Classification from generation: Recognizing deep grammatical information during reading from rapid event-related fMRI

Tali Bitan; Alex Frid; Hananel Hazan; Larry M. Manevitz; Haim Shalelashvili; Yael Weiss

doi:10.1109/IJCNN.2016.7727808

Classification from generation: Recognizing deep grammatical information during reading from rapid event-related fMRI

Tali Bitan, Alex Frid, Hananel Hazan, Larry M. Manevitz, Haim Shalelashvili, Yael Weiss

Department of Psychology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

A novel fMRI classification method designed for rapid event related fMRI experiments is described and applied to the classification of loud reading of isolated words in Hebrew. Three comparisons of different grammatical complexity were performed: (i) words versus asterisks (ii) 'with diacritics versus without diacritics' and (iii) 'with root versus no root'. We discuss the most difficult task and, for comparison, the easiest one. Earlier work using more standard classification techniques (machine learning and statistical) succeeded fully only in the simplest of these tasks (i), but produced only partial results on (ii) and failed completely, even on the training set on the deepest task (iii).

Original language	English
Title of host publication	2016 International Joint Conference on Neural Networks, IJCNN 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4637-4642
Number of pages	6
ISBN (Electronic)	9781509006199
DOIs	https://doi.org/10.1109/IJCNN.2016.7727808
State	Published - 31 Oct 2016
Event	2016 International Joint Conference on Neural Networks, IJCNN 2016 - Vancouver, Canada Duration: 24 Jul 2016 → 29 Jul 2016

Publication series

Name	Proceedings of the International Joint Conference on Neural Networks
Volume	2016-October

Conference

Conference	2016 International Joint Conference on Neural Networks, IJCNN 2016
Country/Territory	Canada
City	Vancouver
Period	24/07/16 → 29/07/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

Classification
Cognitive Processing
Functional magnetic resonance imaging (fMRI)
Machine Learning
Multivoxel pattern analysis (MVPA)
Neural Networks
Pattern Matching

ASJC Scopus subject areas

Software
Artificial Intelligence

Access to Document

10.1109/IJCNN.2016.7727808

Cite this

Bitan, T., Frid, A., Hazan, H., Manevitz, L. M., Shalelashvili, H., & Weiss, Y. (2016). Classification from generation: Recognizing deep grammatical information during reading from rapid event-related fMRI. In 2016 International Joint Conference on Neural Networks, IJCNN 2016 (pp. 4637-4642). Article 7727808 (Proceedings of the International Joint Conference on Neural Networks; Vol. 2016-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN.2016.7727808

Bitan, Tali ; Frid, Alex ; Hazan, Hananel et al. / Classification from generation : Recognizing deep grammatical information during reading from rapid event-related fMRI. 2016 International Joint Conference on Neural Networks, IJCNN 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 4637-4642 (Proceedings of the International Joint Conference on Neural Networks).

@inproceedings{f068590694af4755aa51052fc0978167,

title = "Classification from generation: Recognizing deep grammatical information during reading from rapid event-related fMRI",

abstract = "A novel fMRI classification method designed for rapid event related fMRI experiments is described and applied to the classification of loud reading of isolated words in Hebrew. Three comparisons of different grammatical complexity were performed: (i) words versus asterisks (ii) 'with diacritics versus without diacritics' and (iii) 'with root versus no root'. We discuss the most difficult task and, for comparison, the easiest one. Earlier work using more standard classification techniques (machine learning and statistical) succeeded fully only in the simplest of these tasks (i), but produced only partial results on (ii) and failed completely, even on the training set on the deepest task (iii).",

keywords = "Classification, Cognitive Processing, Functional magnetic resonance imaging (fMRI), Machine Learning, Multivoxel pattern analysis (MVPA), Neural Networks, Pattern Matching",

author = "Tali Bitan and Alex Frid and Hananel Hazan and Manevitz, {Larry M.} and Haim Shalelashvili and Yael Weiss",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 International Joint Conference on Neural Networks, IJCNN 2016 ; Conference date: 24-07-2016 Through 29-07-2016",

year = "2016",

month = oct,

day = "31",

doi = "10.1109/IJCNN.2016.7727808",

language = "English",

series = "Proceedings of the International Joint Conference on Neural Networks",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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booktitle = "2016 International Joint Conference on Neural Networks, IJCNN 2016",

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Bitan, T, Frid, A, Hazan, H, Manevitz, LM, Shalelashvili, H & Weiss, Y 2016, Classification from generation: Recognizing deep grammatical information during reading from rapid event-related fMRI. in 2016 International Joint Conference on Neural Networks, IJCNN 2016., 7727808, Proceedings of the International Joint Conference on Neural Networks, vol. 2016-October, Institute of Electrical and Electronics Engineers Inc., pp. 4637-4642, 2016 International Joint Conference on Neural Networks, IJCNN 2016, Vancouver, Canada, 24/07/16. https://doi.org/10.1109/IJCNN.2016.7727808

Classification from generation: Recognizing deep grammatical information during reading from rapid event-related fMRI. / Bitan, Tali; Frid, Alex; Hazan, Hananel et al.
2016 International Joint Conference on Neural Networks, IJCNN 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 4637-4642 7727808 (Proceedings of the International Joint Conference on Neural Networks; Vol. 2016-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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KW - Cognitive Processing

KW - Functional magnetic resonance imaging (fMRI)

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KW - Multivoxel pattern analysis (MVPA)

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Bitan T, Frid A, Hazan H, Manevitz LM, Shalelashvili H, Weiss Y. Classification from generation: Recognizing deep grammatical information during reading from rapid event-related fMRI. In 2016 International Joint Conference on Neural Networks, IJCNN 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 4637-4642. 7727808. (Proceedings of the International Joint Conference on Neural Networks). doi: 10.1109/IJCNN.2016.7727808

Classification from generation: Recognizing deep grammatical information during reading from rapid event-related fMRI

Abstract

Publication series

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Bibliographical note

Keywords

ASJC Scopus subject areas

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