Microstructural Parcellation of the Human Cerebral Cortex - From Brodmann's Post-Mortem Map to in vivo Mapping with High-Field Magnetic Resonance Imaging

Quantitative MRI at 7-Tesla reveals novel frontocortical myeloarchitecture anomalies in major depressive disorder

Whereas meta-analytical data highlight abnormal frontocortical macrostructure (thickness/surface area/volume) in Major Depressive Disorder (MDD), the underlying microstructural processes remain uncharted, due to the use of conventional MRI scanners and acquisition techniques. We uniquely combined Ultra-High Field MRI at 7.0 Tesla with Quantitative Imaging to map intracortical myelin (proxied by longitudinal relaxation time T1) and iron concentration (proxied by transverse relaxation time T2*), microstructural processes deemed particularly germane to cortical macrostructure. Informed by meta-analytical evidence, we focused specifically on orbitofrontal and rostral anterior cingulate cortices among adult MDD patients (N = 48) and matched healthy controls (HC; N = 10). Analyses probed the association of MDD diagnosis and clinical profile (severity, medication use, comorbid anxiety disorders, childhood trauma) with aforementioned microstructural properties. MDD diagnosis (p's < 0.05, Cohen's D = 0.55-0.66) and symptom severity (p's < 0.01, r = 0.271-0.267) both related to decreased intracortical myelination (higher T1 values) within the lateral orbitofrontal cortex, a region tightly coupled to processing negative affect and feelings of sadness in MDD. No relations were found with local iron concentrations. These findings allow uniquely fine-grained insights on frontocortical microstructure in MDD, and cautiously point to intracortical demyelination as a possible driver of macroscale cortical disintegrity in MDD.

Automated individual cortical parcellation via consensus graph representation learning

Cortical parcellation plays a pivotal role in elucidating the brain organization. Despite the growing efforts to develop parcellation algorithms using functional magnetic resonance imaging, achieving a balance between intra-individual specificity and inter-individual consistency proves challenging, making the generation of high-quality, subject-consistent cortical parcellations particularly elusive. To solve this problem, our paper proposes a fully automated individual cortical parcellation method based on consensus graph representation learning. The method integrates spectral embedding with low-rank tensor learning into a unified optimization model, which uses group-common connectivity patterns captured by low-rank tensor learning to optimize subjects' functional networks. This not only ensures consistency in brain representations across different subjects but also enhances the quality of each subject's representation matrix by eliminating spurious connections. More importantly, it achieves an adaptive balance between intra-individual specificity and inter-individual consistency during this process. Experiments conducted on a test-retest dataset from the Human Connectome Project (HCP) demonstrate that our method outperforms existing methods in terms of reproducibility, functional homogeneity, and alignment with task activation. Extensive network-based comparisons on the HCP S900 dataset reveal that the functional network derived from our cortical parcellation method exhibits greater capabilities in gender identification and behavior prediction than other approaches.

Associations between atypical intracortical myelin content and neuropsychological functions in middle to older aged adults with ASD

INTRODUCTION

In vivo myeloarchitectonic mapping based on Magnetic Resonance Imaging (MRI) provides a unique view of gray matter myelin content and offers information complementary to other morphological indices commonly employed in studies of autism spectrum disorder (ASD). The current study sought to determine if intracortical myelin content (MC) and its age-related trajectories differ between middle aged to older adults with ASD and age-matched typical comparison participants.

METHODS

Data from 30 individuals with ASD and 36 age-matched typical comparison participants aged 40-70 years were analyzed. Given substantial heterogeneity in both etiology and outcomes in ASD, we utilized both group-level and subject-level analysis approaches to test for signs of atypical intracortical MC as estimated by T1w/T2w ratio.

RESULTS

Group-level analyses showed no significant differences in average T1w/T2w ratio or its associations with age between groups, but revealed significant positive main effects of age bilaterally, with T1w/T2w ratio increasing with age across much of the cortex. In subject-level analyses, participants were classified into subgroups based on presence or absence of clusters of aberrant T1w/T2w ratio, and lower neuropsychological function was observed in the ASD subgroup with atypically high T1w/T2w ratio in spatially heterogeneous cortical regions. These differences were observed across several neuropsychological domains, including overall intellectual functioning, processing speed, and aspects of executive function.

CONCLUSIONS

The group-level and subject-level approaches employed here demonstrate the value of examining inter-individual variability and provide important preliminary insights into relationships between brain structure and cognition in the second half of the lifespan in ASD, suggesting shared factors contributing to atypical intracortical myelin content and poorer cognitive outcomes for a subset of middle aged to older autistic adults. These atypicalities likely reflect diverse histories of neurodevelopmental deficits, and possible compensatory changes, compounded by processes of aging, and may serve as useful markers of vulnerability to further cognitive decline in older adults with ASD.

7T MP2RAGE for cortical myelin segmentation: Impact of aging

BACKGROUND

Myelin and iron are major contributors to the cortical MR signal. The aim of this study was to investigate 1. Can MP2RAGE-derived contrasts at 7T in combination with k-means clustering be used to distinguish between heavily and sparsely myelinated layers in cortical gray matter (GM)? 2. Does this approach provide meaningful biological information?

METHODS

The following contrasts were generated from the 7T MP2RAGE images from 45 healthy controls (age: 19-75, f/m = 23/22) from the ATAG data repository: 1. T1 weighted image (UNI). 2. T1 relaxation image (T1map). 3. INVC/T1map ratio (RATIO). K-means clustering identified 6 clusters/tissue maps (csf, csf/gm-transition, wm, wm/gm transition, heavily myelinated cortical GM (dGM), sparsely myelinated cortical GM (sGM)). These tissue maps were then processed with SPM/DARTEL (volume-based analyses) and Freesurfer (surface-based analyses) and dGM and sGM volume/thickness of young adults (n = 27, 19-27 years) compared to those of older adults (n = 18, 42-75 years) at p<0.001 uncorrected.

RESULTS

The resulting maps showed good agreement with histological maps in the literature. Volume- and surface analyses found age-related dGM loss/thinning in the mid-posterior cingulate and parahippocampal/entorhinal gyrus and age-related sGM losses in lateral, mesial and orbitofrontal frontal, insular cortex and superior temporal gyrus.

CONCLUSION

The MP2RAGE derived UNI, T1map and RATIO contrasts can be used to identify dGM and sGM. Considering the close relationship between cortical myelo- and cytoarchitecture, the findings reported here indicate that this new technique might provide new insights into the nature of cortical GM loss in physiological and pathological conditions.

Analyzing the cortical fine structure as revealed by ex-vivo anatomical MRI

The human cortex has a rich fiber structure as revealed by myelin-staining of histological slices. Myelin also contributes to the image contrast in Magnetic Resonance Imaging (MRI). Recent advances in Magnetic Resonance (MR) scanner and imaging technology allowed the acquisition of an ex-vivo data set at an isotropic resolution of 100 µm. This study focused on a computational analysis of this data set with the aim of bridging between histological knowledge and MRI-based results. This work highlights: (1) the design and implementation of a processing chain that extracts intracortical features from a high-resolution MR image; (2) a demonstration of the correspondence between MRI-based cortical intensity profiles and the myelo-architectonic layering of the cortex; (3) the characterization and classification of four basic myelo-architectonic profile types; (4) the distinction of cortical regions based on myelo-architectonic features; and (5) the segmentation of cortical modules in the entorhinal cortex.

T1 relaxation time is prolonged in healthy aging: a whole brain study

BACKGROUND

: Measurement of tissue characteristics such as the longitudinal relaxation time (T1) provides complementary information to the volumetric and surface based structural analyses. We aimed to investigate T1 relaxation time characteristics in healthy aging via an exploratory design in the whole brain. The data processing pipeline was designed to minimize errors related to aging effects such as atrophy.

