Conferences related to Social Neuroscience

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2023 Annual International Conference of the IEEE Engineering in Medicine & Biology Conference (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted full papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions,will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.


2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

HRI is a highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.

  • 2018 13th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchersin robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior,anthropology, and many other fields.

  • 2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    The conference serves as the primary annual meeting for researchers in the field of human-robot interaction. The event will include a main papers track and additional sessions for posters, demos, and exhibits. Additionally, the conference program will include a full day of workshops and tutorials running in parallel.

  • 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    This conference focuses on the interaction between humans and robots.

  • 2015 10th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a single -track, highly selective annual conference that showcases the very bestresearch and thinking in human -robot interaction. HRI is inherently interdisciplinary and multidisciplinary,reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificialintelligence, organizational behavior, anthropology, and many other fields.

  • 2014 9th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a highly selective annual conference that showcases the very best research and thinking in human -robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.

  • 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a single -track, highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.

  • 2012 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a single-track, highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.

  • 2011 6th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    Robot companions Lifelike robots Assistive (health & personal care) robotics Remote robots Mixed initiative interaction Multi-modal interaction Long-term interaction with robots Awareness and monitoring of humans Task allocation and coordination Autonomy and trust Robot-team learning User studies of HRI Experiments on HRI collaboration Ethnography and field studies HRI software architectures HRI foundations Metrics for teamwork HRI group dynamics.

  • 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    TOPICS: Robot companions, Lifelike robots, Assistive (health & personal care) robotics, Remote robots, Mixed initiative interaction, Multi-modal interaction, Long-term interaction with robots, Awareness and monitoring of humans, Task allocation and coordination, Autonomy and trust, Robot-team learning, User studies of HRI, Experiments on HRI collaboration, Ethnography and field studies, HRI software architectures

  • 2009 4th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    * Robot companions * Lifelike robots * Assistive (health & personal care) robotics * Remote robots * Mixed initiative interaction * Multi-modal interaction * Long-term interaction with robots * Awareness and monitoring of humans * Task allocation and coordination * Autonomy and trust * Robot-team learning * User studies of HRI * Experiments on HRI collaboration * Ethnography and field studies * HRI software architectures

  • 2008 3rd ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    Robot companions Lifelike robots Assistive (health & personal care) robotics Remote robots Mixed initiative interaction Multi-modal interaction Long-term interaction with robots Awareness and monitoring of humans Task allocation and coordination Autonomy and trust Robot-team learning User studies of HRI Experiments on HRI collaboration Ethnography and field studies HRI software architectures HRI foundations Metrics for teamwork HRI group dynamics Individual vs. group HRI

  • 2007 2nd Annual Conference on Human-Robot Interaction (HRI)


2019 9th International IEEE/EMBS Conference on Neural Engineering (NER)

Neural Engineering

  • 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER)

    Neural Engineering is an emerging core discipline,which coalesces neuroscience with engineering.Members of both the Neuroscience and Engineering Communities areencouraged to attend this highly multidisciplinarymeeting. The conference will highlight the emergingengineering innovations in the restoration andenhancement of impaired sensory, motor, andcognitive functions, novel engineering for deepeningknowledge of brain function, and advanced designand use of neurotechnologies

  • 2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)

    Neural engineering deals with many aspects of basic and clinical problemsassociated with neural dysfunction including the representation of sensory and motor information, theelectrical stimulation of the neuromuscular system to control the muscle activation and movement, theanalysis and visualization of complex neural systems at multi -scale from the single -cell and to the systemlevels to understand the underlying mechanisms, the development of novel neural prostheses, implantsand wearable devices to restore and enhance the impaired sensory and motor systems and functions.

  • 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)

    Neural engineering deals with many aspects of basic and clinical problems associated with neural dysfunction including the representation of sensory and motor information, the electrical stimulation of the neuromuscular system to control the muscle activation and movement, the analysis and visualization of complex neural systems at multi-scale from the single-cell and to the system levels to understand the underlying mechanisms, the development of novel neural prostheses, implants and wearable devices to restore and enhance the impaired sensory and motor systems and functions.

  • 2011 5th International IEEE/EMBS Conference on Neural Engineering (NER)

    highlight the emerging field, Neural Engineering that unites engineering, physics, chemistry, mathematics, computer science with molecular, cellular, cognitive and behavioral neuroscience and encompasses such areas as replacing or restoring lost sensory and motor abilities, defining the organizing principles and underlying mechanisms of neural systems, neurorobotics, neuroelectronics, brain imaging and mapping, cognitive science and neuroscience.

  • 2009 4th International IEEE/EMBS Conference on Neural Engineering (NER)

    highlight the emerging field, Neural Engineering that unites engineering, physics, chemistry, mathematics, computer science with molecular, cellular, cognitive and behavioral neuroscience and encompasses such areas as replacing or restoring lost sensory and motor abilities, defining the organizing principles and underlying mechanisms of neural systems, neurorobotics, neuroelectronics, brain imaging and mapping, cognitive science and neuroscience.

