Detecting and tracking bottoms and faces of the Crested Black Macaque in the wild

Monkeys are important to many areas of science and ecology. The study of monkeys and their welfare are important components requiring complex observational studies. This work is therefore concerned with the development of computer vision techniques for the purposes of detecting and tracking monkeys with the ultimate aim to help in such studies. Monkeys are complex creatures for the purposes of tracking because of complex deformations. This complexity is further compounded by an in the wild setting where forest conditions result in frequent occlusions and changes in lighting. Despite these complexities monkeys present some interesting features that can make detection and tracking possible: their bottoms and faces. A system is thus described consisting of detectors trained to detect faces and bottoms of monkeys which are used within a tracking framework to initialise a system of tracklet construction. Steps are also described to enable disparate but coincident tracklets to be merged thus enabling longer run analysis of individual monkey movements. Experiments are performed using image data taken from video footage of Crested Black Macaques in natural forest surroundings. Results demonstrate relatively successful detection of monkey bottoms where the correspondence analysis and tracking process helps to reduce false positives

Pyramidal Cell Diversity in the Rat Prefrontal Cortex: Electrophysiology, Dopamine Modulation and Morphology

The prefrontal cortex (PFC) is critically involved in many higher cognitive functions such as goaldirected behaviour, affective behaviour and especially working memory. In vivo extracellular recordings of PFC neural activity during working memory tasks show high variety in observed spiking patterns. These complex dynamics are critically shaped by intrinsic, synaptic and structural parameters of respective prefrontal networks. Moreover, dopamine (DA) is crucial for correct functioning of the PFC during working memory tasks. DA modulates a number of synaptic and intrinsic biophysical properties of single neurons, in particular deep layer pyramidal cells, which represent the major output neurons of the PFC. Despite a high variability of cortical pyramidal cell firing patterns, and somatodendritic morphology, no study has yet systematically examined correlations between intrinsic properties, morphological features and dopaminergic modulation of intrinsic properties. This study investigated properties of deep layer pyramidal cells through whole cell patch clamp in acute brain slices of the adult rat PFC. Cells were characterised physiologically through a variety of stimulation protocols surveying different time scales and wide intensity ranges, while all fast synaptic transmission was blocked. Furthermore the same catalogue of stimuli was recorded whilst applying specific DA receptor agonists to elucidate effects of DA receptor activation on intrinsic properties. All recorded cells were injected with biocytin and dendritic morphology was reconstructed from confocal image stacks of fluorescently labelled neurons. From the resulting data a set of characteristic variables were defined and a combination of principal components analysis and hierarchical cluster analysis was used to identify similarity between recorded cells in different parameter spaces spanned by intrinsic properties, intrinsic properties under dopaminergic modulation and morphology, respectively. The analysis presents evidence for distinct subpopulations within prefrontal deep layer pyramidal cells, as seen by clustering of recorded cells in these high dimensional parameter spaces. These subpopulations also show distinct input-output relationships, bearing implications for computational functions of these subpopulations. Furthermore, this study presents for the first time evidence of subpopulation specific DA effects in deep layer pyramidal cells. The quantitative analysis of somatodendritic morphology confirms physiological subpopulations and identifies characteristic morphological features of deep layer pyramidal cells. Moreover, cluster observed in different parameter spaces overlap, leading to a definition of subpopulations that concurs with previously described prefrontal pyramidal cell types. In conclusion, the results presented provide some deeper insight into fundamental principles of information processing in prefrontal pyramidal cells under the influence of dopamine

