Understanding the semantic structure of human fMRI brain recordings with formal concept analysis

Dominik Endres, Ruth Adam, Martin A. Giese, Uta Noppeney

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

5 Citations (Scopus)

Abstract

We investigate whether semantic information related to object categories can be obtained from human fMRI BOLD responses with Formal Concept Analysis (FCA). While the BOLD response provides only an indirect measure of neural activity on a relatively coarse spatio-temporal scale, it has the advantage that it can be recorded from humans, who can be questioned about their perceptions during the experiment, thereby obviating the need of interpreting animal behavioral responses. Furthermore, the BOLD signal can be recorded from the whole brain simultaneously. In our experiment, a single human subject was scanned while viewing 72 gray-scale pictures of animate and inanimate objects in a target detection task. These pictures comprise the formal objects for FCA. We computed formal attributes by learning a hierarchical Bayesian classifier, which maps BOLD responses onto binary features, and these features onto object labels. The connectivity matrix between the binary features and the object labels can then serve as the formal context. In line with previous reports, FCA revealed a clear dissociation between animate and inanimate objects with the inanimate category also including plants. Furthermore, we found that the inanimate category was subdivided between plants and non-plants when we increased the number of attributes extracted from the BOLD response. FCA also allows for the display of organizational differences between high-level and low-level visual processing areas. We show that subjective familiarity and similarity ratings are strongly correlated with the attribute structure computed from the BOLD signal.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages96-111
Number of pages16
Volume7278 LNAI
DOIs
Publication statusPublished - 2012
Event10th International Conference on Formal Concept Analysis, ICFCA 2012 - Leuven, Belgium
Duration: 7 May 201210 May 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7278 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference10th International Conference on Formal Concept Analysis, ICFCA 2012
Country/TerritoryBelgium
CityLeuven
Period7/05/1210/05/12

Keywords

  • fMRI
  • inferior temporal cortex
  • semantic neural decoding

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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