Titlebook: Artificial Intelligence for Neuroscience and Emotional Systems; 10th International W José Manuel Ferrández Vicente,Mikel Val Calvo,Hojj Con

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Enhancing Intensity Differences in?EEG Cross-Frequency Coupling Maps for?Dyslexia Detectionignificant improvements in the significance of CFC map pixels, particularly in the Alpha-Beta coupling band, post-transformation. This enhancement in discriminative power was further supported by the reduction in entropy and the identification of texture feature changes through Gray-Level Co-occurrence Matrix (GLCM) analysis.

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Explainable Exploration of?the?Interplay Between HRV Features and?EEG Local Connectivity Patterns int most contribute to different HRV features, with a focus on parasympathetic activity. Our findings suggest that HRV features related to stress can explain differential activations in the auditory cortex (Brodmann areas 39 and 40) during auditory stimulation in dyslexic children.

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Zero-Shot Ensemble of?Language Models for?Fine-Grain Mental-Health Topic Classificationmodels with Zero-Shot approaches achieved an accuracy (ACC) of 43.29%, weighted-F1 (W-F1) of 41.32% and Macro-F1 (M-F1) of 31.79% in the 28 topics of Counsel-Chat; and 35.57% of ACC, 39.66% W-F1 and 28.12% of M-F1 in the 39 topics of 7Cups dataset. The error analysis reveals that models have difficu

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Extracting Heart Rate Variability from?NIRS Signals for?an?Explainable Detection of?Learning Disordeing to an area under the ROC curve of 0.79. The explanatory nature of our framework, based on Shapley Additive Explanations (SHAP), yields a deeper understanding of the evaluated phenomenon, revealing the presence of behavioral variables highly correlated with the model’s features. These findings de