Analyzing the neocortical fine-structure

Fast cortical surface reconstruction from MRI using deep learning

Reconstructing cortical surfaces from structural magnetic resonance imaging (MRI) is a prerequisite for surface-based functional and anatomical image analyses. Conventional algorithms for cortical surface reconstruction are computationally inefficient and typically take several hours for each subject, causing a bottleneck in applications when a fast turnaround time is needed. To address this challenge, we propose a fast cortical surface reconstruction (FastCSR) pipeline by leveraging deep machine learning. We trained our model to learn an implicit representation of the cortical surface in volumetric space, termed the “level set representation”. A fast volumetric topology correction method and a topology-preserving surface mesh extraction procedure were employed to reconstruct the cortical surface based on the level set representation. Using 1-mm isotropic T1-weighted images, the FastCSR pipeline was able to reconstruct a subject’s cortical surfaces within 5 min with comparable surface quality, which is approximately 47 times faster than the traditional FreeSurfer pipeline. The advantage of FastCSR becomes even more apparent when processing high-resolution images. Importantly, the model demonstrated good generalizability in previously unseen data and showed high test–retest reliability in cortical morphometrics and anatomical parcellations. Finally, FastCSR was robust to images with compromised quality or with distortions caused by lesions. This fast and robust pipeline for cortical surface reconstruction may facilitate large-scale neuroimaging studies and has potential in clinical applications wherein brain images may be compromised.

Long term cortical thickness changes after a first episode of non- affective psychosis: The 10 year follow-up of the PAFIP cohort

Cortical thickness has been widely studied in individuals with schizophrenia and, in particular, first-episode psychosis. Abnormalities have been described, although there is, to date, a lack of consensus regarding changes across time and correlations with clinical and functional outcomes of the illness. One hundred and twenty-three first-episode psychosis patients and 74 healthy volunteers were subjected to magnetic resonance imaging scans and clinical and functional assessments by different scales at four consecutive visits during a 10 year follow-up period. Linear mixed effects models were applied to our data to compute cortical thickness changes over time in (1) schizophrenia patients versus healthy controls and (2) in patients with good versus poor functional outcome. The associations between cortical thickness percentage changes and clinical and functional status at 10 years were also assessed. The patients presented a thinner cortex than the controls at baseline (b's = -0.06; q ≤ 0.00023) with non-significant coefficients for the interaction term (follow-up time x group) (b's = -0.001; q ≥ 0.681). Poor functioning patients presented statistically significant coefficients for the interaction term (follow-up time x functionality) (left: b = -0.005, q = 0.019; right: b = -0.005, q = 0.022). In contrast, no correlations were found between cortical thickness measurements and clinical variables at 10 years. Overall, there were widespread thickness anomalies in first-episode psychosis patients across cortical regions that remained stable across time. Progressive thickness changes were related to patient functional outcomes, with progressive and steeper cortical thinning in patients with worse functional outcomes and a stabilization in those with better outcomes.

Greater Regional Cortical Thickness is Associated with Selective Vulnerability to Atrophy in Alzheimer's Disease, Independent of Amyloid Load and APOE Genotype

BACKGROUND

Regional cortical thickness (rCTh) among cognitively normal (CN) adults (rCThCN) varies greatly between brain regions, as does the vulnerability to neurodegeneration.

OBJECTIVE

The goal of this study was to: 1) rank order rCThCN for various brain regions, and 2) explore their vulnerability to neurodegeneration in Alzheimer's disease (AD) within these brain regions.

METHODS

The relationship between rCTh among the CN group (rCThCN) and the percent difference in CTh (% CThDiff) in each region between the CN group and AD patients was examined. Pearson correlation analysis was performed accounting for amyloid-β (Aβ) protein and APOE genotype using 210 age, gender, and APOE matched CN (n = 105, age range: 56-90) and AD (n = 105, age range: 56-90) ADNI participants.

RESULTS

Strong positive correlations were observed between rCThCN and % CThDiff accounting for Aβ deposition and APOE status. Regions, such as the entorhinal cortex, which had the greatest CTh in the CN state, were also the regions which had the greatest % CThDiff.

