Auditory temporal assimilation: A discriminant analysis of electrophysiological evidence

Hiroshige Takeichi, Takako Mitsudo, Yoshitaka Nakajima, Gerard B. Remijn, Yoshinobu Goto, Shozo Tobimatsu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

A portion of the data from an event-related potential (ERP) experiment [1] on auditory temporal assimilation [2, 3] was reanalyzed by constructing Gaussian Naïve Bayes Classifiers [4]. In auditory temporal assimilation, two neighboring physically-unequal time intervals marked by three successive tone bursts are illusorily perceived to have the same duration if the two time intervals satisfy a certain relationship. The classifiers could discriminate the subject's task, which was judgment of the equivalence between the two intervals, at an accuracy of 86-96% as well as their subjective judgments to the physically equivalent stimulus at an accuracy of 82-86% from individual ERP average waveforms. Chernoff information [5] provided more consistent interpretations compared with classification errors as to the selection of the component most strongly associated with the perceptual judgment. This may provide us with a simple but somewhat robust neurodecoding scheme.

Original languageEnglish
Title of host publicationNeural Information Processing - 16th International Conference, ICONIP 2009, Proceedings
Pages299-308
Number of pages10
EditionPART 2
DOIs
Publication statusPublished - Dec 1 2009
Event16th International Conference on Neural Information Processing, ICONIP 2009 - Bangkok, Thailand
Duration: Dec 1 2009Dec 5 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5864 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other16th International Conference on Neural Information Processing, ICONIP 2009
CountryThailand
CityBangkok
Period12/1/0912/5/09

Fingerprint

Discriminant analysis
Discriminant Analysis
Event-related Potentials
Classifiers
Interval
Bayes Classifier
Unequal
Burst
Waveform
Classifier
Equivalence
Experiments
Experiment
Evidence
Judgment

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Takeichi, H., Mitsudo, T., Nakajima, Y., Remijn, G. B., Goto, Y., & Tobimatsu, S. (2009). Auditory temporal assimilation: A discriminant analysis of electrophysiological evidence. In Neural Information Processing - 16th International Conference, ICONIP 2009, Proceedings (PART 2 ed., pp. 299-308). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5864 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-10684-2_33

Auditory temporal assimilation : A discriminant analysis of electrophysiological evidence. / Takeichi, Hiroshige; Mitsudo, Takako; Nakajima, Yoshitaka; Remijn, Gerard B.; Goto, Yoshinobu; Tobimatsu, Shozo.

