Abstract
Since the 1990s, Self-Organizing Maps (SOMs) have been instrumental in reducing dimensionality and visualizing high-dimensional data. This study adapts SOMs to explore the neural representation of human concepts, their neural ‘word net’ mapping, and the deterioration of these mappings in certain neurological disorders. Our model draws inspiration from semantic dementia, a severe condition that degrades semantic knowledge in the brain. Although our exploration utilizes a low-dimensional model — a rough simplification with respect of our brains — it successfully replicates observed clinical patterns. These promising results inspire further research to enhance our understanding of language pathophysiology in neurological disorders.
Original language | English |
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Title of host publication | Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - ESANN 2024 |
Publisher | i6doc.com |
Pages | 345-350 |
ISBN (Print) | 978-2-87587-090-2 |
Publication status | Accepted/In press - 2025 |
Event | European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning 2024 - Bruges, Belgium Duration: 9 Oct 2024 → 11 Oct 2024 |
Conference
Conference | European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning 2024 |
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Country/Territory | Belgium |
City | Bruges |
Period | 09/10/2024 → 11/10/2024 |