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1

Yordanova, Juliana, and Vasil Kolev. "Event-Related Brain Oscillations." Journal of Psychophysiology 23, no. 4 (January 2009): 174–82. http://dx.doi.org/10.1027/0269-8803.23.4.174.

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Анотація:
Neuroelectric oscillations provide important tools to study information processing in the brain. In this paper, major concepts and advantages of event-related oscillations (EROs) are considered, with a focus on their relevance for developmental research. Findings from previous studies in passive and oddball conditions are summarized to demonstrate that the age-dependent power decrease of theta (4–7 Hz) and alpha (8–14 Hz) EROs is accompanied by an increase in the synchronization of these oscillations. New data are presented to test whether this dissociation depends on processing demands in a frequency-specific manner. Results from an auditory serial learning task with working memory activation performed by 70 subjects (children from 6 to 10 years of age and adults) indicate that this effect was observed for theta and slow alpha oscillations, whereas an age-dependent decrease in event-related phase synchronization was found for fast alpha oscillations. It is concluded that phase synchronization of only the major theta and alpha EROs may reflect the neurobiological maturation of neural networks involved in perception. Phase synchronization of EROs, however, especially from faster frequency bands, essentially depends on the mode of network involvement and functional competence, which is associated with cognitive processing abilities or strategies in the course of development.
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2

López-Caneda, Eduardo, Socorro Rodríguez Holguín, Ángeles Correas, Carina Carbia, Alberto González-Villar, Fernando Maestú, and Fernando Cadaveira. "Binge drinking affects brain oscillations linked to motor inhibition and execution." Journal of Psychopharmacology 31, no. 7 (February 7, 2017): 873–82. http://dx.doi.org/10.1177/0269881116689258.

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Introduction: Neurofunctional studies have shown that binge drinking patterns of alcohol consumption during adolescence and youth are associated with anomalies in brain functioning. Recent evidence suggests that event-related oscillations may be an appropriate index of neurofunctional damage associated with alcoholism. However, there is no study to date that has evaluated the effects of binge drinking on oscillatory brain responses related to task performance. The purpose of the present study was to examine brain oscillations linked to motor inhibition and execution in young binge drinkers (BDs) compared with age-matched controls. Methods: Electroencephalographic activity was recorded from 64 electrodes while 72 university students (36 controls and 36 BDs) performed a visual Go/NoGo task. Event-related oscillations along with the Go-P3 and NoGo-P3 event-related potential components were analysed. Results: While no significant differences between groups were observed regarding event-related potentials, event-related oscillation analysis showed that BDs displayed a lower oscillatory response than controls in delta and theta frequency ranges during Go and NoGo conditions. Conclusions: Findings are congruent with event-related oscillation studies showing reduced delta and/or theta oscillations in alcoholics during Go/NoGo tasks. Thus, BDs appear to show disruptions in neural oscillations linked to motor inhibition and execution similar to those observed in alcohol-dependent subjects. Finally, these results are the first to evidence that oscillatory brain activity may be a sensitive indicator of underlying brain anomalies in young BDs, which could complement standard event-related potential measures.
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3

Zhang, Guanghui, Xueyan Li, and Fengyu Cong. "Objective Extraction of Evoked Event-Related Oscillation from Time-Frequency Representation of Event-Related Potentials." Neural Plasticity 2020 (December 19, 2020): 1–20. http://dx.doi.org/10.1155/2020/8841354.

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Анотація:
Evoked event-related oscillations (EROs) have been widely used to explore the mechanisms of brain activities for both normal people and neuropsychiatric disease patients. In most previous studies, the calculation of the regions of evoked EROs of interest is commonly based on a predefined time window and a frequency range given by the experimenter, which tends to be subjective. Additionally, evoked EROs sometimes cannot be fully extracted using the conventional time-frequency analysis (TFA) because they may be overlapped with each other or with artifacts in time, frequency, and space domains. To further investigate the related neuronal processes, a novel approach was proposed including three steps: (1) extract the temporal and spatial components of interest simultaneously by temporal principal component analysis (PCA) and Promax rotation and project them to the electrode fields for correcting their variance and polarity indeterminacies, (2) calculate the time-frequency representations (TFRs) of the back-projected components, and (3) compute the regions of evoked EROs of interest on TFRs objectively using the edge detection algorithm. We performed this novel approach, conventional TFA, and TFA-PCA to analyse both the synthetic datasets with different levels of SNR and an actual ERP dataset in a two-factor paradigm of waiting time (short/long) and feedback (loss/gain) separately. Synthetic datasets results indicated that N2-theta and P3-delta oscillations can be stably detected from different SNR-simulated datasets using the proposed approach, but, by comparison, only one oscillation was obtained via the last two approaches. Furthermore, regarding the actual dataset, the statistical results for the proposed approach revealed that P3-delta was sensitive to the waiting time but not for that of the other approaches. This study manifested that the proposed approach could objectively extract evoked EROs of interest, which allows a better understanding of the modulations of the oscillatory responses.
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4