METHODS

Sixty healthy participants underwent MRI scanning (28 F, 32 M, age range: 18-78, 30 young and 30 old) in November 2017-March 2018 at the Bilkent University UMRAM Center. Four images with varying flip angles with FLASH (fast low angle shot magnetic resonance imaging) sequence and a high-resolution structural image with MP-RAGE (Magnetization Prepared - RApid Gradient Echo) were acquired. T1 relaxation times of the entire brain were mapped by using the region of interest (ROI) based method on 134 brain areas in young and old populations.

RESULTS

T1 prolongation was observed in various subcortical (bilateral hippocampus, caudate and thalamus) and cortical brain structures (bilateral precentral gyrus, bilateral middle frontal gyrus, bilateral supplementary motor area (SMA), left middle occipital gyrus, bilateral postcentral gyrus and bilateral Heschl's gyrus) as well as cerebellar regions (GM regions of cerebellum: bilateral cerebellum III, cerebellum IV V, cerebellum X, cerebellar vermis u 4 5, cerebellar vermis u 9 and WM cerebellar regions: left cerebellum IX, bilateral cerebellum X and cerebellar vermis u 4 5).

DISCUSSION

T1 mapping provides a practical quantitative MRI (qMRI) methodology for studying the tissue characteristics in healthy aging. T1 values are significantly increased in the aging group among half of the studied ROIs (57 ROIs out of 134).

Normative quantitative relaxation atlases for characterization of cortical regions using magnetic resonance fingerprinting

Quantitative magnetic resonance (MR) has been used to study cyto- and myelo-architecture of the human brain non-invasively. However, analyzing brain cortex using high-resolution quantitative MR acquisition can be challenging to perform using 3T clinical scanners. MR fingerprinting (MRF) is a highly efficient and clinically feasible quantitative MR technique that simultaneously provides T1 and T2 relaxation maps. Using 3D MRF from 40 healthy subjects (mean age = 25.6 ± 4.3 years) scanned on 3T magnetic resonance imaging, we generated whole-brain gyral-based normative MR relaxation atlases and investigated cortical-region-based T1 and T2 variations. Gender and age dependency of T1 and T2 variations were additionally analyzed. The coefficient of variation of T1 and T2 for each cortical-region was 3.5% and 7.3%, respectively, supporting low variability of MRF measurements across subjects. Significant differences in T1 and T2 were identified among 34 brain regions (P < 0.001), lower in the precentral, postcentral, paracentral lobule, transverse temporal, lateral occipital, and cingulate areas, which contain sensorimotor, auditory, visual, and limbic functions. Significant correlations were identified between age and T1 and T2 values. This study established whole-brain MRF T1 and T2 atlases of healthy subjects using a clinical 3T scanner, which can provide a quantitative and region-specific baseline for future brain studies and pathology detection.

The self and self-knowledge after frontal lobe neurosurgical lesions

BACKGROUND

Evidence suggests that damage to the frontal lobes can be associated with changes in cognitive and behavioral functioning and reduced awareness that such changes have occurred. In the current study, the Cognitive Awareness Model was used as a theoretical framework to explore knowledge of the self in people with acquired frontal lesions.

METHODS

Fifteen individuals with focal frontal lobe lesions (FFL) and their nominated informants were compared with fifteen healthy matched control-informant dyads on questionnaire measures designed to assess awareness of difficulties. Questionnaires were adapted to ensure all enabled pre- and post-injury perspectives to be gained from both patient and informant, and to allow novel exploration of awareness of deficits from a third person perspective.

RESULTS

Individuals with frontal lobe lesions showed adequate awareness of their post-surgery changes, which was substantiated by their informant report. Compared to the control group, the patient group was found to acknowledge more difficulties in current functioning. Perspective-taking ability was limited with both patients and controls being comparatively unreliable in assessing how they were perceived by others.

CONCLUSION

These results demonstrate that FLL patients are engaging in more atypical behaviors compared to healthy controls, but suggest that they are aware of and acknowledge these difficulties. The importance of obtaining multiple viewpoints when examining an individual's level of awareness and the clinical implications of this are discussed.

The Potential of Myelin-Sensitive Imaging: Redefining Spatiotemporal Patterns of Myeloarchitecture

Recent advances in magnetic resonance imaging (MRI) have paved the way for approximation of myelin content in vivo. In this review, our main goal was to determine how to best capitalize on myelin-sensitive imaging. First, we briefly overview the theoretical and empirical basis for the myelin sensitivity of different MRI markers and, in doing so, highlight how multimodal imaging approaches are important for enhancing specificity to myelin. Then, we discuss recent studies that have probed the nonuniform distribution of myelin across cortical layers and along white matter tracts. These approaches, collectively known as myelin profiling, have provided detailed depictions of myeloarchitecture in both the postmortem and living human brain. Notably, MRI-based profiling studies have recently focused on investigating whether it can capture interindividual variability in myelin characteristics as well as trajectories across the lifespan. Finally, another line of recent evidence emphasizes the contribution of region-specific myelination to large-scale organization, demonstrating the impact of myelination on global brain networks. In conclusion, we suggest that combining well-validated MRI markers with profiling techniques holds strong potential to elucidate individual differences in myeloarchitecture, which has important implications for understanding brain function and disease.

Long-range functional connections mirror and link microarchitectural and cognitive hierarchies in the human brain

BACKGROUND

Higher-order cognition is hypothesized to be implemented via distributed cortical networks that are linked via long-range connections. However, it is unknown how computational advantages of long-range connections reflect cortical microstructure and microcircuitry.

METHODS

We investigated this question by (i) profiling long-range cortical connectivity using resting-state functional magnetic resonance imaging (MRI) and cortico-cortical geodesic distance mapping, (ii) assessing how long-range connections reflect local brain microarchitecture, and (iii) examining the microarchitectural similarity of regions connected through long-range connections.

RESULTS

Analysis of 2 independent datasets indicated that sensory/motor areas had more clustered short-range connections, while transmodal association systems hosted distributed, long-range connections. Meta-analytical decoding suggested that this topographical difference mirrored shifts in cognitive function, from perception/action towards emotional/social processing. Analysis of myelin-sensitive in vivo MRI as well as postmortem histology and transcriptomics datasets established that gradients in functional connectivity distance are paralleled by those present in cortical microarchitecture. Notably, long-range connections were found to link spatially remote regions of association cortex with an unexpectedly similar microarchitecture.

CONCLUSIONS

By mapping covarying topographies of long-range functional connections and cortical microcircuits, the current work provides insights into structure-function relations in human neocortex.

Towards automated in vivo parcellation of the human cerebral cortex using supervised classification of magnetic resonance fingerprinting residuals

BACKGROUND

Accurate parcellation of the cerebral cortex in an individual is a guide to its underlying organization. The most promising in vivo quantitative magnetic resonance (MR)-based microstructural cortical mapping methods are yet to achieve a level of parcellation accuracy comparable to quantitative histology.

METHODS

We scanned 6 participants using a 3D echo-planar imaging MR fingerprinting (EPI-MRF) sequence on a 7T Siemens scanner. After projecting MRF signals to the individual-specific inflated model of the cortical surface, normalized autocorrelations of MRF residuals of vertices of 8 microstructurally distinct areas (BA1, BA2, BA4a, BA6, BA44, BA45, BA17, and BA18) from 3 cortical regions were used as feature vector inputs into linear support vector machine (SVM), radial basis function SVM (RBF-SVM), random forest, and k-nearest neighbors supervised classification algorithms. The algorithms' prediction performance was compared using: (i) features from each vertex or (ii) features from neighboring vertices.

RESULTS

The neighborhood-based RBF-SVM classifier achieved the highest prediction score of 0.85 for classification of MRF residuals in the central region from a held-out participant.

