[et_pb_section fb_built=”1″ fullwidth=”on” _builder_version=”4.16″ _module_preset=”default” top_divider_style=”arrow2″ top_divider_color=”#ffffff” top_divider_height=”57px” global_colors_info=”{}”][et_pb_fullwidth_header title=”Tutorials” text_orientation=”center” _builder_version=”4.16″ _module_preset=”default” title_font_size=”40px” background_color=”rgba(0,0,0,0.53)” min_height=”179px” custom_margin=”||-3px|||” custom_padding=”51px||0px|||” text_shadow_style=”preset1″ global_colors_info=”{}”][\/et_pb_fullwidth_header][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_row _builder_version=”4.20.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.20.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” custom_padding=”10px|10px|10px|10px|true|true” border_radii=”on|1px|1px|1px|1px” border_width_all=”1px” border_color_all=”#0C71C3″ global_colors_info=”{}”]<\/p>\n
Spatial Cognition and Artificial Intelligence: Methods for In-The-Wild Behavioural Research in Visual Perception<\/strong> Presenters:<\/i><\/p>\n Mehul Bhatt – \u00d6rebro University – CoDesign Lab EU, Sweden<\/p>\n Vasiliki Kondyli – Orebro university, Sweden<\/p>\n ABOUT<\/p>\n The tutorial on “Spatial Cognition and Artificial Intelligence” addresses the confluence of empirically-based behavioural research in the cognitive and psychological sciences with computationally-driven analytical methods rooted in artificial intelligence and machine learning. This confluence is addressed in the backdrop of human behavioural research concerned with naturalistic, in-the-wild, embodied multimodal interaction. The tutorial presents: Read More<\/a><\/span>\n (1) an interdisciplinary perspective on conducting evidence-based human behaviour research from the viewpoints of visual perception, environmental psychology, and spatial cognition.<\/p>\n (2) AI methods for the semantic interpretation of embodied multimodal interactions (e.g., rooted in behavioural data), and the (empirically-driven) synthesis of interactive embodied cognitive experiences in real-world settings relevant to both everyday life as well to professional creative-technical spatial thinking<\/p>\n (3) the relevance and impact of research in cognitive human-factors in spatial cognition for the design and implementation of human-centred AI technologies<\/p>\n The main technical focus of the tutorial is to provide a high-level demonstration of general AI-based computational methods and tools that can be used for multimodal human behavioural studies. Of special focus are visuospatial, visuo-locomotive, and visuo-auditory cognitive experiences in the context of application areas such as architecture and built environment design, narrative media design, product design, cognitive media studies, and autonomous cognitive systems (e.g., robotics, autonomous vehicles). Presented methods are rooted in foundational research in artificial intelligence, spatial cognition and computation, spatial informatics, human-computer interaction, and design science.<\/p>\n The tutorial utilises case-studies to demonstrate the application of the foundational practical methods and tools. This will also involve practical examples from large-scale experiments in domains such as evidence-based architecture design, communication and media studies, and cognitive film studies.<\/p>\n SCOPE AND AUDIENCE<\/p>\n SCOPE. Interdisciplinary scientific agenda targeting an audience with an interest or curiosity in visual and spatial cognition, visual perception, and artificial intelligence (emphasis on knowledge representation and reasoning, and high-level event perception). Particular focus will be utilising case-studies to demonstrate the state of the art in artificial intelligence, cognitive vision, and applied perception with respect to their impact on eye-tracking in particular, and multi-modal human behavioural research in general.<\/p>\n AUDIENCE. (1) Interdisciplinary audience interested to learn about how research in Cognition, AI, Interaction, and Design comes together; (2) Young researchers (e.g., masters and early stage doctoral candidates) desirous of exploring open research questions and avenues for visual perception research, and how it could influence the design of AI technologies; (3) Learn about applications of spatial cognition research in application domains such as (building) architecture design, (visuo-auditory) narrative media design, human-robot interaction, autonomous vehicles; (4) Design practitioners from areas such as architecture, animation, visual art, digital media, interaction design seeking to get insights from existing case-studies involving eye-tracking based visual perception in their respective domains of application; (5) Research generally curious to lean about what AI methods have to offer to behavioural research in cognitive science and psychology.