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The development of social robots has the potential to address significant societal concerns, however, most people have limited experience of such technology. The present research investigated whether techniques borrowed from the psychology of intergroup relations - namely direct and extended contact - affect people's attitudes towards robots. Participants were provided with either direct contact with a social robot or extended contact (these participants watched a video recorded by a friend who had met the robot) before their explicit and implicit attitudes towards robots were measured. Results indicated that direct contact affected both explicit and implicit attitudes, while extended contact affected implicit attitudes. The implication of these findings is that contact with a robot, direct or indirect, can change attitudes; much as previous research has shown that contact with a person who is a member of an out-group can change attitudes towards that group. We conclude that methods and theories from the study of human intergroup relationships can be usefully applied to understand attitudes toward social robots., (© 2021 The Authors.)

Recognizing that its research may raise various ethical, social, and philosophical issues, the HBP has made the identification, examination, and management of those issues a top priority. The Ethics and Society subproject is part of the core research project., (Copyright © 2019 Elsevier Inc. All rights reserved.)

"Whisker specialists" such as rats, shrews, and seals actively employ their whiskers to explore their environments and extract object properties such as size, shape, and texture. It has been suggested that whiskers could be used to discriminate between different sized objects in one of two ways: (i) to use whisker positions, such as angular position, spread or amplitude to approximate size; or (ii) to calculate the number of whiskers that contact an object. This study describes in detail how two adult harbor seals use their whiskers to differentiate between three sizes of disk. The seals judged size very fast, taking <400 ms. In addition, they oriented their smaller, most rostral, ventral whiskers to the disks, so that more whiskers contacted the surface, complying to a maximal contact sensing strategy. Data from this study supports the suggestion that it is the number of whisker contacts that predict disk size, rather than how the whiskers are positioned (angular position), the degree to which they are moved (amplitude) or how spread out they are (angular spread).

Computational neuroscience is increasingly moving beyond modeling individual neurons or neural systems to consider the integration of multiple models, often constructed by different research groups. We report on our preliminary technical integration of recent hippocampal formation, basal ganglia and physical environment models, together with visualisation tools, as a case study in the use of Python across the modelling tool-chain. We do not present new modeling results here. The architecture incorporates leaky-integrator and rate-coded neurons, a 3D environment with collision detection and tactile sensors, 3D graphics and 2D plots. We found Python to be a flexible platform, offering a significant reduction in development time, without a corresponding significant increase in execution time. We illustrate this by implementing a part of the model in various alternative languages and coding styles, and comparing their execution times. For very large-scale system integration, communication with other languages and parallel execution may be required, which we demonstrate using the BRAHMS framework's Python bindings.