Evidence map›Paper›PMID 22426415›Full record

ReviewJournal of neuroscience methods2012

Connectivity measures applied to human brain electrophysiological data.

R E Greenblatt, M E Pflieger, A E Ossadtchi

Abstract readReview
In one paragraph

Review in Journal of neuroscience methods, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing 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

47 citing papers in PubMed.

  1. Review
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  7. Changes in interhemispheric coherence after total corpus callosotomy: a scalp EEG study in children with non-lesional generalized epilepsy.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2024
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  10. Review
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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

3 authors.

R E GreenblattSource Signal Imaging, Inc., San Diego, CA, USA. Richard.Greenblatt@gmail.com
M E Pflieger
A E Ossadtchi

Funding

Multimodal Resting State Network ToolsR43MH095439 · NIMH · SOURCE SIGNAL IMAGING, INC. · PI PFLIEGER, MARK E · 2011 to 2012
$493k
NIMH NIH HHS R43 MH095439
6 · The paper itself

Abstract

Connectivity measures are (typically bivariate) statistical measures that may be used to estimate interactions between brain regions from electrophysiological data. We review both formal and informal descriptions of a range of such measures, suitable for the analysis of human brain electrophysiological data, principally electro- and magnetoencephalography. Methods are described in the space-time, space-frequency, and space-time-frequency domains. Signal processing and information theoretic measures are considered, and linear and nonlinear methods are distinguished. A novel set of cross-time-frequency measures is introduced, including a cross-time-frequency phase synchronization measure.

Indexed as

Electrophysiological PhenomenaModels, NeurologicalModels, StatisticalSignal Processing, Computer-AssistedBrainHumansNerve NetNeural Pathways

Identifiers

PMID22426415
PMCPMC5549799

What OpenQuestion holds

Textmetadata
LicenceTDM
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.