CONCLUSIONS

We developed an automated method of cortical parcellation using a combination of MR fingerprinting residual analysis and machine learning classification. Our findings provide the basis for employing unsupervised learning algorithms for whole-cortex structural parcellation in individuals.

Iron quantitative analysis of motor combined with bulbar region in M1 cortex may improve diagnosis performance in ALS

OBJECTIVES

To explore whether the combined analysis of motor and bulbar region of M1 on susceptibility-weighted imaging (SWI) can be a valid biomarker for amyotrophic lateral sclerosis (ALS).

METHODS

Thirty-two non-demented ALS patients and 35 age- and gender-matched healthy controls (HC) were retrospectively recruited. SWI and 3D-T1-MPRAGE images were obtained from all individuals using a 3.0-T MRI scan. The bilateral posterior band of M1 was manually delineated by three neuroradiologists on phase images and subdivided into the motor and bulbar regions. We compared the phase values in two groups and performed a stratification analysis (ALSFRS-R score, duration, disease progression rate, and onset). Receiver operating characteristic (ROC) curves were also constructed.

RESULTS

ALS group showed significantly increased phase values in M1 and the two subregions than the HC group, on the all and elderly level (p < 0.001, respectively). On all-age level comparison, negative correlations were found between phase values of M1 and clinical score and duration (p < 0.05, respectively). Similar associations were found in the motor region (p < 0.05, respectively). On both the total (p < 0.01) and elderly (p < 0.05) levels, there were positive relationships between disease progression rate and M1 phase values. In comparing ROC curves, the entire M1 showed the best diagnostic performance.

CONCLUSIONS

Combining motor and bulbar analyses as an integral M1 region on SWI can improve ALS diagnosis performance, especially in the elderly. The phase value could be a valuable biomarker for ALS evaluation.

KEY POINTS

• Integrated analysis of the motor and bulbar as an entire M1 region on SWI can improve the diagnosis performance in ALS. • Quantitative analysis of iron deposition by SWI measurement helps the clinical evaluation, especially for the elderly patients. • Phase value, when combined with the disease progression rate, could be a valuable biomarker for ALS.

Mapping myelin in white matter with T1-weighted/T2-weighted maps: discrepancy with histology and other myelin MRI measures

The ratio of T1-weighted/T2-weighted magnetic resonance images (T1w/T2w MRI) has been successfully applied at the cortical level since 2011 and is now one of the most used myelin mapping methods. However, no reports have explored the histological validity of T1w/T2w myelin mapping in white matter. Here we compare T1w/T2w with ex vivo postmortem histology and in vivo MRI methods, namely quantitative susceptibility mapping (QSM) and multi-echo T2 myelin water fraction (MWF) mapping techniques. We report a discrepancy between T1w/T2w myelin maps of the human corpus callosum and the histology and analyse the putative causes behind such discrepancy. T1w/T2w does not positively correlate with Luxol Fast Blue (LFB)-Optical Density but shows a weak to moderate, yet significant, negative correlation. On the contrary, MWF is strongly and positively correlated with LFB, whereas T1w/T2w and MWF maps are weakly negatively correlated. The discrepancy between T1w/T2w MRI maps, MWF and histological myelin maps suggests caution in using T1w/T2w as a white matter mapping method at the callosal level. While T1w/T2w imaging may correlate with myelin content at the cortical level, it is not a specific method to map myelin density in white matter.

Myeloarchitectonic maps of the human cerebral cortex registered to surface and sections of a standard atlas brain

C. and O. Vogt had set up a research program with the aim of establishing a detailed cartography of the medullary fiber distribution of the human brain. As part of this program, around 200 cortical fields were differentiated based on their myeloarchitectural characteristics and mapped with regard to their exact location in the isocortex. The typical features were graphically documented and classified by a sophisticated linguistic coding. Their results have only recently received adequate attention and applications. The reasons for the revival of this spectrum of their research include interest in the myeloarchitecture of the cortex as a differentiating feature of the cortex architecture and function, as well as the importance for advanced imaging methodologies, particularly tractography and molecular imaging. Here, we describe our approach to exploit the original work of the Vogts and their co-workers to construct a myeloarchitectonic map that is referenced to the Atlas of the Human Brain (AHB) in standard space. We developed a semi-automatic pipeline for processing and integrating the various original maps into a single coherent map. To optimize the precision of the registration between the published maps and the AHB, we augmented the maps with topographic landmarks of the brains that were originally analyzed. Registration of all maps into the AHB opened several possibilities. First, for the majority of the fields, multiple maps from different authors are available, which allows for sophisticated statistical integration, for example, unification with a label-fusion technique. Second, each field in the myeloarchitectonic surface map can be visualized on the myelin-stained cross-section of the AHB at the best possible correspondence. The features of each field can be correlated with the fiber-stained cross-sections in the AHB and with the extensive published materials from the Vogt school and, if necessary, corrected. Third, mapping to the AHB allows the relationship between fiber characteristics of the cortex and the subcortex to be examined. Fourth, the cytoarchitectonic maps from Brodmann and von Economo and Koskinas, which are also registered to the AHB, can be compared. This option allows the study of the correspondence between cyto- and myeloarchitecture in each field. Finally, by using our "stripe" technology - where any other feature registered to the same space can be directly compared owing to the linear and parallel representation of the correlated cortex segments - this map becomes part of a multidimensional co-registration platform.

Cytoarchitecture, myeloarchitecture, and parcellation of the chimpanzee inferior parietal lobe

The parietal lobe is a region of especially pronounced change in human brain evolution. Based on comparative neuroanatomical studies, the inferior parietal lobe (IPL) has been shown to be disproportionately larger in humans relative to chimpanzees and macaques. However, it remains unclear whether the underlying histological architecture of IPL cortical areas displays human-specific organization. Chimpanzees are among the closest living relatives of humans, making them an ideal comparative species to investigate potential evolutionary changes in the IPL. We parcellated the chimpanzee IPL using cytoarchitecture and myeloarchitecture, in combination with quantitative comparison of cellular features between the identified cortical areas. Four major areas on the lateral convexity of the chimpanzee IPL (PF, PFG, PG, OPT) and two opercular areas (PFOP, PGOP) were identified, similar to what has been observed in macaques. Analysis of the quantitative profiles of cytoarchitecture showed that cell profile density was significantly different in a combination of layers III, IV, and V between bordering cortical areas, and that the density profiles of these six areas supports their classification as distinct. The similarity to macaque IPL cytoarchitecture suggests that chimpanzees share homologous IPL areas. In comparison, human rostral IPL is reported to differ in its anatomical organization and to contain additional subdivisions, such as areas PFt and PFm. These changes in human brain evolution might have been important as tool making capacities became more complex.

Mesoscopic in vivo human T2* dataset acquired using quantitative MRI at 7 Tesla

Mesoscopic (0.1-0.5 mm) interrogation of the living human brain is critical for advancing neuroscience and bridging the resolution gap with animal models. Despite the variety of MRI contrasts measured in recent years at the mesoscopic scale, in vivo quantitative imaging of T₂^* has not been performed. Here we provide a dataset containing empirical T₂^* measurements acquired at 0.35 × 0.35 × 0.35 mm³ voxel resolution using 7 Tesla MRI. To demonstrate unique features and high quality of this dataset, we generate flat map visualizations that reveal fine-scale cortical substructures such as layers and vessels, and we report quantitative depth-dependent T₂^* (as well as R₂^*) values in primary visual cortex and auditory cortex that are highly consistent across subjects. This dataset is freely available at https://doi.org/10.17605/OSF.IO/N5BJ7, and may prove useful for anatomical investigations of the human brain, as well as for improving our understanding of the basis of the T₂^*-weighted (f)MRI signal.

