67 research outputs found
Traditional Taxonomic Groupings Mask Evolutionary History: A Molecular Phylogeny and New Classification of the Chromodorid Nudibranchs
Chromodorid nudibranchs (16 genera, 300+ species) are beautiful, brightly colored sea slugs found primarily in tropical coral reef habitats and subtropical coastal waters. The chromodorids are the most speciose family of opisthobranchs and one of the most diverse heterobranch clades. Chromodorids have the potential to be a model group with which to study diversification, color pattern evolution, are important source organisms in natural products chemistry and represent a stunning and widely compelling example of marine biodiversity. Here, we present the most complete molecular phylogeny of the chromodorid nudibranchs to date, with a broad sample of 244 specimens (142 new), representing 157 (106 new) chromodorid species, four actinocylcid species and four additional dorid species utilizing two mitochondrial markers (16s and COI). We confirmed the monophyly of the Chromodorididae and its sister group relationship with the Actinocyclidae. We were also able to, for the first time, test generic monophyly by including more than one member of all 14 of the non-monotypic chromodorid genera. Every one of these 14 traditional chromodorid genera are either non-monophyletic, or render another genus paraphyletic. Additionally, both the monotypic genera Verconia and Diversidoris are nested within clades. Based on data shown here, there are three individual species and five clades limited to the eastern Pacific and Atlantic Oceans (or just one of these ocean regions), while the majority of chromodorid clades and species are strictly Indo-Pacific in distribution. We present a new classification of the chromodorid nudibranchs. We use molecular data to untangle evolutionary relationships and retain a historical connection to traditional systematics by using generic names attached to type species as clade names
Complete mitochondrial genome and phylogenetic relationship of ornate threadfin bream, Nemipterus hexodon
Learning of Visual Navigation Strategies
Hafner VV, Möller R. Learning of Visual Navigation Strategies. In: Quoy M, Gaussier P, Wyatt J, eds. Proc. European Workshop of Learning Robots (EWLR-9), Prague. 2001: 47-56
From Perception-Action loops to imitation processes: A bottom-up approach of learning by imitation
This paper 1 proposes a neural architecture for a robot to learn how to imitate a sequence of movements performed by another robot or by a human. The main idea is that the imitation process does not need to be given to the system but can emerge from a mis-interpretation of the perceived situation at the level of a simple sensorimotor system. We discuss the central position of imitation processes for the understanding of our high level cognitive habilities linked to selfrecognition and to the recognition of the other as something similar to me. Another interesting aspect of this work is that the neural network used for sequences learning is directly inspired from a brain structure called the hippocampus and mainly involved in our memorization capabilities (?)
From Perception-Action loops to imitation processes:
This paper proposes a neural architecture for a robot in order to learn how to imitate a sequence of movements performed by another robot or by a human. The main idea is that the imitation process does not need to be given to the system but can emerge from a mis-interpretation of the perceived situation at the level of a simple sensory-motor system. The robot controller is based on a PerAc (Perception-Action) architecture. This architecture allows an autonomous robot to learn by itself sensory-motor associations with a delayed reward. Here, we show how the same architecture can also be used by a "student" robot to learn to imitate another robot allowing the student robot to discover by itself solutions to a particular problem or to learn from another robot what to do. We discuss the difficulty linked to the segmentation of the actions to imitate. This imitation problem is demonstrated by a task of learning a sequence of movements and their precise timing. Another interesting aspect of this work is that the neural network (N. N.) used for sequence learning is directly inspired from a brain structure named the hippocampus and mainly involved in memory processes (Banquet et al. 1997). We discuss the importance of imitation processes for the understanding of our high level cognitive abilities linked to self-recognition and to the recognition of the other as something similar to me.
New records of gelatinous zooplankton from an oceanic island in the Eastern Tropical Pacific
Gelatinous zooplankton are an abundant and diverse group of animals in the pelagic environment. However, knowledge of species diversity and spatial distributions, as well as their ecological role, is scarce. We present information of epi- and mesopelagic gelatinous zooplankton recorded by the âDeepSeeâ submersible between 2006 and 2012 at Isla del Coco (Cocos Island), Costa Rica, an oceanic island in the Eastern Tropical Pacific. Two species of scyphomedusae, three species of hydromedusae, two genera of siphonophores, and two species of ctenophores were observed in the videos, at depths between 50 and 400 m. None of these species had been previously recorded in the waters around the island. Furthermore, except for the jellyfish Pelagia noctiluca and a siphonophore in the genus Praya, all are new records for Costa Rican waters. This study also includes the first record of the cnidarians Modeeria rotunda, Solmissus sp., Halitrephes maasi and Apolemia spp., and the ctenophore Thalassocalyce inconstans in the Eastern Tropical Pacific. We show that surveys in regions with little information about gelatinous zooplankton may broaden our knowledge of their natural history and may result in new records of gelatinous species.Universidad de Costa Rica/[808-B0-654]/UCR/Costa RicaUCR::VicerrectorĂa de InvestigaciĂłn::Unidades de InvestigaciĂłn::Ciencias BĂĄsicas::Centro de InvestigaciĂłn en Ciencias del Mar y LimnologĂa (CIMAR)UCR::VicerrectorĂa de Docencia::Ciencias BĂĄsicas::Facultad de Ciencias::Escuela de BiologĂ
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