NeuroImage
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Laser and contact heat evoked potentials (LEPs and CHEPs, respectively) provide an objective measure of pathways and processes involved in nociception. The majority of studies analyzing LEP or CHEP outcomes have done so based on conventional, across-trial averaging. With this approach, evoked potential components are potentially confounded by latency jitter and ignore relevant information contained within single trials. ⋯ Age and ratings of perceived intensity were the only subject level characteristics associated with CHEPs outcomes that significantly interacted with the method of analysis (conventional vs single-trial averaging). The strength of relationships for age and ratings of perceived intensity, measured by linear fit, were increased for single-trial compared to conventional across-trial averaged CHEP outcomes. By accounting for latency jitter, single-trial averaging improved the associations between CHEPs and physiological outcomes and should be incorporated as a standard analytical technique in future studies.
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The macro- and microstructural architecture of human brain white matter undergoes substantial alterations throughout development and ageing. Most of our understanding of the spatial and temporal characteristics of these lifespan adaptations come from magnetic resonance imaging (MRI), including diffusion MRI (dMRI), which enables visualisation and quantification of brain white matter with unprecedented sensitivity and detail. However, with some notable exceptions, previous studies have relied on cross-sectional designs, limited age ranges, and diffusion tensor imaging (DTI) based on conventional single-shell dMRI. ⋯ The results showed that the age slopes for conventional DTI metrics (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity [AD], radial diffusivity [RD]) were largely consistent with previous research, and that the highest performing advanced dMRI models showed comparable age prediction accuracy to conventional DTI. Linear mixed effects models and Wilk's theorem analysis showed that the 'FA fine' metric of the RSI model and 'orientation dispersion' (OD) metric of the NODDI model showed the highest sensitivity to age. The results indicate that advanced diffusion models (DKI, NODDI, RSI, SMT mc, WMTI) provide sensitive measures of age-related microstructural changes of white matter in the brain that complement and extend the contribution of conventional DTI.
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Most neuroanatomical studies are based on T1-weighted MR images, whose intensity profiles are not solely determined by the tissue's longitudinal relaxation times (T1), but also affected by varying non-T1 contributions, hampering data reproducibility. In contrast, quantitative imaging using the MP2RAGE sequence, for example, allows direct characterization of the brain based on the tissue property of interest. Combined with 7 Tesla (7T) MRI, this offers unique opportunities to obtain robust high-resolution brain data characterized by a high reproducibility, sensitivity and specificity. ⋯ Finally, removal of B1+ residuals affects hippocampal volumetry and boundary definitions, particularly near structures characterized by strong intensity changes (e.g. cerebral spinal fluid). Taken together, we show that the choice of MP2RAGE parameters can impact T1 comparability across sites and present evidence that hippocampal segmentation results are modulated by B1+ inhomogeneities. This calls for careful (1) consideration of sequence parameters when setting acquisition protocols, as well as (2) acquisition of a B1+ map to correct MP2RAGE data for potential B1+ variations to allow comparison across datasets.