Evidence map›Paper›PMID 39131333›Full record

ArticlebioRxiv : the preprint server for biology2024

How different immersive environments affect intracortical brain computer interfaces.

Ariana F Tortolani, Nicolas G Kunigk, Anton R Sobinov, Michael L Boninger, Sliman J Bensmaia, Jennifer L Collinger, Nicholas G Hatsopoulos, John E Downey

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Ariana F TortolaniCommittee on Computational Neuroscience, University of Chicago, Chicago, IL.ORCID 0000-0002-5046-3201
Nicolas G KunigkRehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA.ORCID 0009-0002-4645-6647
Anton R SobinovDepartment of Organismal Biology and Anatomy, University of Chicago, Chicago, IL.ORCID 0000-0003-0513-9194
Michael L BoningerRehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA.ORCID 0000-0001-6966-919X
Sliman J BensmaiaCommittee on Computational Neuroscience, University of Chicago, Chicago, IL.ORCID 0000-0003-4039-9135
Jennifer L CollingerRehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA.ORCID 0000-0002-4517-5395
Nicholas G HatsopoulosCommittee on Computational Neuroscience, University of Chicago, Chicago, IL.ORCID 0000-0002-4913-6051
John E DowneyDepartment of Organismal Biology and Anatomy, University of Chicago, Chicago, IL.ORCID 0000-0002-2992-2848

Funding

A Biomimetic Approach Towards a Dexterous NeuroprosthesisUH3NS107714 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BONINGER, MICHAEL L. · 2018 to 2023
$7.1M
Improved Brain-Computer Interface Decoding for Activities of Daily LifeR01NS130302 · NINDS · UNIVERSITY OF CHICAGO · PI John E Downey, Matthew Tyler Kaufman · 2023 to 2026
$2.6M
Neural, Computational, and Neuromechanical Approaches to Motor ControlT32NS121763 · NINDS · UNIVERSITY OF CHICAGO · PI MELINA E HALE, Nicholas G Hatsopoulos · 2022 to 2026
$1.6M
NINDS NIH HHS R01 NS130302NINDS NIH HHS T32 NS121763NINDS NIH HHS UH3 NS107714
6 · The paper itself

Abstract

As brain-computer interface (BCI) research advances, many new applications are being developed. Tasks can be performed in different environments, and whether a BCI user can switch environments seamlessly will influence the ultimate utility of a clinical device. Here we investigate the importance of the immersiveness of the virtual environment used to train BCI decoders on the resulting decoder and its generalizability between environments. Two participants who had intracortical electrodes implanted in their precentral gyrus used a BCI to control a virtual arm, either viewed immersively through virtual reality goggles or at a distance on a flat television monitor. Each participant performed better with a decoder trained and tested in the environment they had used the most prior to the study, one for each environment type. The neural tuning to the desired movement was minimally influenced by the immersiveness of the environment. Finally, in further testing with one of the participants, we found that decoders trained in one environment generalized well to the other environment, but the order in which the environments were experienced within a session mattered. Overall, experience with an environment was more influential on performance than the immersiveness of the environment, but BCI performance generalized well after accounting for experience.

Identifiers

PMID39131333
PMCPMC11312620

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.