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Personalized brain network models for assessing structure-function relationships.

Kanika Bansal1, Johan Nakuci2, Sarah Feldt Muldoon3

  • 1Mathematics Department, University at Buffalo - SUNY, Buffalo, NY 14260, USA; Human Sciences, US Army Research Laboratory, Aberdeen Proving Grounds, MD 21005, USA; Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA.

Current Opinion in Neurobiology
|April 29, 2018
PubMed
Summary
This summary is machine-generated.

Personalized brain network models integrate subject data to study brain structure and function. These computational models enable virtual experiments for novel insights and improved epilepsy surgery outcomes.

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Area of Science:

  • Computational neuroscience
  • Neuroimaging analysis
  • Systems neuroscience

Background:

  • Recent computational modeling efforts increasingly use subject-specific data.
  • Integrating structural and functional information is key to understanding brain dynamics.
  • Personalized brain network models offer a data-driven approach.

Purpose of the Study:

  • To discuss recent work on personalized brain network models.
  • To explore structure-function relationships in human brains.
  • To highlight the utility of virtual experiments in neuroscience.

Main Methods:

  • Building personalized brain network models using subject data.
  • Incorporating structural and functional neuroimaging data.
  • Performing in silico (virtual) experiments on these models.

Main Results:

  • Personalized models provide unique insights into brain function.
  • Virtual experiments yield previously unobtainable information.
  • Demonstrated applications in understanding local stimulation effects.

Conclusions:

  • Personalized brain network models are powerful tools for neuroscience research.
  • These models can enhance understanding of brain structure-function coupling.
  • Applications include improving epilepsy surgical planning and outcomes.