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Related Experiment Video

Updated: Feb 11, 2026

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy

Published on: August 5, 2014

Large-scale functional networks connect differently for processing words and symbol strings.

Mia Liljeström^1,2, Johanna Vartiainen^1,2, Jan Kujala¹

¹Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland.

|May 3, 2018

Summary

This summary is machine-generated.

Brain networks flexibly reconfigure for different tasks. Reading words activates left-hemisphere language networks, while symbol processing uses bilateral attention networks, showing distributed neural processing.

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Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits

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Published on: April 15, 2015

Area of Science:

Neuroscience
Cognitive Neuroscience
Network Science

Background:

Synchronized large-scale brain network reconfigurations are crucial for cognition and behavior.
Magnetoencephalography (MEG) and network analysis enable sub-second examination of these dynamic brain networks.

Purpose of the Study:

To compare frequency-resolved functional connectivity during single-word reading versus visual symbol string recognition.
To investigate how different form categories (words vs. symbols) shape large-scale functional network formation and oscillatory dynamics.

Main Methods:

Utilized Magnetoencephalography (MEG) for high temporal resolution brain activity recording.
Applied advanced network analysis techniques to analyze frequency-resolved functional connectivity patterns.

Main Results:

Word reading showed increased coherence in a left-lateralized network (perisylvian regions) within alpha and high gamma bands.
Symbol string processing involved a bilateral network (frontal-parietal regions) with increased coherence in high beta and low gamma bands.
Demonstrated distinct oscillatory frequencies and recruited task-relevant regions for different form categories.

Conclusions:

Functional brain networks are flexible, adapting to process different categories like words and symbols.
Category-specific processing is a distributed neural process implemented in distinct, signature large-scale networks.
Coherence within specific frequency bands serves as a general mechanism for integrating stimulus-dependent information across brain regions.