Category Archives: Magnetic Resonance

Cortical and scalp development

In a recent study, Tsuzuki and colleagues analysed the co-development of the brain and head surfaces during the first two years of life using a sample of 16 infant MRIs, aged from 3 to 22 months. First, they digitized a set of cortical landmarks defined by the major sulci. Then they determined the position of cranial landmarks according to the 10-10 system, a standard method to place electrodes for electroencephalography, using  nasion, inion, and the pre-auriculars as a reference. Besides analysing the spatial variability of the cortical and scalp landmarks with age, they compared the variability of the cortical landmarks to the 10-10 positions, in order to evaluate the validity of the scalp system as a reference for brain development. For that, they transferred a given cortical landmark to the head surface by expressing its position as a composition of vectors in reference to the midpoint between the two pre-auriculars and to the three neighbor 10-10 points. The scalp-transferred landmarks were then transformed to the scalp template of a 12-month-old infant and depicted in reference to the 10-10 system.

Age-related changes in the cortical landmarks were most obvious in the prefrontal and parietal regions. As the brain elongates, the frontal lobe shifts anteriorly and the precentral gyri widen. In addition, the intraparietal sulci and the posterior part of the left Sylvian fissure move forward, suggesting relative enlargement of the parietal region in the anterior direction. The same result was obtained by our team by analyzing cranial and brain landmarks in adults: larger brain size is associated with a relative forward position of the parietal lobe. The scalp showed relative anteroposterior elongation and lateral narrowing with growth. Regarding the contrast between the cortical landmarks and the 10-10 system, the authors observed that the variability in the position of the former was much smaller than the area defined by 10-10 landmarks, indicating this system can be useful to predict the underlying cortical structures. Hence, they conclude that the changes in brain shape during development are well described by cortical landmarks and that the relative scalp positioning based on the 10-10 system can adjust to preserve the correspondence between the scalp and the cortical surfaces.

 

Sofia Pedro


What the brain’s wiring looks like

The world’s most detailed scan of the brain’s internal wiring has been produced by scientists at Cardiff University. The MRI machine reveals the fibres which carry all the brain’s thought processes. It’s been done in Cardiff, Nottingham, Cambridge and Stockport, as well as London England and London Ontario. Doctors hope it will help increase understanding of a range of neurological disorders and could be used instead of invasive biopsies …

[keep on reading this article by Fergus Walsh on BBC News]


Structural MRI artifacts

Magnetic resonance imaging (MRI) is a valuable and increasingly used method for studying brain anatomy as it allows large-scale, high-quality in vivo analyses. However, some artifacts might influence the digital results, and thus require cautious interpretation. In a recent review, these issues are addressed along with possible solutions. First, we need to keep in mind that the images acquired are not mere photographs of the brain, but reflect some biophysical properties of the tissues, by measuring the radio-frequency signals emitted by hydrogen atoms (present in water and fat) after being excited by magnetic waves. Thus, MRI is an indirect analysis of the brain anatomy and depends greatly on specific tissue properties. Second, researchers can choose from a variety of methods, depending on the aim of the survey. Macrostructure, i.e. the size and shape across voxels, can be studied through manual volumetry or automatic segmentation, voxel- or deformation-based morphometry, surface- based algorithms, or diffusion tractography. Microstructure, i.e. within-voxel contents, is usually analyzed through diffusion MRI, but also magnetization transfer imaging, or quantitative susceptibility mapping.

When making inferences on the biological significance of the outputs, the researcher must account for the possible digital artifacts. These can occur both during image acquisition and processing and can be subject-related and methodological-related. A common problem is subject motion, which might contaminate or influence the results, as the amount of motion varies with other factors influencing brain changes (age, sex, and disease status), or can even correlate with a specific effect being studied. For instance, motion induces gray matter reduction, which might be perceived as brain atrophy. Subject motion is unavoidable, but its influence can be reduced by using a motion detector during acquisition, or by estimating the amount of motion allowing statistical adjustments, also useful to  detect outliers. The difficulty in manipulating the magnetic and radio-frequency fields might also introduce deformation. The main magnetic field should be spatially uniform, but it is dispersed by brain tissue while concentrated by air. This can be partially compensated by applying additional fields. The radiofrequency field is not homogeneous, which affects MRI contrast and intensity. Combining multiple transmit coils might help reduce this caveat, although the contribution and sensitivity of each coil must be taken into account when processing the image.

