[Comp-neuro] Fully funded PhD position at the Laboratoire des
Neuroscience Cognitive and Group for Neural Theory, ENS, Paris,
boris.gutkin at gmail.com
Fri Oct 1 15:01:09 CEST 2010
A fully funded PhD is available in the Laboratoire de Neuroscience
Cognitives (Departement des Etudes Cognitives, ENS, Paris) in
computational models of speech perception.
The interdisciplinary PhD will be co-supervised by Anne-Lise Giraud
(neuroscience, Auditory Language Group http://www.giraud.ens.fr/ ) and
Boris Gutkin (modelling, Group for Neural Theory http://
www.gnt.ens.fr/ ). A more detailed description is given below.
We encourage applications from students with quantitive backgrounds
(math, physics, engineering) interested in neuroscience training and/
or students with a strong neuroscience background and quantitive
training interested in computational modeling.
Interested individuals should contact: Alexandre Hayfil (alexandre.hyafil at gmail.com
); Anne-Lise Giraud (Anne-Lise.Giraud at ens.fr) or Boris Gutkin (boris.gutkin at ens.fr
Laboratoire de Neurosciences Cognitives, Département d’Etudes Cognitives
Auditory Langauge Group/ Group for Neural Theory
Ecole Normale Supérieure, Paris
The neural mechanisms underpinning such a complex function as speech
comprehension remain to a large extent unknown. Speech neural networks
have been identified within the brain but it is not clear how the
continous acoustic input is segmented and subsequently categorized
into units of different time scales: phonemes, syllables, words, and
ultimately sentences to which semantic significance can be attached.
Actually, it is not even clear how relevant these different categories
are to brain processing.
A wealth of data suggests that speech processing at each level (from
phonemes to words) is paralelled by synchronisation of neural
responses at a corresponding frequency. Moreover, these oscillations
seem to be nested into each other, so that the lower frequency
oscillator controls the amplitude of higher frequency. A recent
phenomenological model ties up all these elements by proposing that
speech processing is controlled by a cascade of neural oscillators
(from 5-10 Hz to 60-120 Hz) that chunk the acoustic signal into bits
of the relevant size. The oscillators would be phase-locked to the
signal and thus allow appropriate discretization and categorization,
thanks to nesting mechanisms.
The properties of this model need to be clarified and put together
into a computationnal model in order to prove its operability and
provide further tests for neural investigation. At first, though
single-frequency neural oscillators are very well documented, a
plausible model is yet to be proposed showing how low frequency
oscillations can control high frequency oscillations. Second, the
model has so far been only tested on rudimentary signal on a single
time scale. Building a full model with interacting oscillators being
able to deal with natural speech and setting the pathway towards
access to the lexicon is thus the final objective of this work.
This project will be undertaken by a joint team involving the hired
PhD student and a postdoctorate of the lab (Alexandre Hyafil). It will
be supervised both by Anne-Lise Giraud for the functional components
and Boris Gutkin for the modelling aspects. This work also involved a
collaboration with Oded Ghitza (Center for Biodynamics, Boston
University). Computational modelling will be the primary tool. It is
meant to bring together elements taken from a number of scientific
domains, including neurophysiology, neuroimaging, psycholinguistics,
phonetics and automatic speech recognition.
Shamir M, Ghitza O, Epstein S, Kopell N. Representation of time-
varying stimuli by a network exhibiting oscillations on a faster time
scale. PLoS computational biology. PLoS Comput Biol. 2009 May;5(5).
Ghitza O. Speech decoding guided by cascading oscillators locked to
the sensory-input rhythm: towards predicting intelligibility of time-
compressed speech with insertions of silence. Submitted
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