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Fig. 2 | Alzheimer's Research & Therapy

Fig. 2

From: Subject classification and cross-time prediction based on functional connectivity and white matter microstructure features in a rat model of Alzheimer’s using machine learning

Fig. 2

A Schematic of the WMTI-Watson biophysical model. The diffusion signal is described in terms of two non-exchanging compartments, the intra and extra-axonal spaces. Here, the axons are modeled as sticks with a radius equal to zero. The intra-axonal space is described by a relative volume fraction of water f and by the parallel intra-axonal diffusivity \({D}_{a}\). The perpendicular intra-axonal diffusivity is negligible at the relevant diffusion times and weightings. The bundle of axons is embedded in the extra-axonal space, characterized by its parallel \({D}_{e, \parallel }\) and perpendicular extra-axonal diffusivities \({D}_{e,\perp }\). The axons’ orientations are modeled by a Watson distribution, which is characterized by \(\langle {(\mathit{cos}\psi )}^{2}\rangle \equiv {c}_{2}\). B The white matter ROIs

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Alzheimer's Research & Therapy

ISSN: 1758-9193