  • 2007 3rd International IEEE/EMBS Conference on Neural Engineering

  • 2005 2nd International IEEE/EMBS Conference on Neural Engineering

  • 2003 1st International IEEE/EMBS Conference on Neural Engineering


2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS)

The symposium is the premier conference for computational medicine, providing a mechanism for the exchange of ideas and technologies between academics and industrial scientists, and attracts a worldwide audience.


2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE)

CCECE is the flagship conference for researchers, students, and professionals in the area of Electrical and Computer Engineering from Canada and around the world to meet annually in a Canadian city to disseminate their research advancements and discoveries, to network and exchange ideas in order to strengthen existing partnerships and foster new collaborations


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Periodicals related to Social Neuroscience

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Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Computer

Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.


Evolutionary Computation, IEEE Transactions on

Papers on application, design, and theory of evolutionary computation, with emphasis given to engineering systems and scientific applications. Evolutionary optimization, machine learning, intelligent systems design, image processing and machine vision, pattern recognition, evolutionary neurocomputing, evolutionary fuzzy systems, applications in biomedicine and biochemistry, robotics and control, mathematical modelling, civil, chemical, aeronautical, and industrial engineering applications.


Information Technology in Biomedicine, IEEE Transactions on

Telemedicine, teleradiology, telepathology, telemonitoring, telediagnostics, 3D animations in health care, health information networks, clinical information systems, virtual reality applications in medicine, broadband technologies, and global information infrastructure design for health care.


Intelligent Systems, IEEE

IEEE Intelligent Systems, a bimonthly publication of the IEEE Computer Society, provides peer-reviewed, cutting-edge articles on the theory and applications of systems that perceive, reason, learn, and act intelligently. The editorial staff collaborates with authors to produce technically accurate, timely, useful, and readable articles as part of a consistent and consistently valuable editorial product. The magazine serves software engineers, systems ...


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Most published Xplore authors for Social Neuroscience

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Xplore Articles related to Social Neuroscience

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Using interactive virtual characters in social neuroscience

2015 IEEE Virtual Reality (VR), 2015

In recent years, the use of Virtual Characters in experimental studies has opened new research avenues in social neuroscience. In this paper, we present the design, implementation, and preliminary results of two case studies exploring different types of social cognition using interactive Virtual Characters animated with motion captured data.


Source separation of ERP components in brain responses to reward evaluation

2016 IEEE International Conference on Digital Signal Processing (DSP), 2016

An event related potential (ERP) called feedback related negativity (FRN) is believed to encode reward prediction error (RPE) in the human brain. In this paper we conduct an experiment to study the influence of effort on the size of RPE through an investigation on the magnitude of the corresponding FRN. However, FRN is inevitably distorted by the neighboring P2 and ...


Adaptive and intuitive interactions with socially-competent pedagogical assistant robots

2015 International Conference on Information Technology Based Higher Education and Training (ITHET), 2015

The paper presents a novel framework for including social competence in pedagogical assistant robots based on recent social neuroscience investigations. An educational model describing the interplay of social interaction and social observation in typical children and children with autistic spectrum conditions (ASC) is proposed. The behavioral results of a study of human gaze movements while viewing a robot tutor are ...


Coordination dynamics: Bidirectional coupling between humans, machines and brains

2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2014

We describe the Human Dynamic Clamp or virtual partner interaction paradigm- itself inspired by cellular neuroscience-which allows humans to interact in real time with avatars driven by empirically verified models of biological coordination such as the HKB and Jirsa-Kelso Excitator models of rhythmic and discrete movement behavior. The Human Dynamic Clamp allows one to explore the parameter spaces of interactional ...


Statistical significance of task related deep brain EEG dynamic changes in the time-frequency domain

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013

We present an off-line analysis procedure for exploring brain activity recorded from intra-cerebral electroencephalographic data (SEEG). The objective is to determine the statistical differences between different types of stimulations in the time-frequency domain. The procedure is based on computing relative signal power change and subsequent statistical analysis. An example of characteristic statistically significant event-related de/synchronization (ERD/ERS) detected across different frequency ...


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Educational Resources on Social Neuroscience

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IEEE-USA E-Books

  • Using interactive virtual characters in social neuroscience

    In recent years, the use of Virtual Characters in experimental studies has opened new research avenues in social neuroscience. In this paper, we present the design, implementation, and preliminary results of two case studies exploring different types of social cognition using interactive Virtual Characters animated with motion captured data.

