Comparative neurobiology has traditionally been used to describe and quantify the macro-and micro-anatomical changes to the brain between human and non-human primates. Research literature commonly refers to the Stephen dataset with brain volumes measured from a small sample of ex-vivo non-human primate brains with species often represented by only one or two individuals. Although this is common limitation inherent to many physical neuroanatomy collections, caution should be used with such limited samples not representative of a species and the actual variation unknown. The consequences for such assumptions on quantifying the neuroanatomical differences between humans and non-human primates have broader implications for human evolution. Despite the increasing accessibility of primate neuroimaging datasets, many comparative studies still rely on the Stephen brain volumes. This is despite the necessary factoring of numerous bias including cerebral tissue damage from the delay between the post-mortem interval and brain preservation, potential introduction of artifacts from tissue preservation processes causing shrinkage, some cellular destruction and occasional damage during brain extraction.
Navarette and colleagues recently compared digital neuroanatomical volumes from ex-vivo brain MRI with the Stephen data using the same primate species but including an extra 20 species. Results showed differences between the Stephen data and those obtained by Navarrete et al. with larger brain volumes measured in the pre-fixed state versus post-fixed, indicating fixation did noticeably affect brain volume measurement. Although Navarrete et al. aimed to quantify primate brain volume variation by increasing the number of primate species to 39, there were still 29 species represented by only one individual, while the maximum of for the entire sample was never greater than three individuals per species. Although Navarrete et al. argued a lack of larger in-vivo primate brain neuroimaging datastes, several are accessible as part of the National Chimpanzee Research Center. More broadly, Navarrete and colleagues have shown quantifiable differences between pre- and post-fixed brain volumes and emphasised the need for caution in the suitability of ex-vivo brain collections to provide reliable volumetric measurements for comparative primate neuroanatomy.
Reardon and colleagues recently published a study on the variation of human brain organization and its relationship with brain size. Using neuroimaging data from more than 3000 individuals they calculated the local surface area and estimated the areal scaling in relation to the total cortical area in order to generate a reference map for areal scaling in cortical and subcortical structures. By using three separate cohorts, three different platforms of image-acquisition, and two distinct imaging processing pipelines, they obtained the same results. Regions with positive scaling, i.e. which area increases with increasing total cortical size, were found with the prefrontal, lateral temporoparietal, and medial parietal cortices, whereas the limbic, primary visual, and primary somatosensory regions showed negative scaling. These patterns of cortical area distribution relatively to normative brain size variation were also reproduced at the individual level in terms of proportion, as, for instance, areas of positive scaling regions were positively correlated with the total cortical area. These patterns of areal scaling distribution are also comparable with patterns of brain expansion during human development and primate evolution (humans vs. macaques). In terms of cytoarchitecture, the regions of positive scaling were concentrated within association cortices, such as the default mode, dorsal attention, and frontoparietal networks, while the negative scaling regions were found within the limbic network. The association of areal scaling patterns with known patterns of mitochondria-related gene expression suggests these regions that are expanded in larger brains might differ in their metabolic profile. The authors concluded that the similarity of the areal scaling maps across development and evolution, and at the individual level, suggests a shared scaling gradient of the primate cortex. Larger brains tend to preferentially expand association cortex, specialized for integration of information, which might point to a need for an increase of the neural subtracts, such as dendrites or synapses, in order to maintain or enhance brain function in an expanded brain. Further study designs are required to investigate the relationship between cortical areal patterns and brain function.
Magnetic Resonance Imaging (MRI) methods has a primary use in medicine, especially in diagnosis and image-guided surgery. In neuroscience, attention is mainly focused on the brain, and vessels are not always a target of the imaging procedures. The crucial aspect of using imaging during surgery concerns the correspondence with the real physical structures. This correspondence is affected by a displacement of the brain during surgery called brain shift, which can result in 5 – 10 mm difference from the MRI data. Several technical procedures are used in order to avoid this mismatch. Since intraoperative MRI devices are not always available, using local markers for orientation and navigation could be a plausible alternative. In a recent paper, Grabner and colleagues suggest to use the system of veins on the surface of the cerebral cortex as reference landmarks. These veins are well visible during the surgery, and can potentially improve navigation. The study is focused on developing a non-invasive MRI technique for the visualization of the superficial cortical veins and validation of that method by comparing MR images with high resolution photographs of human cadavers.
Considering Magnetic Resonance Angiography (MRA), the main concern of using this method is the use of a contrast agent, and the possibility of overlooking the superficial cortical veins because of the slow blood flow. Alternatively, the authors suggest to use Susceptibility-Weighted Imaging (SWI), which is a blood-oxygen-level dependent technique of MRI with an ability to image vessels smaller than a voxel. Gradient-echo based T2∗-weighted imaging was performed in this study using a 7 Tesla MRI scanner. Image processing relied on automated vessel segmentation and overlaid on anatomical MRI. The results showed high correlation between segmented veins in MRI and actual venous anatomy of the sample, and therefore surface venograms could serve as alternative navigation system for neurosurgery.
Reliable methods of imaging and segmentation of vessels are valuable also in theoretical fields, where those methods could contribute to the investigation of the function of the endocranial venous system. The importance of the veins is usually estimated according to their size, although functional information on these vessels is still scanty, and methodological research to improve craniovascular studies can be beneficial in both anthropology and medicine.