Functional mechanisms of probabilistic inference in feature- and space-based attentional systems.
Neuroimage
; 142: 553-564, 2016 Nov 15.
Article
em En
| MEDLINE
| ID: mdl-27523448
ABSTRACT
Humans flexibly attend to features or locations and these processes are influenced by the probability of sensory events. We combined computational modeling of response times with fMRI to compare the functional correlates of (re-)orienting, and the modulation by probabilistic inference in spatial and feature-based attention systems. Twenty-four volunteers performed two task versions with spatial or color cues. Percentage of cue validity changed unpredictably. A hierarchical Bayesian model was used to derive trial-wise estimates of probability-dependent attention, entering the fMRI analysis as parametric regressors. Attentional orienting activated a dorsal frontoparietal network in both tasks, without significant parametric modulation. Spatially invalid trials activated a bilateral frontoparietal network and the precuneus, while invalid feature trials activated the left intraparietal sulcus (IPS). Probability-dependent attention modulated activity in the precuneus, left posterior IPS, middle occipital gyrus, and right temporoparietal junction for spatial attention, and in the left anterior IPS for feature-based and spatial attention. These findings provide novel insights into the generality and specificity of the functional basis of attentional control. They suggest that probabilistic inference can distinctively affect each attentional subsystem, but that there is an overlap in the left IPS, which responds to both spatial and feature-based expectancy violations.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Desempenho Psicomotor
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Atenção
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Percepção Espacial
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Percepção Visual
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Mapeamento Encefálico
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Imageamento por Ressonância Magnética
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Córtex Cerebral
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Sinais (Psicologia)
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Modelos Teóricos
Tipo de estudo:
Prognostic_studies
Limite:
Adolescent
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Adult
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Female
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Humans
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Male
Idioma:
En
Revista:
Neuroimage
Assunto da revista:
DIAGNOSTICO POR IMAGEM
Ano de publicação:
2016
Tipo de documento:
Article