Scalable mapping of myelin and neuron density in the human brain with micrometer resolution

Optical coherence tomography (OCT) is an emerging 3D imaging technique that allows quantification of intrinsic optical properties such as scattering coefficient and back-scattering coefficient, and has proved useful in distinguishing delicate microstructures in the human brain. The origins of scattering in brain tissues are contributed by the myelin content, neuron size and density primarily; however, no quantitative relationships between them have been reported, which hampers the use of OCT in fundamental studies of architectonic areas in the human brain and the pathological evaluations of diseases. Here, we built a generalized linear model based on Mie scattering theory that quantitatively links tissue scattering to myelin content and neuron density in the human brain. We report a strong linear relationship between scattering coefficient and the myelin content that is retained across different regions of the brain. Neuronal cell body turns out to be a secondary contribution to the overall scattering. The optical property of OCT provides a label-free solution for quantifying volumetric myelin content and neuron cells in the human brain.

The evolution of quantitative sensitivity

The ability to represent approximate quantities appears to be phylogenetically widespread, but the selective pressures and proximate mechanisms favouring this ability remain unknown. We analysed quantity discrimination data from 672 subjects across 33 bird and mammal species, using a novel Bayesian model that combined phylogenetic regression with a model of number psychophysics and random effect components. This allowed us to combine data from 49 studies and calculate the Weber fraction (a measure of quantity representation precision) for each species. We then examined which cognitive, socioecological and biological factors were related to variance in Weber fraction. We found contributions of phylogeny to quantity discrimination performance across taxa. Of the neural, socioecological and general cognitive factors we tested, cortical neuron density and domain-general cognition were the strongest predictors of Weber fraction, controlling for phylogeny. Our study is a new demonstration of evolutionary constraints on cognition, as well as of a relation between species-specific neuron density and a particular cognitive ability. This article is part of the theme issue ‘Systems neuroscience through the lens of evolutionary theory’.

Predicting Parkinson’s Disease and Its Pathology via Simple Clinical Variables

Background: Parkinson’s disease (PD) is a chronic, disabling neurodegenerative disorder. Objective: To predict a future diagnosis of PD using questionnaires and simple non-invasive clinical tests. Methods: Participants in the prospective Kuakini Honolulu-Asia Aging Study (HAAS) were evaluated biannually between 1995–2017 by PD experts using standard diagnostic criteria. Autopsies were sought on all deaths. We input simple clinical and risk factor variables into an ensemble-tree based machine learning algorithm and derived models to predict the probability of developing PD. We also investigated relationships of predictive models and neuropathologic features such as nigral neuron density. Results: The study sample included 292 subjects, 25 of whom developed PD within 3 years and 41 by 5 years. 116 (46%) of 251 subjects not diagnosed with PD underwent autopsy. Light Gradient Boosting Machine modeling of 12 predictors correctly classified a high proportion of individuals who developed PD within 3 years (area under the curve (AUC) 0.82, 95%CI 0.76–0.89) or 5 years (AUC 0.77, 95%CI 0.71–0.84). A large proportion of controls who were misclassified as PD had Lewy pathology at autopsy, including 79%of those who died within 3 years. PD probability estimates correlated inversely with nigral neuron density and were strongest in autopsies conducted within 3 years of index date (r = –0.57, p < 0.01). Conclusion: Machine learning can identify persons likely to develop PD during the prodromal period using questionnaires and simple non-invasive tests. Correlation with neuropathology suggests that true model accuracy may be considerably higher than estimates based solely on clinical diagnosis.

TNF-mediated neuroinflammation is linked to neuronal necroptosis in Alzheimer's disease hippocampus

The pathogenetic mechanisms underlying neuronal death and dysfunction in Alzheimer’s disease (AD) remain unclear. However, chronic neuroinflammation has been implicated in stimulating or exacerbating neuronal damage. The tumor necrosis factor (TNF) superfamily of cytokines are involved in many systemic chronic inflammatory and degenerative conditions and are amongst the key mediators of neuroinflammation. TNF binds to the TNFR1 and TNFR2 receptors to activate diverse cellular responses that can be either neuroprotective or neurodegenerative. In particular, TNF can induce programmed necrosis or necroptosis in an inflammatory environment. Although activation of necroptosis has recently been demonstrated in the AD brain, its significance in AD neuron loss and the role of TNF signaling is unclear. We demonstrate an increase in expression of multiple proteins in the TNF/TNF receptor-1-mediated necroptosis pathway in the AD post-mortem brain, as indicated by the phosphorylation of RIPK3 and MLKL, predominantly observed in the CA1 pyramidal neurons. The density of phosphoRIPK3 + and phosphoMLKL + neurons correlated inversely with total neuron density and showed significant sexual dimorphism within the AD cohort. In addition, apoptotic signaling was not significantly activated in the AD brain compared to the control brain. Exposure of human iPSC-derived glutamatergic neurons to TNF increased necroptotic cell death when apoptosis was inhibited, which was significantly reversed by small molecule inhibitors of RIPK1, RIPK3, and MLKL. In the post-mortem AD brain and in human iPSC neurons, in response to TNF, we show evidence of altered expression of proteins of the ESCRT III complex, which has been recently suggested as an antagonist of necroptosis and a possible mechanism by which cells can survive after necroptosis has been triggered. Taken together, our results suggest that neuronal loss in AD is due to TNF-mediated necroptosis rather than apoptosis, which is amenable to therapeutic intervention at several points in the signaling pathway.

