Skip to main content

Experiments in sensory substitution and spiking neural networks

Time: Mon 2018-09-24 15.15

Location: Fantum

Participating: Jean Rouat

Export to calendar

Talk abstract:
Prof. Rouat, will present a simple vision to audition substitution
system and the results obtained with 50 subjects. He will discuss about
a potential mapping between the timbre of sounds and shape in vision.
Then, he will discuss his research in networks of spiking neurons and
present 2 applications: one in EEG classification with a regulated
spiking reservoir and unsupervised visual feature extractions with a
neurocomputational model of the peripheral visual system (from the
retina to V1) that learns on 10 mns of natural videos recorded outdoor.

Speaker bio:
Jean Rouat holds a M.Sc. degree in Physics from Univ. de Bretagne,
France (1981), an E. & E. M.Sc.A. degree in speech coding and speech
recognition from Univ. Sherbrooke (1984) and an E. & E. Ph.D. in
cognitive and statistical speech recognition jointly with Univ. de
Sherbrooke and McGill Univ. (1988). His post-doc has been in
psychoacoustics with the MRC, App. Psych. Unit, Cambridge, UK and in
electrophysiology with the Institute of physi- ology, Lausanne,
Switzerland. He is now with Univ. de Sherbrooke where he founded the
Computational Neuroscience and Intelligent Signal Processing Research
group (NECOTIS). He is also adjunct prof. in the biological sc. dep.,
Montreal Univ. His translational research links neuroscience and
engineering for the creation of new technologies and a better
understanding of learning multimodal representations. Development of
hardware low power consumption Neural Processing Units for a sustainable
development, interactions with artists for multimedia and musical
creations are examples of transfers that he leads based on the knowledge
he gains from neuroscience. He is leading funded projects to develop
sensory substitution and intelligent systems. He is also leading an
interdisciplinary CHIST-ERA european consortium (IGLU - Interactive
Grounded Language Understanding) for the development of an intelligent
agent that learns through interaction.