Quantitative myelin-related maps from R1 and T2* ratio images using a single ME-MP2RAGE sequence in 7T MRI

Background: There still are limitations associated with quantifying myelin content using brain magnetic resonance imaging (MRI) despite several studies conducted on this subject. Therefore, this study aimed: (1) to propose a myelin-related mapping technique to obtain the quantitative R1/T2* (q-Ratio) that has the advantage of quick processing and less dependency on imaging parameters, (2) to validate this adapted q-Ratio method by comparing the quantitative myelin-related map with those acquired through an existing mapping method [T1-weighted/T2*-weighted (w-Ratio)], and (3) to determine the q-Ratio myelin-related values in the white and gray matter, and the relationship between the q-Ratio myelin-related value and cerebral volume size in regions of interest (ROIs) in a healthy population.

Methods: The multi-echo magnetization-prepared 2 rapid gradient echoes (ME-MP2RAGE) sequence was used in a 7 Tesla (7T) MRI for the acquisition of data regarding myelin content in 10 healthy participants. A correlation analysis was performed between myelin-related values obtained through the q-Ratio and w-Ratio methods. Additionally, myelin distribution was analyzed and compared in the white and gray matter, and the correlation between cerebral volume size and q-Ratio myelin-related value was analyzed in ROIs in the brain.

Results: The myelin-related maps acquired through the q-Ratio and w-Ratio methods were significantly correlated (p &lt; 0.001), but the q-Ratio myelin-related map was much clearer. Additionally, the cerebral volume size in the gray matter was 399.40% larger than that in the white matter, but the q-Ratio myelin-related value in the gray matter was 80.83% lower than that of the white matter. Furthermore, volume size was positively correlated with q-Ratio myelin-related values in the white matter (r = 0.509, p = 0.006) but not in the gray matter (r = -0.133, p = 0.402).

Conclusions: In this study, we validated using a q-Ratio myelin-related map that was acquired in one imaging sequence at 7T MRI. In addition, we found a significant correlation between ROI volume size and the q-Ratio myelin-related value in the white matter but not in the gray matter. It is expected that this technique could be applied to the study of various neuropsychiatric diseases related to demyelination in the future.

Cortical Myelination in Toddlers and Preschoolers with Autism Spectrum Disorder

Intracortical myelin is thought to play a significant role in the development of neural circuits and functional networks, with consistent evidence of atypical network connectivity in children with autism spectrum disorders (ASD). However, little is known about the development of intracortical myelin in the first years of life in ASD, during the critical neurodevelopmental period when autism symptoms first emerge. Using T1-weighted (T1w) and T2-weighted (T2w) structural magnetic resonance imaging (MRI) in 21 young children with ASD and 16 typically developing (TD) children, ages 1.5 to 5.5 years, we demonstrate the feasibility of estimating intracortical myelin in vivo using the T1w/T2w ratio as a proxy. The resultant T1w/T2w maps were largely comparable with those reported in prior T1w/T2w studies in typically developing children and adults, and revealed no group differences between TD children and those with ASD. However, differential associations between T1w/T2w and age were identified in several early myelinated regions (e.g., visual, posterior cingulate, precuneus cortices) in the ASD and TD groups, with age-related increase in estimated myelin content across the toddler and preschool years detected in TD children, but not in children with ASD. The atypical age-related effects in intracortical myelin, suggesting a disrupted myelination in the first years of life in ASD, may be related to the aberrant brain network connectivity reported in young children with ASD in some of the same cortical regions and circuits. This article is protected by copyright. All rights reserved.

In vivo measurements of lamination patterns in the human cortex

The laminar composition of the cerebral cortex is tightly connected to the development and connectivity of the brain, as well as to function and pathology. Although most of the research on the cortical layers is done with the aid of ex vivo histology, there have been recent attempts to use magnetic resonance imaging (MRI) with potential in vivo applications. However, the high‐resolution MRI technology and protocols required for such studies are neither common nor practical. In this article, we present a clinically feasible method for assessing the laminar properties of the human cortex using standard pulse sequence available on any common MRI scanner. Using a series of low‐resolution inversion recovery (IR) MRI scans allows us to calculate multiple T₁ relaxation time constants for each voxel. Based on the whole‐brain T₁‐distribution, we identify six different gray matter T₁ populations and their variation across the cortex. Based on this, we show age‐related differences in these population and demonstrate that this method is able to capture the difference in laminar composition across varying brain areas. We also provide comparison to ex vivo high‐resolution MRI scans. We show that this method is feasible for the estimation of layer variability across large population cohorts, which can lead to research into the links between the cortical layers and function, behavior and pathologies that was heretofore unexplorable.

Test-retest stability of spontaneous brain activity and functional connectivity in the core resting-state networks assessed with ultrahigh field 7-Tesla resting-state functional magnetic resonance imaging

The growing demand for precise and reliable biomarkers in psychiatry is fueling research interest in the hope that identifying quantifiable indicators will improve diagnoses and treatment planning across a range of mental health conditions. The individual properties of brain networks at rest have been highlighted as a possible source for such biomarkers, with the added advantage that they are relatively straightforward to obtain. However, an important prerequisite for their consideration is their reproducibility. While the reliability of resting‐state (RS) measurements has often been studied at standard field strengths, they have rarely been investigated using ultrahigh‐field (UHF) magnetic resonance imaging (MRI) systems. We investigated the intersession stability of four functional MRI RS parameters—amplitude of low‐frequency fluctuations (ALFF) and fractional ALFF (fALFF; representing the spontaneous brain activity), regional homogeneity (ReHo; measure of local connectivity), and degree centrality (DC; measure of long‐range connectivity)—in three RS networks, previously shown to play an important role in several psychiatric diseases—the default mode network (DMN), the central executive network (CEN), and the salience network (SN). Our investigation at individual subject space revealed a strong stability for ALFF, ReHo, and DC in all three networks, and a moderate level of stability in fALFF. Furthermore, the internetwork connectivity between each network pair was strongly stable between CEN/SN and moderately stable between DMN/SN and DMN/SN. The high degree of reliability and reproducibility in capturing the properties of the three major RS networks by means of UHF‐MRI points to its applicability as a potentially useful tool in the search for disease‐relevant biomarkers.

The Representation of Time Windows in Primate Auditory Cortex

Whether human and nonhuman primates process the temporal dimension of sound similarly remains an open question. We examined the brain basis for the processing of acoustic time windows in rhesus macaques using stimuli simulating the spectrotemporal complexity of vocalizations. We conducted functional magnetic resonance imaging in awake macaques to identify the functional anatomy of response patterns to different time windows. We then contrasted it against the responses to identical stimuli used previously in humans. Despite a similar overall pattern, ranging from the processing of shorter time windows in core areas to longer time windows in lateral belt and parabelt areas, monkeys exhibited lower sensitivity to longer time windows than humans. This difference in neuronal sensitivity might be explained by a specialization of the human brain for processing longer time windows in speech.

Mapping the human lateral geniculate nucleus and its cytoarchitectonic subdivisions using quantitative MRI

The human lateral geniculate nucleus (LGN) of the visual thalamus is a key subcortical processing site for visual information analysis. Due to its small size and deep location within the brain, a non-invasive characterization of the LGN and its microstructurally distinct magnocellular (M) and parvocellular (P) subdivisions in humans is challenging. Here, we investigated whether structural quantitative MRI (qMRI) methods that are sensitive to underlying microstructural tissue features enable MR-based mapping of human LGN M and P subdivisions. We employed high-resolution 7 Tesla in-vivo qMRI in N = 27 participants and ultra-high resolution 7 Tesla qMRI of a post-mortem human LGN specimen. We found that a quantitative assessment of the LGN and its subdivisions is possible based on microstructure-informed qMRI contrast alone. In both the in-vivo and post-mortem qMRI data, we identified two components of shorter and longer longitudinal relaxation time (T₁) within the LGN that coincided with the known anatomical locations of a dorsal P and a ventral M subdivision, respectively. Through ground-truth histological validation, we further showed that the microstructural MRI contrast within the LGN pertains to cyto- and myeloarchitectonic tissue differences between its subdivisions. These differences were based on cell and myelin density, but not on iron content. Our qMRI-based mapping strategy paves the way for an in-depth understanding of LGN function and microstructure in humans. It further enables investigations into the selective contributions of LGN subdivisions to human behavior in health and disease.