A particular case that can affect estimates of cortical volume and thickness is the difficulty in discriminating the dura and gray matter due to the similar intensity and anatomical proximity. In this case,  MRI parameters can be manipulated in order to increase the contrast between these tissues, without reducing the contrast between gray and white matter. Individual variability in folding patterns is a further major issue in voxel-based morphometry studies because it complicates the mapping of correspondences between subjects. Registration might be enhanced by analyzing regions with larger variation to find possible anatomical alterations, aligning cortical folding patterns to locate corresponding areas, and mapping sulcal changes to improve sulci identification. Finally, researchers should continuously keep track of the constant advances and innovations in the field. The authors conclude acknowledging the importance of structural MRI when coupled with other biological information, like genetic expression (Allen Brain Atlas), cytoarchitecture (JuBrain), and cognitive associations (Neurosynth).

Sofia Pedro


fMRI Failure? Or a Replication Crisis?

fmri brain

In a recent study,  Eklund et al. sparked an ongoing international debate when it highlighted systemic failures in cluster-based analysis of functional magnetic resonance imaging (fMRI). The fMRI method has been used for decades to investigate correlations between brain region inactivation and task performance. Active regions in the brain are assigned by two methods: voxel-wise and cluster-wise inferences. Voxel-wise inference assigns activity to brain regions based on association of specific voxels.  Meanwhile, cluster-wise inference assigns activity based on correlation between specific clusters of voxels usually associated by size. The occurrence of false-positives is controlled in the most commonly used fMRI software packages (SPM, FSL and AFNI) by a function known as the Family-wise error (FWE). The Eklund et al. study examined the reliability of the five FWE analysis tools offered by the main software packages. The results showed that for the FWE in cluster-wise inference, parametric studies gave extremely high false-positives but were within range for the voxel-wise inference. To analyze the data using a nonparametric test, Eklund et al. utilized a permutation test which gave results for the FWE within the boundaries for both cluster-wise and voxel-wise inferences.

An independent post examined the assumptions behind the comparison of the five different FWE tools based on the differences between voxel-wise and cluster-wise thresholds. In short, voxel-wise thresholding relies on making a decision about ‘active’ brain regions at a specific voxel-level, whereas cluster-wise thresholding relies on this decision made about adjacent ‘clusters’ of voxels and is specific to the spatial distribution or size of the clusters. Eklund et al. also examined the in-built auto-correlation functions in the software packages which assign activity to a brain region based on the cluster representing a squared exponential. This is the basic assumption made by the auto-correlation algorithm but in testing this functionality, Eklund et al. found the assumption of spatial smoothness did not follow a Gaussian distribution or was not normally distributed across the entire brain. The lack of spatial smoothness lead the auto-correlation function to incorrectly calculate clusters and in turn, force a false-positive finding.

With the Eklund et al. research actively calling into question the fMRI studies of the past two decades, a heated debate arose around the validity of such a statement and the methods used in the research. Subsequently, the statement was retracted and redefined but this did not go unnoticed. Unfortunately, it does appear that the issue at the heart of this debate has been overlooked and somewhat downplayed which is the matter of reproducibility affecting neuroscience and all science in general. The replication of all results are essential to removing incorrect inferences and misassumptions that lead discoveries to be meaningless without validation. While the debate over the ‘failure’ of fMRI continues to evolve the premise holds that without validation of scientific hypotheses there will never be an opportunity for these to graduate into scientific theories.

