Do We Need a Human post mortem Whole-Brain Anatomical Ground Truth in in vivo Magnetic Resonance Imaging?

Non-invasive in vivo neuroimaging techniques provide a wide array of possibilities to study human brain function. A number of approaches are available that improve our understanding of the anatomical location of brain activation patterns, including the development of probabilistic conversion tools to register individual in vivo data to population based neuroanatomical templates. Two elegant examples were published by Horn et al. (2017) in which a method was described to warp DBS electrode coordinates, and histological data to MNI-space (Ewert et al., 2017). The conversion of individual brain scans to a standard space is done assuming that individual anatomical scans provide a reliable image of the underlying neuroanatomy. It is unclear to what extent spatial distortions related to tissue properties, or MRI artifacts exist in these scans. Therefore, the question rises whether the anatomical information from the individual scans can be considered a real ground truth. To accommodate the knowledge-gap as a result of limited anatomical information, generative brain models have been developed circumventing these challenges through the application of assumption sets without recourse to any ground truth. We would like to argue that, although these efforts are valuable, the definition of an anatomical ground truth is preferred. Its definition requires a system in which non-invasive approaches can be validated using invasive methods of investigation. We argue that the application of post mortem MRI studies in combination with microscopy analyses brings an anatomical ground truth for the human brain within reach, which is of importance for all research within the human in vivo neuroimaging field

Swallow Tail Sign: Revisited

The loss of the radiologic swallow tail sign on MRI scans of the substantia nigra is a promising diagnostic marker of Parkinson disease (1), although its anatom-ic underpinning is unclear. An early influential study showed that the hyperintense inner part of the swallow tail sign on T2*-weighted images (STh) corresponds to iron-poor areas in substantia nigra and suggested it to equal nigrosome 1, the dopaminergic region affected earliest and strongest in Parkinson disease (2). This would render the STh a cellularly specific marker (2). However, recent postmortem tissue studies have chal-lenged this interpretation, reporting that nigrosome 1 is hypointense in T2*-weighted images (3,4). We com-bined three-dimensional histology with 7-T in vivo and postmortem MRI to demonstrate that nigrosome 1 and the radiologic STh are partially overlapping but distinct

Thyroid hormone signaling in the hypothalamus

PURPOSE OF REVIEW: Proper thyroid hormone signaling is essential for brain development and adult brain function. Signaling can be disrupted at many levels due to altered thyroid hormone secretion, conversion or thyroid hormone receptor binding. RECENT FINDINGS: Mutated genes involved in thyroid hormone signaling in patients and animal models have increased the understanding of the (patho-)physiological consequences of altered thyroid hormone signaling. Neuroanatomical studies have provided more insight in the underlying neuroanatomical pathways. SUMMARY: A number of thyroid hormone signaling pathways in the hypothalamus have been proposed, which may be involved in the adaptation of the thyroid axis, not only to hypo- and hyperthyroidism, but also to inflammation, critical illness and fasting. Studies in knockout and transgenic mouse models have shown that the individual characteristics of mutations in thyroid hormone receptors can cause striking differences in the observed phenotype

Functional neuroanatomy of thyroid hormone feedback in the human hypothalamus and pituitary gland

A major change in thyroid setpoint regulation occurs in various clinical conditions such as critical illness and psychiatric disorders. As a first step towards identifying determinants of these setpoint changes, we have studied the distribution and expression of thyroid hormone receptor (TR) isoforms, type 2 and type 3 deiodinase (D2 and D3), and the thyroid hormone transporter monocarboxylate transporter 8 (MCT8) in the human hypothalamus and anterior pituitary. Although the post-mortem specimens used for these studies originated from patients who had died from many different pathologies, the anatomical distribution of these proteins was similar in all patients. D2 enzyme activity was detectable in the infundibular nucleus/median eminence (IFN/ME) region coinciding with local D2 immunoreactivity in glial cells. Additional D2 immunostaining was present in tanycytes lining the third ventricle. Thyrotropin-releasing hormone (TRH) containing neurons in the paraventricular nucleus (PVN) expressed MCT8, TRs as well as D3. These findings suggest that the prohormone thyroxine (T4) is taken up in hypothalamic glial cells that convert T4 into the biologically active triiodothyronine (T3) via the enzyme D2, and that T3 is subsequently transported to TRH producing neurons in the PVN. In these neurons, T3 may either bind to TRs or be metabolized into inactive iodothyronines by D3. By inference, local changes in thyroid hormone metabolism resulting from altered hypothalamic deiodinase or MCT8 expression may underlie the decrease in TRH mRNA reported earlier in the PVN of patients with critical illness and depression. In the anterior pituitary, D2 and MCT8 immunoreactivity occurred exclusively in folliculostellate (FS) cells. Both TR and D3 immunoreactivity was observed in gonadotropes and to a lesser extent in thyrotropes and other hormone producing cell types. Based upon these neuroanatomical findings, we propose a novel model for central thyroid hormone feedback in humans, with a pivotal role for hypothalamic glial cells and pituitary FS cells in processing and activation of T4. Production and action of T3 appear to occur in separate cell types of the human hypothalamus and anterior pituitar

Structure-function similarities in deep brain stimulation targets cross-species

Data, Syntax and results from the LDA topic modelling cross-species DBS projec

Quantity and quality: Normative open-access neuroimaging databases.

The focus of this article is to compare twenty normative and open-access neuroimaging databases based on quantitative measures of image quality, namely, signal-to-noise (SNR) and contrast-to-noise ratios (CNR). We further the analysis through discussing to what extent these databases can be used for the visualization of deeper regions of the brain, such as the subcortex, as well as provide an overview of the types of inferences that can be drawn. A quantitative comparison of contrasts including T1-weighted (T1w) and T2-weighted (T2w) images are summarized, providing evidence for the benefit of ultra-high field MRI. Our analysis suggests a decline in SNR in the caudate nuclei with increasing age, in T1w, T2w, qT1 and qT2* contrasts, potentially indicative of complex structural age-dependent changes. A similar decline was found in the corpus callosum of the T1w, qT1 and qT2* contrasts, though this relationship is not as extensive as within the caudate nuclei. These declines were accompanied by a declining CNR over age in all image contrasts. A positive correlation was found between scan time and the estimated SNR as well as a negative correlation between scan time and spatial resolution. Image quality as well as the number and types of contrasts acquired by these databases are important factors to take into account when selecting structural data for reuse. This article highlights the opportunities and pitfalls associated with sampling existing databases, and provides a quantitative backing for their usage

Multi-contrast anatomical subcortical structures parcellation

The human subcortex is comprised of more than 450 individual nuclei which lie deep in the brain. Due to their small size and close proximity, up until now only 7% have been depicted in standard MRI atlases. Thus, the human subcortex can largely be considered as terra incognita. Here, we present a new open-source parcellation algorithm to automatically map the subcortex. The new algorithm has been tested on 17 prominent subcortical structures based on a large quantitative MRI dataset at 7 Tesla. It has been carefully validated against expert human raters and previous methods, and can easily be extended to other subcortical structures and applied to any quantitative MRI dataset. In sum, we hope this novel parcellation algorithm will facilitate functional and structural neuroimaging research into small subcortical nuclei and help to chart terra incognita