Giving Deep Neural Networks Semantic Dementia: Using the Picture Naming Task as a Measure of Neuromorphism

dc.contributor.advisor	Kietzmann, Tim
dc.contributor.advisor	Jones, Emer
dc.contributor.author	Ufer, Tim
dc.date.issued	2021-01-30
dc.description.abstract	Neural networks that model the way the brain works are usually evaluated based on data from exclusively healthy patients. This project provides an additional perspective for these networks by ’lesioning’ them in correspondence with atrophy locations in the brains of Semantic Dementia patients. Then, their behaviour on the Picture Naming task can be compared to the robust error patterns of these patients. This allows for model comparison between two networks not based on their performance on a test-bed of healthy brain data but in an impaired state. For this project, two vNet models with di erent training structures were tested. While both demonstrated a considerable degree of neuromorphism, the category-trained model performed better on the test-bed than the model trained on a semantic objective, contrary to expectations.
dc.identifier.uri	https://theses.ubn.ru.nl/handle/123456789/15804
dc.language.iso	en
dc.thesis.faculty	Faculteit der Sociale Wetenschappen
dc.thesis.specialisation	specialisations::Faculteit der Sociale Wetenschappen::Artificial Intelligence::Bachelor Artificial Intelligence
dc.thesis.studyprogramme	studyprogrammes::Faculteit der Sociale Wetenschappen::Artificial Intelligence
dc.thesis.type	Bachelor
dc.title	Giving Deep Neural Networks Semantic Dementia: Using the Picture Naming Task as a Measure of Neuromorphism

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