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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

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Best practices in data analysis and sharing in neuroimaging using MRI.

Thomas E Nichols¹, Samir Das^2,3, Simon B Eickhoff^4,5

¹University of Warwick, Coventry, UK.

Nature Neuroscience

|February 24, 2017

Summary

Neuroimaging research needs clear best practices for data analysis, reporting, and sharing to improve reproducibility and collaboration. Addressing barriers is key to maximizing the potential of global neuroimaging data.

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Area of Science:

Neuroscience
Medical Imaging

Background:

Concerns exist regarding the reproducibility of scientific findings in neuroimaging.
Lack of standardized best practices hinders transparency, reliability, and collaboration.

Purpose of the Study:

To develop and describe recommendations for best practices in neuroimaging data analysis, results reporting, and data sharing.
To identify barriers impeding the adoption of these practices.

Main Methods:

Development of a set of recommendations on behalf of the Organization for Human Brain Mapping.
Analysis of impediments to implementing best practices in the field.

Main Results:

Insights gained from developing recommendations for enhanced scientific rigor.
Identification of key barriers that hinder transparency, reliability, and data sharing in neuroimaging.

Conclusions:

Establishing best practices is crucial for the reproducibility of neuroimaging studies.
The field must adapt to overcome identified barriers and fully leverage global neuroimaging data resources.