Characterizing individual differences in reward sensitivity from the brain networks involved in response inhibition
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Scholar |
Otros documentos de la autoría: Fuentes-Claramonte, Paola; Avila, Cesar; Rodríguez Pujadas, Aina; Costumero, Víctor; Ventura Campos, Mercedes; Bustamante, Juan Carlos; Rosell Negre, Patricia; Barrós-Loscertales, Alfonso
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/8033
comunitat-uji-handle3:10234/8636
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http://dx.doi.org/10.1016/j.neuroimage.2015.08.067 |
Metadatos
Título
Characterizing individual differences in reward sensitivity from the brain networks involved in response inhibitionAutoría
Fecha de publicación
2016Editor
ElsevierISSN
1053-8119; 1095-9572Cita bibliográfica
FUENTES-CLARAMONTE, Paola, et al. Characterizing individual differences in reward sensitivity from the brain networks involved in response inhibition. NeuroImage, 2016, vol. 124, Part A, p. 287-299.Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://www.sciencedirect.com/science/article/pii/S1053811915007880Palabras clave / Materias
Resumen
A “disinhibited” cognitive profile has been proposed for individuals with high reward sensitivity, characterized by increased engagement in goal-directed responses and reduced processing of negative or unexpected cues, ... [+]
A “disinhibited” cognitive profile has been proposed for individuals with high reward sensitivity, characterized by increased engagement in goal-directed responses and reduced processing of negative or unexpected cues, which impairs adequate behavioral regulation after feedback in these individuals. This pattern is manifested through deficits in inhibitory control and/or increases in RT variability. In the present work, we aimed to test whether this profile is associated with the activity of functional networks during a stop-signal task using independent component analysis (ICA). Sixty-one participants underwent fMRI while performing a stop-signal task, during which a manual response had to be inhibited. ICA was used to mainly replicate the functional networks involved in the task (Zhang and Li, 2012): two motor networks involved in the go response, the left and right fronto-parietal networks for stopping, a midline error-processing network, and the default-mode network (DMN), which was further subdivided into its anterior and posterior parts. Reward sensitivity was mainly associated with greater activity of motor networks, reduced activity in the midline network during correct stop trials and, behaviorally, increased RT variability. All these variables explained 36% of variance of the SR scores. This pattern of associations suggests that reward sensitivity involves greater motor engagement in the dominant response, more distractibility and reduced processing of salient or unexpected events, which may lead to disinhibited behavior. [-]
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NeuroImage, 2016, vol. 124, Part ADerechos de acceso
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