Abstract: Significance: Mueller matrix imaging (MMI) is a comprehensive form of polarization imaging useful for assessing structural changes. However, there is limited literatura on the polarimetric properties of brain specimens, especially with multispectral analysis. Aim: We aim to employ multispectral MMI for an exhaustive polarimetric analysis of brain structures, providing a reference dataset for future studies and enhancing the understanding of brain anatomy for clinicians and researchers. Approach: A multispectral wide-field MMI system was used to measure six fresh lamb brain specimens. Multiple decomposition methods (forward polar, symmetric, and differential) and polarization invariants (indices of polarimetric purity and anisotropy coefficients) have been calculated to obtain a complete polarimetric description of the samples. A total of 16 labels based on major brain structures, including grey matter (GM) and white matter (WM), were identified. K-nearest neighbors classification was used to distinguish between GM and WM and validate the feasibility of MMI for WM identification. Results: As the wavelength increases, both depolarization and retardance increase, suggesting enhanced tissue penetration into deeper layers. Moreover, utilizing multiple wavelengths allowed us to track dynamic shifts in the optical axis of retardance within the brain tissue, providing insights into morphological changes in WM beneath the cortical surface. The use of multispectral data for classification outperformed all results obtained with single-wavelength data and provided over 95% accuracy for the test dataset. Conclusions: The consistency of these observations highlights the potential of multispectral wide-field MMI as a non-invasive and effective technique for investigating the brain's architecture.

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