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Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.
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Computational anatomy for studying use-dependant brain plasticity.

Bogdan Draganski1, Ferath Kherif2, Antoine Lutti2

  • 1LREN - Department for Clinical Neurosciences, CHUV, University of Lausanne Lausanne, Switzerland ; Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany.

Frontiers in Human Neuroscience
|July 15, 2014
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Summary
This summary is machine-generated.

This review explores how magnetic resonance imaging (MRI) reveals brain structure changes due to use. Advanced MRI techniques offer new insights into brain plasticity mechanisms.

Keywords:
brain plasticitycomputational anatomymagnetic resonance imaging

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Area of Science:

  • Neuroscience
  • Neuroimaging
  • Computational Anatomy

Background:

  • Use-dependent brain structure changes are critical for understanding brain plasticity.
  • Current understanding of the neurobiological basis of these changes is limited.
  • Existing theoretical models need refinement based on empirical evidence.

Purpose of the Study:

  • To review literature on in vivo assessment of use-dependent brain structure changes using MRI and computational anatomy.
  • To highlight recent findings and uncover principles of brain plasticity.
  • To emphasize the need for a paradigm shift in studying use-dependent plasticity.

Main Methods:

  • Comprehensive literature review.
  • Analysis of findings from magnetic resonance imaging (MRI) studies.
  • Application of computational anatomy techniques.

Main Results:

  • Recent findings reveal basic principles of brain plasticity across different observation scales.
  • Novel quantitative MRI techniques provide in vivo insights into microstructural properties (myelin, iron, water content).
  • These techniques allow for specific insights into the mechanisms of brain plasticity.

Conclusions:

  • A paradigm shift is necessary for investigating and interpreting use-dependent brain plasticity.
  • Quantitative MRI and advanced analysis methods are crucial for understanding plasticity mechanisms.
  • Future research should focus on novel methods for longitudinal data analysis to infer causality.