An Oscillatory Model for Multimodal Processing of Short Language Instructions

Christo Panchev

doi:10.1007/978-3-540-74695-9_96

An Oscillatory Model for Multimodal Processing of Short Language Instructions

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Language skills are dominantly implemented in one hemisphere (usually the left), with the pre-frontal areas playing a critical part (the inferior frontal area of Broca and the superior temporal area of Wernicke), but a network of additional regions in the brain, including some from the non-dominant hemisphere, are necessary for complete language functionality. This paper presents a neural architecture built on spiking neurons which implements a mechanism of associating representations of concepts in different modalities; as well as integrating sequential language input into a coherent representation/interpretation of an instruction. It follows the paradigm of temporal binding, namely synchronisation and phase locking of distributed representations in nested gamma-theta oscillations. The functionality of the architecture is presented in a set of experiments of language instructions given to a real robot.

Original language	English
Title of host publication	Artificial Neural Networks ICANN 2007
Editors	J P Marques de Sá, Luís A Alexandre, Wlodzislaw Duch, Danilo P Mandic
Place of Publication	Berlin
Publisher	Springer Verlag
Pages	943-952
Number of pages	10
ISBN (Print)	978-3-540-74695-9
DOIs	https://doi.org/10.1007/978-3-540-74695-9_96
Publication status	Published - 2007
Externally published	Yes
Event	17th International Conference on Artificial Neural Networks - Porto, Portugal Duration: 9 Sep 2007 → 13 Sep 2007 Conference number: 17

Publication series

Name	Lecture Notes in Computer Science

Conference

Conference	17th International Conference on Artificial Neural Networks
Abbreviated title	ICANN 2007
Country	Portugal
City	Porto
Period	9/09/07 → 13/09/07

Keywords

Central Pattern Generator
Language Instruction
Oscillatory Model
Neural Architecture
Theta Oscillation

Access to Document

10.1007/978-3-540-74695-9_96

Fingerprint Dive into the research topics of 'An Oscillatory Model for Multimodal Processing of Short Language Instructions'. Together they form a unique fingerprint.

Cite this

An Oscillatory Model for Multimodal Processing of Short Language Instructions. / Panchev, Christo.

Artificial Neural Networks ICANN 2007 . ed. / J P Marques de Sá; Luís A Alexandre; Wlodzislaw Duch; Danilo P Mandic. Berlin : Springer Verlag, 2007. p. 943-952 ( Lecture Notes in Computer Science).

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Panchev, C 2007, An Oscillatory Model for Multimodal Processing of Short Language Instructions. in JP Marques de Sá, LA Alexandre, W Duch & DP Mandic (eds), Artificial Neural Networks ICANN 2007 . Lecture Notes in Computer Science, Springer Verlag, Berlin, pp. 943-952, 17th International Conference on Artificial Neural Networks, Porto, Portugal, 9/09/07. https://doi.org/10.1007/978-3-540-74695-9_96

@inbook{5088ed2727d346e09916abb7b3cd9a03,

title = "An Oscillatory Model for Multimodal Processing of Short Language Instructions",

abstract = "Language skills are dominantly implemented in one hemisphere (usually the left), with the pre-frontal areas playing a critical part (the inferior frontal area of Broca and the superior temporal area of Wernicke), but a network of additional regions in the brain, including some from the non-dominant hemisphere, are necessary for complete language functionality. This paper presents a neural architecture built on spiking neurons which implements a mechanism of associating representations of concepts in different modalities; as well as integrating sequential language input into a coherent representation/interpretation of an instruction. It follows the paradigm of temporal binding, namely synchronisation and phase locking of distributed representations in nested gamma-theta oscillations. The functionality of the architecture is presented in a set of experiments of language instructions given to a real robot.",

keywords = "Central Pattern Generator, Language Instruction, Oscillatory Model, Neural Architecture, Theta Oscillation",

author = "Christo Panchev",

year = "2007",

doi = "10.1007/978-3-540-74695-9_96",

language = "English",

isbn = "978-3-540-74695-9",

series = " Lecture Notes in Computer Science",

publisher = "Springer Verlag",

pages = "943--952",

editor = "{Marques de S{\'a}}, {J P } and Alexandre, {Lu{\'i}s A } and Duch, {Wlodzislaw } and Mandic, {Danilo P }",

booktitle = "Artificial Neural Networks ICANN 2007",

address = "Austria",

note = "17th International Conference on Artificial Neural Networks, ICANN 2007 ; Conference date: 09-09-2007 Through 13-09-2007",

}

TY - CHAP

T1 - An Oscillatory Model for Multimodal Processing of Short Language Instructions

AU - Panchev, Christo

N1 - Conference code: 17

PY - 2007

Y1 - 2007

N2 - Language skills are dominantly implemented in one hemisphere (usually the left), with the pre-frontal areas playing a critical part (the inferior frontal area of Broca and the superior temporal area of Wernicke), but a network of additional regions in the brain, including some from the non-dominant hemisphere, are necessary for complete language functionality. This paper presents a neural architecture built on spiking neurons which implements a mechanism of associating representations of concepts in different modalities; as well as integrating sequential language input into a coherent representation/interpretation of an instruction. It follows the paradigm of temporal binding, namely synchronisation and phase locking of distributed representations in nested gamma-theta oscillations. The functionality of the architecture is presented in a set of experiments of language instructions given to a real robot.

AB - Language skills are dominantly implemented in one hemisphere (usually the left), with the pre-frontal areas playing a critical part (the inferior frontal area of Broca and the superior temporal area of Wernicke), but a network of additional regions in the brain, including some from the non-dominant hemisphere, are necessary for complete language functionality. This paper presents a neural architecture built on spiking neurons which implements a mechanism of associating representations of concepts in different modalities; as well as integrating sequential language input into a coherent representation/interpretation of an instruction. It follows the paradigm of temporal binding, namely synchronisation and phase locking of distributed representations in nested gamma-theta oscillations. The functionality of the architecture is presented in a set of experiments of language instructions given to a real robot.

KW - Central Pattern Generator

KW - Language Instruction

KW - Oscillatory Model

KW - Neural Architecture

KW - Theta Oscillation

U2 - 10.1007/978-3-540-74695-9_96

DO - 10.1007/978-3-540-74695-9_96

M3 - Chapter

SN - 978-3-540-74695-9

T3 - Lecture Notes in Computer Science

SP - 943

EP - 952

BT - Artificial Neural Networks ICANN 2007

A2 - Marques de Sá, J P

A2 - Alexandre, Luís A

A2 - Duch, Wlodzislaw

A2 - Mandic, Danilo P

PB - Springer Verlag

CY - Berlin

T2 - 17th International Conference on Artificial Neural Networks

Y2 - 9 September 2007 through 13 September 2007

ER -