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Toward a “treadmill test” for cognition: Improved prediction of general cognitive ability from the task activated brain

dc.contributor.authorSripada, Chandra
dc.contributor.authorAngstadt, Mike
dc.contributor.authorRutherford, Saige
dc.contributor.authorTaxali, Aman
dc.contributor.authorShedden, Kerby
dc.date.accessioned2020-08-10T20:53:59Z
dc.date.availableWITHHELD_13_MONTHS
dc.date.available2020-08-10T20:53:59Z
dc.date.issued2020-08-15
dc.identifier.citationSripada, Chandra; Angstadt, Mike; Rutherford, Saige; Taxali, Aman; Shedden, Kerby (2020). "Toward a “treadmill test” for cognition: Improved prediction of general cognitive ability from the task activated brain." Human Brain Mapping 41(12): 3186-3197.
dc.identifier.issn1065-9471
dc.identifier.issn1097-0193
dc.identifier.urihttps://hdl.handle.net/2027.42/156167
dc.description.abstractGeneral cognitive ability (GCA) refers to a trait‐like ability that contributes to performance across diverse cognitive tasks. Identifying brain‐based markers of GCA has been a longstanding goal of cognitive and clinical neuroscience. Recently, predictive modeling methods have emerged that build whole‐brain, distributed neural signatures for phenotypes of interest. In this study, we employ a predictive modeling approach to predict GCA based on fMRI task activation patterns during the N‐back working memory task as well as six other tasks in the Human Connectome Project dataset (n = 967), encompassing 15 task contrasts in total. We found tasks are a highly effective basis for prediction of GCA: The 2‐back versus 0‐back contrast achieved a 0.50 correlation with GCA scores in 10‐fold cross‐validation, and 13 out of 15 task contrasts afforded statistically significant prediction of GCA. Additionally, we found that task contrasts that produce greater frontoparietal activation and default mode network deactivation—a brain activation pattern associated with executive processing and higher cognitive demand—are more effective in the prediction of GCA. These results suggest a picture analogous to treadmill testing for cardiac function: Placing the brain in a more cognitively demanding task state significantly improves brain‐based prediction of GCA.We investigated prediction of general cognitive ability (GCA) based on fMRI task activation patterns with 15 task contrasts in the Human Connectome Project dataset. The 2‐back versus 0‐back contrast achieved a 0.50 correlation with GCA scores in ten10‐fold cross‐validation analysis. Additionally, we found that task contrasts that produce greater fronto‐parietal activation and default mode network deactivation—a brain activation pattern associated with executive processing and higher cognitive demand—are more effective in GCA prediction.
dc.publisherJohn Wiley & Sons, Inc.
dc.titleToward a “treadmill test” for cognition: Improved prediction of general cognitive ability from the task activated brain
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelKinesiology and Sports
dc.subject.hlbsecondlevelNeurosciences
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/156167/2/hbm25007.pdfen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/156167/1/hbm25007_am.pdfen_US
dc.identifier.doi10.1002/hbm.25007
dc.identifier.sourceHuman Brain Mapping
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