Time-Frequency Analysis of Chemosensory Event-Related Potentials to Characterize the Cortical Representation of Odors in Humans

BACKGROUND: The recording of olfactory and trigeminal chemosensory event-related potentials (ERPs) has been proposed as an objective and non-invasive technique to study the cortical processing of odors in humans. Until now, the responses have been characterized mainly using across-trial averaging in the time domain. Unfortunately, chemosensory ERPs, in particular, olfactory ERPs, exhibit a relatively low signal-to-noise ratio. Hence, although the technique is increasingly used in basic research as well as in clinical practice to evaluate people suffering from olfactory disorders, its current clinical relevance remains very limited. Here, we used a time-frequency analysis based on the wavelet transform to reveal EEG responses that are not strictly phase-locked to onset of the chemosensory stimulus. We hypothesized that this approach would significantly enhance the signal-to-noise ratio of the EEG responses to chemosensory stimulation because, as compared to conventional time-domain averaging, (1) it is less sensitive to temporal jitter and (2) it can reveal non phase-locked EEG responses such as event-related synchronization and desynchronization. METHODOLOGY/PRINCIPAL FINDINGS: EEG responses to selective trigeminal and olfactory stimulation were recorded in 11 normosmic subjects. A Morlet wavelet was used to characterize the elicited responses in the time-frequency domain. We found that this approach markedly improved the signal-to-noise ratio of the obtained EEG responses, in particular, following olfactory stimulation. Furthermore, the approach allowed characterizing non phase-locked components that could not be identified using conventional time-domain averaging. CONCLUSION/SIGNIFICANCE: By providing a more robust and complete view of how odors are represented in the human brain, our approach could constitute the basis for a robust tool to study olfaction, both for basic research and clinicians

Novel measure of olfactory bulb function in health and disease

Present neuroimaging techniques are capable of recording the neural activity from all over the brain but the olfactory bulb (OB). The OB is the first olfactory processing stage of the central nervous system and the site of insult in several neurological disorders, particularly Parkinson’s disease (PD). It has been suggested that the OB has a pivotal role in the olfactory system anal-ogous to primary visual cortex (V1) and thalamus in the visual system. However, due to the existing technical limitations, there has not been any non-invasive technique that can reliably measure the OB function in humans, consequently limiting its functional recording to one in-tracranial study dating back to the 60s. Initially in Study I, a non-invasive method of measuring the function of human OB is devel-oped, so-called electrobulbogram (EBG). In line with previous animal literature as well as the only intracranial study in human OB, it was demonstrated that gamma oscillations on the EBG electrodes occurred shortly after the odor onset. Subsequently, applying source recon-struction analysis provided evidence that observed oscillations were localized to the OB. Ad-ditionally, the OB recording with the EBG method showed a test-retest reliability comparable with visual event related potentials. Notably, the detected gamma oscillations were demon-strated to be insensitive to habituation, the OB’s marked characteristic which has previously been demonstrated in rodents. Last, but not least, assessing the EBG response in an individual who did not have the bilateral OB indicated that the lack of OB results in disappearance of gamma oscillations in the EBG electrodes. Given that Study I determined the possibility of reliably measuring the function of the OB using the EBG, in Study II, I assessed the functional role of OB’s oscillations in the pro-cessing of the odor valence. Odor valence has been suggested to be linked to approach–avoidance responses and therefore, processing of odor valence is thought to be one of the core aspects of odor processing in the olfactory system. Consequently, using combined EBG and EEG recording, OB activity was reconstructed on the source level during processing of odors with different valences. Gamma and beta oscillations were found to be related to va-lence perception in the human OB. Moreover, the early beta oscillations were associated with negative but not positive odors, where these beta oscillations can be linked to preparatory neural responses in the motor cortex. Subsequently, in a separate experiment, negative odors were demonstrated to trigger a whole-body motor avoidance response in the time window overlapping with the valence processes in the OB. These negative odor-elicited motor re-sponses were measured by a force plate as a leaning backward motion. Altogether, the results from Study II indicated that the human OB processes odor valence sequentially in the gamma and beta frequency bands, where the early processing of negative odors in the OB might be facilitating rapid approach-avoidance behaviors. To further evaluate the functional role of the OB in odor processing, in Study III, OB’s communication with its immediate recipient, namely piriform cortex (PC), was assessed. These two areas are critical nodes of the olfactory system which communicate with each other through neural oscillations. The activity of the OB and the PC were reconstructed using a combination of EBG, EEG, and source reconstruction techniques. Subsequently, the cross spectrogram of the OB and the PC was assessed as a measure of functional connectivity where temporal evolution from fast to slow oscillations in the OB–PC connectivity was found during the one second odor processing. Furthermore, the spectrally resolved Granger causal-ity analysis suggested that the afferent connection form the OB to the PC occurred in the gamma and beta bands whereas the efferent connection from the PC to the OB was concen-trated in the theta and delta bands. Notably, odor identity could be deciphered from the low gamma oscillatory pattern in the OB–PC connectivity as early as 100ms after the odor onset. Hence, findings from this study elucidate on our understanding of the bidirectional infor-mation flow in the human olfactory system. Olfactory dysfunction, due to neurodegeneration in the OB, commonly appears several years earlier than the occurrence of the PD-related characteristic motor symptoms. Consequently, a functional measure of the OB may serve as a potential early biomarker of PD. In Study IV, OB function was assessed in PD to answer whether the EBG method can be used to dissociate individuals with a PD diagnosis from healthy age-matched controls. The spectrogram of the EBG signals indicated that there were different values in gamma, beta, and theta for PDs compared with healthy controls. Specifically, six components were found in the EBG re-sponse during early and late time points which together dissociate PDs from controls with a 90% sensitivity and a 100% specificity. Furthermore, these components were linked to med-ication, disease duration and severity, as well as clinical odor identification performance. Overall, these findings support the notion that EBG has a diagnostic value and can be further developed to serve as an early biomarker for PD. In the last study, Study V, the prevalence of COVID-19 was determined using odor intensity ratings as an indication of olfactory dysfunction. Using a large sample data (n = 2440) from a Swedish population, odor intensity ratings of common household items over time were found to be closely associated with prevalence prediction of COVID-19 in the Stockholm region over the same time-period (r = -.83). Impairment in odor intensity rating was further correlated with the number of reported COVID-19 symptoms. Relatedly, individuals who progressed from having no symptoms to having at least one symptom had a marked decline in their odor intensity ratings. The results from this study, given the relatively large sample size, provided a concrete basis for the future studies to further assess the potential association between the deficits in the OB function and olfactory dysfunction in COVID-19. In conclusion, our proposed method for non-invasive measurement of the OB function was shown to provide a reliable recording with a potential as a diagnostic tool for PD. Combining EBG and EEG allowed for reconstruction of the OB signal at the source level, where specific oscillations were found to be critical for odor valence processing and rapid avoidance re-sponse. Moreover, oscillations in different frequency bands were found to be critical for the OB reciprocal communications and transfer of odor identity information to higher order ol-factory subsystems. Finally, COVID-19 was found to be associated with a decline in olfactory acuity which might originate from damage to the patient’s OB. In conclusion, the results from the studies within this thesis provide a new perspective on the functional role of oscillations in the human OB

