Inferring Mental States from Neuroimaging Data: From Reverse Inference to Large-Scale Decoding

A common goal of neuroimaging research is to use imaging data to identify the mental processes that are engaged when a subject performs a mental task. The use of reasoning from activation to mental functions, known as “reverse inference,” has been previously criticized on the basis that it does not...

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Bibliographic Details
Published inNeuron (Cambridge, Mass.) Vol. 72; no. 5; pp. 692 - 697
Main Author Poldrack, Russell A.
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 08.12.2011
Elsevier Limited
Subjects
Brain
Brain - physiology
Cognition & reasoning
Computed tomography
Humans
Hypotheses
Medical imaging
Mental Processes - physiology
Neuroimaging
Neurosciences
Ontology
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ISSN0896-6273
1097-4199
1097-4199
DOI10.1016/j.neuron.2011.11.001

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Summary:A common goal of neuroimaging research is to use imaging data to identify the mental processes that are engaged when a subject performs a mental task. The use of reasoning from activation to mental functions, known as “reverse inference,” has been previously criticized on the basis that it does not take into account how selectively the area is activated by the mental process in question. In this Perspective, I outline the critique of informal reverse inference and describe a number of new developments that provide the ability to more formally test the predictive power of neuroimaging data.
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ISSN:0896-6273
1097-4199
1097-4199
DOI:10.1016/j.neuron.2011.11.001