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- Type of Document: Ph.D. Dissertation
- Language: Farsi
- Document No: 55666 (05)
- University: Sharif University of Technology
- Department: Electrical Engineering
- Advisor(s): Karbalai Aghajan, Hamid
- Abstract:
- The brain is constantly anticipating the future of sensory inputs based on past experiences. When new sensory data is different from predictions shaped by recent trends, neural signals are generated to report this surprise. Surprise leads to garnering attention, causes arousal, and motivates engagement. It motivates the formation of an explanation or updating of current models. Three models have been proposed for quantifying surprise as the Shannon, Bayesian, and confidence-corrected surprises. In this thesis, we analyze EEG and MEG signals recorded during oddball tasks to examine and statistically compare the value of temporal/ spatial components in decoding the brain’s surprise. We observed that for both recordings, components of the middle temporal segment of the response are the best descriptors of all three surprise concepts. We observed that the central electrodes are the most powerful ones for describing all the three surprise values. Also, the right and left fronto-central regions offer the strongest power for decoding surprise by magnetometers. In addition, using the equivalent current dipole model for source localization, we did not observe differences between the location of neural modulators of the three surprise values.
- Keywords:
- Confidence-Corrected Surprise ; Equivalent Current Dipole ; Bayesian Surprise ; Shannon Surprise ; Statistical Significant Difference ; Decoding Power ; Oddball Paradaigm ; Brain Waves
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