Evidence map›Paper›PMID 31156761›Full record

ArticleInternational IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering2019

Sparse Multi-task Inverse Covariance Estimation for Connectivity Analysis in EEG Source Space.

Feng Liu, Emily P Stephen, Michael J Prerau, Patrick L Purdon

Abstract read
In one paragraph

Article in International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
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

4 authors.

Feng LiuDepartment of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Emily P StephenDepartment of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Michael J PrerauDepartment of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Patrick L PurdonDepartment of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

Funding

Noninvasive Low-cost Biomarkers for Preclinical Diagnosis and Longitudinal Tracking of Alzheimer's Disease Using Sleep and Resting State EEGR01AG054081 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI DICKERSON, BRADFORD C, PRERAU, MICHAEL J · 2017 to 2021
$4.2M
The Aging Brain Under General Anesthesia: Neurophysiology, Neuroimaging Biomarkers of Aging and Alzheimer's Disease, and Post-Operative Cognitive OutcomesR01AG056015 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI DICKERSON, BRADFORD C, PURDON, PATRICK L. · 2017 to 2021
$3.2M
Modeling Multi-scale Sleep EEG Dynamics as a Framework for Biomarker DiscoveryR01NS096177 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI PRERAU, MICHAEL J · 2016 to 2020
$1.9M
NIA NIH HHS R01 AG054081NIA NIH HHS R01 AG056015NINDS NIH HHS R01 NS096177
6 · The paper itself

Abstract

Understanding how different brain areas interact to generate complex behavior is a primary goal of neuroscience research. One approach, functional connectivity analysis, aims to characterize the connectivity patterns within brain networks. In this paper, we address the problem of

Indexed as

Alternating Direction Method of Multipliers (ADMM)EEG Source ImagingInverse Covariance EstimationSleeping α-Burst

Identifiers

PMID31156761
PMCPMC6541022

What OpenQuestion holds

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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.