Brain and artificial intelligence: from the viewpoint of spontaneous and task-evoked brain dynamics
Recently, the field of brain science often yields ‘big’ data and utilizes machine learning, which is central for the present artificial intelligence (AI) field and starts usually from extracting the hidden features. However, the data recorded from the brain are dynamic where the property of the da...
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| Format: | Article |
| Language: | English English |
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American Scientific Publishers
2019
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| Online Access: | http://irep.iium.edu.my/74311/ http://irep.iium.edu.my/74311/1/74311_Brain%20and%20Artificial%20Intelligence_article.pdf http://irep.iium.edu.my/74311/2/74311_Brain%20and%20Artificial%20Intelligence_scopus.pdf |
| _version_ | 1848787944886763520 |
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| author | Sase, Takumi Hassan, Raini |
| author_facet | Sase, Takumi Hassan, Raini |
| author_sort | Sase, Takumi |
| building | IIUM Repository |
| collection | Online Access |
| description | Recently, the field of brain science often yields ‘big’ data and utilizes machine learning, which is
central for the present artificial intelligence (AI) field and starts usually from extracting the hidden
features. However, the data recorded from the brain are dynamic where the property of the data
changes with time, different from photos that are static over the time. Then, the following question
emerges: Are brain’s dynamic data really suitable for the present AI techniques? More specifically,
can we extract exact features from brain’s dynamic data and what kind of dynamics makes this
feature extraction more reliable? To answer these questions, in this study, we generated two kinds
of the brain dynamics computationally, i.e., spontaneous and task-evoked brain dynamics, and both
dynamics were applied to a fundamental technique for most feature extraction methods, that is, the
principal component analysis (PCA). We suggest that the task-evoked brain dynamics can give rise
to a feature space where different features, possibly related to personality traits, are classified more
robustly and may lead to a better brain-AI system |
| first_indexed | 2025-11-14T17:32:59Z |
| format | Article |
| id | iium-74311 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T17:32:59Z |
| publishDate | 2019 |
| publisher | American Scientific Publishers |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-743112019-08-25T11:38:16Z http://irep.iium.edu.my/74311/ Brain and artificial intelligence: from the viewpoint of spontaneous and task-evoked brain dynamics Sase, Takumi Hassan, Raini T Technology (General) Recently, the field of brain science often yields ‘big’ data and utilizes machine learning, which is central for the present artificial intelligence (AI) field and starts usually from extracting the hidden features. However, the data recorded from the brain are dynamic where the property of the data changes with time, different from photos that are static over the time. Then, the following question emerges: Are brain’s dynamic data really suitable for the present AI techniques? More specifically, can we extract exact features from brain’s dynamic data and what kind of dynamics makes this feature extraction more reliable? To answer these questions, in this study, we generated two kinds of the brain dynamics computationally, i.e., spontaneous and task-evoked brain dynamics, and both dynamics were applied to a fundamental technique for most feature extraction methods, that is, the principal component analysis (PCA). We suggest that the task-evoked brain dynamics can give rise to a feature space where different features, possibly related to personality traits, are classified more robustly and may lead to a better brain-AI system American Scientific Publishers 2019-03 Article PeerReviewed application/pdf en http://irep.iium.edu.my/74311/1/74311_Brain%20and%20Artificial%20Intelligence_article.pdf application/pdf en http://irep.iium.edu.my/74311/2/74311_Brain%20and%20Artificial%20Intelligence_scopus.pdf Sase, Takumi and Hassan, Raini (2019) Brain and artificial intelligence: from the viewpoint of spontaneous and task-evoked brain dynamics. Journal of Computational and Theoretical Nanoscience, 16 (3). pp. 1081-1092. ISSN 1546-1955 E-ISSN 1546-1963 https://www.ingentaconnect.com/content/asp/jctn/2019/00000016/00000003/art00044 10.1166/jctn.2019.8000 |
| spellingShingle | T Technology (General) Sase, Takumi Hassan, Raini Brain and artificial intelligence: from the viewpoint of spontaneous and task-evoked brain dynamics |
| title | Brain and artificial intelligence: from the viewpoint of
spontaneous and task-evoked brain dynamics |
| title_full | Brain and artificial intelligence: from the viewpoint of
spontaneous and task-evoked brain dynamics |
| title_fullStr | Brain and artificial intelligence: from the viewpoint of
spontaneous and task-evoked brain dynamics |
| title_full_unstemmed | Brain and artificial intelligence: from the viewpoint of
spontaneous and task-evoked brain dynamics |
| title_short | Brain and artificial intelligence: from the viewpoint of
spontaneous and task-evoked brain dynamics |
| title_sort | brain and artificial intelligence: from the viewpoint of
spontaneous and task-evoked brain dynamics |
| topic | T Technology (General) |
| url | http://irep.iium.edu.my/74311/ http://irep.iium.edu.my/74311/ http://irep.iium.edu.my/74311/ http://irep.iium.edu.my/74311/1/74311_Brain%20and%20Artificial%20Intelligence_article.pdf http://irep.iium.edu.my/74311/2/74311_Brain%20and%20Artificial%20Intelligence_scopus.pdf |