Developmental trajectories for model-free and model-based reinforcement learning: computational and neural bases

Información del proyecto

DEVELOP‐LEARNING

Identificador del acuerdo de subvención: 328822

Proyecto cerrado

Fecha de inicio 1 Enero 2014

Fecha de finalización 31 Diciembre 2015

Financiado con arreglo a

• Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)

Coste total

€ 231 283,20

Aportación de la UE

€ 231 283,20

Coordinado por

UNIVERSITY COLLEGE LONDON

Objetivo

Adolescence is defined as the period of life that starts with the biological changes of puberty and ends at the time at which the individual attains a stable, independent role in society. During this period, decisions are characterized by being impulsive and high-risk, and this can have serious consequences, for example accidents caused by dangerous driving and experimentation with alcohol and drugs. It is thus important to understand the neurocognitive processes that underlie decision-making in adolescence.
Decision-making depends on the interaction of several component processes, including the representation of value, response selection and learning. In reinforcement learning all these processes are integrated. Reinforcement learning deals with the ability of learning to improve one’s future choices in order to maximize the occurrence of pleasant events (rewards) and minimize the occurrence of unpleasant events (punishments).
Theoretical models for reinforcement learning postulate the existence of a dual controller for action selection: ‘Model-free’, which is computationally simple, more reflexive and inflexible and ‘Model-based’, which is more reflective and flexible, but computationally complex.
The development of reinforcement learning in human adolescence has been studied only recently. Studies to date have not attempted to disentangle model-free and model-based behaviour. The aims of the current project are: i. to map the development of reinforcement learning systems – via behavioural/computational analysis - and ii. to relate the maturation of model-based reinforcement learning to the functional maturation of specific neural circuits – via functional magnetic resonance experiment.
This study will provide further insights in adolescent reward-based decision-making and its neural bases, within the theoretical framework of reinforcement learning.

Ámbito científico (EuroSciVoc)

• ciencias naturales › informática y ciencias de la información › inteligencia artificial › aprendizaje automático › aprendizaje por refuerzo

Programa(s)

• FP7-PEOPLE - Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)

Tema(s)

• FP7-PEOPLE-2012-IEF - Marie-Curie Action: "Intra-European fellowships for career development"

Convocatoria de propuestas

FP7-PEOPLE-2012-IEF
Consulte otros proyectos de esta convocatoria

Régimen de financiación

MC-IEF - Intra-European Fellowships (IEF)

Coordinador

UNIVERSITY COLLEGE LONDON

• Aportación de la UE: € 231 283,20
• Dirección: GOWER STREET ; WC1E 6BT LONDON ;
• Tipo de actividad: Higher or Secondary Education Establishments
• Coste total: Sin datos