On the Origin and Trigger of the Notothenioid Adaptive Radiation

Adaptive radiation is usually triggered by ecological opportunity, arising through (i) the colonization of a new habitat by its progenitor; (ii) the extinction of competitors; or (iii) the emergence of an evolutionary key innovation in the ancestral lineage. Support for the key innovation hypothesis is scarce, however, even in textbook examples of adaptive radiation. Antifreeze glycoproteins (AFGPs) have been proposed as putative key innovation for the adaptive radiation of notothenioid fishes in the ice-cold waters of Antarctica. A crucial prerequisite for this assumption is the concurrence of the notothenioid radiation with the onset of Antarctic sea ice conditions. Here, we use a fossil-calibrated multi-marker phylogeny of nothothenioid and related acanthomorph fishes to date AFGP emergence and the notothenioid radiation. All time-constraints are cross-validated to assess their reliability resulting in six powerful calibration points. We find that the notothenioid radiation began near the Oligocene-Miocene transition, which coincides with the increasing presence of Antarctic sea ice. Divergence dates of notothenioids are thus consistent with the key innovation hypothesis of AFGP. Early notothenioid divergences are furthermore congruent with vicariant speciation and the breakup of Gondwana

Neuron-glial Interactions

Although lagging behind classical computational neuroscience, theoretical and computational approaches are beginning to emerge to characterize different aspects of neuron-glial interactions. This chapter aims to provide essential knowledge on neuron-glial interactions in the mammalian brain, leveraging on computational studies that focus on structure (anatomy) and function (physiology) of such interactions in the healthy brain. Although our understanding of the need of neuron-glial interactions in the brain is still at its infancy, being mostly based on predictions that await for experimental validation, simple general modeling arguments borrowed from control theory are introduced to support the importance of including such interactions in traditional neuron-based modeling paradigms.Junior Leader Fellowship Program by “la Caixa” Banking Foundation (LCF/BQ/LI18/11630006

Tectonic Reconstructions of the Southernmost Andes and the Scotia Sea During the Opening of the Drake Passage

Study of the tectonic development of the Scotia Sea region started with basic lithological and structural studies of outcrop geology in Tierra del Fuego and the Antarctic Peninsula. To nineteenth- and early twentieth-century geologists, the results of these studies suggested the presence of a submerged orocline running around the margins of the Scotia Sea. Subsequent increases in detailed knowledge about the fragmentary outcrop geology from islands distributed around the margins of the Scotia Sea, and later their interpretation in the light of the plate tectonic paradigm led to large modifications in the hypothesis such that by the present day the concept of oroclinal bending in the region persists only in vestigial form. Of the early comparative lithostratigraphic work in the region, only the likenesses between Jurassic–Cretaceous basin floor and fill sequences in South Georgia and Tierra del Fuego are regarded as strong enough to be useful in plate kinematic reconstruction by permitting the interpretation of those regions’ contiguity in mid-Mesozoic times. Marine and satellite geophysical data sets reveal features of the remaining, submerged, 98 % of the Scotia Sea region between the outcrops. These data enable a more detailed and quantitative approach to the region’s plate kinematics. In contrast to long-used interpretations of the outcrop geology, these data do not prescribe the proximity of South Georgia to Tierra del Fuego in any past period. It is, however, possible to reinterpret the geology of those two regions in terms of the plate kinematic history that the seafloor has preserved

Neuron-Glial Interactions

Although lagging behind classical computational neuroscience, theoretical and computational approaches are beginning to emerge to characterize different aspects of neuron-glial interactions. This chapter aims to provide essential knowledge on neuron-glial interactions in the mammalian brain, leveraging on computational studies that focus on structure (anatomy) and function (physiology) of such interactions in the healthy brain. Although our understanding of the need of neuron-glial interactions in the brain is still at its infancy, being mostly based on predictions that await for experimental validation, simple general modeling arguments borrowed from control theory are introduced to support the importance of including such interactions in traditional neuron-based modeling paradigms.Comment: 43 pages, 2 figures, 1 table. Accepted for publication in the "Encyclopedia of Computational Neuroscience," D. Jaeger and R. Jung eds., Springer-Verlag New York, 2020 (2nd edition