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Default Mode Contributions to Automated Information Processing

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Menon, DK 
Stamatakis, EA 


Concurrent with mental processes that require rigorous computation and control, a series of automated decisions and actions govern our daily lives, providing efficient and adaptive responses to environmental demands. Using a cognitive flexibility task, we show that a set of brain regions collectively known as the default mode network play a crucial role in such “autopilot” behavior, i.e. when rapidly selecting appropriate responses under predictable behavioral contexts. While applying learned rules, the default mode network shows both greater activity and connectivity. Furthermore, functional interactions between this network and hippocampal, parahippocampal areas as well as primary visual cortex correlate with the speed of accurate responses. These findings indicate a memory-based “autopilot role” for the default mode network, which may have important implications for our current understanding of healthy and adaptive brain processing.



autopilot, cognitive flexibility, default mode network, functional connectivity, functional magnetic resonance imaging, Adult, Brain Mapping, Female, Hippocampus, Humans, Magnetic Resonance Imaging, Male, Mental Processes, Models, Neurological, Nerve Net, Neural Pathways, Neuropsychological Tests, Visual Cortex

Journal Title

Proceedings of the National Academy of Sciences of the United States of America

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National Academy of Sciences
Department of Health (via National Institute for Health Research (NIHR)) (unknown)
Department of Health (via National Institute for Health Research (NIHR)) (unknown)
We thank Mrs. Victoria Lupson, Ms. Karen Welsh, Dr. Marius Mada, and the rest of the staff in the Wolfson Brain Imaging Centre (WBIC) at Addenbrooke’s Hospital for their assistance in MRI scanning. In addition, we thank all the participants for their contribution to this study. This study was funded by the Yousef Jameel Academic Program grant (awarded to D.V.). Additionally, D.K.M. is supported by the National Institute for Health Research (NIHR) Cambridge Biomedical Centre (RCZB/004) and an NIHR Senior Investigator Award (RCZB/014), and E.A.S. is funded by the Stephen Erskine Fellowship Queens’ College, Cambridge.