TNF-mediated neuroinflammation is linked to neuronal necroptosis in Alzheimer's disease hippocampus

The pathogenetic mechanisms underlying neuronal death and dysfunction in Alzheimers disease (AD) remain unclear. However, chronic neuroinflammation has been implicated in stimulating or exacerbating neuronal damage. The tumor necrosis factor (TNF) superfamily of cytokines are involved in many systemic chronic inflammatory and degenerative conditions and are amongst the key mediators of neuroinflammation. TNF binds to the TNFR1 and TNFR2 receptors to activate diverse cellular responses that can be either neuroprotective or neurodegenerative. In particular, TNF can induce programmed necrosis or necroptosis in an inflammatory environment. Although activation of necroptosis has recently been demonstrated in the AD brain, its significance in AD neuron loss and the role of TNF signaling is unclear. We demonstrate an increase in expression of multiple proteins in the TNF/TNF receptor-1-mediated necroptosis pathway in the AD post-mortem brain, as indicated by the phosphorylation of RIPK3 and MLKL, predominantly observed in the CA1 pyramidal neurons. The density of phosphoRIPK3+ and phosphoMLKL+ neurons correlated inversely with total neuron density and showed significant sexual dimorphism within the AD cohort. In addition, apoptotic signaling was not significantly activated in the AD brain compared to the control brain. Exposure of human iPSC-derived glutamatergic neurons to TNF increased necroptotic cell death when apoptosis was inhibited, which was significantly reversed by small molecule inhibitors of RIPK1, RIPK3, and MLKL. In the post-mortem AD brain and in human iPSC neurons to TNF, we show evidence of altered expression of proteins of the ESCRT III complex, which has been recently suggested as an antagonist of necroptosis and a possible mechanism by which cells can survive after necroptosis has been triggered. Taken together, our results suggest that neuronal loss in AD is due to TNF-mediated necroptosis rather than apoptosis, which is amenable to therapeutic intervention at several points in the signaling pathway.

Structural Degradation in Midcingulate Cortex Is Associated with Pathological Aggression in Mice

Pathological aggression is a debilitating feature of many neuropsychiatric disorders, and cingulate cortex is one of the brain areas centrally implicated in its control. Here we explore the specific role of midcingulate cortex (MCC) in the development of pathological aggression. To this end, we investigated the structural and functional degeneration of MCC in the BALB/cJ strain, a mouse model for pathological aggression. Compared to control animals from the BALB/cByJ strain, BALB/cJ mice expressed consistently heightened levels of aggression, as assessed by the resident-intruder test. At the same time, immunohistochemistry demonstrated stark structural degradation in the MCC of aggressive BALB/cJ mice: Decreased neuron density and widespread neuron death were accompanied by increased microglia and astroglia concentrations and reactive astrogliosis. cFos staining indicated that this degradation had functional consequences: MCC activity did not differ between BALB/cJ and BALB/cByJ mice at baseline, but unlike BALB/cByJ mice, BALB/cJ mice failed to activate MCC during resident-intruder encounters. This suggests that structural and functional impairments of MCC, triggered by neuronal degeneration, may be one of the drivers of pathological aggression in mice, highlighting MCC as a potential key area for pathologies of aggression in humans.

Scalable mapping of myelin and neuron density in the human brain with micrometer resolution

Optical Coherence Tomography (OCT) is an emerging 3D imaging technique that allows quantification of intrinsic optical properties such as scattering coefficient and back-scattering coefficient, and has proved useful in distinguishing delicate microstructures in the human brain. The origins of scattering in brain tissues are contributed by the myelin content, neuron size and density primarily; however, no quantitative relationships between them have been reported, which hampers the use of OCT in fundamental studies of architectonic areas in the human brain and the pathological evaluations of diseases. To date, histology remains the golden standard, which is prone to errors and can only work on a small number of subjects. Here, we demonstrate a novel method that uses serial sectioning OCT to quantitatively measure myelin content and neuron density in the human brain. We found that the scattering coefficient possesses a strong linear relationship with the myelin content across different regions of the human brain, while the neuron density serves as a secondary contribution that only slightly modulates the overall tissue scattering.