Alannah Pearson


Precuneus: folding and metrics

Pereira-Pedro and Bruner 2016_1 This month we have published a study featuring the cortical extension and anatomy of the precuneus, dealing with its metrics as well as with its sulcal pattern. The analysis was based on a MRI sample of 50 adult humans from both sexes. Our previous works concerned the variation, position, and surface, as well as the phylogenetic differences in the midsagittal plane. Instead, in this survey metrics was assessed on the coronal plane, “cutting” the precuneus in its anterior, middle and posterior sections, taking into account its curvature. The lateral (inner) extension of the precuneus was measured along the subparietal sulcus and its height was measured from the subparietal sulcus to the endocranial wall. Then a set of 10 two dimensional landmarks were digitized on the middle section along the outline of the parietal lobe, to analyze the correlation between outer brain profile and inner precuneus dimensions. We found that, on average, the precuneus extends 14 mm laterally and 36 mm vertically. It is wider on the anterior and middle sections, and usually larger on the right hemisphere, possibly due to the length of the fold (surface area) rather than to the thickness of the grey matter. The precuneus height influences the outer brain morphology (vertical stretching), but the subparietal size apparently has no influence on the external outline. Therefore, at least the former trait could be investigated in paleoneurology, by indirect inference on the inner dimensions as evaluated through their external effects. The lateral (parasagittal) surface of the upper parietal lobules seems to be unrelated to the size of the precuneus. Therefore, when a change of these areas is detected (like in Neandertals) the intraparietal sulcus is a better candidate as the cortical element involved in the morphological variations.

Pereira-Pedro and Bruner 2016_2

The sulcal pattern was analyzed on the average density projection of the 5 most sagittal stacks (5 mm of the cortex), a thickness which displays most of the sulcal features. Three characteristics were taken into consideration: the connections of the subparietal sulcus, the connections of other sulci in the precuneus, and the general sulcal scheme. Some of these features have been analyzed in other surveys, but  the consideration of other folds beyond the subparietal one is specific of this study. Roughly half of the precuneus sulci that reach the external surface are not linked to the subparietal sulcus. Contrary to other studies which found higher frequencies of an H-like pattern of the subparietal sulcus, we found a larger proportion of an inverted-T pattern (subparietal sulcus connected with one precuneus sulcus). The differences between studies might be due to random effects of the samples, because of the relevant individual variability of these traits. The left hemisphere displays more sulci reaching the external surface while the right hemisphere displays deeper folding. The anterior area shows more sulcal complexity than the posterior one. There seems to be no relationship between the size of the subparietal sulcus and its folding pattern, and these characteristics might be hence influenced by genetics or folding biomechanics.

Sofia Pedro


Chimp brains

NCBSDear colleagues,
We are very pleased to announce the launch of the National Chimpanzee Brain Resource (NCBR) website. The NCBR is supported by the National Institute of Neurological Disorders and Stroke. We encourage you to browse the site, where you will find information about MRI datasets and tissue samples that are available by request to researchers. The NCBR website also serves as a data repository for studies that include chimpanzee brains. In the near future, the NCBR website will grow with the addition of a searchable database of behavioral and cognitive tasks, pedigrees, rearing history, neuroimaging data, and postmortem brain samples; chimpanzee brain atlas tools; and educational information about chimpanzee neuroscience. We invite you to make a request for MRI data or tissue. Please contribute your datasets that include chimpanzee brains to the repository. Our aim is for the NCBR to facilitate research advancement through the distribution of chimpanzee brain resources and dissemination of information, promoting the value of chimpanzees as a comparative reference to better understand the structure, function, and evolution of the human brain.

