Some common fallacies in arguments from M/EEG data

Like all humans, M/EEG researchers commit certain fallacies or mistakes in reasoning. This article surveys seven well-known but still common fallacies, including reverse inference, hasty generalization, hasty exclusion, inferring from group to individual, inferring from correlation to causation, aff...

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Autores principales:	Walter Sinnott-Armstrong, Claire Simmons
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/203e0a97997946c49d4fc28c1619a836
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spelling	oai:doaj.org-article:203e0a97997946c49d4fc28c1619a8362021-12-02T04:59:31ZSome common fallacies in arguments from M/EEG data1095-957210.1016/j.neuroimage.2021.118725https://doaj.org/article/203e0a97997946c49d4fc28c1619a8362021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1053811921009976https://doaj.org/toc/1095-9572Like all humans, M/EEG researchers commit certain fallacies or mistakes in reasoning. This article surveys seven well-known but still common fallacies, including reverse inference, hasty generalization, hasty exclusion, inferring from group to individual, inferring from correlation to causation, affirming a disjunct, and false dichotomy. These fallacies are illustrated with classic EEG research by Libet and collaborators, but many researchers (not just Libet) continue to commit them in all areas of research (not just M/EEG). This article gives practical suggestions about how to spot and avoid each fallacy.Walter Sinnott-ArmstrongClaire SimmonsElsevierarticleNeurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENNeuroImage, Vol 245, Iss , Pp 118725- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
spellingShingle	Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Walter Sinnott-Armstrong Claire Simmons Some common fallacies in arguments from M/EEG data
description	Like all humans, M/EEG researchers commit certain fallacies or mistakes in reasoning. This article surveys seven well-known but still common fallacies, including reverse inference, hasty generalization, hasty exclusion, inferring from group to individual, inferring from correlation to causation, affirming a disjunct, and false dichotomy. These fallacies are illustrated with classic EEG research by Libet and collaborators, but many researchers (not just Libet) continue to commit them in all areas of research (not just M/EEG). This article gives practical suggestions about how to spot and avoid each fallacy.
format	article
author	Walter Sinnott-Armstrong Claire Simmons
author_facet	Walter Sinnott-Armstrong Claire Simmons
author_sort	Walter Sinnott-Armstrong
title	Some common fallacies in arguments from M/EEG data
title_short	Some common fallacies in arguments from M/EEG data
title_full	Some common fallacies in arguments from M/EEG data
title_fullStr	Some common fallacies in arguments from M/EEG data
title_full_unstemmed	Some common fallacies in arguments from M/EEG data
title_sort	some common fallacies in arguments from m/eeg data
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/203e0a97997946c49d4fc28c1619a836
work_keys_str_mv	AT waltersinnottarmstrong somecommonfallaciesinargumentsfrommeegdata AT clairesimmons somecommonfallaciesinargumentsfrommeegdata
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Some common fallacies in arguments from M/EEG data

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