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Schneider, C. J.

Publications and source records attributed to Schneider, C. J..

2 recordsLinked to original sources

A frog adaptive radiation: Ecomorphological evolution in Old-World shrub frogs (Rhacophoridae: Pseudophilautus)

Ecomorphs result from divergent natural selection, leading to species-rich adaptive radiations. Identifying ecomorphs and the resulting adaptive radiations in frogs is challenging due to conserved morphology and high species diversity. In this study, we demonstrate the ecological and climate specializations that have driven the diversification of shrub frogs of the genus Pseudophilautus in Sri Lanka, a tropical continental island. We use a time-calibrated phylogeny, morphometric analyses, and climate-niche evolution, and identify five ecomorphological categories, including Tree-shrub, Rock-boulder, Leaf-litter, Habitat Generalists, and Canopy forms, and describe their evolution. Body size is the primary factor separating species, and specific body features correlate with habitat type. Ecomorphs likely evolved multiple times in disparate lineages, and in different regions and altitudes, during cold climatic periods owing to monsoon cycles resulting from the Himalayan-Tibetan orogeny. The common ancestor was a medium-sized, wet-adapted, tree-shrub habitat specialist which originated in the late Oligocene. Extreme size classes (diminutive leaf litter forms and large canopy forms) evolved recently and suggest that morphological disparity arose late in diversification, possibly aided by favorable climates. This work will facilitate understanding of adaptive radiations in frogs, which possibly will help uncover the prevalence of subtle adaptive radiations in frogs, just as in tailed-vertebrates.

evolutionary biology↗

Towards a general framework for modeling large-scale biophysical neuronal networks: a full-scale computational model of the rat dentate gyrus

Large-scale computational models of the brain are necessary to accurately represent anatomical and functional variability in neuronal biophysics across brain regions and also to capture and study local and global interactions between neuronal populations on a behaviorally-relevant temporal scale. We present the methodology behind and an initial implementation of a novel open-source computational framework for construction, simulation, and analysis of models consisting of millions of neurons on high-performance computing systems, based on the NEURON and CoreNEURON simulators (Carnevale and Hines, 2006, Kumbhar et al., 2019). This framework uses the HDF5 data format and software library (HDF Group, 2021) and includes a data format for storing morphological, synaptic, and connectivity information of large neuronal network models, and an accompanying open-source software library that provides efficient, scalable parallel storage and MPI-based data movement capabilities. We outline our approaches for constructing detailed large-scale biophysical models with topographical connectivity and input stimuli, and present simulation results obtained with a full-scale model of the dentate gyrus constructed with our framework. The model generates sparse and spatially selective population activity that fits well with in-vivo experimental data. Moreover, our approach is fully general and can be applied to modeling other regions of the hippocampal formation in order to rapidly evaluate specific hypotheses about large-scale neural architectural features.

neuroscience↗