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Voltage-Sensitive Dye and Intrinsic Signal Optical Imaging
Published in Yu Chen, Babak Kateb, Neurophotonics and Brain Mapping, 2017
Vassiliy Tsytsarev, Reha S. Erzurumlu
The details of the biological origin underlying fast IOSs remains unclear, but most investigators believe that the ion and water movement as well as small changes in the cellular volume, associated with neural activity, causes a change in the optical scattering of the brain parenchyma. A special case of the IOS is fast optical imaging and, in particular, the event-related optical signal (EROS). EROS imaging uses near-infrared or infrared light through optical fibers to monitor changes in the optical properties of the brain tissue (Baniqued et al., 2013). This method is based on the scattering properties of the neurons and therefore provides a direct measure of the neural activity within centimeters (spatial) and milliseconds (temporal) resolution. In the auditory system, a mismatch negativity (a brain response to acoustic irregularities), previously demonstrated by evoked potential recordings in humans, has been confirmed by EROS (Sable et al., 2007). Recently associative aspects of memory have been examined by EROS methods. It was found that a brain region involved in face recognition was activated not only in response to the face representation but also when viewing scenes, associated with specific faces (Walker et al., 2014).
Psychophysiological Measures of Workload: Potential Applications to Adaptively Automated Systems
Published in Raja Parasuraman, Mustapha Mouloua, Automation and Human Performance: Theory and Applications, 2018
Arthur F. Kramer, Leonard J. Trejo, Darryl G. Humphrey
In the study we describe next we assessed the utility of the irrelevant probe technique in a high-fidelity radar simulator with 10 highly experienced Navy radar operators. The radar operators performed a standard training exercise that contained periods of low- and high-processing demands. The ERPs were elicited by three different tones that differed in frequency of occurrence. One of the three tones occurred on 80% of the probe trials, whereas each of the other two tones occurred on 10% of the probe trials. Prior to the radar monitoring task, in which the tones were to be ignored, the radar operators performed a baseline oddball condition in which they pushed a response button every time one of the two low-probability tones was presented. The other low-probability tone and the high-probability tone did not require an overt response. The baseline condition was used to establish a record of each individual’s ERP components in the absence of the demands of the radar monitoring task. The dual-deviant/single-standard (i.e., two different low-probability tones and one high-probability tone) tone presentation was used for two reasons. First, low-probability stimuli often elicit larger amplitude ERP components than do high-probability stimuli. Thus, the use of two low-probability tones would presumably enable us to increase the frequency of detecting changes in the amplitude of ERP components in response to variations in the processing demands in the radar monitoring task. Second, we were interested in examining ERP components such as the N100, N200 and P300 as well as the mismatch negativity (MMN; Naatanen, 1990). Although the N100, N200, and P300 components are often easiest to observe when subjects actively attend or respond to the ERP eliciting events, MMNs are difference waveform components that can most easily be dissociated from other ERP components when elicited by high- and low-probability events that do not require any overt action. Thus, the use of two deviant probe events, one that required a response and one that did not, would enable us to discern the MMN as well as the other ERP components in the baseline condition.
Certified Flight Instructors’ Performance – Review of the Literature and Exploration of Future Steps
Published in The International Journal of Aerospace Psychology, 2020
Christophe Lazure, Laurence Dumont, Sofia El Mouderrib, Jean-François Delisle, Sylvain Sénécal, Pierre-Majorique Léger
The neural mechanisms at the root of error detection and expectation violation are studied using electroencephalogram (EEG) event related potential (ERP) components called error related negativity (ERN) and mismatch negativity (MMN). ERN usually occurs when someone commits an error and it is a reaction attributed to the anterior cingulate cortex (Holroyd & Coles, 2002). Its detection can be due either to the presentation of the stimuli or to the response and it is usually detectable even when the individual is unaware they made the mistake. MMN on the other hand, usually occurs between 250 and 450 milliseconds after conflicting stimuli are presented, and is seen as an automatic reaction that triggers a redirection of attention toward the detected conflict (Garrido et al., 2009). It has been shown to be defective in pathologies where false conclusions are made such as schizophrenia (Umbricht & Krljesb, 2005) or dyslexia (Bishop, 2007). Furthermore, larger MMN in typical individuals lead to better and faster error detection (Garrido et al., 2009), pointing toward a causal role of this ERP.