Interactions between neuroanatomy, cognition, and ecology in Anolis lizards

The interactions between an organism and its environment are mediated by cognition, the substrates of which are in the brain. Cognition is ubiquitous across vertebrates, yet we still know very little about the factors shaping its evolution, particularly outside of birds and mammals. In natural environments, cognition likely impacts organism fitness. Behavioral flexibility, which enables an animal to modulate its behavior to match its environment, may facilitate success in novel habitats, such as in dispersal to islands, biotic invasions, and urban adaptation. Cognitive specializations may also be associated with specific ecological traits, such as habitat complexity. Furthermore, our understanding of the neural substrates of cognition in the brain is primarily limited to studies of relative brain size. The first chapter provides a more in depth introduction to these topics. In this dissertation, I explore the interactions between cognition, neuroanatomy, and ecology in Anolis lizards. Anolis lizards exhibit a diversity of habitat specializations, which is the result of adaptive radiation in the West Indies. As mentioned above, cognitive mechanisms in anoles may play a role in adjusting to novel environments and exploiting new niches. In the second chapter, I modified a detour task to evaluate whether wild, free-living Anolis sagrei can solve a novel detour problem under natural conditions. In the second chapter, I compare the neuron and nonneuron number and density of Anolis cristatellus and Anolis evermanni to see whether differences in neuroanatomy reflect their differential performance on an extractive foraging task. I also explore how these data relate to published observations from other vertebrates. Finally, in the fourth chapter I expand upon two previous studies by evaluating whether neuron number follows the predictions of concerted or mosaic evolution in five species of Puerto Rican Anolis and whether habitat complexity explains differences in neuron density between species. I conclude in the final chapter by summarizing my results and outlining future directions. Taken together, the results presented in this dissertation demonstrate the potential for studying cognition and neuroanatomy in an evolutionary context. The methods applied in my second chapter can be used in the future to explore the connection between cognition and fitness in lizards, which are a tractable model for such studies under natural conditions. My third and fourth chapters took a novel approach by studying neuroanatomical differences between species in neuron number and density, and generated novel insights into brain evolution in Anolis. By studying cognition and the brain in lizards and other ectotherms, we can begin to finally understand factors shaping the evolution of cognition and neuroanatomy across vertebrates.

Neonatal valproic acid exposure produces altered gyrification related to increased parvalbumin-immunopositive neuron density with thickened sulcal floors

Valproic acid (VPA) treatment is associated with autism spectrum disorder in humans, and ferrets can be used as a model to test this; so far, it is not known whether ferrets react to developmental VPA exposure with gyrencephalic abnormalities. The current study characterized gyrification abnormalities in ferrets following VPA exposure during neonatal periods, corresponding to the late stage of cortical neurogenesis as well as the early stage of sulcogyrogenesis. Ferret pups received intraperitoneal VPA injections (200 μg/g of body weight) on postnatal days (PD) 6 and 7. BrdU was administered simultaneously at the last VPA injection. Ex vivo MRI-based morphometry demonstrated significantly lower gyrification index (GI) throughout the cortex in VPA-treated ferrets (1.265 ± 0.027) than in control ferrets (1.327 ± 0.018) on PD 20, when primary sulcogyrogenesis is complete. VPA-treated ferrets showed significantly smaller sulcal-GIs in the rostral suprasylvian sulcus and splenial sulcus but a larger lateral sulcus surface area than control ferrets. The floor cortex of the inner stratum of both the rostral suprasylvian and splenial sulci and the outer stratum of the lateral sulcus showed a relatively prominent expansion. Parvalbumin-positive neuron density was significantly greater in the expanded cortical strata of sulcal floors in VPA-treated ferrets, regardless of the BrdU-labeled status. Thus, VPA exposure during the late stage of cortical neurogenesis may alter gyrification, primarily in the frontal and parietotemporal cortical divisions. Altered gyrification may thicken the outer or inner stratum of the cerebral cortex by increasing parvalbumin-positive neuron density.

Allometric analysis of brain cell number in Hymenoptera suggests ant brains diverge from general trends

Many comparative neurobiological studies seek to connect sensory or behavioural attributes across taxa with differences in their brain composition. Recent studies in vertebrates suggest cell number and density may be better correlated with behavioural ability than brain mass or volume, but few estimates of such figures exist for insects. Here, we use the isotropic fractionator (IF) method to estimate total brain cell numbers for 32 species of Hymenoptera spanning seven subfamilies. We find estimates from using this method are comparable to traditional, whole-brain cell counts of two species and to published estimates from established stereological methods. We present allometric scaling relationships between body and brain mass, brain mass and nuclei number, and body mass and cell density and find that ants stand out from bees and wasps as having particularly small brains by measures of mass and cell number. We find that Hymenoptera follow the general trend of smaller animals having proportionally larger brains. Smaller Hymenoptera also feature higher brain cell densities than the larger ones, as is the case in most vertebrates, but in contrast with primates, in which neuron density remains rather constant across changes in brain mass. Overall, our findings establish the IF as a useful method for comparative studies of brain size evolution in insects.