<\/p>\n Further details about the tutorial may be consulted at: https:\/\/codesign-lab.org\/space-cognition-ai\/<\/a> <\/div><\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” custom_padding=”10px|10px|10px|10px|true|true” border_radii=”on|1px|1px|1px|1px” border_width_all=”1px” border_color_all=”#0C71C3″ global_colors_info=”{}”]<\/p>\n Multiple Object Tracking in Virtual Reality with Eye-tracking and FNIRS for Cognitive Workload<\/strong><\/p>\n Presenters:<\/i><\/p>\n Aleksandar Dimov – <\/span>BIOPAC Systems Inc, USA<\/span><\/p>\n <\/i><\/p>\n During this workshop we will present the use of Virtual Reality, eye-tracking and FNIRS for the Multiple Object Tracking paradigm. The specific paradigm was chosen to illustrate the integration of the various techniques via an example but general applications will be discussed as well. We will explain experiment design and optimal data collection techniques. Live participant data will be recorded and performance, eye-tracking data and FNIRS (functional near-infrared spectroscopy) will be analyzed so that attendees can see the entire process from start to finish.<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” custom_padding=”10px|10px|10px|10px|true|true” border_radii=”on|1px|1px|1px|1px” border_width_all=”1px” border_color_all=”#0C71C3″ global_colors_info=”{}”]<\/p>\n Modelling the spatio-temporal properties of eye movements: methods, devices and applications<\/strong> Presenter:\u00a0<\/i><\/p>\n Alessandro Grillini – <\/span><\/span><\/span>Reyedar B.V., Netherlands<\/p>\n Participants should have their own laptops and have access to Python 3 (Jupyter Notebook is also fine) – Please install Google Research Colab in your browser (preferably Chrome).<\/p>\n This tutorial aims to provide a comprehensive overview of SONDA (Standardized Oculomotor Neuro-ophthalmic Disorders Assessment), a powerful yet simple method for analyzing the spatio-temporal properties of eye movements with relevant applications in fundamental and clinical vision research. By integrating insights from experimental research in visual neuroscience, psychophysics, and machine learning, this tutorial will offer participants a unique opportunity to understand better how the SONDA method can be used to study eye movements and their practical application in different clinical contexts. A novel medical device based on this method will be demonstrated during the tutorial. Read More<\/a><\/span>\n The expected learning outcomes of this tutorial include: The importance of this tutorial lies in the increasing relevance and availability of eye-tracking tools. Eye movements provide a valuable source of information about how the visual system processes information and generates behavior that can be used to investigate a wide range of research questions, from basic visual neuroscience to clinical applications. The SONDA method offers a powerful framework for analyzing eye movement data by integrating multiple types of analyses into a single experimental pipeline and providing a unified approach for investigating different aspects of visual perception in a simple and fast manner.<\/p>\n By providing a comprehensive overview of the SONDA method, compatible experimental setups and applications, this tutorial will enable participants to stay at the forefront of eye movement research in visual perception and contribute to developing new knowledge and applications in this area. Participants will be able to work with real eye movement data from different clinical populations and develop practical skills in applying the SONDA method to their research questions. <\/div><\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” custom_padding=”10px|10px|10px|10px|true|true” border_radii=”on|1px|1px|1px|1px” border_width_all=”1px” border_color_all=”#0C71C3″ global_colors_info=”{}”]<\/p>\n Visual psychophysics with OpenSesame<\/b> Presenter: <\/i><\/p>\n Sebastiaan Math\u00f4t, University of\u00a0 Groningen In this ECVP tutorial, you will learn how to build a visual-psychophysics experiment in OpenSesame 4.0. You will learn how to display complex visual stimuli (Gabor patches, noise textures, etc.) and how to use a Quest adaptive procedure to maintain equal performance between participants and conditions. You will also learn how to verify the temporal precision of your experiment. The tutorial will focus on the graphical user interface, but there will additional challenges for those of you with Python coding experience.<\/i> Please bring your own laptop and install the latest version of OpenSesame 4.0 (not 3.3).<\/i>
Understanding the basic principles of the SONDA method: continuous psychophysics, eye-tracking signal processing, fundamentals of neuro-ophthalmology.
Familiarization with the different components of the SONDA method, including stimuli design, spatio-temporal analysis based on cross-correlograms, saccadic perimetry, and saccadic dynamic properties.
Gaining insights into the strengths and limitations of the SONDA method and how to choose the appropriate analysis techniques for a given research question.
Understanding how to interpret and communicate the results of SONDA analyses to other researchers, clinicians, and the broader scientific community.
This tutorial is targeted towards researchers and students with a background in visual neuroscience, psychophysics, neurology, optometry, or ophthalmology who are interested in learning more functional vision assessment through eye movement data. Participants should have a basic understanding of statistical methods and programming skills.<\/p>\n