Evidence map›Paper›PMID 36704631›Full record

ArticleCognitive neurodynamics2023

Generalised exponential-Gaussian distribution: a method for neural reaction time analysis.

Fernando Marmolejo-Ramos, Carlos Barrera-Causil, Shenbing Kuang, Zeinab Fazlali, Detlef Wegener, Thomas Kneib, Fernanda De Bastiani, Guillermo Martinez-Flórez

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cognitive neurodynamics, 2023. 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
2.0field-weighted citation impact, top 14% of its field
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, 23 citations in OpenAlex.

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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

8 authors at 8 institutions in 7 countries.

Fernando Marmolejo-RamosCentre for Change and Complexity in Learning, University of South Australia, Adelaide, 5000 Australia.ORCID 0000-0003-4680-1287
Carlos Barrera-CausilFacultad de Ciencias Exactas y Aplicadas, Instituto Tecnológico Metropolitano -ITM, Medellín, 050034 Colombia.
Shenbing KuangInstitute of Psychology, Chinese Academy of Sciences, Beijing, 100101 China.
Zeinab FazlaliSchool of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.
Detlef WegenerBrain Research Institute, Center for Cognitive Science, University of Bremen, Bremen, Germany.
Thomas KneibCampus Institute Data Science (CIDAS) and Chair of Statistics, Georg-August-Universität Göttingen, Göttingen, Germany.
Fernanda De BastianiStatistics Department, Federal University of Pernambuco, Recife, Pernambuco Brazil.
Guillermo Martinez-FlórezDepartamento de Matemáticas y Estadística, Facultad de Ciencias, Universidad de Córdoba, Córdoba, 2300 Colombia.
Institute of Psychology, Chinese Academy of Sciences · CNInstituto Tecnológico Metropolitano · CONew York Psychoanalytic Society and Institute · USUniversidade Federal de Pernambuco · BRUniversidade Federal do Ceará · BRUniversity of Bremen · DEUniversity of Göttingen · DEUniversity of South Australia · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reaction times (RTs) are an essential metric used for understanding the link between brain and behaviour. As research is reaffirming the tight coupling between neuronal and behavioural RTs, thorough statistical modelling of RT data is thus essential to enrich current theories and motivate novel findings. A statistical distribution is proposed herein that is able to model the complete RT's distribution, including location, scale and shape: the generalised-exponential-Gaussian (GEG) distribution. The GEG distribution enables shifting the attention from traditional means and standard deviations to the entire RT distribution. The mathematical properties of the GEG distribution are presented and investigated via simulations. Additionally, the GEG distribution is featured via four real-life data sets. Finally, we discuss how the proposed distribution can be used for regression analyses via generalised additive models for location, scale and shape (GAMLSS).

Indexed as

Cognitive neuroscienceExponential Gaussian distributionGeneralised additive models for location, Scale and shapeNeuronal response latencyReaction times

Identifiers

PMID36704631
PMCPMC9871144
OpenAlexW4280566858

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.