Intelligent analysis of irregular physical factors for panic disorder using quantum probability
Published in Journal of Experimental & Theoretical Artificial Intelligence, 2022
Ankush Manocha, Yasir Afaq, Munish Bhatia
Rees et al. (1998) have considered a total of 11 health symptoms acquired from PD patients to identify the health irregularity by rating the scale from 0 to 4 such as not present, mild, moderate, severe, and very severe by utilising principal component analysis. A total of five clusters, such as shortness of breath; dizziness; nausea; cardiovascular signs; and chest pain have been maintained for the classification. Segui et al. (1998) have classified the targeted parameter into three clusters named cardiorespiratory, vestibular, and general excitement. The cardiorespiratory cluster is considered the most descriptive cluster, which is containing the symptoms of headaches, fear of death, difficulty breathing, paraesthesia, trembling, and dyspnoea (26.1% variance). Moreover, dyspnoea and choking were classified in a respiratory cluster in two other studies (Bruno et al., 2018; Neerakal & Srinivasan, 2002). Zhou et al. (2022) have utilised magnetic resonance imaging resting-state scans of 40 patients suffering from PD to identify abnormal resting-state networks of the brain. These scans were categorised into two groups where 35 samples belong to drug-based and 5 samples belong to drug-free patients and analysed the abnormal brain activities manually. Cheng et al. (2021) performed a clinical study and utilised magnetoencephalography over electroencephalography to evaluate Mismatch negativity in the patients suffering from PD. A total of 20 individuals suffering from PD were selected to capture MEG recordings. The connections between mismatch negativity-based responses and clinical estimation were additionally inspected to investigate the change in the individuals with PD.
An empirical comparison of machine learning algorithms for the classification of brain signals to assess the impact of combined yoga and Sudarshan Kriya
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2022
Himika Sharma, Rajnish Raj, Mamta Juneja
SK is one of the most powerful breathing techniques or meditation for management of stress (Bhatia 2002). There are many studies which have been conducted to study the effect of SK on EEG signals. Initially, the study reported the antidepressant effect of SK (Murthy et al. 1998). After that an investigation represents an enhancement in beta 1 and beta 2 activity in midline and left frontal occipital regions of the brain which increased the cortical activation of the brain. Hence, improved the awareness and focus of the brain (Bhatia et al. 2003). Further, Event Related Potential (ERP) study revealed an increase in Mismatch Negativity (MMN) amplitude among SK practitioners which enhanced pre-attentive and emotional processing (Srinivasan and Baijal 2007). One more study presented a reduction in ERP magnitude which elevated the optimism and emotions management after practice of SK (Gootjes et al. 2011). Similarly, the investigation showed increase in coherence value in theta, beta and alpha bands in central areas of the brain after practice of SK which increased the connectivity emphasizes the efficient processing of information (Bhatia 2002). Moreover, the study revealed that alpha, beta, delta and theta waves energy was more in right brain occipital and prefrontal regions than left brain after SK (Kochupillai 2015). Similarly, study reported that after practice of SK increase in alpha energy and significant difference was found in gamma, alpha, and theta2 rhythms (Chandra et al. 2016). Further, the study observed, entropy and relative band energy was elevated and kurtosis value was depressed in SK practitioners as compared to non-practitioners (Shaw and Routray 2016). Recent study conducted on combined yoga and SK showed an increase in variance, standard deviation, zero crossing, maximum and minimum values in SK practitioners whereas decreased in non-practitioners. Kurtosis value decreased in both SK practitioners and non-practitioners but in SK practitioners decrement was more as compared to non-practitioners. As per this recent study conducted in the literature, it has been observed that only one study has been conducted on the combined effect of yoga and SK on EEG signal. Also the study conducted utilized only Artificial Neural Network (ANN) classifiers to classify the meditator and non-meditator groups from statistical parameters. Now, as the studies have not utilised all the classifiers at the same time, there remains a drawback in the existing study to find the optimal classifier that can classify the meditator and non-meditator groups from statistical parameters such as standard deviation, maximum, minimum, variance, kurtosis and zero crossing with improved accuracy (Sharma et al. 2019).