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Related Concept Videos

Autism Spectrum Disorder01:19

Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by persistent deficits in social communication and interaction alongside restrictive and repetitive behaviors or interests. ASD is sometimes accompanied by intellectual impairment.
These core symptoms manifest differently among individuals, ranging from mild to severe. The disorder's complexity extends beyond its clinical presentation, encompassing a diverse range of biological, cognitive, and sociocultural influences.
Entropy Changes Accompanying Specific Processes01:21

Entropy Changes Accompanying Specific Processes

Entropy, a measure of disorder in a system, changes during phase transitions like freezing or boiling. At the transition temperature Ttrs, where two phases are in equilibrium, the phase transition is a reversible process. The entropy change can be calculated from a substance's enthalpy of transition using the equation ΔStrs = ΔtrsH /Ttrs.When a perfect gas expands isothermally from one volume to another, entropy increases logarithmically with volume. Conversely, isothermal compression results...

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Related Experiment Video

Updated: May 28, 2026

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
12:21

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Published on: September 12, 2011

Exploring Neurofunctional Phase Transition Patterns in Autism Spectrum Disorder via Thermodynamics Parameters.

Dayu Qin1, Yuzhe Chen1, Ercan E Kuruoglu1

  • 1Institute of Data and Information, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.

Entropy (Basel, Switzerland)
|May 26, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a novel thermodynamics-inspired framework for analyzing dynamic graphs, using Spectral Core Entropy (SCE) and a temperature index. The framework reveals network changes in brain data and synthetic models, offering insights into autism spectrum disorder (ASD).

Keywords:
autismbrain networkdynamic functional connectivityspectral core entropythermodynamics framework

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Last Updated: May 28, 2026

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Published on: December 28, 2010

Area of Science:

  • Complex Systems Science
  • Network Science
  • Computational Neuroscience

Background:

  • Characterizing structural changes in dynamic complex networks is crucial for understanding evolving systems.
  • Existing methods may lack compact representations for temporal graph organization.
  • Thermodynamics offers a potential analogy for describing system reconfiguration.

Purpose of the Study:

  • To introduce a thermodynamics-inspired framework for dynamic graph analysis.
  • To apply this framework to resting-state fMRI data from individuals with autism spectrum disorder (ASD) and controls.
  • To evaluate the framework's sensitivity on synthetic dynamic graphs.

Main Methods:

  • Development of a framework based on Spectral Core Entropy (SCE), node energy, internal energy, and a temperature-like reconfiguration index.
  • Application to resting-state fMRI data from ASD and control subjects.
  • Testing on controlled synthetic dynamic graphs with varying reconfiguration mechanisms (rewiring, gain modulation).

Main Results:

  • The temperature index weakly but reproducibly marks rapid network changes in fMRI data.
  • Framework sensitivity is regime-dependent on synthetic data: spectral-core change for rewiring, temperature index for gain modulation.
  • Node energy analysis revealed regional differences in dynamic brain connectivity between ASD and control groups.

Conclusions:

  • The proposed framework offers a computationally tractable approach for characterizing reconfiguration in dynamic brain networks.
  • Node energy provides interpretable neuroscientific insights into group differences in dynamic connectivity.
  • The framework shows promise for analyzing evolving complex systems beyond neuroimaging.