Cortical Surface Registration and Shape Analysis

A population analysis of human cortical morphometry is critical for insights into brain development or degeneration. Such an analysis allows for investigating sulcal and gyral folding patterns. In general, such a population analysis requires both a well-established cortical correspondence and a well-defined quantification of the cortical morphometry. The highly folded and convoluted structures render a reliable and consistent population analysis challenging. Three key challenges have been identified for such an analysis: 1) consistent sulcal landmark extraction from the cortical surface to guide better cortical correspondence, 2) a correspondence establishment for a reliable and stable population analysis, and 3) quantification of the cortical folding in a more reliable and biologically meaningful fashion. The main focus of this dissertation is to develop a fully automatic pipeline that supports a population analysis of local cortical folding changes. My proposed pipeline consists of three novel components I developed to overcome the challenges in the population analysis: 1) automatic sulcal curve extraction for stable/reliable anatomical landmark selection, 2) group-wise registration for establishing cortical shape correspondence across a population with no template selection bias, and 3) quantification of local cortical folding using a novel cortical-shape-adaptive kernel. To evaluate my methodological contributions, I applied all of them in an application to early postnatal brain development. I studied the human cortical morphological development using the proposed quantification of local cortical folding from neonate age to 1 year and 2 years of age, with quantitative developmental assessments. This study revealed a novel pattern of associations between the cortical gyrification and cognitive development.Doctor of Philosoph

INVESTIGATING THE SPATIAL BEHAVIOR AND HABITAT USE OF THE MATSCHIE’S TREE-KANGAROO (DENDROLAGUS MATSCHIEI) USING GPS COLLARS AND UNMANNED AIRCRAFT SYSTEMS (UAS)

Understanding the movement patterns and habitat needs of the endangered Matschie’s tree-kangaroo (Dendrolagus matschiei) is important for their conservation and management. Endemic to the montane cloud forests of the Huon Peninsula in northeastern Papua New Guinea, these elusive arboreal marsupials are tremendously challenging to study using traditional observational methods. This study is an assessment of novel techniques to overcome the significant challenges to in-situ data collection in remote and rugged tropical cloud forests. Animal locations are remotely tracked using purpose built altitude and motion logging GPS collars and habitat structure data is measured using photogrammetry from small Unmanned Aircraft Systems (UAS) aerial imagery. Leveraging the autocorrelation of regular GPS location sampling, this study applied a Time-Local Convex Hull (T-LoCoH) analysis to investigate particular locations that may be important to D. matschiei as well as potential barriers to movement that would be inside of the home range as identified in previous studies. A novel technique of ground surface interpolation from canopy gaps is presented to overcome the challenges of photogrammetric reconstruction of terrain surfaces under closed canopy forests. From this a variety of forest structure variables were calculated to understand the 3D complexity of these heterogeneous cloud forests. This investigation found that custom GPS collars can provide high fix success rates in dense multilayer forests found at the research site. The regular sampling intervals resulted in areas of utilization that were notably smaller than with traditional home range analyses, and provided insight into landscape features that the animals do not use. D. matschiei were found to preferentially use trees that were taller than average and were found in closer than average proximity to canopy emergent trees. The reconstruction of 3D habitat data from UAS aerial photogrammetry resulted in forest structure maps that have significant potential to overcome the necessity of manual habitat data collection that hinders large scale habitat research, for this and many other species

Micro-, Meso- and Macro-Connectomics of the Brain

Neurosciences, Neurolog

The Brains of Babies: A Surface Based Approach To Study Cortical Development in Term and Preterm Human Infants

