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Paul Bach Y Rita [1] is the precursor of sensory substitutions. He started thirty years ago using visuo-tactile prostheses with the intent of satisfying blind people. These prostheses, called Tactile Vision Substitution Systems (TVSS), transform a sensory input from a given modality (vision) into another modality (touch). These new systems seemed to induce quasi-visual perceptions. One of the authors interests dealt with the understanding of the coupling between actions and sensations in perception mechanisms [4]. Throughout his search, he noticed that the subjects had to move the camera themselves in order to recognise a 3D target-object or a figure placed in front of them. Our work consists in understanding how sensory information provided by a visuo-tactile prosthesis can be used for motor behaviour. In this aim, we used the most simple substitution device (one photoreceptor coupled with one tactile stimulator) in order to control and enrich our knowledge of the ties between perception and action.
In this preliminary study we address the question of the influence of handedness on the localization of targets perceived through a visuo-auditory substitution device. Participants hold the device in one hand in order to explore the environment and t
We present a theoretical study aiming at model fitting for sensory neurons. Conventional neural network training approaches are not applicable to this problem due to lack of continuous data. Although the stimulus can be considered as a smooth time de
The cerebrospinal fluid (CSF) constitutes an interface through which chemical cues can reach and modulate the activity of neurons located at the epithelial boundary within the entire nervous system. Here, we investigate the role and functional connec
Pain is a multidimensional process, which can be modulated by emotions, however, the mechanisms underlying this modulation are unknown. We used pictures with different emotional valence (negative, positive, neutral) as primes and applied electrical p
Correlations in sensory neural networks have both extrinsic and intrinsic origins. Extrinsic or stimulus correlations arise from shared inputs to the network, and thus depend strongly on the stimulus ensemble. Intrinsic or noise correlations reflect