Concept-level recognition from neuroimages for understanding learning in the brain

Yiping Zhang, Liqian Sun, Jingheng Wang, Yan Shen, Yupei Zhang, Shuhui Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Functional magnetic resonance imaging (fMRI) can measure changes in blood oxygenation level-dependent (BOLD) in the human brain caused by some stimuli or tasks, which helps us understand human brain mechanisms and functions. Recent studies demonstrate that there are both shared and specific neural representations between nature and drawing images. However, there is a lack of more detailed studies on the differences at the various levels of image abstraction. In this paper, we proposed to recognize concept levels from the image abstractions, including photographs, drawings, and sketches. More specifically, this study first conducts preprocessing processes to mitigate fMRI noise, such as respiratory and head movement, and then constructs the functional connectivity matrix based on the fMRI segmentation corresponding to different stimuli, leading to our used datasets. On the resulting dataset, we trained several data classifiers to obtain the mapping from fMRIs to the three types of stimuli. In addition, we discussed experimental parameters to check their impacts on classification performance. The evaluated results show that different concept-level images could be recognized at an effective accuracy, where the deep learning model achieves the best performance. This study contributes to an understanding of the abstraction level of concept formulation in the brain. The results can help treat brain disorders and make learning plans.

Original languageEnglish
Title of host publicationProceedings - 2023 2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023
EditorsXingpeng Jiang, Haiying Wang, Reda Alhajj, Xiaohua Hu, Felix Engel, Mufti Mahmud, Nadia Pisanti, Xuefeng Cui, Hong Song
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3984-3990
Number of pages7
ISBN (Electronic)9798350337488
DOIs
StatePublished - 2023
Event2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023 - Istanbul, Turkey
Duration: 5 Dec 20238 Dec 2023

Publication series

NameProceedings - 2023 2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

Conference

Conference2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023
Country/TerritoryTurkey
CityIstanbul
Period5/12/238/12/23

Keywords

  • Concept-level recognition
  • data classification
  • fMRIs
  • image abstraction
  • machine learning

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