bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2020.09.08.286518

Can MRI measure myelin? Systematic review, qualitative assessment, and meta-analysis of studies validating microstructural imaging with myelin histology

Lazari, A.·Lipp, I.
View original source ↗Export metadata ↓

Abstract

Recent years have seen an increased understanding of the importance of myelination in healthy brain function and neuropsychiatric diseases. Non-invasive microstructural magnetic resonance imaging (MRI) holds the potential to expand and translate these insights to basic and clinical human research, but the sensitivity and specificity of different MR markers to myelination is a subject of debate. To consolidate current knowledge on the topic, we perform a systematic review and meta-analysis of studies that validate microstructural imaging by combining it with myelin histology. We find meta-analytic evidence for correlations between myelin histology and markers from different MRI modalities, including fractional anisotropy, radial diffusivity, macromolecular pool, magnetization transfer ratio, susceptibility and longitudinal relaxation rate, but not mean diffusivity. Meta-analytic correlation effect sizes range widely, between R2 = 0.26 and R2 = 0.82. However, formal comparisons between MRI-based myelin markers are limited by methodological variability, inconsistent reporting and potential for publication bias, thus preventing the establishment of a single most sensitive strategy to measure myelin with MRI. To facilitate further progress, we provide a detailed characterisation of the evaluated studies as an online resource. We also share a set of 12 recommendations for future studies validating putative MR-based myelin markers and deploying them in vivo in humans. HighlightsO_LISystematic review and meta-analysis of studies validating microstructural imaging with myelin histology C_LIO_LIWe find many MR markers are sensitive to myelin, including FA, RD, MP, MTR, Susceptibility, R1, but not MD C_LIO_LIFormal comparisons between MRI-based myelin markers are limited by methodological variability, inconsistent reporting and potential for publication bias C_LIO_LIResults emphasize the advantage of using multimodal imaging when testing hypotheses related to myelin in vivo in humans. C_LI

Source connections

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Lazari, A., Lipp, I.. 2020-09-09. Can MRI measure myelin? Systematic review, qualitative assessment, and meta-analysis of studies validating microstructural imaging with myelin histology. https://doi.org/10.1101/2020.09.08.286518

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Simple, static, spiking nonlinearities can account for seemingly complex interactions between visual, motor and cognitive variables in the visual cortex.

Neural activity in the visual cortex is driven by the stimulus and modulated by multiple task-related variables, including spatial attention, eye movements, and perceptual decisions. These multiple influences are each typically described as nonlinear interactions such as gain or normalization, raising the question of how these diverse signals can be combined through cellular or circuit mechanisms. Here we address this problem by examining neuronal responses in macaque visual areas V2 and V3 during a visual discrimination task that dissociates spatial attention from motor planning and microsaccadic eye movements. Using a statistical modeling framework, we show that attentional, microsaccade-related, and choice-related influences on neural activity are best explained by a simple additive stimulus-independent input modulation, which manifests as a gain via a spiking nonlinearity. In addition to explaining how interactions between variables might be accomplished mechanistically, this framework also resolves a controversy about the relationship between microsaccades and spatial attention. We find that neither microsaccade direction nor microsaccade-related neural activity accounts for attentional modulation, although these variables are often correlated, leading to apparent interactions. Thus, visual cortex can integrate sensory, motor-related, and cognitive signals through a parsimonious mechanism that preserves stable stimulus representations while supporting flexible, context-dependent modulation.

neuroscience↗
bioRxiv2026

40 Hz visual stimulation increases gamma-band functional connectivity between visual, parietal and frontal regions

Visual stimulation at 40 Hz is being investigated as a non-invasive intervention for Alzheimer's disease. Its neural responses have been reported in regions beyond the visual cortex, and concurrent cognitive tasks have been shown to increase their spatial extent. However, it is unclear whether these responses reflect increased functional connectivity between regions or a common response to the stimulus, and whether a concurrent task changes this connectivity. We recorded EEG from 29 healthy young adults during Regular 40 Hz flicker and Irregular 30-50 Hz flicker, each with and without a target-counting task (2 x 2 within-participant design). Source-space connectivity between visual, parietal, and frontal regions was estimated with the debiased squared weighted phase-lag index (dWPLI). Regular stimulation increased 38-42 Hz connectivity for all three region pairs, with the largest increase between visual and parietal regions (increase in all 29 participants). The increase was specific to the stimulation frequency and was observed with two source reconstruction methods and in sensor space. The visual-parietal increase remained significant after correction for source leakage (spatial mixing between reconstructed sources) and after removal of the estimated stimulus-locked component, whereas the increases in visual-frontal and parietal-frontal connectivity did not. The concurrent task did not modulate the visual-parietal effect. For visual-frontal and parietal-frontal connectivity, the stimulation-by-ask interaction was not significant. These results show that 40 Hz visual stimulation increases gamma-band connectivity beyond the visual cortex, and much of this increase reflects a common stimulus-locked response, and connectivity beyond this response was observed mainly between visual and parietal regions.

neuroscience↗
bioRxiv2026

Feedback Valence, Prediction Error, and the Limits of Computational Attribution in Symptom-Related EEG

Feedback-locked electroencephalography (EEG) responses are often interpreted using model-derived prediction errors (PEs), although signed PE can be strongly coupled to feedback valence in binary-outcome tasks. We revisited a published anxiety-related EEG association using two open probabilistic-learning datasets to examine measurement reliability, predictor separability, and participant-level recovery. In the primary dataset, greater trait anxiety was associated with a larger negative-minus-positive FCz theta response among 46 participants with elevated depressive symptoms after adjustment for depression severity. The association also differed between the sampled depression-symptom groups. The feedback contrast showed useful within-session reliability, but matched delta and P3-minus-N2 analyses did not establish theta specificity. Within participants, feedback valence and signed PE were highly correlated (r = -0.964). Exact-design simulations showed that population-level model discrimination could succeed despite poor recovery of individual neural slopes. Participant-specific learning-model refits recovered overall signed PE more consistently than the within-valence variation needed to distinguish it from feedback valence. An independent dataset reproduced the FCz feedback contrast in untreated and placebo cohorts but lacked trait-anxiety scores. Adding signed PE to valence yielded a small held-out predictive improvement under one reinforcement-learning specification, with limited support across sessions and no comparable support under the dual-rate model or in placebo. Together, these findings support a symptom-related feedback EEG association while constraining its theta-specific and participant-level computational interpretation.

neuroscience↗