Evidence map›Paper›PMID 32082371›Full record

ArticleComputational intelligence and neuroscience2019

Ant Colony Clustering for ROI Identification in Functional Magnetic Resonance Imaging.

Alejandro Veloz, Alejandro Weinstein, Stefan Pszczolkowski, Luis Hernández-García, Rodrigo Olivares, Roberto Muñoz, Carla Taramasco

Abstract readEvaluation Study
In one paragraph

Article in Computational intelligence and neuroscience, 2019. 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

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

7 authors.

Alejandro VelozEscuela de Ingeniería Civil Biomédica, Universidad de Valparaíso, Valparaíso 2340000, Chile.
Alejandro WeinsteinEscuela de Ingeniería Civil Biomédica, Universidad de Valparaíso, Valparaíso 2340000, Chile.ORCID https://orcid.org/0000-0003-1486-7003
Stefan PszczolkowskiRadiological Sciences, Division of Clinical Neuroscience, University of Nottingham, Nottingham NG7 2UH, UK.ORCID https://orcid.org/0000-0002-5859-3190
Luis Hernández-GarcíaFunctional MRI Laboratory, University of Michigan, Ann Arbor 48109, USA.
Rodrigo OlivaresCentro de Investigación y Desarrollo en Ingeniería en Salud, Universidad de Valparaíso, Valparaíso 2340000, Chile.ORCID https://orcid.org/0000-0003-0582-954X
Roberto MuñozCentro de Investigación y Desarrollo en Ingeniería en Salud, Universidad de Valparaíso, Valparaíso 2340000, Chile.ORCID https://orcid.org/0000-0003-1302-0206
Carla TaramascoCentro de Investigación y Desarrollo en Ingeniería en Salud, Universidad de Valparaíso, Valparaíso 2340000, Chile.ORCID https://orcid.org/0000-0001-8318-4201

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brain network analysis using functional magnetic resonance imaging (fMRI) is a widely used technique. The first step of brain network analysis in fMRI is to detect regions of interest (ROIs). The signals from these ROIs are then used to evaluate neural networks and quantify neuronal dynamics. The two main methods to identify ROIs are based on brain atlas registration and clustering. This work proposes a bioinspired method that combines both paradigms. The method, dubbed HAnt, consists of an anatomical clustering of the signal followed by an ant clustering step. The method is evaluated empirically in both

Indexed as

AlgorithmsAdultAtlases as TopicAuditory PerceptionBrainBrain MappingCluster AnalysisComputer SimulationFemaleHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleYoung Adult

Identifiers

PMID32082371
PMCPMC7012274

What OpenQuestion holds

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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.