CONCLUSIONS

Regions with the greatest CTh at the CN stage are found to aggregate in disease prone regions of AD, namely in the medial temporal lobe, including the temporal pole, ERC, parahippocampal gyrus, fusiform and the middle and inferior temporal gyrus. Although rCTh has been found to vary considerably across the different regions of the brain, our results indicate that regions with the greatest CTh at the CN stage are actually regions which have been found to be most vulnerable to neurodegeneration in AD.

Assessing Relevance of External Cognitive Measures

The arrival of modern brain imaging technologies has provided new opportunities for examining the biological essence of human intelligence as well as the relationship between brain size and cognition. Thanks to these advances, we can now state that the relationship between brain size and intelligence has never been well understood. This view is supported by findings showing that cognition is correlated more with brain tissues than sheer brain size. The complexity of cellular and molecular organization of neural connections actually determines the computational capacity of the brain. In this review article, we determine that while genotypes are responsible for defining the theoretical limits of intelligence, what is primarily responsible for determining whether those limits are reached or exceeded is experience (environmental influence). Therefore, we contend that the gene-environment interplay defines the intelligent quotient of an individual.

Structural changes of the brain in relation to occupational stress

Despite mounting reports about the negative effects of chronic occupational stress on cognitive functions, it is still uncertain whether and how this type of stress is associated with cerebral changes. This issue was addressed in the present MRI study, in which cortical thickness (Cth) and subcortical volumes were compared between 40 subjects reporting symptoms of chronic occupational stress (38 ± 6 years) and 40 matched controls (36 ± 6 years). The degree of perceived stress was measured with Maslach Burnout Inventory. In stressed subjects, there was a significant thinning of the mesial frontal cortex. When investigating the correlation between age and Cth, the thinning effect of age was more pronounced in the stressed group in the frontal cortex. Furthermore, their amygdala volumes were bilaterally increased (P = 0.020 and P = 0.003), whereas their caudate volumes were reduced (P = 0.040), and accompanied by impaired fine motor function. The perceived stress correlated positively with the amygdala volumes (r = 0.44, P = 0.04; r = 0.43, P = 04). Occupational stress was found to be associated with cortical thinning as well as with selective changes of subcortical volumes, with behavioral correlates. The findings support the hypothesis that stress-related excitotoxicity might be an underlying mechanism, and that the described condition is a stress related illness.

Exposure to music and noise during pregnancy influences neurogenesis and thickness in motor and somatosensory cortex of rat pups

Purpose

Prenatal environmental conditions affect the development of the fetus. In the present study, we investigated the effects of exposure to music and noise during pregnancy on neurogenesis and thickness in the motor and somatosensory cortex of rat pups.

Methods

The pregnant rats in the music-applied group were exposed to 65 dB of comfortable music for 1 hour, once per day, from the 15th day of pregnancy until delivery. The pregnant rats in the noise-applied group were exposed to 95 dB of sound from a supersonic sound machine for 1 hour, once per day, from the 15th day of pregnancy until delivery. After birth, the offspring were left undisturbed together with their mother. The rat pups were sacrificed at 21 days after birth.

Results

Exposure to music during pregnancy increased neurogenesis in the motor and somatosensory cortex of rat pups. In contrast, rat pups exposed to noise during pregnancy showed decreased neurogenesis and thickness in the motor and somatosensory cortex.

Conclusions

Our study suggests that music and noise during the developmental period are important factors influencing brain development and urogenital disorders.

Sex differences in cortical thickness and their possible genetic and sex hormonal underpinnings

Although it has been shown that cortical thickness (Cth) differs between sexes, the underlying mechanisms are unknown. Seeing as XXY males have 1 extra X chromosome, we investigated the possible effects of X- and sex-chromosome dosage on Cth by comparing data from 31 XXY males with 39 XY and 47 XX controls. Plasma testosterone and estrogen were also measured in an effort to differentiate between possible sex-hormone and sex-chromosome gene effects. Cth was calculated with FreeSurfer software. Parietal and occipital Cth was greater in XX females than XY males. In these regions Cth was inversely correlated with z-normalized testosterone. In the motor strip, the cortex was thinner in XY males compared with both XX females and XXY males, indicating the possibility of an X-chromosome gene-dosage effect. XXY males had thinner right superior temporal and left middle temporal cortex, and a thicker right orbitofrontal cortex and lingual cortex than both control groups. Based on these data and previous reports from women with XO monosomy, it is hypothesized that programming of the motor cortex is influenced by processes linked to X-escapee genes, which do not have Y-chromosome homologs, and that programming of the superior temporal cortex is mediated by X-chromosome escapee genes with Y-homologs.

