Dataset Information

Learning of arbitrary association between visual and auditory novel stimuli in adults: the "bond effect" of haptic exploration.

ABSTRACT: BACKGROUND: It is well-known that human beings are able to associate stimuli (novel or not) perceived in their environment. For example, this ability is used by children in reading acquisition when arbitrary associations between visual and auditory stimuli must be learned. The studies tend to consider it as an "implicit" process triggered by the learning of letter/sound correspondences. The study described in this paper examined whether the addition of the visuo-haptic exploration would help adults to learn more effectively the arbitrary association between visual and auditory novel stimuli. METHODOLOGY/PRINCIPAL FINDINGS: Adults were asked to learn 15 new arbitrary associations between visual stimuli and their corresponding sounds using two learning methods which differed according to the perceptual modalities involved in the exploration of the visual stimuli. Adults used their visual modality in the "classic" learning method and both their visual and haptic modalities in the "multisensory" learning one. After both learning methods, participants showed a similar above-chance ability to recognize the visual and auditory stimuli and the audio-visual associations. However, the ability to recognize the visual-auditory associations was better after the multisensory method than after the classic one. CONCLUSION/SIGNIFICANCE: This study revealed that adults learned more efficiently the arbitrary association between visual and auditory novel stimuli when the visual stimuli were explored with both vision and touch. The results are discussed from the perspective of how they relate to the functional differences of the manual haptic modality and the hypothesis of a "haptic bond" between visual and auditory stimuli.

SUBMITTER: Fredembach B

PROVIDER: S-EPMC2653648 | biostudies-other | 2009

REPOSITORIES: biostudies-other

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Learning of arbitrary association between visual and auditory novel stimuli in adults: the "bond effect" of haptic exploration.

Fredembach Benjamin B de Boisferon Anne Hillairet AH Gentaz Edouard E

PloS one 20090316 3

<h4>Background</h4>It is well-known that human beings are able to associate stimuli (novel or not) perceived in their environment. For example, this ability is used by children in reading acquisition when arbitrary associations between visual and auditory stimuli must be learned. The studies tend to consider it as an "implicit" process triggered by the learning of letter/sound correspondences. The study described in this paper examined whether the addition of the visuo-haptic exploration would h ...[more]

PMID: 19287486

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Project description:Haptic exploration is a key skill for both robots and humans to discriminate and handle unknown objects or to recognize familiar objects. Its active nature is evident in humans who from early on reliably acquire sophisticated sensory-motor capabilities for active exploratory touch and directed manual exploration that associates surfaces and object properties with their spatial locations. This is in stark contrast to robotics. In this field, the relative lack of good real-world interaction models-along with very restricted sensors and a scarcity of suitable training data to leverage machine learning methods-has so far rendered haptic exploration a largely underdeveloped skill. In robot vision however, deep learning approaches and an abundance of available training data have triggered huge advances. In the present work, we connect recent advances in recurrent models of visual attention with previous insights about the organisation of human haptic search behavior, exploratory procedures and haptic glances for a novel architecture that learns a generative model of haptic exploration in a simulated three-dimensional environment. This environment contains a set of rigid static objects representing a selection of one-dimensional local shape features embedded in a 3D space: an edge, a flat and a convex surface. The proposed algorithm simultaneously optimizes main perception-action loop components: feature extraction, integration of features over time, and the control strategy, while continuously acquiring data online. Inspired by the Recurrent Attention Model, we formalize the target task of haptic object identification in a reinforcement learning framework and reward the learner in the case of success only. We perform a multi-module neural network training, including a feature extractor and a recurrent neural network module aiding pose control for storing and combining sequential sensory data. The resulting haptic meta-controller for the rigid 16 × 16 tactile sensor array moving in a physics-driven simulation environment, called the Haptic Attention Model, performs a sequence of haptic glances, and outputs corresponding force measurements. The resulting method has been successfully tested with four different objects. It achieved results close to 100% while performing object contour exploration that has been optimized for its own sensor morphology.

Project description:Robotic algorithms that augment movement errors have been proposed as promising training strategies to enhance motor learning and neurorehabilitation. However, most research effort has focused on rehabilitation of upper limbs, probably because large movement errors are especially dangerous during gait training, as they might result in stumbling and falling. Furthermore, systematic large movement errors might limit the participants' motivation during training. In this study, we investigated the effect of training with novel error modulating strategies, which guarantee a safe training environment, on motivation and learning of a modified asymmetric gait pattern. Thirty healthy young participants walked in the exoskeletal robotic system Lokomat while performing a foot target-tracking task, which required an increased hip and knee flexion in the dominant leg. Learning the asymmetric gait pattern with three different strategies was evaluated: (i) No disturbance: no robot disturbance/guidance was applied, (ii) haptic error amplification: unsafe and discouraging large errors were limited with haptic guidance, while haptic error amplification enhanced awareness of small errors relevant for learning, and (iii) visual error amplification: visually observed errors were amplified in a virtual reality environment. We also evaluated whether increasing the movement variability during training by adding randomly varying haptic disturbances on top of the other training strategies further enhances learning. We analyzed participants' motor performance and self-reported intrinsic motivation before, during and after training. We found that training with the novel haptic error amplification strategy did not hamper motor adaptation and enhanced transfer of the practiced asymmetric gait pattern to free walking. Training with visual error amplification, on the other hand, increased errors during training and hampered motor learning. Participants who trained with visual error amplification also reported a reduced perceived competence. Adding haptic disturbance increased the movement variability during training, but did not have a significant effect on motor adaptation, probably because training with haptic disturbance on top of visual and haptic error amplification decreased the participants' feelings of competence. The proposed novel haptic error modulating controller that amplifies small task-relevant errors while limiting large errors outperformed visual error augmentation and might provide a promising framework to improve robotic gait training outcomes in neurological patients.

Dataset Information

Learning of arbitrary association between visual and auditory novel stimuli in adults: the "bond effect" of haptic exploration.

Publications

Learning of arbitrary association between visual and auditory novel stimuli in adults: the "bond effect" of haptic exploration.

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