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Interpreting and validating complexity and causality in lesion-symptom prognoses.

Mohamed L Seghier1,2, Cathy J Price3

  • 1Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi, UAE.

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|June 22, 2023
PubMed
Summary
This summary is machine-generated.

This study outlines steps for creating reliable lesion-symptom mappings. It emphasizes probabilistic relationships and distinguishes lesion site types for accurate clinical prognoses in neurological disorders.

Keywords:
brain–behaviour relationshipslesion-symptom mappinglogicprobabilistic causalityprognoses

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Area of Science:

  • Neuroscience
  • Neurology
  • Biostatistics

Background:

  • Accurate lesion-symptom mapping is crucial for clinical prognoses in neurological disorders.
  • Current methods often lack the precision to differentiate various lesion site impacts on symptoms.
  • Interpreting lesion-symptom associations requires accounting for neurobiological and methodological constraints.

Purpose of the Study:

  • To define constraints for generating pragmatic and interpretable lesion-symptom mappings.
  • To formulate lesion-symptom mappings using logical notations for better understanding brain-behavior relationships.
  • To adapt epidemiological causality criteria for lesion-symptom mapping in stroke survivors.

Main Methods:

  • Defined five neurobiological and five methodological constraints for lesion-symptom mapping.
  • Formulated lesion-symptom mappings using logical notations and combinatorial rules.
  • Applied Bradford Hill criteria for inferring probabilistic causality to lesion-symptom mapping.

Main Results:

  • Lesion-symptom mapping should focus on probabilistic relationships between multivariate lesion patterns and time-dependent behavioral profiles.
  • Distinguishing between causal, incidental, spared but dysfunctional, and intact lesion sites is necessary for accurate predictions.
  • A logical and theoretical framework was developed applicable to various neurological disorders, particularly stroke.

Conclusions:

  • Neurobiological and methodological constraints must be addressed a priori in experimental design, not just post hoc.
  • Probabilistic causality inference using adapted epidemiological criteria can enhance lesion-symptom mapping reliability.
  • An open platform for sharing and validating lesion rules is proposed to improve clinical utility.