Cortical Surface Reconstruction from High-Resolution MR Brain Images

Reconstruction of the cerebral cortex from magnetic resonance (MR) images is an important step in quantitative analysis of the human brain structure, for example, in sulcal morphometry and in studies of cortical thickness. Existing cortical reconstruction approaches are typically optimized for standard resolution (~1 mm) data and are not directly applicable to higher resolution images. A new PDE-based method is presented for the automated cortical reconstruction that is computationally efficient and scales well with grid resolution, and thus is particularly suitable for high-resolution MR images with submillimeter voxel size. The method uses a mathematical model of a field in an inhomogeneous dielectric. This field mapping, similarly to a Laplacian mapping, has nice laminar properties in the cortical layer, and helps to identify the unresolved boundaries between cortical banks in narrow sulci. The pial cortical surface is reconstructed by advection along the field gradient as a geometric deformable model constrained by topology-preserving level set approach. The method's performance is illustrated on exvivo images with 0.25–0.35 mm isotropic voxels. The method is further evaluated by cross-comparison with results of the FreeSurfer software on standard resolution data sets from the OASIS database featuring pairs of repeated scans for 20 healthy young subjects.

External measures of cognition

The human brain is undoubtedly the most impressive, complex, and intricate organ that has evolved over time. It is also probably the least understood, and for that reason, the one that is currently attracting the most attention. In fact, the number of comparative analyses that focus on the evolution of brain size in Homo sapiens and other species has increased dramatically in recent years. In neuroscience, no other issue has generated so much interest and been the topic of so many heated debates as the difference in brain size between socially defined population groups, both its connotations and implications. For over a century, external measures of cognition have been related to intelligence. However, it is still unclear whether these measures actually correspond to cognitive abilities. In summary, this paper must be reviewed with this premise in mind.

Global and regional cortical thinning in first-episode psychosis patients: relationships with clinical and cognitive features

BACKGROUND

The thickness of the cortical mantle is a sensitive measure for identifying alterations in cortical structure. We aimed to explore whether first episode schizophrenia patients already show a significant cortical thinning and whether cortical thickness anomalies may significantly influence clinical and cognitive features.

METHOD

We investigated regional changes in cortical thickness in a large and heterogeneous sample of schizophrenia spectrum patients (n=142) at their first break of the illness and healthy controls (n=83). Magnetic resonance imaging brain scans (1.5 T) were obtained and images were analyzed by using brains2. The contribution of sociodemographic, cognitive and clinical characterictics was investigated.

RESULTS

Patients showed a significant total cortical thinning (F=17.55, d=-0.62, p<0.001) and there was a diffuse pattern of reduced thickness (encompassing frontal, temporal and parietal cortices) (all p's<0.001, d's>0.53). No significant group×gender interactions were observed (all p's>0.15). There were no significant associations between the clinical and pre-morbid variables and cortical thickness measurements (all r's<0.12). A weak significant negative correlation between attention and total (r=-0.24, p=0.021) and parietal cortical thickness (r=-0.27, p=0.009) was found in patients (thicker cortex was associated with lower attention). Our data revealed a similar pattern of cortical thickness changes related to age in patients and controls.

CONCLUSIONS

Cortical thinning is independent of gender, age, age of onset and duration of the illness and does not seem to significantly influence clinical and functional symptomatology. These findings support a primary neurodevelopment disorder affecting the normal cerebral cortex development in schizophrenia.

