-accuracy intracortical oculomotor BCIs that require little or no practice to operate and may be ideally suited for 'point and click' computer operation as used in most current AAC systems.

Indexed as

Brain-Computer InterfacesElectrodes, ImplantedAnimalsMacaca fascicularisMacaca mulattaMaleOculomotor NervePhotic StimulationPrefrontal CortexRandom AllocationSaccades

Identifiers

PMID28098561
PMCPMC5764173

What OpenQuestion holds

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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.