Abstract:

Voxel-based morphometry has proved an extremely useful tool for computational neuroanatomy studies and provided many important insights, e.g. identifying plasticity due to learning or dementia-related atrophy. However, the measures derived in these analyses depend on a wide variety of factors, e.g. multiple MRI tissue
parameters, processing techniques and priors, making the micro-architectural effects underlying identified changes difficult to elicit. Recent methodological developments in the realm of quantitative MRI (qMRI) have meant that multiple, specific MRI parameters can be mapped in feasible scan times, e.g. using the
multi-parameter mapping (MPM) protocol. qMRI aims to produce measurements directly related to tissue microstructure with high diagnostic and research value, independent of scanner and acquisition protocol. In addition, qMRI can be used to provide direct indicators of the mechanisms driving morphological findings. The emerging field of in vivo histology using MRI (hMRI) aims to further extend qMRI by combining these measures with biophysical models so as to extract, in vivo, biologically-relevant histological measures such as myelin and iron concentration or the g-ratio of white matter fibres. hMRI is expected to shed new light on the relationship between the brain’s microstructure, function and behaviour both in health and disease.