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Topographical layer imaging as a tool to track neurodegenerative disease spread in M1

In their recent Review (McColgan, P., Joubert, J., Tabrizi, S. J. & Rees, G. The human motor cortex microcircuit: insights for neurodegenerative disease. Nat. Rev. Neurosci. 21, 401–415 (2020))1, McColgan et al. provide a comprehensive overview of the in vivo microcircuits of the human primary motor cortex (M1) and develop hypothetical models of M1 cell loss and layer-specific dysfunction in neurodegenerative disorders. Ultra-high-field (UHF) MRI is promoted in the article as a methodology to uncover the neuronal mechanisms of disease pathophysiology and disease spread in the living individual. This is particularly important given existing ex vivo methods can investigate neurodegeneration only at (usually very) advanced stages and after massive cell loss. Building on this, we here add to this argument that in vivo models on microstructural M1 degeneration can only be successfully developed if local inhomogeneities within M1 are taken into consideration.

The microarchitecture in M1 exhibits a surprisingly high heterogeneity even in healthy individuals and warrants a precise investigation. The M1 myeloarchitecture varies according to cortical depth (with deep layers being most densely myelinated) and along the cortical surface (for example, the area representing the hand is more myelinated than the area representing the face)2 (Fig. 1a). In addition, there are boundaries of low myelin that separate major body part representations in M1, such as between the hand area and the face area, and that divide M1 into different cortical fields2,3. These heterogeneities may explain some of the variance in how neurodegenerative disorders spread through M1 and how neurodegenerative changes are visible in in vivo MRI. Three-dimensional models of cortical structure and cortical function (one dimension in cortical depth and two dimensions along the cortical surface4) could elucidate layer-wise, body-part-wise and hemisphere-wise disease spread and its accordance with motor phenotype and symptom progression (Fig. 1b).

Fig. 1: Topographical layer imaging in M1.
figure1

a | The myelination within M1 presents with high heterogeneity even in healthy participants. Two major gradients are microstructural variations in different cortical depth (right), where deeper layers are more myelinated than superficial layers, and microstructural variations along the cortical surface (left), where inferior areas show lower cortical myelin than superior areas. In addition, there are areas of reduced cortical myelin that separate major body part representations such as the hand and the face (marked with an arrow). b | A three-dimensional model of disease spread takes into account both gradients, which allows monitoring of disease spread through cortical depth and across topographical areas. Vertical arrow indicating initial spread from L5 to L2/3, followed by the affection of other cortical areas (horizontal arrows).

The authors discuss the possibility to use in vivo UHF MRI to characterize amyotrophic lateral sclerosis (ALS), a disorder that rapidly spreads through M1. However, the authors do not mention that symptom onset may be bulbar or lateralized according to the upper or lower limbs and therefore differs with respect to the topographical location in M1. The spread of motor symptoms commonly mirrors body-part-wise disease spread first across the ipsilateral and afterwards across the contralateral hemisphere5. With an assumed disease onset in cortical layer 5 (L5), as McColgan et al. suggest, ALS demands an investigation across three rather than two dimensions, to take into account inherent variations in the M1 microstructure. McColgan et al. suggest that, in ALS, myelin and cell loss spreads from L5 to L2/3 before affecting other cortical areas1 (Fig. 1b centre, arrows). One practical way to test this hypothesis is to scan patients directly after diagnosis6 using 7 T UHF MRI M1 quantitative myelin imaging together with functional imaging, in which individuals are asked to move their foot, hand or face2. This allows for the identification of layer-specific myelin changes in early-affected, late-affected and non-affected body part areas in M1 and to monitor disease spread body-part-wise and layer-wise in subsequent scans. This approach may offer the possibility to detect M1 microstructural changes at a stage before the disease spreads through L2/3 connections to other topographical areas, or to the contralateral hemisphere, but after the disease has spread from L5 to L2/3, and would thus allow testing the model as proposed by McColgan et al.

In summary, when investigating neurodegenerative disease spread in M1, it is of critical importance to consider local microstructural gradients and the inherent differentiation between topographical areas within M1. Their combined investigation at different clinical stages may allow novel pathophysiological insights into disease spread as well as insights into which individual profiles of the local myeloarchitecture and cell architecture relate to slow versus fast disease progression (that is, factors that constitute microstructural resilience).

There is a reply to this letter by McColgan, P., Joubert, J., Tabrizi, S. J. & Rees, G. Nat. Rev. Neurosci. https://doi.org/10.1038/s41583-020-00405-9 (2020).

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Acknowledgements

E.K. was funded by ESIF/EFRE 2014-2020; and FKZ: ZS/2016/04/78113, Vorhaben: Center for Behavioral Brain Sciences (CBBS). S.S. and E.K. received funding within the CBBS Neuronetwork initiative (Project Diagnostic Glove). A.N. was funded by the Else Kröner Fresenius Stiftung (EKFS) (2019-A03). This work was further supported by a grant to S.S. and S.V. from the Foundation of Medical Research, Frankfurt/Main, Germany. E.K., S.S. and S.V. are affiliated to the German Center for Neurodegenerative Diseases (DZNE) Magdeburg and to the CBBS.

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Correspondence to Stefanie Schreiber.

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Schreiber, S., Northall, A., Weber, M. et al. Topographical layer imaging as a tool to track neurodegenerative disease spread in M1. Nat Rev Neurosci 22, 68–69 (2021). https://doi.org/10.1038/s41583-020-00404-w

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