Ülgen, Zehra, Mert Küçük, Christina Schmiedt-Fehr, and Canan Başar-Eroğlu. "Event Related Theta Oscillations During Sustained Attention." International Journal of Psychophysiology 168 (October 2021): S98—S99. http://dx.doi.org/10.1016/j.ijpsycho.2021.07.298.

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5

Kolev, Vasil, Juliana Yordanova, Martin Schürmann, and Erol Baţar. "Event-related alpha oscillations in task processing." Clinical Neurophysiology 110, no. 10 (October 1999): 1784–92. http://dx.doi.org/10.1016/s1388-2457(99)00105-4.

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6

Sanchez-Alavez, Manuel, Patricia Robledo, Derek N. Wills, James Havstad, and Cindy L. Ehlers. "Cholinergic modulation of event-related oscillations (ERO)." Brain Research 1559 (April 2014): 11–25. http://dx.doi.org/10.1016/j.brainres.2014.02.043.

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7

Balconi, Michela, and Uberto Pozzoli. "Event-Related Oscillations (ERO) and Event-Related Potentials (ERP) in Emotional Face Recognition." International Journal of Neuroscience 118, no. 10 (January 2008): 1412–24. http://dx.doi.org/10.1080/00207450601047119.

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8

Heinrich, Hartmut, Vasil Kolev, Aribert Rothenberger, and Juliana Yordanova. "Event-Related Oscillations and Cognitive Processes in Children." Journal of Psychophysiology 23, no. 4 (January 2009): 199–207. http://dx.doi.org/10.1027/0269-8803.23.4.199.

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Анотація:
Event-related EEG modulations, which are phase-locked to perceptual, cognitive, and motor processes, are often studied by means of event-related potentials (ERPs), although event-related oscillatory responses in different EEG frequency bands allow a more refined analysis, closer to brain physiology. This article introduces the basics of time-frequency methods, which are typically applied for the analysis of event-related oscillations, focusing on adaptive procedures (e.g., wavelet networks). The potential of these methods is illustrated. Findings about event-related oscillations (gamma responses, theta responses) in children performing an auditory selective attention task are reviewed. Both the neuronal substrates of gamma (30–70 Hz) networks and the ability to synchronize these networks in relation to task-specific processes are available in children and adolescents from 9 to 16 years of age. Developmental changes in the task reactivity of synchronized gamma oscillations may provide evidence for a transition in cognitive processing strategies emerging at the age of 12–13 years. Event-related theta (3–7.5 Hz) activity is enhanced in two latency ranges. The early event-related theta response occurring 0–200 ms after a stimulus may be associated with representations of relevant target features in working memory. The late fronto-central theta response (200 – 450 ms) could be related to the processing of task-irrelevant information. In summary, event-related oscillations can be analyzed using time-frequency methods like wavelet networks. This approach should be used intensively to study neurocognitive development in children.
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9

Balconi, Michela, and Uberto Pozzoli. "Event-related oscillations (EROs) and event-related potentials (ERPs) comparison in facial expression recognition." Journal of Neuropsychology 1, no. 2 (September 2007): 283–94. http://dx.doi.org/10.1348/174866407x184789.

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10

Andrew, Colin, and George Fein. "Event-Related Oscillations Versus Event-Related Potentials in a P300 Task as Biomarkers for Alcoholism." Alcoholism: Clinical and Experimental Research 34, no. 4 (April 2010): 669–80. http://dx.doi.org/10.1111/j.1530-0277.2009.01136.x.

