Investigating Emergent Synchronization Patterns and Information Processing of Neural Networks using Data Analysis

• Grant number: 23/16273-8
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
• Start date: May 31, 2024
• End date: May 30, 2025
• Field of knowledge: Engineering - Electrical Engineering - Industrial Electronics, Electronic Systems and Controls
• Principal Investigator: Elbert Einstein Nehrer Macau
• Grantee: Bruno Rafael Reichert Boaretto
• Supervisor: Cristina Masoller
• Host Institution: Instituto de Ciência e Tecnologia (ICT). Universidade Federal de São Paulo (UNIFESP). Campus São José dos Campos. São José dos Campos , SP, Brazil
• Institution abroad: Universitat Politècnica de Catalunya (UPC), Spain
• Associated to the scholarship: 21/09839-0 - The role of synaptic current in synchronizing of neuronal networks, BP.PD

Abstract

The brain operates in a noisy environment. Neocortical neurons undergo a constant bombardment of thousands of action potentials due to the spontaneous activity in the brain. The complex behavior observed in the brain is related to activity patterns which may lead to synchronization when oscillatory activities are dynamically related. Synchronization plays a crucial role in information processing, coordinating brain activity, and facilitating complex cognitive functions. Moreover, abnormal levels of synchronization have been associated with neurological and psychiatric disorders such as epilepsy, Alzheimer's disease, and autism. This research proposal aims to investigate the role of synaptic currents in the emergence of synchronization and their impact on information processing within neuronal networks. Through computational modeling and data analysis techniques, it aims to understand the effects of a train of Poissoninan spikes on the synchronization process in a network of Hodgkin-Huxley neurons. Modeling Poissonian spikes in cognitive neurons captures the stochastic nature of the neural activity, integrates external inputs, studies noise effects, and aligns with experimental observations, contributing to understanding cognitive processes. The results will offer insights into the interplay between synaptic currents and emergent synchronization in complex neuronal networks, enhancing our understanding of network dynamics and their functional implications. This study seeks to unravel the complex dynamics of synaptic currents in neuronal networks, elucidating their role in synchronization and information processing through data analysis methods.

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

BOARETTO, BRUNO R. R.; MACAU, ELBERT E. N.; MASOLLER, CRISTINA. Noise-induced extreme events in Hodgkin-Huxley neural networks. CHAOS SOLITONS & FRACTALS, v. 194, p. 7-pg., 2025-02-21. (18/03211-6)