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In this study we present a brain model for decoding mental states that are captured using functional brain imaging (fMRI). We postulate that, the human brain processes information coming from the senses using specialized brain regions and the brain combines the activity of the specialized regions to come up with a coherent mental state. We model the postulated pattern of information processing in the brain as follows: First, we propose to capture the activity of specialized brain regions using homogenous voxel (volumetric pixel) groups: Supervoxels. Second, we combine the activity of supervoxels to decode the overall mental state using classifier ensembles: Brain Region Ensembles (BRE).
We test our model in three distinct fMRI datasets, where our model performs better, in terms of accuracy of classification of mental states, than the widely used brain decoding methods that rely on voxel selection. Also, we present how supervoxels can be used for the localization of the brain regions that are effective in discriminating the mental states under consideration regarding fMRI experiments.
Date: 07.10.2019 14:30 Place: Conference Hall 1
In this study, ‘awareness’ and ‘knowledge’ are used as means of measurement to evaluate the effectiveness of persuasive games. A game about online trolling behavior is designed and impleted. After exploring how the toxic behaviors that are considered as trolling in the context of online gaming are perceived, this study observes if the persuasive game is effective in raising awareness and knowledge about these behaviors.
Date: 09.09.2019 / 10:00 Place: B-116
In this study, firstly, the effect of kinemorphs on F-formation shapes are investigated by focusing on the differences between the virtual environment and the real life settings. Secondly, the role of one-to-one F-formation shapes on joining a dyadic interaction as a third interactant is also studied.
Date: 12.09.2019 / 15:00 Place: A-212
Our project brings together the concept of sound generation from free text input. Because a good story text can describe an environment quite well, both in terms of visual and aural aspects, we decided to use this feature to create virtual soundscapes that will both be generated procedurally and have the depth, complexity and control of a story text. In this thesis we describe the mechanics of analyzing free text user input queries and a way of converting this analysis into procedural soundscape generation.
Date: 05.09.2019 / 10:00 Place: A-108
In this study we implement a tool that compiles the combinatory categorial grammar rules to extract type-raising rules out of verb categories’ arguments and use them to test it out on natural language corpora like Eve.
Date: 05.09.2019 / 15:00 Place: S-06 (Conference Hall - 2)
