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Model-based fMRI analysis of memory

Love, BC; (2020) Model-based fMRI analysis of memory. Current Opinion in Behavioral Sciences , 32 pp. 88-93. 10.1016/j.cobeha.2020.02.012. Green open access

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Abstract

Recent advances in Model-based fMRI approaches enable researchers to investigate hypotheses about the time course and latent structure in data that were previously inaccessible. Cognitive models, especially when validated on multiple datasets, allow for additional constraints to be marshalled when interpreting neuroimaging data. Models can be related to BOLD response in a variety of ways, such as constraining the cognitive model by neural data, interpreting the neural data in light of behavioural fit, or simultaneously accounting for both neural and behavioural data. Using cognitive models as a lens on fMRI data is complementary to popular multivariate decoding and representational similarity analysis approaches. Indeed, these approaches can realise greater theoretical significance when situated within a model-based approach.

Type: Article
Title: Model-based fMRI analysis of memory
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.cobeha.2020.02.012
Publisher version: https://doi.org/10.1016/j.cobeha.2020.02.012
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Experimental Psychology
URI: https://discovery.ucl.ac.uk/id/eprint/10094472
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