The mismatch negativity (MMN) in basic research of central auditory processing: a review.

In the present article, the basic research using the mismatch negativity (MMN) and analogous results obtained by using the magnetoencephalography (MEG) and other brain-imaging technologies is reviewed. This response is elicited by any discriminable change in auditory stimulation but recent studies extended the notion of the MMN even to higher-order cognitive processes such as those involving grammar and semantic meaning. Moreover, MMN data also show the presence of automatic intelligent processes such as stimulus anticipation at the level of auditory cortex. In addition, the MMN enables one to establish the brain processes underlying the initiation of attention switch to, conscious perception of, sound change in an unattended stimulus stream. 2007 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

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Invited review The mismatch negativity (MMN) in basic research of central auditory processing: A review

Sensorimotor Integration in Speech Processing: Computational Basis and Neural Organization

The study of speech production has largely been divided into investigations of lower-level articulatory motor control and of higher-level linguistic processing, with these research traditions rarely interacting. In this Opinion article, Hickok argues that these approaches have much to offer each other, and he presents a model of speech production that incorporates ideas from both research traditions and findings from neuroscientific studies of sensorimotor integration. Speech production has been studied predominantly from within two traditions, psycholinguistics and motor control. These traditions have rarely interacted, and the resulting chasm between these approaches seems to reflect a level of analysis difference: whereas motor control is concerned with lower-level articulatory control, psycholinguistics focuses on higher-level linguistic processing. However, closer examination of both approaches reveals a substantial convergence of ideas. The goal of this article is to integrate psycholinguistic and motor control approaches to speech production. The result of this synthesis is a neuroanatomically grounded, hierarchical state feedback control model of speech production.

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Computational neuroanatomy of speech production

Audiovisual Integration of Speech Falters under High Attention Demands

This paper deals with the influence of ambient speech on individual speech
productions A methodological framework is defined to gather the experimental
data necessary to feed computer models simula

The influence of ambient speech on adult speech productions through unintentional imitation.

Mismatch negativity evoked by the McGurk–MacDonald effect: a phonetic representation within short-term memory

The paper investigates the possibility of using a simple approximation for evaluating the error which must be back-propagated to allow a neural net to learn to control a plant in an adaptive way. The algorithm is based on an approximation of the Jacobian of the plant. The method is applied to five simulations. The first two simulations allow a comparison between the proposed algorithm and the standard back-propagation, for which the error to be back-propagated is precisely known. The results for the two methods show equivalent performances, and equivalent convergence time, for the test problems. This shows that the rate of convergence of the neural net does not seem to depend crucially on the values of the Jacobian. The last three simulations investigate the possibility of online adaptive learning. The results show that control based on some approximation of theJacobian is possible for a neural network.

Neural controller based on back-propagation algorithm

Error back-propagation is a method whereby a neural net can learn to control a plant in an autonomous way, without a specific learning stage. The paper presents an evaluation method for it, based on qualitative knowledge of the plant. The field of application of the method is specified. The proposed method is applied to three different problems. These three simulations investigate the possibility of online learning with dynamic targets. The results show that dynamic control based on the proposed learning scheme is possible for a neural network. >

https://ieeexplore.ieee.org/iel3/1151/1872/00051961.pdf

Alain Soquet

Papers

The influence of ambient speech on adult speech productions through unintentional imitation.

Mismatch negativity evoked by the McGurk–MacDonald effect: a phonetic representation within short-term memory

Neural controller based on back-propagation algorithm

A neural controller

The aerodynamics of nasalization in French