Sex-specific variation of MRI-based cortical morphometry in adult healthy volunteers: the effect on cognitive functioning

Previous investigations have revealed sex-specific differences in brain morphometry. The effect of sex on cortical thickness may be influencing cognitive differences between sexes. With this exploratory study, we aimed to investigate the effect of sex in MRI-based cerebral cortex morphometry in healthy young volunteers and how the variability in cortical measures might affect cognitive functioning in men and women. 76 young healthy volunteers (45 men and 31 women) underwent a 1.5 T MR scan and 53 of them completed a comprehensive cognitive battery. Overall no gross significant differences between sexes were found in cortical thickness, surface area and curvature indexes. However, there was a significant group by hemisphere interaction in the total cortical thickness (F(1,72)=5.02; p=0.03). A greater leftward asymmetry was observed in cortical thickness in males. Only females show significant associations between cortical thickness and cognitive functioning (IQ and executive functioning). In conclusion, our findings do not support the notion of sexual dimorphism in cortical mantle morphology. The results also suggest that variability in cortical thickness may affect cognitive functioning in females but not in males.

PDE-based reconstruction of the cerebral cortex from MR images

The topologically correct and geometrically accurate reconstruction of the cerebral cortex from magnetic resonance (MR) images is an important step in quantitative analysis of the human brain structure, e.g. in cortical thickness measurement studies. Limited resolution of MR images, noise, intensity inhomogeneities, and partial volume effects can all contribute to geometrical inaccuracies and topological errors in the model of cortical surfaces. For example, unresolved touching banks of gray matter (GM) in narrow sulci pose a particular challenge for an automated algorithm, requiring specific steps for the recovery of separating boundaries. We present a method for the automated reconstruction of the cortical compartment from MR images. The method is based on several partial differential equation (PDE) modelling stages. First, a potential field is computed in an electrostatic model with GM posing as an insulating dielectric layer surrounding a charged conductive white matter (WM) object. Second, geodesic distances from WM along the streamlines of the potential field are computed in a Eulerian framework PDE. Third, a digital skeleton surface separating GM sulcal banks is derived by finding shocks in the distance field. At the last stage, a geometric deformable model based on the level set PDE is used to reconstruct the outer cortical surface by advection along the gradient of the distance or potential field. The rule preserving the digital topology, and the skeleton of the distance field resolving fused adjacent banks in sulci, constrain the deformable model evolution. In addition, the deformable model may use the distance field as a constraint on thickness of the reconstructed cortical layer.

Neuroanatomical Correlates of Intelligence

With the advancement of image acquisition and analysis methods in recent decades, unique opportunities have emerged to study the neuroanatomical correlates of intelligence. Traditional approaches examining global measures have been complemented by insights from more regional analyses based on pre-defined areas. Newer state-of-the-art approaches have further enhanced our ability to localize the presence of correlations between cerebral characteristics and intelligence with high anatomic precision. These in vivo assessments have confirmed mainly positive correlations, suggesting that optimally increased brain regions are associated with better cognitive performance. Findings further suggest that the models proposed to explain the anatomical substrates of intelligence should address contributions from not only (pre)frontal regions, but also widely distributed networks throughout the whole brain.

Applications of magnetic resonance spectroscopy to tinnitus research: initial data, current issues, and future perspectives

Conducting tinnitus research on humans poses challenges for investigators because of its subjective nature, the complexities involved in establishing underlying generator sites, the diversity of potential causes, and the inherent difficulties in dissociating reactive changes in the central nervous system (CNS), secondary to peripheral hearing loss, from those effects that may be due to tinnitus. One area of considerable interest concerns biomarker development, particularly in the areas of metabolism and biochemistry. Establishing a biomarker or a profile of metabolic and neurobiochemical constituents of tinnitus-related activity within the CNS could be of considerable importance for understanding the fundamental properties of this disorder. Therefore, in an effort to gain greater insight into mechanisms of tinnitus, magnetic resonance spectroscopy (MRS) is being proposed as one of the several tools that can address pertinent issues. Apart from its long-standing use in analytical chemistry and physics, MRS is also being applied with greater frequency in the neurosciences to gain insight into human brain function under normal and pathological states. By considering the history of this method and advances made to date, MRS has the potential to: (1) identify unique in vivo metabolic and neurobiochemical biomarkers associated with tinnitus in specific regions of the CNS, (2) clarify and track disease pathogenesis, (3) monitor short and long-term treatment effects, and (4) serve as a tool in testing of drugs that may be used in treatment of tinnitus.

