dc.creatorWainstein Bezamat Gabriel
dc.creatorRojas Libano, Daniel
dc.creatorMedel Sierralta, Vicente Nicolas
dc.creatorAlnaes, Dag
dc.creatorKolskar, Knut K.
dc.creatorEndestad, Tor
dc.creatorLaeng, Bruno
dc.creatorOssandon Valdes Tomas
dc.creatorCrossley Karmelic, Nicolas Andrés
dc.creatorMatar, Elie
dc.creatorShine, James M.
dc.date.accessioned2024-06-09T01:50:51Z
dc.date.accessioned2024-07-17T21:25:31Z
dc.date.available2024-06-09T01:50:51Z
dc.date.available2024-07-17T21:25:31Z
dc.date.created2024-06-09T01:50:51Z
dc.date.issued2021
dc.identifier10.1162/netn_a_00205
dc.identifier2472-1751
dc.identifierhttps://doi.org/10.1162/netn_a_00205
dc.identifierhttps://repositorio.uc.cl/handle/11534/86648
dc.identifierWOS:000731689000003
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9509882
dc.description.abstractIn our daily lives, it is usual to encounter highly demanding cognitive tasks. They have been traditionally regarded as challenges that are solved mainly through cerebral activity, specifically via information-processing steps carried by neurons in the cerebral cortex. Activity in cortical networks thus constitutes a key factor for improving our understanding of cognitive processes. However, recent evidence has shown that evolutionary older players in the central nervous system, such as brain stem's ascending modulatory systems, might play an equally important role in diverse cognitive mechanisms. Our article examines the role of the ascending arousal system on large-scale network dynamics by combining pupillometry, functional MRI, and graph theoretical analysis.
dc.languageen
dc.publisherThe Mit Press
dc.rightsacceso abierto
dc.subjectPupil diameter
dc.subjectLocus coeruleus
dc.subjectNetwork integration
dc.subjectNoradrenergic system
dc.subjectNeuromodulation
dc.subjectAttention
dc.subjectMental effort
dc.subjectfMRI
dc.subjectCortical States
dc.subjectResponse-Time
dc.subjectAdaptive Gain
dc.subjectNoradrenaline
dc.subjectConnectivity
dc.subjectActivation
dc.titleThe ascending arousal system promotes optimal performance through mesoscale network integration in a visuospatial attentional task
dc.typeartículo


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