Spatially Covarying Patterns of Gray Matter Volume and Concentration Highlight Distinct Regions in Schizophrenia

Introduction: Individuals with schizophrenia have consistent gray matter reduction throughout the cortex when compared to healthy individuals. However, the reduction patterns vary based on the quantity (concentration or volume) utilized by study. The objective of this study was to identify commonalities between gray matter concentration and gray matter volume effects in schizophrenia.

Methods: We performed both univariate and multivariate analyses of case/control effects on 145 gray matter images from 66 participants with schizophrenia and 79 healthy controls, and processed to compare the concentration and volume estimates.

Results: Diagnosis effects in the univariate analysis showed similar areas of volume and concentration reductions in the insula, occipitotemporal gyrus, temporopolar area, and fusiform gyrus. In the multivariate analysis, healthy controls had greater gray matter volume and concentration additionally in the superior temporal gyrus, prefrontal cortex, cerebellum, calcarine, and thalamus. In the univariate analyses there was moderate overlap between gray matter concentration and volume across the entire cortex (r = 0.56, p = 0.02). The multivariate analyses revealed only low overlap across most brain patterns, with the largest correlation (r = 0.37) found in the cerebellum and vermis.

Conclusions: Individuals with schizophrenia showed reduced gray matter volume and concentration in previously identified areas of the prefrontal cortex, cerebellum, and thalamus. However, there were only moderate correlations across the cortex when examining the different gray matter quantities. Although these two quantities are related, concentration and volume do not show identical results, and therefore, should not be used interchangeably in the literature.

Magnetic resonance fingerprinting residual signals can disassociate human grey matter regions

The importance of accurate structural discrimination of the human grey matter regions has motivated the development of observer-independent reproducible methods that account for inter-individual architectonic variations. We introduce a non-invasive statistical residual analysis framework, employing unique tissue-specific magnetic resonance fingerprinting (MRF) signals after adjusting for the effect of T₁ and T₂^* MR relaxometry parameters (here termed MRF residuals). A 7 T Siemens MR scanner was used to acquire MRF signals, quantitative transmit magnetic field (B₁⁺) maps and T₁-weighted anatomical images of eleven cortical areas (5L, 5M, 5Ci, 7A, 7P, 7PC, hIP3, BA2, BA4a, BA4p and BA6) from six female participants. MRF residual signal for each voxel was calculated as the difference between the actual and best matching MRF signal evolutions from a precomputed MRF dictionary covering a range of T₁, T₂^* and B₁⁺ values. To compare MRF residuals between regions of interest, normalised autocorrelation was used as a shape-based statistical signal characterisation method and the Euclidean distance between autocorrelation profiles of residuals was used to measure the interareal dissimilarity. In the eleven cortical areas in both cerebral hemispheres of six participants, the proposed MRF residual analysis consistently showed interareal dissimilarity profiles that concorded with histological studies, indicating that MRF residuals potentially contain tissue microstructural information. MRF residual signals provide additional area-specific information that is complementary to the MR relaxometry-based (T₁, T₂^*) information used previously for distinguishing microstructural differences between human cerebral cortex regions in vivo. The proposed approach led to more accurate identification of structural variations across cortical areas of interest.

The effects of age on resting-state BOLD signal variability is explained by cardiovascular and cerebrovascular factors

Accurate identification of brain function is necessary to understand neurocognitive aging, and thereby promote health and well-being. Many studies of neurocognitive aging have investigated brain function with the blood-oxygen level-dependent (BOLD) signal measured by functional magnetic resonance imaging. However, the BOLD signal is a composite of neural and vascular signals, which are differentially affected by aging. It is, therefore, essential to distinguish the age effects on vascular versus neural function. The BOLD signal variability at rest (known as resting state fluctuation amplitude, RSFA), is a safe, scalable, and robust means to calibrate vascular responsivity, as an alternative to breath-holding and hypercapnia. However, the use of RSFA for normalization of BOLD imaging assumes that age differences in RSFA reflecting only vascular factors, rather than age-related differences in neural function (activity) or neuronal loss (atrophy). Previous studies indicate that two vascular factors, cardiovascular health (CVH) and cerebrovascular function, are insufficient when used alone to fully explain age-related differences in RSFA. It remains possible that their joint consideration is required to fully capture age differences in RSFA. We tested the hypothesis that RSFA no longer varies with age after adjusting for a combination of cardiovascular and cerebrovascular measures. We also tested the hypothesis that RSFA variation with age is not associated with atrophy. We used data from the population-based, lifespan Cam-CAN cohort. After controlling for cardiovascular and cerebrovascular estimates alone, the residual variance in RSFA across individuals was significantly associated with age. However, when controlling for both cardiovascular and cerebrovascular estimates, the variance in RSFA was no longer associated with age. Grey matter volumes did not explain age differences in RSFA, after controlling for CVH. The results were consistent between voxel-level analysis and independent component analysis. Our findings indicate that cardiovascular and cerebrovascular signals are together sufficient predictors of age differences in RSFA. We suggest that RSFA can be used to separate vascular from neuronal factors, to characterize neurocognitive aging. We discuss the implications and make recommendations for the use of RSFA in the research of aging.

Quantitative T1 mapping using multi-slice multi-shot inversion recovery EPI

An efficient multi-slice inversion–recovery EPI (MS-IR-EPI) sequence for fast, high spatial resolution, quantitative T₁ mapping is presented, using a segmented simultaneous multi-slice acquisition, combined with slice order shifting across multiple acquisitions. The segmented acquisition minimises the effective TE and readout duration compared to a single-shot EPI scheme, reducing geometric distortions to provide high quality T₁ maps with a narrow point-spread function. The precision and repeatability of MS-IR-EPI T₁ measurements are assessed using both T₁-calibrated and T₂-calibrated ISMRM/NIST phantom spheres at 3 and 7 T and compared with single slice IR and MP2RAGE methods. Magnetization transfer (MT) effects of the spectrally-selective fat-suppression (FS) pulses required for in vivo imaging are shown to shorten the measured in-vivo T₁ values. We model the effect of these fat suppression pulses on T₁ measurements and show that the model can remove their MT contribution from the measured T₁, thus providing accurate T₁ quantification. High spatial resolution T₁ maps of the human brain generated with MS-IR-EPI at 7 T are compared with those generated with the widely implemented MP2RAGE sequence. Our MS-IR-EPI sequence provides high SNR per unit time and sharper T₁ maps than MP2RAGE, demonstrating the potential for ultra-high resolution T₁ mapping and the improved discrimination of functionally relevant cortical areas in the human brain.