Half a million infants are born before term gestation each year in the United States. Although advances in newborn medicine have increased survival rates of very preterm infants to almost 90%, surviving preterm infants are at increased risk for developing lasting neurologic impairments. In order to develop a plausible neuroprotective strategy it is imperative that we improve our understanding of normal cortical development and develop tools to evaluate injury. Using a surface based approach we have characterized normal cortical development in healthy term infants and analyzed abnormalities associated with preterm birth. Accurate cortical surface reconstructions for each hemisphere of 12 healthy term gestation infants and 12 low-risk preterm infants at term equivalent postmenstrual age were generated from structural magnetic resonance imaging data using a novel segmentation algorithm. Data from the 12 term infants were used to establish the first population average surface based atlas of human cerebral cortex at term gestation. Comparing this atlas to a previously established atlas of adult cortex revealed that cortical structure in term infants is similar to the adult in many respects, including the pattern of individual variability and the presence of statistically significant structural asymmetries in lateral temporal cortex, suggesting that that several features of cortical shape are minimally reliant on the postnatal environment. Surprisingly, the pattern of postnatal expansion in surface area is strikingly non-uniform; regions of lateral temporal, parietal, and frontal cortex expand nearly twice as much as other regions in insular and medial occipital cortex. Differential expansion may point to differential sensitivity of cortical circuits to normal or aberrant childhood experiences. The pattern of human postnatal expansion parallels the pattern of evolutionary cortical expansion revealed by comparison between the human and the macaque monkey. Finally, in comparing term and preterm infants, region-specific alterations in cortical folding in the preterm population were found. The most striking shape differences were present in the orbitofrontal and inferior occipital regions with reductions in folding in the insular, lateral temporal, lateral parietal, and lateral frontal cortex. Overall these findings improve our understanding of normal cortical development and help elucidate the potential pathways for cortical injury in preterm infants

Recent hominim cranial form and function

This thesis aims to assess if biting mechanics drives craniofacial morphology in recent hominins. To that end, a virtual functional morphology toolkit, that includes Finite Element Analysis (FEA) and Geometric Morphometrics (GM), is used to simulate biting, measure bite force and quantify deformations arising due to simulated biting in Homo sapiens and its proposed ancestral species, Homo heidelbergensis. Moreover, the mechanical significance of the frontal sinus and of the brow-ridge is also assessed in Kabwe 1 (a Homo heidelbergensis specimen). The frontal sinus is examined by comparing the mechanical performance in three FE models with varying sinus morphology. A similar approach is applied to the brow-ridge study. This approach relies on the assumption that FEA approximates reality. Thus, a validation study compares the deformations experienced by a real cranium under experimental loading with those experienced by an FE model under equivalent virtual loading to verify this assumption. A sensitivity analysis examines how simplifications in segmentation impact on FEA results. Lastly, the virtual reconstruction of Kabwe 1 is described.Results show that prediction of absolute strain magnitudes is not precise, but the distribution of regions of larger and smaller (i.e. pattern of) deformations experienced by the real cranium is reasonably approximated by FEA, despite discrepancies in the alveolus. Simplification of segmentation stiffens the model but has no impact on the pattern of deformations, with the exception of the alveolus. Comparison of the biting performance of Kabwe 1 and H. sapiens suggests that morphological differences between the two species are likely not driven by selection of the masticatory system. Frontal sinus morphogenesis and morphology are possibly impacted by biting mechanics in the sense that very low strains are experienced by this region. Because bone adapts to strains, the frontal sinus is possibly impacted by this mechanism. Lastly, biting mechanics has limited impact on brow-ridge morphology and does not explain fully the enormous brow-ridge of Kabwe 1. Hence, other explanations are necessary to explain this prominent feature

From fossils to mind

Fossil endocasts record features of brains from the past: size, shape, vasculature, and gyrification. These data, alongside experimental and comparative evidence, are needed to resolve questions about brain energetics, cognitive specializations, and developmental plasticity. Through the application of interdisciplinary techniques to the fossil record, paleoneurology has been leading major innovations. Neuroimaging is shedding light on fossil brain organization and behaviors. Inferences about the development and physiology of the brains of extinct species can be experimentally investigated through brain organoids and transgenic models based on ancient DNA. Phylogenetic comparative methods integrate data across species and associate genotypes to phenotypes, and brains to behaviors. Meanwhile, fossil and archeological discoveries continuously contribute new knowledge. Through cooperation, the scientific community can accelerate knowledge acquisition. Sharing digitized museum collections improves the availability of rare fossils and artifacts. Comparative neuroanatomical data are available through online databases, along with tools for their measurement and analysis. In the context of these advances, the paleoneurological record provides ample opportunity for future research. Biomedical and ecological sciences can benefit from paleoneurology's approach to understanding the mind as well as its novel research pipelines that establish connections between neuroanatomy, genes and behavior