Manipulation of perception: HsMM-MVPA analysis on EEG

Stokvisch, Stefan (2021) Manipulation of perception: HsMM-MVPA analysis on EEG. Bachelor's Thesis, Artificial Intelligence.

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Abstract

In 1950 the cognitive revolution started, which resulted in a new intellectual movement called cognitive science. One of the great interests of this movement is the discovery of processing stages, which were first discovered by Donders (1869). Nowadays, with advent of neuroimaging, the electrical activity originating from these underlying cognitive processes can be measured by using an electroencephalogram (EEG). We performed a visual discrimination task where we investigated whether the perceptual processing stages are longer for transparent stimuli. Previously, Berberyan, van Maanen, van Rijn, and Borst (2021) showed evidence that the Hidden semi-Markov model multivariate pattern (HsMM-MVPA) analysis can be used to deduce cognitive stages from a visual discrimination task. Our research uses this method directly on EEG data and investigates whether there is a difference in processing stages when compared to the stages resulting from the research done by Berberyan and colleagues (2021). The results showed no significant difference in reaction times as well as in stage durations. From this we concluded that the speed of visual perception is not influenced by transparency of the stimuli. However, we did find further proof that HsMM-MVPA is a valid method for deducing processing stages directly from EEG.

Item Type:	Thesis (Bachelor's Thesis)
Supervisor name:	Berberyan, H. and Borst, J.P.
Degree programme:	Artificial Intelligence
Thesis type:	Bachelor's Thesis
Language:	English
Date Deposited:	24 Feb 2021 16:32
Last Modified:	24 Feb 2021 16:32
URI:	https://fse.studenttheses.ub.rug.nl/id/eprint/23999

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