Neural Information Processing - 16th International Conference, ICONIP 2009, Proceedings. PART 2. ed. 2009. p. 299-308 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5864 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Takeichi, H, Mitsudo, T, Nakajima, Y, Remijn, GB, Goto, Y & Tobimatsu, S 2009, Auditory temporal assimilation: A discriminant analysis of electrophysiological evidence. in Neural Information Processing - 16th International Conference, ICONIP 2009, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 5864 LNCS, pp. 299-308, 16th International Conference on Neural Information Processing, ICONIP 2009, Bangkok, Thailand, 12/1/09. https://doi.org/10.1007/978-3-642-10684-2_33
Takeichi H, Mitsudo T, Nakajima Y, Remijn GB, Goto Y, Tobimatsu S. Auditory temporal assimilation: A discriminant analysis of electrophysiological evidence. In Neural Information Processing - 16th International Conference, ICONIP 2009, Proceedings. PART 2 ed. 2009. p. 299-308. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). https://doi.org/10.1007/978-3-642-10684-2_33
Takeichi, Hiroshige ; Mitsudo, Takako ; Nakajima, Yoshitaka ; Remijn, Gerard B. ; Goto, Yoshinobu ; Tobimatsu, Shozo. / Auditory temporal assimilation : A discriminant analysis of electrophysiological evidence. Neural Information Processing - 16th International Conference, ICONIP 2009, Proceedings. PART 2. ed. 2009. pp. 299-308 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).
@inproceedings{aeb0a41ac254419a80f8067096a48c75,
title = "Auditory temporal assimilation: A discriminant analysis of electrophysiological evidence",
abstract = "A portion of the data from an event-related potential (ERP) experiment [1] on auditory temporal assimilation [2, 3] was reanalyzed by constructing Gaussian Na{\"i}ve Bayes Classifiers [4]. In auditory temporal assimilation, two neighboring physically-unequal time intervals marked by three successive tone bursts are illusorily perceived to have the same duration if the two time intervals satisfy a certain relationship. The classifiers could discriminate the subject's task, which was judgment of the equivalence between the two intervals, at an accuracy of 86-96{\%} as well as their subjective judgments to the physically equivalent stimulus at an accuracy of 82-86{\%} from individual ERP average waveforms. Chernoff information [5] provided more consistent interpretations compared with classification errors as to the selection of the component most strongly associated with the perceptual judgment. This may provide us with a simple but somewhat robust neurodecoding scheme.",
author = "Hiroshige Takeichi and Takako Mitsudo and Yoshitaka Nakajima and Remijn, {Gerard B.} and Yoshinobu Goto and Shozo Tobimatsu",
year = "2009",
month = "12",
day = "1",
doi = "10.1007/978-3-642-10684-2_33",
language = "English",
isbn = "364210682X",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 2",
pages = "299--308",
booktitle = "Neural Information Processing - 16th International Conference, ICONIP 2009, Proceedings",
edition = "PART 2",

}

TY - GEN

T1 - Auditory temporal assimilation

T2 - A discriminant analysis of electrophysiological evidence

AU - Takeichi, Hiroshige

AU - Mitsudo, Takako

AU - Nakajima, Yoshitaka

AU - Remijn, Gerard B.

AU - Goto, Yoshinobu

AU - Tobimatsu, Shozo

PY - 2009/12/1

Y1 - 2009/12/1

N2 - A portion of the data from an event-related potential (ERP) experiment [1] on auditory temporal assimilation [2, 3] was reanalyzed by constructing Gaussian Naïve Bayes Classifiers [4]. In auditory temporal assimilation, two neighboring physically-unequal time intervals marked by three successive tone bursts are illusorily perceived to have the same duration if the two time intervals satisfy a certain relationship. The classifiers could discriminate the subject's task, which was judgment of the equivalence between the two intervals, at an accuracy of 86-96% as well as their subjective judgments to the physically equivalent stimulus at an accuracy of 82-86% from individual ERP average waveforms. Chernoff information [5] provided more consistent interpretations compared with classification errors as to the selection of the component most strongly associated with the perceptual judgment. This may provide us with a simple but somewhat robust neurodecoding scheme.

AB - A portion of the data from an event-related potential (ERP) experiment [1] on auditory temporal assimilation [2, 3] was reanalyzed by constructing Gaussian Naïve Bayes Classifiers [4]. In auditory temporal assimilation, two neighboring physically-unequal time intervals marked by three successive tone bursts are illusorily perceived to have the same duration if the two time intervals satisfy a certain relationship. The classifiers could discriminate the subject's task, which was judgment of the equivalence between the two intervals, at an accuracy of 86-96% as well as their subjective judgments to the physically equivalent stimulus at an accuracy of 82-86% from individual ERP average waveforms. Chernoff information [5] provided more consistent interpretations compared with classification errors as to the selection of the component most strongly associated with the perceptual judgment. This may provide us with a simple but somewhat robust neurodecoding scheme.

UR - http://www.scopus.com/inward/record.url?scp=76249093130&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=76249093130&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-10684-2_33

DO - 10.1007/978-3-642-10684-2_33

M3 - Conference contribution

AN - SCOPUS:76249093130

SN - 364210682X

SN - 9783642106828

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 299

EP - 308

BT - Neural Information Processing - 16th International Conference, ICONIP 2009, Proceedings

ER -