Category Archives: Brain

Advances in brain imaging

Klein et al 2017The diagnosis of human brain abnormalities depends on knowing the norm and yet defining the range of normal variation is still far from resolved. Understanding what is within the normal human range has been limited by samples and the constraints of producing accurate brain mapping. Access to large brain imaging databases has been possible for a while but producing reliable atlases of key structures including folding patterns (sulci, gyri and fundii), volumes and major shape changes has not had large enough sample sizes to reliably grasp the range of normal brain variation. Current approaches have relied on highly skilled professionals to assess neuroanatomy. While this approach is adequate, it does introduce an inherent level of subjectivity and potential bias with each neuroanatomist dependent on the individual level of experience. To begin reducing this error while increasing sample sizes, new computational technologies allow more automated imaging processes that combine speed and quality.

Mindboggle is a new software platform recently released after development through a long-term research project addressing a need for integrating morphometry (measurements of morphology) to assess the quantitative differences in brain structure. Mindboggle relies on specially developed algorithms to segment brain tissue in MRI images, produce volumetric and structural parallelization of the brain and asses shape variation. Klein and colleagues highlighted issues with similar algorithm-based software that produced errors in segmenting brain from non-brain tissue. Freesurfer was shown to underestimate grey matter while overestimating white matter, while ANTs included more grey matter yet sometimes excluded white matter that extended deep in gyral folds. To resolve this issue, Mindboggle employed a hybrid algorithm that overlays the Freesurfer and ANTs segmentation imaging then combines these to produce a more faithful imaging set negating any errors in volume estimates, folding patterns or shape differences. Further results indicated the geodesic algorithm produced an exaggerated depth for brain regions like the insula, while the time depth algorithm unique to Mindboggle produced more valid results for shallow brain structures than other comparable algorithms. Finally, Mindboggle was shown to be reliable with minimal error estimate showing a consistently greater shape difference between left and right hemispheres than the difference between repeated scans of the same individuals.

Mindboggle also introduced many new and innovative features for extracting and measuring fundii but these algorithms have not yet been thoroughly evaluated. Additionally, the Mindboggle algorithms are developed for human brain anatomy and expansion into non-human neuroanatomy has not yet been fully developed. The potential of Mindboggle and similar platforms lies in the allowance to expand knowledge of normal human brain variation by using much larger samples to more accurately capture the normal range in human neuroanatomy to better inform diagnoses of brain abnormalities.

Alannah Pearson


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


Brain Volume Database

ibvd-brain-coloured

The Internet Brain Volume Database (IBVD) is an online collection of neuroimaging data funded as a part of the international initiative, the Human Brain Project. The IBVD provides access data for both individual and among-group comparisons that allow total volume comparisons with parallelization of the brain into hemispheres, specific lobes or grey matter volumes. While the database contains data on humans, there is also non-human primate (macaque) and rat studies. A summary search provides information on sex, age and handedness as well as age-related pathology, neuro-psychiatric disease, structural disease and twin-studies (monozygotic and dizygotic). These selected individuals can be compared to normal studies or pooled into user-specified group results. For example, it is very easy to generate a plot of  left vs. right temporal lobe volume compared to age in normal human in vivo males and females.

Alannah Pearson


Seasonal skull reduction

dechmann-et-al-2017Braincase shrinkage during winter was firstly described in shrews by Dehnel in 1949, and is known as the Dehnel’s Phenomenon. Recently, Dechmann et al. investigated the seasonal size variation in the skulls of shrews (Sorex araneus) and least weasels (Mustela nivalis). They measured skull length and braincase depth on specimens previously collected from a Polish National Park, sampling all seasons. Both species showed an initial juvenile growth until the first winter, followed by shrinkage until spring in the adults, and a subsequent re-grow on the second summer, though never reaching the initial size. Heat maps built from high resolution CT scans demonstrated that size changes also involved changes in shape and in bone thickness, with the thinnest skulls coinciding with the smallest braincase size. Interestingly, these patterns differed between sexes, especially in weasels as only males were observed to re-grow. Despite phylogenetically distant, both species have similar life histories, having short life spans and high metabolisms, and inhabiting an environment with seasonal fluctuation of resources availability. Winter shrinkage would reduce energetic requirements and prepare individuals for the harder conditions, and re-growth during the resources-abundant season would prepare the males for reproduction while females would allocate the energy into caring for the offspring.  The authors conclude these seasonal reversible size changes are genetically fixed and exclusive of animals with such life histories, as an adaptation to extreme environmental conditions. Future investigation shall clarify the potential drivers and consequences of this phenomenon, including how the variation in size affects brain size and reorganization.

