5 papers
Decoding Neural Emotion Patterns through Large Language Model Embeddings
Gideon Vos, Maryam Ebrahimpour, Liza van Eijk +2
Understanding how emotional expression in language relates to brain function is a challenge in computational neuroscience and affective computing. Traditional neuroimaging is costl…
Synaptic Pruning: A Biological Inspiration for Deep Learning Regularization
Gideon Vos, Liza van Eijk, Zoltan Sarnyai +1
Synaptic pruning in biological brains removes weak connections to improve efficiency. In contrast, dropout regularization in artificial neural networks randomly deactivates neurons…
A Statistical Approach for Synthetic EEG Data Generation
Gideon Vos, Maryam Ebrahimpour, Liza van Eijk +2
Electroencephalogram (EEG) data is crucial for diagnosing mental health conditions but is costly and time-consuming to collect at scale. Synthetic data generation offers a promisin…
Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights
Gideon Vos, Liza van Eijk, Zoltan Sarnyai +1
Machine Learning is transforming medical research by improving diagnostic accuracy and personalizing treatments. General ML models trained on large datasets identify broad patterns…
The Effect of Acute Stress on the Interpretability and Generalization of Schizophrenia Predictive Machine Learning Models
Gideon Vos, Maryam Ebrahimpour, Liza van Eijk +2
Introduction Schizophrenia is a severe mental disorder, and early diagnosis is key to improving outcomes. Its complexity makes predicting onset and progression challenging. EEG has…