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11

Ramos-Loyo, Julieta, Andrés A. González-Garrido, Luis Miguel Sánchez-Loyo, Virginia Medina, and Canan Basar-Eroglu. "Event-related potentials and event-related oscillations during identity and facial emotional processing in schizophrenia." International Journal of Psychophysiology 71, no. 1 (January 2009): 84–90. http://dx.doi.org/10.1016/j.ijpsycho.2008.07.008.

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12

Yener, Gorsev. "Event-Related Oscillations (EROs) in Dementia During Cognitive Paradigms." International Journal of Psychophysiology 168 (October 2021): S69. http://dx.doi.org/10.1016/j.ijpsycho.2021.07.212.

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13

Yordanova, Juliana, Vasil Kolev, Hartmut Heinrich, Wolfgang Woerner, Tobias Banaschewski, and Aribert Rothenberger. "Developmental event-related gamma oscillations: effects of auditory attention." European Journal of Neuroscience 16, no. 11 (December 2002): 2214–24. http://dx.doi.org/10.1046/j.1460-9568.2002.02286.x.

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14

Ehlers, Cindy L., and Jose R. Criado. "Event-related oscillations in mice: Effects of stimulus characteristics." Journal of Neuroscience Methods 181, no. 1 (June 2009): 52–57. http://dx.doi.org/10.1016/j.jneumeth.2009.04.015.

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15

Özerdem, Ayşegül, Sibel Kocaaslan, Zeliha Tunca, and Erol Başar. "Event related oscillations in euthymic patients with bipolar disorder." Neuroscience Letters 444, no. 1 (October 2008): 5–10. http://dx.doi.org/10.1016/j.neulet.2008.07.081.

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16

Herrmann, Christoph S., and Robert T. Knight. "Mechanisms of human attention: event-related potentials and oscillations." Neuroscience & Biobehavioral Reviews 25, no. 6 (August 2001): 465–76. http://dx.doi.org/10.1016/s0149-7634(01)00027-6.

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17

Jones, Kevin A., Bernice Porjesz, Laura Almasy, Laura Bierut, Danielle Dick, Alison Goate, Anthony Hinrichs, et al. "A Cholinergic Receptor Gene (CHRM2) Affects Event-related Oscillations." Behavior Genetics 36, no. 5 (July 6, 2006): 627–39. http://dx.doi.org/10.1007/s10519-006-9075-6.

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18

Danilova, N. N. "Dipole analysis of event-related oscillations in anticipation processes." International Journal of Psychophysiology 69, no. 3 (September 2008): 161–62. http://dx.doi.org/10.1016/j.ijpsycho.2008.05.413.

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19

Kolev, V., and J. Yordanova. "349 Correlations between event-related alpha oscillations and P300." International Journal of Psychophysiology 30, no. 1-2 (September 1998): 135–36. http://dx.doi.org/10.1016/s0167-8760(98)90348-8.

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20

KLIMESCH, WOLFGANG, MANUEL SCHABUS, MICHAEL DOPPELMAYR, WALTER GRUBER, and PAUL SAUSENG. "EVOKED OSCILLATIONS AND EARLY COMPONENTS OF EVENT-RELATED POTENTIALS: AN ANALYSIS." International Journal of Bifurcation and Chaos 14, no. 02 (February 2004): 705–18. http://dx.doi.org/10.1142/s0218127404009417.

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Анотація:
In the present work, we provide new arguments and data indicating that early ERP components are generated at least in part by evoked theta and alpha oscillations. We proceed from the general hypothesis, originally proposed by Erol Basar that ERP's are generated by a superposition of evoked oscillations with different frequencies. Based on findings about event-related desynchronization/synchronization (ERD/ERS), we analyze the following specific hypotheses. If evoked theta and alpha oscillations contribute to the generation of ERP components and if their functional role, type of reactivity and frequency specificity are similar to those of event-related oscillations (measured by ERD/ERS), we expect (i) to see the same functional relationship between frequency and cognitive processes, (ii) the same type of "reactivity" and a (iii) dependency of latency measures of evoked components on IAF. By reviewing respective data, we demonstrate that similar to research about event-related oscillations, evoked alpha reflects attention, whereas evoked theta reflects working memory processes. Furthermore, it was found that individual alpha frequency (IAF) has a significant influence on P1 latency in particular. For a better understanding of these findings, we outline a new theoretical framework. We assume that the P1–N1 complex is generated by an interplay between the synchronous activation of three neuronal network systems, a working memory, attentional, and semantic memory system, each operating with a different frequency, the first in the theta (about 6 Hz), the second in the lower alpha (about 8 Hz) and the third in the upper alpha (about 12 Hz) frequency range. The implications of this theoretical framework are discussed by reviewing research using phase sensitive measures to analyze "local" and "large scale" integration processes between different neural networks.
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21

