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Prediction in infants and adults: A pupillometry study
- Source :
- Dev Sci
- Publication Year :
- 2018
-
Abstract
- Adults use both bottom-up sensory inputs and top-down signals to generate predictions about future sensory inputs. Infants have also been shown to make predictions with simple stimuli and recent work has suggested top-down processing is available early in infancy. However, it is unknown whether this indicates that top-down prediction is an ability that is continuous across the lifespan or whether an infant's ability to predict is different from an adult's, qualitatively or quantitatively. We employed pupillometry to provide a direct comparison of prediction abilities across these disparate age groups. Pupil dilation response (PDR) was measured in 6-month olds and adults as they completed an identical implicit learning task designed to help learn associations between sounds and pictures. We found significantly larger PDR for visual omission trials (i.e. trials that violated participants' predictions without the presentation of new stimuli to control for bottom-up signals) compared to visual present trials (i.e. trials that confirmed participants' predictions) in both age groups. Furthermore, a computational learning model that is closely linked to prediction error (Rescorla-Wagner model) demonstrated similar learning trajectories suggesting a continuity of predictive capacity and learning across the two age groups.
- Subjects :
- Adult
Male
medicine.medical_specialty
Visual perception
Cognitive Neuroscience
Sensory system
Audiology
Reflex, Pupillary
050105 experimental psychology
Article
Task (project management)
03 medical and health sciences
Young Adult
0302 clinical medicine
Cognition
Developmental and Educational Psychology
Pupillary response
medicine
Humans
Learning
0501 psychology and cognitive sciences
Computer Simulation
05 social sciences
Eye movement
Infant
Implicit learning
Sound
Female
Psychology
030217 neurology & neurosurgery
Pupillometry
Forecasting
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Dev Sci
- Accession number :
- edsair.doi.dedup.....8d3ea5df78c1cce0b4f30cc202557e28