Pattern mining approaches used in sensor-based biometric recognition: a review

Sensing technologies place significant interest in the use of biometrics for the recognition and assessment of individuals. Pattern mining techniques have established a critical step in the progress of sensor-based biometric systems that are capable of perceiving, recognizing and computing sensor data, being a technology that searches for the high-level information about pattern recognition from low-level sensor readings in order to construct an artificial substitute for human recognition. The design of a successful sensor-based biometric recognition system needs to pay attention to the different issues involved in processing variable data being - acquisition of biometric data from a sensor, data pre-processing, feature extraction, recognition and/or classification, clustering and validation. A significant number of approaches from image processing, pattern identification and machine learning have been used to process sensor data. This paper aims to deliver a state-of-the-art summary and present strategies for utilizing the broadly utilized pattern mining methods in order to identify the challenges as well as future research directions of sensor-based biometric systems

Intelligent Biosignal Analysis Methods

This book describes recent efforts in improving intelligent systems for automatic biosignal analysis. It focuses on machine learning and deep learning methods used for classification of different organism states and disorders based on biomedical signals such as EEG, ECG, HRV, and others

Electrophysiological Responses in the Human Amygdala Discriminate Emotion Categories of Complex Visual Stimuli

The human amygdala has been shown to participate in processing emotionally salient stimuli related to threat, danger, and aversion, data that have come primarily from functional imaging and lesion studies. Recording intracranial field potentials from five amygdalas in four patients with chronically implanted depth electrodes, we analyzed responses in the gamma frequency range, a region of the power spectrum thought to reflect especially the contribution of neuronal activity to cognitive processes. Significant changes in the power amplitude of responses were obtained selectively to visual images judged to look aversive but not to those judged to look pleasant or neutral. Several possible confounds were addressed: all four patients had been carefully selected so that the amygdalas from which recordings were obtained were distal to epileptogenic foci, making it likely that we recorded from healthy tissue, and the observed responses could not be attributed to luminance or color differences between the stimuli. A further analysis of differences in power between the high and low gamma bands revealed an additional structure that discriminated those stimuli related to bodily injury from those related to disgust. Despite the increased power amplitude in the gamma range, there was no stimulus-locked phase coherence. The observed responses in the gamma frequency range may reflect the role of the amygdala in binding perceptual representations of the stimuli with memory, emotional response, and modulation of ongoing cognition, on the basis of the emotional significance of the stimuli

Wavelet Correlation Analysis for Quantifying Similarities and Real-Time Estimates of Information Encoded or Decoded in Single-Trial Oscillatory Brain Waves

Even in cases when we recognize identical objects or when we behave similarly, the spatiotemporal activities in the brain are likely to fluctuate to various degrees. Temporally fluctuating responses easily decrease by averaging replicate measures. We previously developed a wavelet correlation analysis that tolerates the across-trial oscillatory phase variability observed in odor-induced cortical responses. The wavelet correlation analysis revealed a change in the neuronal information redundancy of transient and oscillatory brain waves from the dependencies on stimulus experience (high redundancy) to stimulus quality (low redundancy) between the input and output layers of the anterior piriform cortex in guinea pigs. We report on its application to estimate information in the fine temporal structures of single-trial brain waves. By using a set of standard brain waves for each information in a given category, the highest wavelet correlation coefficients provided the first candidate of estimated information with 75% accuracy. Moreover, the probability of including the correct information for the two upper candidates, regardless of information redundancy of the signal sources, was >92%. The wavelet correlation analysis is useful for similarity analyses and real-time estimates of in-brain information and for its application to brain-machine interfaces or medical/research tools

Magnetoencephalography

This is a practical book on MEG that covers a wide range of topics. The book begins with a series of reviews on the use of MEG for clinical applications, the study of cognitive functions in various diseases, and one chapter focusing specifically on studies of memory with MEG. There are sections with chapters that describe source localization issues, the use of beamformers and dipole source methods, as well as phase-based analyses, and a step-by-step guide to using dipoles for epilepsy spike analyses. The book ends with a section describing new innovations in MEG systems, namely an on-line real-time MEG data acquisition system, novel applications for MEG research, and a proposal for a helium re-circulation system. With such breadth of topics, there will be a chapter that is of interest to every MEG researcher or clinician