Functional Mesh Model with Temporal Measurements for brain decoding

Itir Onal, Mete Ozay, Fatos T.Yarman Vural

研究成果: Conference contribution

7 被引用数 (Scopus)

抄録

We propose a method called Functional Mesh Model with Temporal Measurements (FMM-TM) to estimate a functional relationship among voxels using temporal data, and employ these relationships for brain decoding. For each sample, we measure Blood Oxygenation Level Dependent (BOLD) responses from each voxel, and construct a functional mesh around each voxel (called seed voxel) with its nearest neighbors selected using distance metrics namely Pearson correlation, cosine similarity and Euclidean distance. Then, we represent the BOLD response of a seed voxel in terms of linear combination of BOLD responses of its p-nearest neighbors. The relationship between the seed voxel and its neighbors is represented using a set of weights which are estimated by employing linear regression. We train Support Vector Machine and k-Nearest Neighbor classifiers using the estimated weights as features. We test our model in an event-related design experiment, namely object recognition, and observe that our features perform better than raw voxel intensity values, features obtained using various pairwise distance metrics, and local mesh model features extracted using stationary and temporal measurements.

本文言語English
ホスト出版物のタイトル2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
出版社Institute of Electrical and Electronics Engineers Inc.
ページ2624-2628
ページ数5
ISBN(電子版)9781424492718
DOI
出版ステータスPublished - 2015 11 4
イベント37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
継続期間: 2015 8 252015 8 29

出版物シリーズ

名前Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
2015-November
ISSN(印刷版)1557-170X

Other

Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
CountryItaly
CityMilan
Period15/8/2515/8/29

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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