Cole, Scott, and Bradley Voytek. "Cycle-by-cycle analysis of neural oscillations." Journal of Neurophysiology 122, no. 2 (August 1, 2019): 849–61. http://dx.doi.org/10.1152/jn.00273.2019.

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Neural oscillations are widely studied using methods based on the Fourier transform, which models data as sums of sinusoids. This has successfully uncovered numerous links between oscillations and cognition or disease. However, neural data are nonsinusoidal, and these nonsinusoidal features are increasingly linked to a variety of behavioral and cognitive states, pathophysiology, and underlying neuronal circuit properties. We present a new analysis framework, one that is complementary to existing Fourier and Hilbert transform-based approaches, that quantifies oscillatory features in the time domain on a cycle-by-cycle basis. We have released this cycle-by-cycle analysis suite as “bycycle,” a fully documented, open-source Python package with detailed tutorials and troubleshooting cases. This approach performs tests to assess whether an oscillation is present at any given moment and, if so, quantifies each oscillatory cycle by its amplitude, period, and waveform symmetry, the latter of which is missed with the use of conventional approaches. In a series of simulated event-related studies, we show how conventional Fourier and Hilbert transform approaches can conflate event-related changes in oscillation burst duration as increased oscillatory amplitude and as a change in the oscillation frequency, even though those features were unchanged in simulation. Our approach avoids these errors. Furthermore, we validate this approach in simulation and against experimental recordings of patients with Parkinson’s disease, who are known to have nonsinusoidal beta (12–30 Hz) oscillations. NEW & NOTEWORTHY We introduce a fully documented, open-source Python package, bycycle, for analyzing neural oscillations on a cycle-by-cycle basis. This approach is complementary to traditional Fourier and Hilbert transform-based approaches but avoids specific pitfalls. First, bycycle confirms an oscillation is present, to avoid analyzing aperiodic, nonoscillatory data as oscillations. Next, it quantifies nonsinusoidal aspects of oscillations, increasingly linked to neural circuit physiology, behavioral states, and diseases. This approach is tested against simulated and real data.
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22

Guntekin, Bahar. "Alterations of Event-Related Oscillations in Patients With Parkinson’s Disease." International Journal of Psychophysiology 168 (October 2021): S75. http://dx.doi.org/10.1016/j.ijpsycho.2021.07.232.

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23

Rektor, Ivan, Marek Baláž, and Martina Bočková. "Cognitive Event-Related Potentials and Oscillations in the Subthalamic Nucleus." Neurodegenerative Diseases 7, no. 1-3 (2010): 160–62. http://dx.doi.org/10.1159/000289228.

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24

Imas, O. A., K. M. Ropella, J. D. Wood та A. G. Hudetz. "Halothane augments event-related γ oscillations in rat visual cortex". Neuroscience 123, № 1 (січень 2004): 269–78. http://dx.doi.org/10.1016/j.neuroscience.2003.09.014.

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25

Sakihara, Kotoe, Atsuko Gunji, Wakana Furushima, and Masumi Inagaki. "Event-related oscillations in structural and semantic encoding of faces." Clinical Neurophysiology 123, no. 2 (February 2012): 270–77. http://dx.doi.org/10.1016/j.clinph.2011.06.023.

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26

De Pascalis, V., V. Varriale, and L. Dantuono. "Event-related oscillations to feedback signal during a learning task." International Journal of Psychophysiology 69, no. 3 (September 2008): 161. http://dx.doi.org/10.1016/j.ijpsycho.2008.05.412.

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27

Mu, Yan, Yan Fan, Lihua Mao, and Shihui Han. "Event-related theta and alpha oscillations mediate empathy for pain." Brain Research 1234 (October 2008): 128–36. http://dx.doi.org/10.1016/j.brainres.2008.07.113.

