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Title: Spatial cognition in Virtual Environments
Tutor: Olivetti Belardinelli, Marta
Keywords: spatial cognition
virtual environments
evaluation of distances
navigation in virtual reality
Issue Date: Dec-2011
Abstract: Since the last decades of the past century, Virtual Reality (VR) has been developed also as a methodology in research, besides a set of helpful applications in medical field (trainings for surgeons, but also rehabilitation tools). In science, there is still no agreement if the use of this technology in research on cognitive processes allows us to generalize results found in a Virtual Environment (VE) to the human behavior or cognition in the real world. This happens because of a series of differences found in basic perceptual processes (for example, depth perception) suggest a big difference in visual environmental representation capabilities of Virtual scenarios. On the other side, in literature quite a lot of studies can be found, which give a proof of VEs reliability in more than one field (trainings and rehabilitation, but also in some research paradigms). The main aim of this thesis is to investigate if, and in which cases, these two different views can be integrated and shed a new light and insights on the use of VR in research. Through the many experiments conducted in the "Virtual Development and Training Center" of the Fraunhofer Institute in Magdeburg, we addressed both low-level spatial processes (within an "evaluation of distances paradigm") and high-level spatial cognition (using a navigation and visuospatial planning task, called "3D Maps"), trying to address, at the same time, also practical problems as, for example, the use of stereoscopy in VEs or the problem of "Simulator Sickness" during navigation in immersive VEs. The results obtained with our research fill some gaps in literature about spatial cognition in VR and allow us to suggest that the use of VEs in research is quite reliable, mainly if the investigated processes are from the higher level of complexity. In this case, in fact, human brain "adapts" pretty well even to a "new" reality like the one offered by the VR, providing of course a familiarization period and the possibility to interact with the environment; the behavior will then be “like if” the environment was real: what is strongly lacking, at the moment, is the possibility to give a completely multisensorial experience, which is a very important issue in order to get the best from this kind of “visualization” of an artificial world. From a low-level point of view, we can confirm what already found in literature, that there are some basic differences in how our visual system perceives important spatial cues as depth and relationships between objects, and, therefore, we cannot talk about "similar environments" talking about VR and reality. The idea that VR is a "different" reality, offering potentially unlimited possibilities of use, even overcoming some physical limits of the real world, in which this "new" reality can be acquired by our cognitive system just by interacting with it, is therefore discussed in the conclusions of this work.
Description: Research developed in collaboration with the Virtual Development and Training Center of the Fraunhofer Institute of Magdeburg, Germany.
Research interests: Human cognition, cognitive processes, spatial processes, visual perception, mind-body problem, theory of consciousness, computer science, user-based applications, human-computer interaction, human-robot interaction, artificial intelligence, neural networks.
Skills short description: During my interfaculty course between Psychology and Informatics Engineering faculties, I learned both methodologies typical from general psychology research and some programming skills which helped me interacting with the programmers and engineers who helped me developing my doctoral project in the Fraunhofer Institute in Germany. I learned how to administer TMS stimulation and how to register EEG during my previous bachelor and master degrees.
Personal skills keywords: scientific paradigm creation
statistical data analysis
cognitive interpretation of data
basic programming skills
use of TMS, EEG and theoretical knowledge of neuroimaging technologies

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