CALL FOR PAPERS Special Issue on Computational Models for Crossmodal Learning of the Cognitive Systems Research Journal. https://www.journals.elsevier.com/cognitive-systems-research/  I. Aim and Scope The ability of processing crossmodal information is a fundamental feature of the brain that provides a robust perceptual experience for an efficient interaction with the environment. Consequently, the integration of multisensory information plays a crucial role in autonomous systems to create robust and meaningful representations of objects and events. For dealing with real-world information, an autonomous, intelligent system must be capable of processing, integrating, and segregating different modalities for the purpose of coherent perception, decision-making, and cognitive learning. Recent neurophysiological findings in crossmodal learning have inspired novel computational models with the aim to trigger biologically inspired behavioral responses. A rich set of neural mechanisms support the integration and segregation of multimodal stimuli, providing the means to efficiently solve conflicts across modalities. This special issue aims to invite contributors from psychology, computational neuroscience, artificial intelligence, and cognitive robotics to discuss current research on crossmodal learning mechanisms both from the theoretical and modelling perspective. II. Potential Topics Topics include, but are not limited to: - New theories and findings on crossmodal processing - New neuroscientific results on crossmodal learning - Machine learning and neural networks for learning multisensory representations - Computational models of crossmodal attention and perception - Brain-inspired approaches for multisensory integration - Multisensory robot perception III. Submission Authors must use the Evise system to submit their contibutions, more informations can be found here: https://www.journals.elsevier.com/cognitive-systems-research/ *All manuscripts must be submitted to the Special Issue "VSI: Crossmodal Learning"* - Paper submission deadline: 09.02.2018 IV. Guest Editors Pablo Barros, University of Hamburg, Germany German I. Parisi, University of Hamburg, Germany Doreen Jirak, Hamburg University, Germany Bruno Fernandes, Universidade de Pernambuco, Brazil -- Dr.rer.nat. Pablo Barros Research Associate Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.de https://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.html www.knowledge-technology.info