Data

Latin Square Task MRI

The University of Queensland
Dr Luca Cocchi (Aggregated by) Dr Luca Cocchi (Aggregated by) Dr Luke Hearne (Aggregated by) Dr Luke Hearne (Aggregated by) Professor Jason Mattingley (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.14264/uql.2019.780&rft.title=Latin Square Task MRI&rft.identifier=10.14264/uql.2019.780&rft.publisher=The University of Queensland&rft.description=This dataset was collected as part of Luke Hearne’s PhD work at the University of Queensland. We were interested in investigating how functional brain networks (as measured by MRI) change as individuals complete increasingly complex tasks. We were also interested in whether these network changes are related to task performance and differences in fluid intelligence. To investigate this, we collected a number of behavioural data measures (including tests of fluid intelligence) and recorded brain signals while participants completed the Latin Square Task. Each participant completed a pre-task resting state scan, followed by three runs of the Latin Square Task, a structural brain scan and a post-task resting state scan. In addition, they completed the Raven’s advanced progressive matrices, the form boards task, the paper folding task and a visual search task outside of the scanner. The data has been deidentified and is organised in BIDS format. Please cite the following paper if you use the data: Hearne, L. J., Cocchi, L., Zalesky, A., & Mattingley. (2017). Reconfiguration of brain network architectures between resting state and complexity-dependent cognitive reasoning, Journal of Neuroscience&rft.creator=Dr Luca Cocchi&rft.creator=Dr Luca Cocchi&rft.creator=Dr Luke Hearne&rft.creator=Dr Luke Hearne&rft.creator=Professor Jason Mattingley&rft.creator=Professor Jason Mattingley&rft.date=2019&rft_rights= http://creativecommons.org/licenses/by/3.0/deed.en_US&rft_subject=eng&rft_subject=fMRI&rft_subject=MRI&rft_subject=Reasoning&rft_subject=Fluid intelligence&rft_subject=Neurocognitive Patterns and Neural Networks&rft_subject=PSYCHOLOGY AND COGNITIVE SCIENCES&rft_subject=COGNITIVE SCIENCE&rft_subject=Expanding Knowledge in Psychology and Cognitive Sciences&rft_subject=EXPANDING KNOWLEDGE&rft_subject=EXPANDING KNOWLEDGE&rft.type=dataset&rft.language=English Access the data
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This dataset was collected as part of Luke Hearne’s PhD work at the University of Queensland. We were interested in investigating how functional brain networks (as measured by MRI) change as individuals complete increasingly complex tasks. We were also interested in whether these network changes are related to task performance and differences in fluid intelligence. To investigate this, we collected a number of behavioural data measures (including tests of fluid intelligence) and recorded brain signals while participants completed the Latin Square Task. Each participant completed a pre-task resting state scan, followed by three runs of the Latin Square Task, a structural brain scan and a post-task resting state scan. In addition, they completed the Raven’s advanced progressive matrices, the form boards task, the paper folding task and a visual search task outside of the scanner. The data has been deidentified and is organised in BIDS format. Please cite the following paper if you use the data: Hearne, L. J., Cocchi, L., Zalesky, A., & Mattingley. (2017). Reconfiguration of brain network architectures between resting state and complexity-dependent cognitive reasoning, Journal of Neuroscience

Issued: 2019

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Subjects
Cognitive Science | Expanding Knowledge | Expanding Knowledge | Expanding Knowledge in Psychology and Cognitive Sciences | Fluid intelligence | MRI | Neurocognitive Patterns and Neural Networks | Psychology and Cognitive Sciences | Reasoning | eng | fMRI |

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