NCBR Directors
Chet Sherwood, Bill Hopkins, Todd Preuss


Brain gyrification and simulations

The advantages of brain gyrification are well established, but the mechanisms behind this process are yet matter of discussion. However, early this month, a group of researchers published two models for brain gyrification based on the mechanical stress generated by the differential growth of the cortical layer. They created a physical model of a brain in three steps: (1) 3D printing a plastic replica from a MRI of a smooth fetal brain; (2) build a silicon negative mould to cast the core of a gel brain, which would represent the white matter; and after cooled, (3)  deposited the same gel polymer in the surface of the core to form the cortical layer. These polymer layers act as elastic solids. The mimicking of fetal brain growth was accomplished by placing the gel brain in a substrate of hexanes that would cause swelling and differential growth of the outer cortical layer, in respect to the core of the model. Starting from the same MRI, they also built a numerical model based on finite element and parameters like cortical thickness, brain growth and tissue stiffness, creating functions for folding and unfolding simulations. The combined results of the physical and numerical simulations showed that the pattern of gyrification depends on the overall shape of the brain, and the primary sulci are formed perpendicularly to the largest compressive stress. Their models are robust and reproducible, capturing the main gyral scheme and even account for variability and hemispherical differences. Furthermore, when comparing the simulated brain to a real one, they were able to find a correspondence with all the primary folds.

Sofia Pedro


Chiari malformation and the posterior fossa

SyringomyeliaChiari Malformation type 1 (CM-I) is an anatomical hindbrain abnormality having various symptoms (headache, pain in the neck and shoulders) because of obstruction of cerebrospinal fluid circulation and compression of hindbrain tissues such as the cerebellum, brain stem and spinal nerve. Most CM-I have syringomyelia. There is no direct test for CM-I and often symptoms are misinterpreted. Indicating tests are MRI, CT, neurological tests and CINE PC MRI. Treatment is a surgical operation called “posterior fossa compression”. Recently, researchers from the Netherlands and Turkey conducted different studies to examine this disorder. Akar et al. tested the usefulness of fractal analysis to examine the morphological complexity features of CM-I. Fractal Dimension (FD) analysis conducts the structural differences between patients with MCI (n=17) and healthy control subjects (n=16). Results showed that patients with CMI have larger cerebellar gray matter (GM) areas compared to controls, in contrast to other studies. FD could be a significant indicator for brain abnormalities in the cerebellum of CMI. It seems to be the case that the higher the FD value of cerebellar , the more complex object structure was. Rijken et al. found by examining 28 not operated, 85 operated craniosynostosis patients and 34 control that development of CMI is more likely to be supra tentorial. Craniosynostosis patients with CMI have similar cerebellar volume (CV) and posterior fossa volume (PFV) to control subjects, but they do have a significantly higher CV/PFV ratio. A higher CV/PFV ratio can be regarded as a predisposing factor for the development of CMI. In the end Rijken et al. advise to focus more on the skull vault itself.

Johannes Freiherr von Boeselager


Cortical morphology and ancestry

Fan et al 2015_2A recent study published by a large neuroscience team involved in imaging, cognition, and genetics, showed that cortical geometry is correlated with genetic ancestry. Using a sample of US citizens from the PING data, they reconstructed 3D cortical surfaces to obtain information on the morphological variation of the sulci and gyri. To calculate proportions of genetic ancestry they used as reference populations from west Africa, east Asia, a sample of native Americans and a sample of European descendants. The main finding of the study is that cortical folding patterns are strongly related to the genetic ancestry. According to the authors, African ancestry is associated with more posterior and narrower temporal areas. Frontal and occipital surfaces are more projected in Europeans and flatter in Native Americans. Asians have more variability in the temporal and parietal regions. Their results were similar to  Howells’ craniometric analysis. Moreover, all but Europeans display increased morphological variation in the posterolateral-temporal region. Due to these  morphological differences among populations, the authors warn for a possible methodological bias when mixing sample from different geographical origins in imaging studies.

Sofia Pedro


Brain and braincase

 Bruner et al JAnat 2015

New article on the spatial relationships between brain and braincase …

Bruner E., Amano H., de la Cuétara J.M. & Ogihara N.
The brain and the braincase: a spatial analysis
on the midsagittal profile in adult humans.
Journal of Anatomy, 2015

[Link]

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