Evolution of Human Brain Atlases in Terms of Content, Applications, Functionality, and Availability

Human brain atlases have been evolving tremendously, propelled recently by brain big projects, and driven by sophisticated imaging techniques, advanced brain mapping methods, vast data, analytical strategies, and powerful computing. We overview here this evolution in four categories: content, applications, functionality, and availability, in contrast to other works limited mostly to content. Four atlas generations are distinguished: early cortical maps, print stereotactic atlases, early digital atlases, and advanced brain atlas platforms, and 5 avenues in electronic atlases spanning the last two generations. Content-wise, new electronic atlases are categorized into eight groups considering their scope, parcellation, modality, plurality, scale, ethnicity, abnormality, and a mixture of them. Atlas content developments in these groups are heading in 23 various directions. Application-wise, we overview atlases in neuroeducation, research, and clinics, including stereotactic and functional neurosurgery, neuroradiology, neurology, and stroke. Functionality-wise, tools and functionalities are addressed for atlas creation, navigation, individualization, enabling operations, and application-specific. Availability is discussed in media and platforms, ranging from mobile solutions to leading-edge supercomputers, with three accessibility levels. The major application-wise shift has been from research to clinical practice, particularly in stereotactic and functional neurosurgery, although clinical applications are still lagging behind the atlas content progress. Atlas functionality also has been relatively neglected until recently, as the management of brain data explosion requires powerful tools. We suggest that the future human brain atlas-related research and development activities shall be founded on and benefit from a standard framework containing the core virtual brain model cum the brain atlas platform general architecture.

Pragmatic spatial sampling for wearable MEG arrays

Several new technologies have emerged promising new Magnetoencephalography (MEG) systems in which the sensors can be placed close to the scalp. One such technology, Optically Pumped MEG (OP-MEG) allows for a scalp mounted system that provides measurements within millimetres of the scalp surface. A question that arises in developing on-scalp systems is: how many sensors are necessary to achieve adequate performance/spatial discrimination? There are many factors to consider in answering this question such as the signal to noise ratio (SNR), the locations and depths of the sources, density of spatial sampling, sensor gain errors (due to interference, subject movement, cross-talk, etc.) and, of course, the desired spatial discrimination. In this paper, we provide simulations which show the impact these factors have on designing sensor arrays for wearable MEG. While OP-MEG has the potential to provide high information content at dense spatial samplings, we find that adequate spatial discrimination of sources (< 1 cm) can be achieved with relatively few sensors (< 100) at coarse spatial samplings (~ 30 mm) at high SNR. After this point approximately 50 more sensors are required for every 1 mm improvement in spatial discrimination. Comparable discrimination for traditional cryogenic systems require more channels by these same metrics. We also show that sensor gain errors have the greatest impact on discrimination between deep sources at high SNR. Finally, we also examine the limitation that aliasing due to undersampling has on the effective SNR of on-scalp sensors.

Source localization of epileptic spikes using Multiple Sparse Priors

OBJECTIVE

To evaluate epileptic source estimation using multiple sparse priors (MSP) inverse method and high-resolution, individual electrical head models.

METHODS

Accurate source localization is dependent on accurate electrical head models and appropriate inverse solvers. Using high-resolution, individual electrical head models in fifteen epilepsy patients, with surgical resection and clinical outcome as criteria for accuracy, performance of MSP method was compared against standardized low-resolution brain electromagnetic tomography (sLORETA) and coherent maximum entropy on the mean (cMEM) methods.

RESULTS

The MSP method performed similarly to the sLORETA method and slightly better than the cMEM method in terms of success rate. The MSP and cMEM methods were more focal than sLORETA with the advantage of not requiring an arbitrary selection of a hyperparameter or thresholding of reconstructed current density values to determine focus. MSP and cMEM methods were better than sLORETA in terms of spatial dispersion.

CONCLUSIONS

Results suggest that the three methods are complementary and could be used together. In practice, the MSP method will be easier to use and interpret compared to sLORETA, and slightly more accurate and faster than the cMEM method.

SIGNIFICANCE

Source localization of interictal spikes from dense-array electroencephalography data has been shown to be a reliable marker of epileptic foci and useful for pre-surgical planning. The advantages of MSP make it a useful complement to other inverse solvers in clinical practice.

Pure Apraxia of Speech After Resection Based in the Posterior Middle Frontal Gyrus

BACKGROUND AND IMPORTANCE

Apraxia of speech is a disorder of articulatory coordination and planning in speech sound production. Its diagnosis is based on deficits in articulation, prosody, and fluency. It is often described concurrent with aphasia or dysarthria, while pure apraxia of speech is a rare entity.

CLINICAL PRESENTATION

A right-handed man underwent focal surgical resection of a recurrent grade III astrocytoma in the left hemisphere dorsal premotor cortex located in the posterior middle frontal gyrus. After the procedure, he experienced significant long-term speech production difficulties. A battery of standard and custom language and articulatory assessments were administered, revealing intact comprehension and naming abilities, and preserved strength in orofacial articulators, but considerable deficits in articulatory coordination, fluency, and prosody-consistent with diagnosis of pure apraxia of speech. Tractography and resection volumes compared with publicly available imaging data from the Human Connectome Project suggest possible overlap with area 55b, an under-recognized language area in the dorsal premotor cortex and has white matter connectivity with the superior longitudinal fasciculus.

CONCLUSION

The case reported here details a rare clinical entity, pure apraxia of speech resulting from resection of posterior middle frontal gyrus. While not a classical language area, emerging literature supports the role of this area in the production of fluent speech, and has implications for surgical planning and the general neurobiology of language.

Neuroscience of the auditory-motor system: How does sound interact with movement?

Human musicality is a complex problem because it involves the coupling of multiple exogenous and endogenous signals with different physical properties. The synchronization of these signals translates into specific behaviors. The study of this synchronization, based on the physical properties of two oscillatory bodies, is the first step in understanding the behaviors associated with rhythmic auditory stimuli. In recent years, different neurorehabilitation therapies have emerged for motor pathologies involving music. However, the neurophysiological bases that describe the coupling phenomenon are not yet fully understood. In this article, two theories are addressed that attempt to explain the convergence of the auditory system and the motor system according to new neuroanatomical, neurophysiological and artificial neural network findings. It also reflects on the different approaches to a complex problem in cognitive neuroscience and the need for a study model for the different motor behaviors evoked by auditory stimuli.

So You Want to Image Myelin Using MRI: An Overview and Practical Guide for Myelin Water Imaging

Myelin water imaging (MWI) is an MRI imaging biomarker for myelin. This method can generate an in vivo whole-brain myelin water fraction map in approximately 10 minutes. It has been applied in various applications including neurodegenerative disease, neurodevelopmental, and neuroplasticity studies. In this review we start with a brief introduction of myelin biology and discuss the contributions of myelin in conventional MRI contrasts. Then the MRI properties of myelin water and four different MWI methods, which are categorized as T₂ -, T₂ *-, T₁ -, and steady-state-based MWI, are summarized. After that, we cover more practical issues such as availability, interpretation, and validation of these methods. To illustrate the utility of MWI as a clinical research tool, MWI studies for two diseases, multiple sclerosis and neuromyelitis optica, are introduced. Additional topics about imaging myelin in gray matter and non-MWI methods for myelin imaging are also included. Although technical and physiological limitations exist, MWI is a potent surrogate biomarker of myelin that carries valuable and useful information of myelin. Evidence Level: 5 Technical Efficacy: 1 J. MAGN. RESON. IMAGING 2021;53:360-373.

Brainglance: Visualizing Group Level MRI Data at One Glance

The vast majority of studies using functional magnetic resonance imaging (fMRI) are analyzed on the group level. Standard group-level analyses, however, come with severe drawbacks: First, they assume functional homogeneity within the group, building on the idea that we use our brains in similar ways. Second, group-level analyses require spatial warping and substantial smoothing to accommodate for anatomical variability across subjects. Such procedures massively distort the underlying fMRI data, which hampers the spatial specificity. Taken together, group statistics capture the effective overlap, rendering the modeling of individual deviations impossible – a major source of false positivity and negativity. The alternative analysis approach is to leave the data in the native subject space, but this makes comparison across individuals difficult. Here, we propose a new framework for visualizing group-level information, better preserving the information of individual subjects. Our proposal is to limit the use of invasive data procedures such as spatial smoothing and warping and rather extract regional information from the individuals. This information is then visualized for all subjects and brain areas at one glance – hence we term the method brainglance. Additionally, our method incorporates a means for clustering individuals to further identify common traits. We showcase our method on two publicly available data sets and discuss our findings.

