Due to a number of requests, we are currently still accepting papers for the special issue of the journal Information Fusion on "Biologically Inspired Information Fusion". If you are currently intending to submit a paper then please contact the guest editors as soon as possible. All extensions will be agreed on a case-by-case basis. Full details at http://www.elsevier.com/locate/inffus Bringing together research on the biology and psychology of multi-sensory processing, computational neuroscience and theoretical work on mechanisms for combining different information sources. Topics appropriate for this special issue include, but are not limited to: * Biologically inspired fusion schemes * Adaptive information fusion which emphasize biological motivations * Biologically inspired fusion in robotics * Multimodal integration: * Modeling combined sensory processing * Including, but not exclusively, combining vision, audition, olfaction, taste or touch * Combining artificial and biological sensors * Attention or emotional biasing on sensory processing * Biologically motivated applications of multi-sensor integration Our understanding of both natural and artificial cognitive systems is an exciting area of research that is developing into a multi-disciplinary subject with the potential for significant impact on science, engineering and society in general. There is considerable interest in how our understanding of natural systems may help us to apply biological strategies to artificial systems. Of particular interest is our understanding of how to build adaptive information fusion systems by combining knowledge from different domains. In natural systems, the integration of sensory information is learnt at an early stage of development. Therefore, through a better understanding of the structures and processes involved in this natural adaptive integration, we may be able to construct a truly artificial multi-sensory processing system. Here then, psychological and physiological knowledge of multisensory processing, and particularly the low level influence that different modalities have on one another, can be used to build upon existing theoretical work on computational mechanisms, such as self organization and the combination of multiple neural networks, to build systems that can fuse together different information sources. These themes were recently discussed at an International Workshop on Biologically Inspired Information Fusion. As well as presenting the state-of-the-art on multi-sensory processing and information fusion from the life and physical sciences, the workshop provided a forum for researchers to discuss priorities for developing this multi-disciplinary area. This special issue of Information Fusion is therefore aimed at following up from these discussions by focusing on the highlighted priorities, whilst also providing an opportunity for the wider dissemination of relevant themes. For this special issue, papers should either have a biological motivation and/or inspiration, or otherwise be of biological relevance and interest. Manuscripts should make the biological dimension explicit. Information Fusion related papers lacking this dimension are to be submitted to a regular issue of the journal. Manuscripts (which should be original and not previously published or presented even in a more or less similar form under any other forum) covering biologically inspired information fusion methods and their applications as well as the theories and algorithms developed to address these applications are invited. Contributions should be described in sufficient detail to be reproducible on the basis of the material presented in the paper. Manuscripts should be submitted electronically online at http://ees.elsevier.com/inffus. The corresponding author will have to create a user profile if one has not been established before at Elsevier. Simultaneously, please also send without fail an electronic copy (PDF format preferred), to the Guest Editors listed below. Please identify clearly that the submission is meant for this special issue. Guest Editors Dr Matthew Casey, Department of Computing, University of Surrey, UK, [log in to unmask] Professor Robert Damper, School of Electronics and Computer Science, University of Southampton, UK, [log in to unmask] Further information can be found at: http://www.cs.surrey.ac.uk/people/academic/M.Casey/biif2006.html http://www.elsevier.com/authored_subject_sections/P05/pdf/cfp_bif.pdf http://www.elsevier.com/locate/inffus