Pilot corpus: NIH-funded biomedical datasets. Any DOI can be scored on demand — network effects sharpen as coverage grows.

Continuous tracking using deep learning-based decoding for noninvasive brain–computer interface

PNAS Nexus(2024)10.1093/pnasnexus/pgae145Source: DataRank Database

Continuous tracking using deep learning-based decoding for noninvasive brain–computer interface is a research paper published in PNAS Nexus (2024). On theSindex it has a DataRank of 0.510. It has been cited 29 times.

N/A

0.510DataRank · unranked

Scored on demand from live citation data

Open Access29 citations

Download PDF

Cite:

Linked data & code

DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (19 grants)OA: goldTopics (8)Linked Datasets (2)DataCite Reuse (2)IDs (PubMed, PMC)

FAIR Checklist

Context only (not used in score)

Findable (2/2)

Has DOI
Indexed in repositories

Accessible (1/2)

Open Access

Interoperable (2/2)

DataCite relations
Linked datasets

Reusable (0/3)

FAIR checklist signals are shown for context only and do not affect DataRank scoring.

Run a calibrated FAIR evaluation for this paper →

We only score data papers we can read in full — never from an abstract alone.

DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.510

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.

Learn more about DataRank methodology →

Authors (5)

Hao Zhu ORCID,J.G. Shanahan,Jaehyun Lim ORCID,Bin He ORCID,Dylan Forenzo ORCID

Live enrichment

PubMed:38689706 PMC:PMC11060102

NIH

Grant: AT009263

NIH

Grant: NS127849

NIH

Grant: NS096761

NIH

Grant: NS131069

NIH

Grant: NS124564

NIH

Grant: EB029354

NINDS NIH HHS

Grant: R01 NS096761

NCCIH NIH HHS

Grant: R01 AT009263

NINDS NIH HHS

Grant: R01 NS127849

NINDS NIH HHS

Grant: RF1 NS131069

NINDS NIH HHS

Grant: R01 NS124564

NIBIB NIH HHS

Grant: U18 EB029354

NINDS NIH HHS

Grant: RF1 NS124564

NIBIB NIH HHS

Grant: T32 EB029365

National Institutes of Health

Grant: 1R01NS124564-01

Characterization of in vivo neuronal and inter-neuronal responses to transcranial focused ultrasound

National Institutes of Health

Grant: 5R01AT009263-06

Mind-body awareness training and brain-computer interface

National Institutes of Health

Grant: 1R01NS127849-01A1

Imaging Epilepsy Sources with Biophysically Constrained Deep Neural Networks

National Institutes of Health

Grant: 1RF1NS131069-01

Electrophysiology-Compatible Wearable Transcranial Focused Ultrasound Neuromodulation Array Probes

National Institutes of Health

Grant: 2R01NS096761-06

Electrophysiological Source Imaging of Partial Epilepsy

goldLicense: cc-by

publisherhttps://academic.oup.com/pnasnexus/article-pdf/3/4/pgae145/57336375/pgae145.pdf

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC11060102/pdf/pgae145.pdf

Unpaywallhttps://doi.org/10.1093/pnasnexus/pgae145

Europe_PMChttps://europepmc.org/articles/PMC11060102

Europe_PMChttps://europepmc.org/articles/PMC11060102?pdf=render

Fields of Study

0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

Motor imageryBrain–computer InterfaceDeep LearningHuman–machine IntelligenceContinuous PursuitBiological, Health, and Medical Sciences

EEG-BCI Dataset for "Continuous Tracking using Deep Learning-based Decoding for Non-invasive Brain-Computer Interface"

10.1184/r1/25360300.v1Carnegie Mellon University

EEG-BCI Dataset for "Continuous Tracking using Deep Learning-based Decoding for Non-invasive Brain-Computer Interface"

10.1184/r1/25360300Carnegie Mellon University