Layer-dependent activity in human prefrontal cortex during working memory

Working memory involves storing and/or manipulating previously encoded information over a short-term delay period, which is typically followed by a behavioral response based on the remembered information. Although working memory tasks often engage dorsolateral prefrontal cortex, few studies have investigated whether their subprocesses are localized to different cortical depths in this region, and none have done so in humans. Here we use high-resolution functional MRI to interrogate the layer specificity of neural activity during different periods of a delayed-response task in dorsolateral prefrontal cortex. We detect activity time courses that follow the hypothesized patterns: namely, superficial layers are preferentially active during the delay period, specifically in trials requiring manipulation (rather than mere maintenance) of information held in working memory, and deeper layers are preferentially active during the response. Results demonstrate that layer-specific functional MRI can be used in higher-order brain regions to noninvasively map cognitive processing in humans.

Large-scale comparative neuroimaging: Where are we and what do we need?

Neuroimaging has a lot to offer comparative neuroscience. Although invasive "gold standard" techniques have a better spatial resolution, neuroimaging allows fast, whole-brain, repeatable, and multi-modal measurements of structure and function in living animals and post-mortem tissue. In the past years, comparative neuroimaging has increased in popularity. However, we argue that its most significant potential lies in its ability to collect large-scale datasets of many species to investigate principles of variability in brain organisation across whole orders of species-an ambition that is presently unfulfilled but achievable. We briefly review the current state of the field and explore what the current obstacles to such an approach are. We propose some calls to action.

A comparison of in vivo MRI based cortical myelin mapping using T1w/T2w and R1 mapping at 3T

In this manuscript, we compare two commonly used methods to perform cortical mapping based on myelination of the human neocortex. T1w/T2w and R1 maps with matched total acquisition times were obtained from a young cohort in randomized order and using a test–retest design. Both methodologies showed cortical myelin maps that enhanced similar anatomical features, namely primary sensory regions known to be myelin rich. T1w/T2w maps showed increased robustness to movement artifacts in comparison to R1 maps, while the test re-test reproducibility of both methods was comparable. Based on Brodmann parcellation, both methods showed comparable variability within each region. Having parcellated cortical myelin maps into VDG11b areas of 4a, 4p, 3a, 3b, 1, 2, V2, and MT, both methods behave identically with R1 showing an increased variability between subjects. In combination with the test re-test evaluation, we concluded that this increased variability between subjects reflects relevant tissue variability. A high level of correlation was found between the R1 and T1w/T2w regions with regions of higher deviations being co-localized with those where the transmit RF field deviated most from its nominal value. We conclude that R1 mapping strategies might be preferable when studying different population cohorts where cortical properties are expected to be altered while T1w/T2w mapping will have advantages when performing cortical based segmentation.

Myelin and Modeling: Bootstrapping Cortical Microcircuits

Histological studies of myelin-stained sectioned cadaver brain and in vivo myelin-weighted magnetic resonance imaging (MRI) show that the cerebral cortex is organized into cortical areas with generally well-defined boundaries, which have consistent internal patterns of myelination. The process of myelination is largely driven by neural experience, in which the axonal passage of action potentials stimulates neighboring oligodendrocytes to perform their task. This bootstrapping process, such that the traffic of action potentials facilitates increased traffic, suggests the hypothesis that the specific pattern of myelination (myeloarchitecture) in each cortical area reveals the principal cortical microcircuits required for the function of that area. If this idea is correct, the observable sequential maturation of specific brain areas can provide evidence for models of the stages of cognitive development.

Microstructural and functional gradients are increasingly dissociated in transmodal cortices

While the role of cortical microstructure in organising neural function is well established, it remains unclear how structural constraints can give rise to more flexible elements of cognition. While nonhuman primate research has demonstrated a close structure-function correspondence, the relationship between microstructure and function remains poorly understood in humans, in part because of the reliance on post mortem analyses, which cannot be directly related to functional data. To overcome this barrier, we developed a novel approach to model the similarity of microstructural profiles sampled in the direction of cortical columns. Our approach was initially formulated based on an ultra-high-resolution 3D histological reconstruction of an entire human brain and then translated to myelin-sensitive magnetic resonance imaging (MRI) data in a large cohort of healthy adults. This novel method identified a system-level gradient of microstructural differentiation traversing from primary sensory to limbic regions that followed shifts in laminar differentiation and cytoarchitectural complexity. Importantly, while microstructural and functional gradients described a similar hierarchy, they became increasingly dissociated in transmodal default mode and fronto-parietal networks. Meta-analytic decoding of these topographic dissociations highlighted involvement in higher-level aspects of cognition, such as cognitive control and social cognition. Our findings demonstrate a relative decoupling of macroscale functional from microstructural gradients in transmodal regions, which likely contributes to the flexible role these regions play in human cognition.

Signal intensity of peri-rolandic cortex identifies the central sulcus on double inversion recovery MRI

BACKGROUND

Identification of the central sulcus can require inspection of subtle differences or require certain pulse sequences. This study identifies the central sulcus by signal intensity on Double Inversion Recovery (DIR) images in multiple anatomic locations and imaging planes.

METHODS

49 patients (98 hemispheres) were retrospectively reviewed by three neuroradiologists and one radiology resident. The central sulcus was compared to the surrounding sulci for differences in signal intensity at axial hand knob, axial operculum, and lateral convexity sagittal images (294 locations) on DIR images. The use of the 'disappearing central sulcus sign' where the window level is increased at constant width and black/white inversion were also assessed.

RESULTS

In 49 patients (22 female, 27 male; median age 36 years), the central sulcus cortex signal intensity was lower than adjacent sulci with a frequency of 90/98 (91.8%) at the axial hand knob level, 68/98 (69.4%) at the axial operculum level, and 76/98 (77.5%) at the sagittal level. With black and white inversion, the frequencies were of 96/98 (98%), 92/98 (94%), and 87/98 (89%). The central sulcus was the first to disappear at all three levels with high degrees of inter-reader agreement (86%-99%). Traditional anatomic landmarks were absent or conflicting in seven hemispheres (5 patients). The central sulcus was identified by DIR signal intensity in all seven hemispheres.

CONCLUSIONS

The central sulcus can be identified by differences in signal intensity of the peri-rolandic cortex on DIR. Use of black/white inversion and the disappearing central sulcus sign may further facilitate identification.

Age-related deficits in intracortical myelination in young adults with bipolar disorder type I

BACKGROUND

Previous studies have implicated white-matter-related changes in the pathophysiology of bipolar disorder. However, most of what is known is derived from in vivo subcortical white-matter imaging or postmortem studies. In this study, we investigated whole-brain intracortical myelin (ICM) content in people with bipolar disorder type I and controls.

METHODS

Between Sept. 1, 2014, and Jan. 31, 2017, we used a 3 T General Electric scanner to collect T1-weighted images in 45 people with bipolar disorder type I and 60 controls aged 17 to 45 years using an optimized sequence that was sensitive to ICM content. We analyzed images using a surfacebased approach. We used general linear models with quadratic age terms to examine the signal trajectory of ICM across the age range.

RESULTS

In healthy controls, the T1-weighted signal followed an inverted-U trajectory over age; in people with bipolar disorder type I, the association between ICM and age followed a flat trajectory (p < 0.05, Bonferroni corrected). Exploratory analyses showed that ICM signal intensity was associated with duration of illness, age of onset, and anticonvulsant and antipsychotic use in people with bipolar disorder type I (p < 0.05, uncorrected).