Virtual definition of neuronal tissue by cluster analysis of multi-parametric imaging (virtual-dot-com imaging)

Individual mapping of cerebral, morphological, functionally related structures using MRI was carried out using a new multi-contrast acquisition and analysis framework, called virtual-dot-com imaging. So far, conventional anatomical MRI has been able to provide gross segmentation of gray/white matter boundaries and a few sub-cortical structures. By combining a handful of imaging contrasts mechanisms (T1, T2, magnetization transfer, T2* and proton density), we were able to further segment sub-cortical tissue to its sub-nuclei arrangement, a segmentation that is difficult based on conventional, single-contrast MRI. Using an automatic four-step image and signal processing algorithm, we segmented the thalamus to at least 7 sub-nuclei with high similarity across subjects and high statistical significance within subjects (p<0.0001). The identified sub-nuclei resembled the known anatomical arrangement of the thalamus given in various atlases. Each cluster was characterized by a unique MRI contrast fingerprint. With this procedure, the weighted proportions of the different cellular compartments could be estimated, a property available to date only by histological analysis. Each sub-nucleus could be characterized in terms of normalized MRI contrast and compared to other sub-nuclei. The different weights of the contrasts (T1/T2/T2*/PD/MT, etc.) for each sub-nuclei cluster might indicate the intra-cluster morphological arrangement of the tissue that it represents. The implications of this methodology are far-ranging, from non-invasive, in vivo, individual mapping of histologically distinct brain areas to automatic identification of pathological processes.

A tracking approach to parcellation of the cerebral cortex

The cerebral cortex is composed of regions with distinct laminar structure. Functional neuroimaging results are often reported with respect to these regions, usually by means of a brain "atlas". Motivated by the need for more precise atlases, and the lack of model-based approaches in prior work in the field, this paper introduces a novel approach to parcellating the cortex into regions of distinct laminar structure, based on the theory of target tracking. The cortical layers are modelled by hidden Markov models and are tracked to determine the Bayesian evidence of layer hypotheses. This model-based parcellation method, evaluated here on a set of histological images of the cortex, is extensible to 3-D images.

A novel quantitative cross-validation of different cortical surface reconstruction algorithms using MRI phantom

Cortical surface reconstruction is important for functional brain mapping and morphometric analysis of the brain cortex. Several methods have been developed for the faithful reconstruction of surface models which represent the true cortical surface in both geometry and topology. However, there has been no explicit comparison study among those methods because each method has its own procedures, file formats, coordinate systems, and use of the reconstructed surface. There has also been no explicit evaluation method except visual inspection to validate the whole-cortical surface models quantitatively. In this study, we presented a novel phantom-based validation method of the cortical surface reconstruction algorithm and quantitatively cross-validated the three most prominent cortical surface reconstruction algorithms which are used in Freesurfer, BrainVISA, and CLASP, respectively. The validation included geometrical accuracy and mesh characteristics such as Euler number, fractal dimension (FD), total surface area, and local density of points. CLASP showed the best geometric/topologic accuracy and mesh characteristics such as FD and total surface area compared to Freesurfer and BrainVISA. In the validation of local density of points, Freesurfer and BrainVISA showed more even distribution of points on the cortical surface compared to CLASP.

Gender effects on cortical thickness and the influence of scaling

Using magnetic resonance imaging and well-validated computational cortical pattern matching methods in a large and well-matched sample of healthy subjects (n = 60), we analyzed the regional specificity of gender-related cortical thickness differences across the lateral and medial cortices at submillimeter resolution. To establish the influences of brain size correction on gender effects, comparisons were performed with and without applying affine transformations to scale each image volume to a template. We revealed significantly greater cortical thickness in women compared to men, after correcting for individual differences in brain size, while no significant regional thickness increases were observed in males. The pattern and direction of the results were similar without brain size correction, although effects were less pronounced and a small cortical region in the lateral temporal lobes showed greater thickness in males. Our gender-specific findings support a dimorphic organization in male and female brains that appears to involve the architecture of the cortical mantle and that manifests as increased thickness in female brains. This sexual dimorphism favoring women, even without correcting for brain size, may have functional significance and possibly account for gender-specific abilities and/or behavioral differences between sexes.