Sofia Pedro


Fractal brains

the-fractal-geometry-of-the-brain

[click here!]


Evolution of Nervous Systems II

ens2017

[Elsevier]   [Science Direct]


Mapping the brain

The Rhoton Collection is composed by an outstanding anatomical presentations of the brain created by the renowned surgeon and educator Dr. Albert Rhoton Jr throughout his life. These presentations were made using bright blue and red dyes in the blood vessels, so that surgeons could easily visualize and explore the brain and vascular structures for planning surgical interventions.

[Here a post in Spanish]

Gizéh Rangel de Lázaro


Unfixed brain

A bit splatter …

“In this teaching video, Suzanne Stensaas, Ph.D., Professor of Neurobiology and Anatomy at the University of Utah School of Medicine, demonstrates the properties and anatomy of an unfixed brain. WARNING: The video contains graphic images, a human brain from a recent autopsy. Background noise is unrelated to this brain or the deceased. There are two purposes for this video: 1) to stress the vulnerability of the brain to highlight the importance of wearing helmets, seat belts, and taking care of this very precious tissue, and 2) to use as a teaching aid for students who only have access to fixed tissue, models, and pictures.” (University of Utah Neuroscience Initiative).


Hyena paleoneurology

hyenasA series of works by Sharleen T. Sakai’s group have correlated the proportions of the anterior endocranial region with social behaviour in hyenas. They found that in spotted hyenas (Crocuta crocuta), males have relatively larger anterior cerebrum than females. The relative volume of the anterior endocranial region is also significantly larger in this species when compared to other extant species of hyenas. The spotted hyenas are the most gregarious species, living in large clans, where females are dominant and philopatric, and males disperse and must adapt to the hierarchic system of a new clan. The anterior region of the hyena’s brain comprises mostly the frontal cortex, which mediates social behaviour. The authors hypothesize, in the light of the social brain hypothesis, that the development of the frontal region in this species, and particularly in males, might have been enhanced by the need for a larger behavioural flexibility in their complex social environment. More recently, Joan Madurell-Malapeira and his colleagues compared the endocasts of two extinct spotted hyenas (C. spelaea and C. ultima) with those of extant species. The fossil specimens have similar morphology to that of C. crocuta, but less developed anterior portion of their endocranium. The authors therefore propose this feature to be an autapomorphy of C. crocuta. Consequently, the social and foraging behaviour of these fossil species are presumably less specialized, and this might contradict some speculations about competition between hyenas and humans during Pleistocene.

Sofia Pedro


The Primate Cerebral Subplate

subplate-thickness-primatesThe mature primate brain consists of many layers with the outer layer or cerebral cortex forming folds known as sulci and gyri. During embryonic development, the brain is divided into zones with the inner-most ventricular zone where neurons are formed and a series of cytoarchitecturally distinct layers forming plates radiating outward. The subplate is located between the inner ventricular zone and the outer cortical plate hosting the migration of neurons allowing brain expansion. Most embryonic brain research is conducted on non-primate mammals but there are substantial differences in the development of the non-primate  and primate brain.  A very recent study utilized existing primate tissue databases to examine the embryonic development of the subplate zone in non-human and human primates. Duque et al. found during that development of the macaque brain, once the neurons have migrated to the subplate they then are pushed downward by axons derived from the subcortical layer before further compression occurs from further axonal development originating from the cortical layer. The implications of this force acting on the neurons within the subplate suggests that thickness of the subplate differs unevenly throughout the brain potentially due to an increased axonal density. Duque et al. suggest the density of axonal fibers increases with demand for more connectivity between brain regions with those areas possessing a high-demand for greater complexity causing a thicker subplate.

Changes at the cellular-level of the subplate also have implications for the development of the cerebral convolutions such as sulci and gyri. It was recently posed that the folding patterns in the human brain are the result of mechanical forces related to the subplate and outer expansion of the cerebral cortex. Tallinen et al. showed through numeric and physical simulations with the support of MRI that during fetal development the subplate stabilizes while the outer cortical plate continues to expand. The final stages of growth see the cortical layer undergo extensive gyrification to form the folding patterns we see in the adult human brain. Overall, a better understanding of human neurobiology informed through non-human primate neurobiology offers a glimpse into the evolutionary pathways which led to the evolution of modern humans.

Alannah Pearson