  • Source separation of ERP components in brain responses to reward evaluation

    An event related potential (ERP) called feedback related negativity (FRN) is believed to encode reward prediction error (RPE) in the human brain. In this paper we conduct an experiment to study the influence of effort on the size of RPE through an investigation on the magnitude of the corresponding FRN. However, FRN is inevitably distorted by the neighboring P2 and P300 ERP components, and this makes the evaluation of FRN difficult. To resolve this issue, we apply blind source separation to decompose the ERP signal into isolated ERP components, adopting two-step temporal and spatial decompositions, using the Promax and information-maximization algorithms, respectively. Experimental results show that FRN can be reliably isolated and the influence of effort on RPE can then be evaluated.

  • Adaptive and intuitive interactions with socially-competent pedagogical assistant robots

    The paper presents a novel framework for including social competence in pedagogical assistant robots based on recent social neuroscience investigations. An educational model describing the interplay of social interaction and social observation in typical children and children with autistic spectrum conditions (ASC) is proposed. The behavioral results of a study of human gaze movements while viewing a robot tutor are briefly presented. The implications for design of adaptive and intuitive robotic tutoring systems as pedagogical assistants for typical children and children with special educational needs are discussed.

  • Coordination dynamics: Bidirectional coupling between humans, machines and brains

    We describe the Human Dynamic Clamp or virtual partner interaction paradigm- itself inspired by cellular neuroscience-which allows humans to interact in real time with avatars driven by empirically verified models of biological coordination such as the HKB and Jirsa-Kelso Excitator models of rhythmic and discrete movement behavior. The Human Dynamic Clamp allows one to explore the parameter spaces of interactional dynamics in a variety of different contexts as well as to produce some surprising emergent effects, including the possibility of relating 1st and 3rd person descriptions and their neural correlates.

  • Statistical significance of task related deep brain EEG dynamic changes in the time-frequency domain

    We present an off-line analysis procedure for exploring brain activity recorded from intra-cerebral electroencephalographic data (SEEG). The objective is to determine the statistical differences between different types of stimulations in the time-frequency domain. The procedure is based on computing relative signal power change and subsequent statistical analysis. An example of characteristic statistically significant event-related de/synchronization (ERD/ERS) detected across different frequency bands following different oddball stimuli is presented. The method is used for off- line functional classification of different brain areas.

  • Analysis of evoked deep brain connectivity

    Establishing dependencies and connectivity among different structures in the human brain is an extremely complex issue. Methods that are often used for connectivity analysis are based on correlation mechanisms. Correlation methods can analyze changes in signal shape or instantaneous power level. Although recent studies imply that observation of results from both groups of methods together can disclose some of the basic functions and behavior of the human brain during mental activity and decision-making, there is no technique covering changes in the shape of signals along with changes in their power levels. We present a method using a time evaluation of the correlation along with a comparison of power levels in every available contact pair from intracranial electrodes placed in deep brain structures. Observing shape changes in signals after stimulation together with their power levels provides us with new information about signal character between different structures in the brain during task-related events - visual stimulation with motor response. The results for a subject with 95 intracerebral contacts used in this paper demonstrate a clear methodology capable of spatially analyzing connectivity among deep brain structures.

  • Computational Analysis of the Impacts of Emotion on Learning in a Social Context

    This paper addresses how affective states and social interactions can strengthen learning processes. Using recent insights from Cognitive, Affective and Social Neuroscience it provides a computational model of learning processes, integrating mechanisms for the impact of a person's own emotions on these processes, as well as for the impact of emotions of others. By means of simulation experiments it is shown how these impacts strengthen the learning process. Based on these insights, and the presented computational model, support is provided for designing and testing (in silico) learning environments that enable and promote these impacts.

  • Modelling the Role of Cognitive Metaphors in Joint Decision Making

    In this paper, a social agent model is presented for the influence of cognitive metaphors on joint decision making processes. The social agent model is based on mechanisms known from cognitive and social neuroscience and cognitive metaphor theory. The model was illustrated in particular for two types of metaphors that can affect joint decision making in different manners: a cooperative metaphor and a competitive metaphor. By a number of scenarios it was shown how the obtained social agent model can be used to simulate and analyze joint decision processes influenced by cognitive metaphor.

  • EEG hyperscanning study of inter-brain synchrony during cooperative and competitive interaction

    Social cognition is the study of how people interact with each other in a social situation. An effective interaction would require higher degree of cognitive involvement between the participants and consequently, an enhanced synchrony between their neural mechanisms. In this study, twelve pairs of subjects interacted with each other via a cognitively engaging experimental paradigm in which they either competed or cooperated with each other for performing a task. While they were performing the task we incorporated electroencephalographic (EEG) hyperscanning techniques by simultaneously recording the EEG activities of the interacting subjects. We quantified these interactions by computing the inter-brain synchrony (IBS) and studied the changes in IBS under different experimental conditions. We found that the inter-brain synchrony between the subjects was significantly higher when they cooperated with each other as compared to the competitive scenario. Furthermore, we found that IBS was significantly enhanced when the subjects were physically separated i.e. they cooperated via an intranet network. In this work, we have demonstrated how EEG hyperscanning technique can be employed to study inter-brain synchronization under different conditions.



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