Quantitative architectural analysis: a new approach to cortical mapping

Recent progress in anatomical and functional MRI has revived the demand for a reliable, topographic map of the human cerebral cortex. Till date, interpretations of specific activations found in functional imaging studies and their topographical analysis in a spatial reference system are, often, still based on classical architectonic maps. The most commonly used reference atlas is that of Brodmann and his successors, despite its severe inherent drawbacks. One obvious weakness in traditional, architectural mapping is the subjective nature of localising borders between cortical areas, by means of a purely visual, microscopical examination of histological specimens. To overcome this limitation, more objective, quantitative mapping procedures have been established in the past years. The quantification of the neocortical, laminar pattern by defining intensity line profiles across the cortical layers, has a long tradition. During the last years, this method has been extended to enable a reliable, reproducible mapping of the cortex based on image analysis and multivariate statistics. Methodological approaches to such algorithm-based, cortical mapping were published for various architectural modalities. In our contribution, principles of algorithm-based mapping are described for cyto- and receptorarchitecture. In a cytoarchitectural parcellation of the human auditory cortex, using a sliding window procedure, the classical areal pattern of the human superior temporal gyrus was modified by a replacing of Brodmann's areas 41, 42, 22 and parts of area 21, with a novel, more detailed map. An extension and optimisation of the sliding window procedure to the specific requirements of receptorarchitectonic mapping, is also described using the macaque central sulcus and adjacent superior parietal lobule as a second, biologically independent example. Algorithm-based mapping procedures, however, are not limited to these two architectural modalities, but can be applied to all images in which a laminar cortical pattern can be detected and quantified, e.g. myeloarchitectonic and in vivo high resolution MR imaging. Defining cortical borders, based on changes in cortical lamination in high resolution, in vivo structural MR images will result in a rapid increase of our knowledge on the structural parcellation of the human cerebral cortex.

Hemispheric Asymmetries in Cortical Thickness

Using magnetic resonance imaging and computational cortical pattern matching methods, we analyzed hemispheric differences in regional gray matter thickness across the lateral and medial cortices in young, healthy adults (n = 60). In addition, we investigated the influence of gender on the degree of thickness asymmetry. Results revealed global and regionally specific differences between the two hemispheres, with generally thicker cortex in the left hemisphere. Regions with significant leftward asymmetry were identified in the precentral gyrus, middle frontal, anterior temporal and superior parietal lobes, while rightward asymmetry was prominent in the inferior posterior temporal lobe and inferior frontal lobe. On the medial surface, significant rightward asymmetries were observed in posterior regions, while significant leftward asymmetries were evident from the vicinity of the paracentral gyrus extending anteriorly. Asymmetry profiles were similar in both sexes, but hemispheric differences appeared slightly pronounced in males compared with females, albeit a few regions also indicated greater asymmetry in females compared with males. Hemispheric differences in the thickness of the cortex might be related to hemisphere-specific functional specializations that are possibly related to behavioral asymmetries.

CRUISE: Cortical reconstruction using implicit surface evolution

Segmentation and representation of the human cerebral cortex from magnetic resonance (MR) images play an important role in neuroscience and medicine. A successful segmentation method must be robust to various imaging artifacts and produce anatomically meaningful and consistent cortical representations. A method for the automatic reconstruction of the inner, central, and outer surfaces of the cerebral cortex from T1-weighted MR brain images is presented. The method combines a fuzzy tissue classification method, an efficient topology correction algorithm, and a topology-preserving geometric deformable surface model (TGDM). The algorithm is fast and numerically stable, and yields accurate brain surface reconstructions that are guaranteed to be topologically correct and free from self-intersections. Validation results on real MR data are presented to demonstrate the performance of the method.

A framework to study the cortical folding patterns

This paper describes a decade-long research program focused on the variability of the cortical folding patterns. The program has developed a framework of using artificial neuroanatomists that are trained to identify sulci from a database. The framework relies on a renormalization of the brain warping problem, which consists in matching the cortices at the scale of the folds. Another component of the program is the search for the alphabet of the folding patterns, namely, a list of indivisible elementary sulci. The search relies on the study of the cortical folding process using antenatal imaging and on backward simulations of morphogenesis aimed at revealing traces of the embryologic dimples in the mature cortical surface. The importance of sulcal-based morphometry is illustrated by a simple study of the correlates of handedness on asymmetry indices. The study shows for instance that the central sulcus is larger in the dominant hemisphere.