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Neurofind: using deep learning to make individualised inferences in brain-based disorders.

S Vieira1,2,3, L Baecker1, W H L Pinaya1,4

  • 1Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.

Translational Psychiatry
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Neurofind is a free web tool simplifying brain morphology analysis using normative models. It provides Outlier Index Scores and Brain Age from MRI scans, aiding precision psychiatry research.

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Area of Science:

  • Neuroscience
  • Psychiatry
  • Medical Imaging

Background:

  • Precision psychiatry increasingly uses normative models to understand brain heterogeneity.
  • Developing these models typically requires significant technical expertise and resources, limiting accessibility for many researchers.

Purpose of the Study:

  • To introduce Neurofind, a freely available web-based tool designed to democratize the use of advanced normative models for brain morphology analysis.
  • To provide researchers with an accessible platform for generating Outlier Index Scores and Brain Age from structural MRI data.

Main Methods:

  • Neurofind was developed using harmonized structural MRI data from 3362 healthy controls (ages 20-80).
  • Brain region volumes were extracted and analyzed using an adversarial autoencoder for the Outlier Index Score and support vector regression for Brain Age.
  • The platform requires minimal user input, processing structural MRI images through a four-step web interface (www.neurofind.ai).

Main Results:

  • Neurofind outputs Outlier Index Scores (deviation from normative morphology) and Brain Age (predicted age from morphometry).
  • Application to Alzheimer's disease (AD) and schizophrenia (SCZ) datasets revealed distinct patterns: AD patients showed extreme outliers (55.2%) with temporal-limbic deviations, while SCZ patients (30.1%) had hippocampal/pallidal deviations and greater heterogeneity.
  • Both AD and SCZ patient groups exhibited accelerated brain aging compared to normative data.

Conclusions:

  • Neurofind offers an accessible solution for researchers to apply sophisticated normative modeling techniques to structural MRI data.
  • The tool facilitates the identification of deviations in brain morphology and estimates brain age, supporting research in psychiatric and neurodegenerative disorders.
  • Findings in AD and SCZ highlight the utility of Neurofind in characterizing disease-specific patterns of brain morphology and aging.