LIMITATIONS

Because of the cross-sectional nature of the study, we were unable to comment on whether the effects were due to dysmyelination or demyelination in bipolar disorder.

CONCLUSION

This foundational study is, to our knowledge, the first to show global age-related deficits in ICM maturation throughout the cortex in bipolar disorder. Considering the impact of myelination on the maintenance of neural synchrony and the integrity of neural connections, this work may help us better understand the cognitive and behavioural deficits seen in bipolar disorder.

A framework for cortical laminar composition analysis using low-resolution T1 MRI images

The layer composition of the cerebral cortex represents a unique anatomical fingerprint of brain development, function, connectivity, and pathology. Historically, the cortical layers were investigated solely ex-vivo using histological means, but recent magnetic resonance imaging (MRI) studies suggest that T1 relaxation images can be utilized to separate the layers. Despite technological advancements in the field of high-resolution MRI, accurate estimation of whole-brain cortical laminar composition has remained limited due to partial volume effects, leaving some layers far beyond the image resolution. In this study, we offer a simple and accurate method for cortical laminar composition analysis, resolving partial volume effects and cortical curvature heterogeneity. We use a low-resolution 3T MRI echo planar imaging inversion recovery (EPI IR) scan protocol that provides fast acquisition (~ 12 min) and enables extraction of multiple T1 relaxation time components per voxel, which are assigned to types of brain tissue and utilized to extract the subvoxel composition of six T1 layers. While previous investigation of the layers required the estimation of cortical normals or smoothing of layer widths (similar to VBM), here we developed a sphere-based approach to explore the inner mesoscale architecture of the cortex. Our novel algorithm conducts spatial analysis using volumetric sampling of a system of virtual spheres dispersed throughout the entire cortical space. The methodology offers a robust and powerful framework for quantification and visualization of the cortical laminar structure on the cortical surface, providing a basis for quantitative investigation of its role in cognition, physiology and pathology.

Addressing challenges of high spatial resolution UHF fMRI for group analysis of higher-order cognitive tasks: An inter-sensory task directing attention between visual and somatosensory domains

Functional MRI at ultra‐high field (UHF, ≥7 T) provides significant increases in BOLD contrast‐to‐noise ratio (CNR) compared with conventional field strength (3 T), and has been exploited for reduced field‐of‐view, high spatial resolution mapping of primary sensory areas. Applying these high spatial resolution methods to investigate whole brain functional responses to higher‐order cognitive tasks leads to a number of challenges, in particular how to perform robust group‐level statistical analyses. This study addresses these challenges using an inter‐sensory cognitive task which modulates top‐down attention at graded levels between the visual and somatosensory domains. At the individual level, highly focal functional activation to the task and task difficulty (modulated by attention levels) were detectable due to the high CNR at UHF. However, to assess group level effects, both anatomical and functional variability must be considered during analysis. We demonstrate the importance of surface over volume normalisation and the requirement of no spatial smoothing when assessing highly focal activity. Using novel group analysis on anatomically parcellated brain regions, we show that in higher cognitive areas (parietal and dorsal‐lateral‐prefrontal cortex) fMRI responses to graded attention levels were modulated quadratically, whilst in visual cortex and VIP, responses were modulated linearly. These group fMRI responses were not seen clearly using conventional second‐level GLM analyses, illustrating the limitations of a conventional approach when investigating such focal responses in higher cognitive regions which are more anatomically variable. The approaches demonstrated here complement other advanced analysis methods such as multivariate pattern analysis, allowing UHF to be fully exploited in cognitive neuroscience.

Developing 3D microscopy with CLARITY on human brain tissue: Towards a tool for informing and validating MRI-based histology

Recent breakthroughs in magnetic resonance imaging (MRI) enabled quantitative relaxometry and diffusion-weighted imaging with sub-millimeter resolution. Combined with biophysical models of MR contrast the emerging methods promise in vivo mapping of cyto- and myelo-architectonics, i.e., in vivo histology using MRI (hMRI) in humans. The hMRI methods require histological reference data for model building and validation. This is currently provided by MRI on post mortem human brain tissue in combination with classical histology on sections. However, this well established approach is limited to qualitative 2D information, while a systematic validation of hMRI requires quantitative 3D information on macroscopic voxels. We present a promising histological method based on optical 3D imaging combined with a tissue clearing method, Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging compatible Tissue hYdrogel (CLARITY), adapted for hMRI validation. Adapting CLARITY to the needs of hMRI is challenging due to poor antibody penetration into large sample volumes and high opacity of aged post mortem human brain tissue. In a pilot experiment we achieved transparency of up to 8 mm-thick and immunohistochemical staining of up to 5 mm-thick post mortem brain tissue by a combination of active and passive clearing, prolonged clearing and staining times. We combined 3D optical imaging of the cleared samples with tailored image processing methods. We demonstrated the feasibility for quantification of neuron density, fiber orientation distribution and cell type classification within a volume with size similar to a typical MRI voxel. The presented combination of MRI, 3D optical microscopy and image processing is a promising tool for validation of MRI-based microstructure estimates.

Parcellating Cerebral Cortex: How Invasive Animal Studies Inform Noninvasive Mapmaking in Humans

The cerebral cortex in mammals contains a mosaic of cortical areas that differ in function, architecture, connectivity, and/or topographic organization. A combination of local connectivity (within-area microcircuitry) and long-distance (between-area) connectivity enables each area to perform a unique set of computations. Some areas also have characteristic within-area mesoscale organization, reflecting specialized representations of distinct types of information. Cortical areas interact with one another to form functional networks that mediate behavior, and each area may be a part of multiple, partially overlapping networks. Given their importance to the understanding of brain organization, mapping cortical areas across species is a major objective of systems neuroscience and has been a century-long challenge. Here, we review recent progress in multi-modal mapping of mouse and nonhuman primate cortex, mainly using invasive experimental methods. These studies also provide a neuroanatomical foundation for mapping human cerebral cortex using noninvasive neuroimaging, including a new map of human cortical areas that we generated using a semiautomated analysis of high-quality, multimodal neuroimaging data. We contrast our semiautomated approach to human multimodal cortical mapping with various extant fully automated human brain parcellations that are based on only a single imaging modality and offer suggestions on how to best advance the noninvasive brain parcellation field. We discuss the limitations as well as the strengths of current noninvasive methods of mapping brain function, architecture, connectivity, and topography and of current approaches to mapping the brain's functional networks.

Cortical fibers orientation mapping using in-vivo whole brain 7 T diffusion MRI

Diffusion MRI of the cortical gray matter is challenging because the micro-environment probed by water molecules is much more complex than within the white matter. High spatial and angular resolutions are therefore necessary to uncover anisotropic diffusion patterns and laminar structures, which provide complementary (e.g. to anatomical and functional MRI) microstructural information about the cortex architectonic. Several ex-vivo and in-vivo MRI studies have recently addressed this question, however predominantly with an emphasis on specific cortical areas. There is currently no whole brain in-vivo data leveraging multi-shell diffusion MRI acquisition at high spatial resolution, and depth dependent analysis, to characterize the complex organization of cortical fibers. Here, we present unique in-vivo human 7T diffusion MRI data, and a dedicated cortical depth dependent analysis pipeline. We leverage the high spatial (1.05 mm isotropic) and angular (198 diffusion gradient directions) resolution of this whole brain dataset to improve cortical fiber orientations mapping, and study neurites (axons and/or dendrites) trajectories across cortical depths. Tangential fibers in superficial cortical depths and crossing fiber configurations in deep cortical depths are identified. Fibers gradually inserting into the gyral walls are visualized, which contributes to mitigating the gyral bias effect. Quantitative radiality maps and histograms in individual subjects and cortex-based aligned datasets further support our results.