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28

Güntekin, Bahar, and Erol Başar. "Event-related beta oscillations are affected by emotional eliciting stimuli." Neuroscience Letters 483, no. 3 (October 2010): 173–78. http://dx.doi.org/10.1016/j.neulet.2010.08.002.

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29

Yordanova, J., and V. Kolev. "Phase-Locking of Event-Related EEG Oscillations: Analysis and Application." Applied Signal Processing 5, no. 1 (1998): 24. http://dx.doi.org/10.1007/s005290050003.

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30

Yu, Bo, Lin Ma, Haifeng Li, Lun Zhao, Hongjian Bo, and Xunda Wang. "Biological Computation Indexes of Brain Oscillations in Unattended Facial Expression Processing Based on Event-Related Synchronization/Desynchronization." Computational and Mathematical Methods in Medicine 2016 (2016): 1–17. http://dx.doi.org/10.1155/2016/8958750.

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Анотація:
Estimation of human emotions from Electroencephalogram (EEG) signals plays a vital role in affective Brain Computer Interface (BCI). The present study investigated the different event-related synchronization (ERS) and event-related desynchronization (ERD) of typical brain oscillations in processing Facial Expressions under nonattentional condition. The results show that the lower-frequency bands are mainly used to update Facial Expressions and distinguish the deviant stimuli from the standard ones, whereas the higher-frequency bands are relevant to automatically processing different Facial Expressions. Accordingly, we set up the relations between each brain oscillation and processing unattended Facial Expressions by the measures of ERD and ERS. This research first reveals the contributions of each frequency band for comprehension of Facial Expressions in preattentive stage. It also evidences that participants have emotional experience under nonattentional condition. Therefore, the user’s emotional state under nonattentional condition can be recognized in real time by the ERD/ERS computation indexes of different frequency bands of brain oscillations, which can be used in affective BCI to provide the user with more natural and friendly ways.
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31

Basar, E., C. Schmiedt-Fehr, A. Oniz, and C. Basar-Eroglu. "Event related oscillations triggered by the face of the loved person." International Journal of Psychophysiology 69, no. 3 (September 2008): 314–15. http://dx.doi.org/10.1016/j.ijpsycho.2008.05.335.

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32

Nanova, Plamenka, Vasil Kolev, and Juliana Yordanova. "Developmental gender differences in the synchronization of auditory event-related oscillations." Clinical Neurophysiology 122, no. 5 (May 2011): 907–15. http://dx.doi.org/10.1016/j.clinph.2010.09.012.

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33

Lu, Mingou, Nuria Doñamayor, Thomas F. Münte, and Jörg Bahlmann. "Event-related potentials and neural oscillations dissociate levels of cognitive control." Behavioural Brain Research 320 (March 2017): 154–64. http://dx.doi.org/10.1016/j.bbr.2016.12.012.

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34

Schmiedt-Fehr, Christina, Birgit Mathes, and Canan Basar-Eroglu. "Alpha Brain Oscillations and Inhibitory Control." Journal of Psychophysiology 23, no. 4 (January 2009): 208–15. http://dx.doi.org/10.1027/0269-8803.23.4.208.

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Анотація:
A major challenge for developmental cognitive neuroscience is to understand how changes in cognitive functions related to aging are associated with changes in the neuronal information processing architecture. Previous studies on EEG event-related brain oscillations suggest functional changes in alpha-bands with age during sensory and memory tasks. Specifically, the topographical distribution of both single-trial lower and upper alpha magnitude and the corresponding phase coherence is altered in elderly persons. Thus, alpha oscillations, associated not only with sensory, but also with sensorimotor functions, may be altered with age. Compensatory mechanisms, possibly reflected in increased frontal alpha synchronization, may thereby be of profound relevance. The present study investigates age-related differences in the modulation of alpha oscillatory activity related to sensory and sensorimotor functions, including response preparation, execution, and inhibition. EEG was recorded while 10 young and 10 elderly persons performed a visual evoked potential (VEP), a cued stimulus response (S-R), and a cued visual Go/NoGo task. Early event-related synchronization (ERS, 0–250 ms) and late event-related desynchronization (ERD, 200–600 ms) of single-trial lower and upper alpha was analyzed using poststimulus amplitude enhancement and intertrial phase coherence measures. The results show comparable modulations of lower (8–10 Hz) and upper (10–15 Hz) alpha activity in young and elderly related to the sensory and different forms of motor response processing. Specifically, reduced early lower alpha ERS as well as late upper alpha ERD at central locations characterized response inhibition processing in both age groups. We discuss the counterintuitive hypothesis that reduced efficacy of some basal neural inhibitory mechanisms enables older observers to perform better than or comparable to younger observers on some visual tasks, and conclude that alterations in alpha oscillatory networks with age may depend on the stimuli applied.
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35

