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Related Concept Videos

Brain Imaging01:14

Brain Imaging

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Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
448

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BACON: A tool for reverse inference in brain activation and alteration.

Tommaso Costa1,2,3, Jordi Manuello1,2,3, Mario Ferraro3,4

  • 1GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.

Human Brain Mapping
|May 15, 2021
PubMed
Summary

This study introduces BACON, a new tool for neuroimaging analysis. BACON enhances brain activity and anatomical variation studies by performing reverse inference for improved specificity in mental function and brain disorder research.

Keywords:
Bayes' factoractivation likelihood estimationcoordinate-based meta-analysisfMRIreverse inferencevoxel-based morphometry

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Area of Science:

  • Neuroimaging
  • Cognitive Neuroscience
  • Computational Psychiatry

Background:

  • Magnetic Resonance Imaging (MRI) methods provide voxel-based maps of brain activity and anatomical variation.
  • Forward inference in neuroimaging lacks specificity, identifying brain areas not exclusive to the studied process or condition.
  • A need exists for methods to assess the specificity of brain alterations for mental functions or pathologies.

Purpose of the Study:

  • To introduce BACON (Bayes fACtor mOdeliNg), a novel tool for neuroimaging data analysis.
  • To enable reverse inference for both functional and structural MRI data.
  • To improve the specificity of associations between brain patterns and mental functions or pathologies.

Main Methods:

  • BACON implements Bayes' factor for statistical inference.
  • Utilizes activation likelihood estimation (ALE) derived-maps.
  • Calculates posterior probability distributions to evidence specificity.

Main Results:

  • BACON provides a framework for reverse inference in neuroimaging.
  • The tool quantifies the specificity of brain activation or alteration patterns.
  • Enables more precise links between neuroimaging findings and cognitive or clinical conditions.

Conclusions:

  • BACON offers a significant advancement for neuroimaging research by enabling specific reverse inferences.
  • The tool aids in determining the unique association of brain patterns with specific mental functions or pathologies.
  • Facilitates more accurate interpretation of functional and structural MRI data in clinical and cognitive neuroscience.