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.
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]
A perspective review on cerebellum and Alzheimer’s disease, coordinated by Heidi Jacobs …
Jacobs H.I., Hopkins D.A., Mayrhofer H.C., Bruner E., van Leeuwen F.W., Raaijmakers W., Schmahmann J.D.
The cerebellum in Alzheimer’s disease: evaluating its role in cognitive decline.
(and here a post on cerebellum and paleoneurology …)
The Finite Element (FE) method has increasing application to biological sciences but frequently lacks proper validation by robust experimental research. One aspect of particular biological and bio-mechanical importance is growth of the human infant skull. Specific local changes during growth of the infant skull are largely unknown with only the general rate of cranial increase from 25% at birth to 65% of the adult size by age six. The potential adverse effects of any abnormalities in infant skull growth is difficult to approximate if the isolated local areas likely to be most impacted are not accurately known. If properly validated, computer simulated modelling such as Finite Element methods would be invaluable in surgical settings. A new comprehensive study focusing on human infant cranial vault expansion utilized robust laboratory experiments of a fetal skull (ex-vivo), replicate physical model (in-vitro), several FE models (in-silico) and a sample of micro-CT infant skulls (in-vivo). The first validation tested a physical model against a FE model (A) in which the cranial base and facial bones formed a single structure with only the cranial vault comprising individual bones. The FE model (A) over-predicted size changes to the anterior of the skull especially near the orbits and mediolateral expansion of the skull. The second validation tested in-vivo models against an FE model (B) in which the only the facial bones formed a single structure while the vault and cranial base comprised individual bones. All analyses associated discrepancy between the FE model (B) and the in-vivo models with age-related changes. As age increased, the regions under-predicted by the FE model (B) were first the orbits and upper vault before tending toward the cranial base, while the regions over-predicted by the FE model (B) were focused on the anterior and posterior fontanelles.
This validation study showed that FE modelling could be used to approximate growth in the human skull with only small discrepancies. The differences between the predicted ranges of growth (FE models) and the observed growth (in-vivo models) was explained by assumption of isotropic brain expansion which simplified the highly complex and uneven growth rates in real brain expansion. The artificial construction of a single structure representing the facial bones added further constraints. The development of more advanced simulations could narrow the discrepancy between expected and observed growth patterns allowing a more accurate representation of human skull growth.
The human brain is the most expensive and costly organ in terms of energetic resources and management. However, the current understanding of its sophisticated thermal control mechanisms remains insufficient. Wang et al., 2016, have reviewed the most recent studies on brain thermoregulation and examined the anatomical and physiological elements associated with selective brain cooling. Modern humans have a brain that is approximately three times larger than a primate with a similar body size, which uses 20%– 25% of the total body energy compared with a maximum of 10% in other primates and 5% in other mammals. The evolution of a large and expensive brain in modern humans effectively influences critical factors such as temperature, and functional limits can affect cerebral complexity and neural processes. Brain thermoregulation depends on many anatomical components and physiological processes, and it is sensitive to various behavioral and pathological factors, which have specific relevance for clinical applications and human evolution. The anatomical structures protecting the brain, such as the human calvaria, the scalp, and the endocranial vascular system, act as a thermal interface, which collectively maintains and shield the brain from heat challenges, and preserves a stable equilibrium between heat production and dissipation. Future advances in biomedical imaging techniques would allow a better understanding of the physiological and anatomical responses related to the cerebral heat management and brain temperature in modern humans.
Gizéh Rangel de Lázaro
The 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.
Recently Brazil has declared state of emergency due to an epidemic of newborn microcephaly. Children with microcephaly have significantly smaller head circumference than the mean for their age and body size. It results from abnormal brain development before birth or during infancy that can be caused by genetic (e.g. Down syndrome) or environmental factors affecting development, for instance craniosynostosis, malnutrition, and infection. Children with this condition may be cognitively impaired and need special medical care throughout their lives. During 2015 Brazil has been registering a drastic increase in the cases of microcephaly, mainly in the northeastern states. For instance in Pernambuco there was 141 cases while the mean is around 10 per year. Coincident with this epidemic, Brazil was also affected by a Zika virus outbreak firstly detected in late April and confirmed in 14 states by November. This virus was first identified in the 1940’s in Uganda, and it is now distributed throughout several tropical countries. It is transmitted to humans by bites of infected mosquitoes of the genus Aedes, the same that transmit dengue and yellow fever. Because symptoms of infection by Zika virus are mild it has not been given much attention. However the coincidence between the virus outbreak and increased microcephaly incidence in Brazil led to a suspicion that there was an association, further reinforced by the confirmation of the virus during an autopsy of a microcephalic baby.
The relationship between microcephaly and Zika virus is now being investigated and the government is taking steps to control the mosquitoes’ population and to assist the children with microcephaly. This virus may have spread from the French Polynesia, where there was an outbreak in 2013-2014, and where the Zika virus was associated with neurological complications like Guillain-Barré syndrome. If an association between a mosquito-transmitted virus and neurological conditions is confirmed, further measures of prevention must be taken as the area favorable for mosquitoes spreading seems to be increasing.
There are plenty of reports about anatomical and morphological variation of cranial foramina; however, their developmental mechanisms fundamental for interpretation of such a variation and understanding of vital medical conditions related to their aberrant formation are poorly known. Cranial foramina transmitting the vessels and nerves emerge within the cranial bones which themselves show complex origin and development. Recent embryological study in chicks by Akbareian et al. (2015) presents development of cranial foramina in mesoderm derived occipital bone arising through endochondral ossification. Unexpectedly, the formation mechanism did not show any extensive apoptotic cell activity and target proliferation. Instead as a “clearing” mechanism forming the cavity of foramina was proposed localized restriction of ossification caused by the presence of vessel and nerve elements with minimal mesenchymal cell death. Further importance for morphological studies of foramina can bear a discovery that the shape of vessel dictates the overall shape of the foramen.
Chiari 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
A 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.