Team PhyPA, Biological Psychology and Neuroergonomics,
TU Berlin, Germany
Today's interaction with technology is asymmetrical in the sense that
With increasingly powerful machines this asymmetry has grown, but our interaction techniques have remained the same, presenting a clear communication bottleneck: users must still translate their high level concepts into machine‐mandated sequences of explicit commands, and only then does a machine act. During such asymmetrical interaction the human brain is continuously and automatically processing information concerning its internal and external context, including the environment the human is in and the events happening there. I will discuss how this information could be made available in real time and how it could be interpreted automatically by the machine to generate a model of its operator’s cognition. This model then can serve as a predictor to estimate the operator’s intentions, situational interpretations and emotions, enabling the machine to adapt to them. Such adaptations can even replace standard input, without any form of explicit communication from the operator. I will illustrate this approach by several brief examples.
The above mentioned cognitive model can be refined continuously by giving agency to the technological system to probe its operator’s mind for additional information. It could deliberately and iteratively elicit, and subsequently detect and decode cognitive responses to selected stimuli in a goal-directed fashion. Effectively, the machine can pose a question directly to a person’s brain and immediately receive an answer, potentially even without the person being aware of this happening. This cognitive probing allows for the generation of a more fine‐grained user model. It can be used to fully replace any direct input to the machine, establishing effective, goal-oriented implicit control of a computer system. I will give a more detailed example showing the potential of this approach.
These approaches fuse human and machine information processing, introduce fundamentally new notions of ‘interaction’, and allow completely new neuroadaptive technology to be developed. This technology bears specific relevance to auto‐adaptive experimental designs, but opens up paradigm shifting possibilities for technology in general, addressing the issue of asymmetry and widening the above‐mentioned communication bottleneck.
Department of Informatics, and NeuroCognitive Laboratory, Center for Modern Interdisciplinary Technologies
Nicolaus Copernicus University, Poland
The value of information for a given cognitive system depends on the knowledge that cognitive system already has.
Interactions that carry low value information may activate existing memory pattern leading to priming effects. Interactions that carry high value information create significant changes in the system, influencing its future behavior.
All mental states result from highly non-linear neural dynamics of the brain. Top-down models of mind that try to describe mental processes in a conceptual way, without understanding of their underlying neurodynamics, will always be limited.
In case of cognitive systems that share similar structures (such as animal brains) communication may be characterized in terms of resonance patterns, invoking functionally equivalent states in all communicating systems. Humanized interfaces or artificial infocommunication devices that provide information of high value for the user need to have some model of cognitive system they interact with, for example based on Brain-Inspired Cognitive Architecture (BICA) that represents concepts in a way roughly similar as in the human brain.
A brief review of neuroscience relevant to the representation of concepts in the brain will be presented. Functional neuroimaging techniques show brain processes during various mental tasks. The brain-computer interfaces learn to identify and assign meaning to spatiotemporal patterns of activity in the brain, translating such patterns into decisions and actions. Progress in this direction will eventually show how to transform brain activity into mental activity defined in psychological spaces based on dimensions that characterize subjective experiences. A computational model of word meaning based on spreading neural activation in layered networks will be used to visualize mental trajectories using novel technique based on fuzzy symbolic dynamics. Concepts are fluid, defined by dynamical attractor states oscillating around distributions of neural activity, as has been demonstrated in computational simulations and recent results of fMRI studies. BICA systems based on attractor states should allow for deep understanding of interactions with humans, creating resonant internal states. Symbolic interpretation of the sequence of transitions between internal states in such cognitive systems will be similar to verbal description of the stream of consciousness.
University of Debrecen, Hungary
Chief Technology Officer, Polish-Japanese Academy of Information Technology Research & Development Center
Short presentation on October 16, 18:00, Room A
Shareconomy is a peer-to-peer model including non-profits, government, corporations and individuals, with shared access to resources and services which optimizes their utilization.
The Polish-Japanese Academy of Information Technology (PJAIT) conducts research and development in information and communications technology (ICT) specializing in Artificial Intelligence, Bioinformatics, Social Informatics, Computer Graphics, Image and Video Processing and Human Motion Analysis and Synthesis. During the last five years, in the Research and Development Center of PJAIT in Bytom, Poland concept evolved of motion analysis and synthesis labs in shareconomy model. In this period four research laboratories: Human Motion Lab (HML), Human Microexpression Lab (HMX), Human Seeing Lab (HSL) focused on video and image analysis, Human Facial Modeling Lab (HFML) have been created with the help of using EU and national grants. Also, two more have been formed: Human Dynamics and Multimodal Interaction Lab (HDMI), and Wearable Technology Lab (WTL) to study performing movement analysis in real-time, with immediate feedback to both expert and patient. This presentation will provide a description of the PJAIT R&D Center and conducted there research activities. It will begin with an overview of the R&D Center’s research areas, laboratories and resources and will explain the shareconomy model of activity.
The Living Labs for Human Motion Analysis and Synthesis is a shareconomy model integrating local and geographically distributed stakeholders, enabling collaborative research and innovations in human motion analysis and synthesis. All resources from Research and Development Center PJAIT in Bytom, Poland are elements of an ecosystem capable of supporting advanced research activities remotely and efficient utilization of research and development resources in shareconomy model. For telepresence we use communication system with unified communication and voice-over-IP solutions providing an optimal user experience, regardless of location or device and reducing interworking complexity.