Mental rotation, a classic experimental paradigm of cognitive psychology, tests the capacity of humans to mentally rotate a seen object to decide if it matches a target object. In recent years, mental rotation has been investigated with brain imaging techniques to identify the brain areas involved. Mental rotation has also been investigated through the development of neural-network models, used to identify the specific mechanisms that underlie its process, and with neurorobotics models to investigate its embodied nature. Current models, however, have limited capacities to relate to neuro-scientific evidence, to generalise mental rotation to new objects, to suitably represent decision making mechanisms, and to allow the study of the effects of overt gestures on mental rotation. The work presented in this study overcomes these limitations by proposing a novel neurorobotic model that has a macro-architecture constrained by knowledge held on brain, encompasses a rather general mental rotation mechanism, and incorporates a biologically plausible decision making mechanism. The model was tested using the humanoid robot iCub in tasks requiring the robot to mentally rotate 2D geometrical images appearing on a computer screen. The results show that the robot gained an enhanced capacity to generalise mental rotation to new objects and to express the possible effects of overt movements of the wrist on mental rotation. The model also represents a further step in the identification of the embodied neural mechanisms that may underlie mental rotation in humans and might also give hints to enhance robots' planning capabilities.

Generalization, decision making, and embodiment effects in mental rotation: a neurorobotic architecture tested with a humanoid robot

Caligiore Daniele;Baldassarre Gianluca
2015

Abstract

Mental rotation, a classic experimental paradigm of cognitive psychology, tests the capacity of humans to mentally rotate a seen object to decide if it matches a target object. In recent years, mental rotation has been investigated with brain imaging techniques to identify the brain areas involved. Mental rotation has also been investigated through the development of neural-network models, used to identify the specific mechanisms that underlie its process, and with neurorobotics models to investigate its embodied nature. Current models, however, have limited capacities to relate to neuro-scientific evidence, to generalise mental rotation to new objects, to suitably represent decision making mechanisms, and to allow the study of the effects of overt gestures on mental rotation. The work presented in this study overcomes these limitations by proposing a novel neurorobotic model that has a macro-architecture constrained by knowledge held on brain, encompasses a rather general mental rotation mechanism, and incorporates a biologically plausible decision making mechanism. The model was tested using the humanoid robot iCub in tasks requiring the robot to mentally rotate 2D geometrical images appearing on a computer screen. The results show that the robot gained an enhanced capacity to generalise mental rotation to new objects and to express the possible effects of overt movements of the wrist on mental rotation. The model also represents a further step in the identification of the embodied neural mechanisms that may underlie mental rotation in humans and might also give hints to enhance robots' planning capabilities.
2015
Istituto di Scienze e Tecnologie della Cognizione - ISTC
Neural networks; Neurorobotic model of mental rotation; Brain cortex areas; Embodiment and robots; Mental imagery; Forward models
planning and decision making
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/303708
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