Every day we discern and recognize objects. But how objectively can we perceive and distinguish them? And how can we objectively describe these objects to others? This thesis started from these questions and tried to find the answers by analyzing the sense of smell, which is known to be more subjective than other senses. Therefore, I focused on finding a general mechanism of differentiating odors by checking cognitive features using brain signals. I especially focused on the changing temporal pattern of brain signals. Our nerves encode information using both spatial and temporal methods, and our brain performs many different functions depending on which part is activated and when. In humans, temporal brain signals have been relatively less studied than spatial brain signals; thus, this study used electroencephalography (EEG) because of its good temporal resolution. The first study examined whether the olfactory signal can be directly measured by means of the EEG signal. Because olfactory signals start to be processed from the deep brain areas, the EEG signal can be weakened. Moreover, some in vitro studies suggested that olfactory processing in the brain starts from over 200ms, although recent MEG or behavioral studies suggest that olfactory processing starts before 200 ms. Thus, it is necessary to verify whether the olfactory signal can be directly measured before 200 ms by EEG signal. From this study, I found that the olfactory-specific signal was measured before 200 ms and was observed to be changed by changes in the olfactory stimulus; it was also verified that the olfactory signal before 200 ms can be directly measured with EEG. In the second study, based on first study, the odor categorization mechanism was addressed and confirmed in terms of time. Two similar odors and one completely different odor were selected and the corresponding EEG signals were measured. I found that two similar odors showed similar pattern at time range of 50–100 ms, 150-200ms and 350-400ms in theta. The gamma wave also showed similar pattern at 100–150ms and 350–400 ms. Moreover, these results were related with olfactory related brain areas. These results revealed that odor discrimination processed by each olfactory related brain areas, especially at a specific time range. In the third study, I focused on characterizing odor in the behavioral and survey level. Although I verified that differentiating process of odor can be represented by EEG, the object of my thesis is to add a greater understanding of odor information processing. Ever-increasing physiological and behavioral studies suggested several features for characterizing odor quality (including study 1 and 2), but there are no precise methods for measuring the multidimensional axis of odor quality. Moreover, this issue has other difficult problems that odor quality can be altered by individual experience. Therefore, to clarify the preceding question, I tried to quantify and determine the odor responses by alteration using verbal cues. I found that the odor descriptors with a high score (top 25%) was not changed significantly by verbal cues, and using this finding, I suggest that odor quality can be characterized. These studies suggest that theta and gamma are important frequency bands in the early stages of odor categorization. In particular, between 50 and 100 ms is the active time zone in which the primary olfactory cortex first starts to be activated during olfactory signal processing. This means that odor categorization can be clearly performed before interacting with cognitive functions such as memory during the olfactory process, and that it can be an objective odor categorization index through the activation pattern at 50–100 ms. Therefore, I suggest that people perceive odor objectively at least in the 50–100 ms period after odor recognition. Moreover, although less evidence, I found that these central olfactory processing features may be related to final behavior output.
Table Of Contents
Abstract i List of Contents ii List of Tables iv List of Figures iv I. Introduction - 1 - II. Theoretical background - 4 - 1 Our senses - 4 - 2 Upstream stages of olfactory processing - 5 - 3 Olfactory processing in the brain - 10 - 4 Odor object quality perception - 14 - 5 Temporal view of olfactory processing - 17 - 6 Use of EEG in the current study - 21 - III. Aims of the thesis - 24 - IV. Materials and Methods - 25 - 1 General methods - 25 - 1.1 Participants - 25 - 1.2 Ethics - 26 - 1.3 Sniffin’ sticks test - 26 - 2 Stimuli - 29 - 2.1 Odor preparation - 29 - 2.2 Odor delivery - 29 - 3 Survey - 30 - 3.1 Odor quality response - 30 - 3.2 General odor response - 30 - 4 EEG - 36 - 4.1 Electroencephalogram (EEG) Recording - 36 - 4.2 Experimental environment during EEG recording - 36 - 4.3 ERP preprocessing - 37 - 4.4 EEG preprocessing - 39 - 4.5 EEG data extraction for analysis - 39 - 4.6 Classification design and procedure - 41 - 5 Statistics and analysis - 43 - V. Verifying performance of olfactory EEG signal within 200ms - 44 - 1 Background - 44 - 2 Results - 47 - 2.1 ERP signal observed during olfaction before 200 ms - 47 - 2.2 The perceived intensity of the odor decreased when the same odor was offered again - 50 - 2.3 Significant changes in amplitude and latency of negative and positive potentials within 200 ms - 53 - 2.4 Changes in the NP and PP patterns across the conditions are related to the behavioral test - 57 - 3 Discussion - 61 - VI. Screening of odor categorization features in the brain based on temporal view - 63 - 1 Background - 63 - 2 Results - 66 - 2.1 Odor quality similarity. - 66 - 2.2 AP- and TP-induced spatial patterns of theta ERSP at 0-100 ms and 150-200 ms. - 69 - 2.3 Multivariate pattern of theta ERSPs indicates that AP and TP induce similar theta ERSPs at 50-100 ms and 150-200 ms. - 73 - 2.4 Verification of EEG source origination from olfactory-related brain areas - 78 - 3 Discussion - 81 - VII. Characterization of odor quality perception using odor profiling - 84 - 1 Background - 84 - 2 Results - 86 - 2.1 Experimental design for sorting objective-rated odor descriptors. - 86 - 2.2 Verbal cues altered odor quality pattern. - 89 - 2.3 Odor quality patterns are altered depending on rating score of descriptors by conditions. - 93 - 2.4 UD descriptors are less altered compared to LD descriptors in IVA - 99 - 2.5 Additional experiments find results similar to the first experiment. - 103 - 3 Discussion - 108 - VIII. Conclusion - 112 - IX. Nomenclature - 115 - References - 116 - 요 약 문 - 122 -