Computational Neuroscience

5th Latin American Workshop, LAWCN 2025, La Plata, Argentina, November 12-14, 2025, Revised Selected Papers
Erscheinungsjahr 2026
ISBN: 978-3-032-14663-2
Verlag: Springer

Buch, Englisch, 123 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 219 g

Reihe: Communications in Computer and Information Science

This book constitutes the refereed proceedings of the 5th Latin American Workshop, LAWCN 2025, held in La Plata, Argentina, during November 12–14, 2025.

The 6 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 11 submissions. They were organized in the follwing topical sections as follows: Artificial Intelligence and Machine Learning; and Neuroengineering.

Zielgruppe

Research

Autoren/Hrsg.

Talevi, Alan

Rosa Cota, Vinicius

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Angewandte Informatik
• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung

Inhaltsverzeichnis

.- Artificial Intelligence and Machine Learning .

.- Multimodal Physiological Signal Statistical Analysis and Random Forest Classification for Epileptic Seizure Detection.

.- Detection of Epileptogenic Patterns in Thalamic Neurostimulated Signals through Spatial Deep Attention.

.- In Silico Screening to Identify Metabotropic Glutamate Receptor 1 Allosteric Modulators Using Ensemble Learning.

.- A Comparative Analysis of ANN, TabNet and FT-Transformer models in EEG Classification of Neuropsychiatric Disorders.

.- Computational and Experimental Approaches for the Discovery of New Anticonvulsant Drugs.

.- Application of Machine Learning in Drug Repurposing of a New Antiseizure Drugs Active in the PTZ Kindling Model.

.- Neuroengineering .

.- Design and Development of a Functional Prototype of an Upper-Limb Exoskeleton for Neurorehabilitation Assistance.

.- An Inverted Perspective for the Reference Electrode and a Heuristic Metric for Spectra-Temporal Mapping of EEG Signals Aiming at Motor-Imagery Classification.

.- Beyond Full Electrode Arrays: Optimizing Channel Selection for Motor Imagery BCIs via Individual Channel Classifiers and Ensembles.

.- Hemispheric-Specific Coupling Improves Modeling of Functional Connectivity Using Wilson–Cowan Dynamics.