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Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study

Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study

Published on: July 21, 2021

Probing scale interaction in brain dynamics through synchronization.

Alessandro Barardi¹, Daniel Malagarriga², Belén Sancristobal³

¹Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), Dr. Aiguader 88, 08003 Barcelona, Spain Departament de Fìsica i Enginyeria Nuclear, Universitat Politécnica de Catalunya, Edifici Gaia, Rambla Sant Nebridi 22, 08222 Terrassa, Spain.

Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences

|September 3, 2014

Summary

This summary is machine-generated.

This study shows how fast microscopic neuronal networks (NNs) can link slower mesoscopic neural masses (NMs). The brain

Keywords:

brain synchronization conductance-based models multiscale dynamics neural mass models

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Area of Science:

Neuroscience
Computational Neuroscience
Theoretical Neuroscience

Background:

The mammalian brain functions across multiple spatial and temporal scales.
Understanding interactions between these scales is crucial for brain function.

Purpose of the Study:

To theoretically investigate how microscopic neuronal networks mediate coupling between mesoscopic neural masses.
To analyze the synchronization dynamics between neural masses influenced by a neuronal network.

Main Methods:

Modeling two mesoscopic neural mass (NM) oscillators with different low frequencies.
Simulating a microscopic neuronal network (NN) of spiking neurons with gamma-range rhythms.
Analyzing synchronization between NMs as a function of NN properties (topology, size, frequency).

Main Results:

A fast microscopic neuronal network (NN) can effectively mediate slower coupling between mesoscopic neural masses (NMs).
Synchronization between NMs is dependent on the topological properties, size, and oscillation frequency of the mediating NN.

Conclusions:

Microscopic neuronal networks play a vital role in integrating information across different scales in the brain.
The findings provide insights into how neural synchrony emerges from the interplay of various neural population scales.