Yener, Görsev G., Bahar Güntekin, Elif Tülay, and Erol Başar. "A comparative analysis of sensory visual evoked oscillations with visual cognitive event related oscillations in Alzheimer's disease." Neuroscience Letters 462, no. 3 (September 2009): 193–97. http://dx.doi.org/10.1016/j.neulet.2009.07.036.

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36

Missonnier, Pascal, François R. Herrmann, Christelle Rodriguez, Marie-Pierre Deiber, Phiippe Millet, Lara Fazio-costa, Gabriel Gold, and Panteleimon Giannakopoulos. "Age-related differences on event-related potentials and brain rhythm oscillations during working memory activation." Journal of Neural Transmission 118, no. 6 (February 18, 2011): 945–55. http://dx.doi.org/10.1007/s00702-011-0600-2.

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37

Yener, Gorsev. "Alterations of Event-Related Potentials/Oscillations (ERPs/EROs) in Various Memory Impairments." International Journal of Psychophysiology 168 (October 2021): S75. http://dx.doi.org/10.1016/j.ijpsycho.2021.07.233.

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38

Hayashi, Takuto, Yuko Mizuno-Matsumoto, Shimpei Kohri, Yoshinori Nitta, and Mitsuo Tonoike. "Event-related theta and alpha oscillations under emotional stimuli: an MEG study." Intelligent Automation & Soft Computing 23, no. 1 (March 21, 2016): 175–82. http://dx.doi.org/10.1080/10798587.2016.1151190.

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39

Yordanova, Juliana, and Vasil Kolev. "Event-related alpha oscillations are functionally associated with P300 during information processing." NeuroReport 9, no. 14 (October 1998): 3159–64. http://dx.doi.org/10.1097/00001756-199810050-00007.

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40

Başar, E. rol, M. artin Schürmann, T. amer Demiralp, C. anan Başar-Eroglu, and A. hmet Ademoglu. "Event-related oscillations are ‘real brain responses’ — wavelet analysis and new strategies." International Journal of Psychophysiology 39, no. 2-3 (January 2001): 91–127. http://dx.doi.org/10.1016/s0167-8760(00)00135-5.

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41

Kolev, Vasil, Juliana Yordanova, Martin Schürmann, and Erol Başar. "Increased frontal phase-locking of event-related alpha oscillations during task processing." International Journal of Psychophysiology 39, no. 2-3 (January 2001): 159–65. http://dx.doi.org/10.1016/s0167-8760(00)00139-2.

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42

Atagün, Murat İlhan, Bahar Güntekin, Belinda Maşalı, Elif Tülay, and Erol Başar. "Decrease of event-related delta oscillations in euthymic patients with bipolar disorder." Psychiatry Research: Neuroimaging 223, no. 1 (July 2014): 43–48. http://dx.doi.org/10.1016/j.pscychresns.2014.04.001.

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43

Christie, Sommer, Penny Werthner, and Maurizio Bertollo. "Exploration of event-related dynamics of brain oscillations in ice hockey shooting." Sport, Exercise, and Performance Psychology 8, no. 1 (February 2019): 38–52. http://dx.doi.org/10.1037/spy0000134.

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44

Yener, Görsev G., and Erol Başar. "Sensory evoked and event related oscillations in Alzheimer’s disease: a short review." Cognitive Neurodynamics 4, no. 4 (October 21, 2010): 263–74. http://dx.doi.org/10.1007/s11571-010-9138-5.

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45

Atagün, Murat İlhan, Bahar Güntekin, Devran Tan, Emine Elif Tülay, and Erol Başar. "Lithium excessively enhances event related beta oscillations in patients with bipolar disorder." Journal of Affective Disorders 170 (January 2015): 59–65. http://dx.doi.org/10.1016/j.jad.2014.08.024.

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46

Fu, Shen-Ming, Rui-Xin Liu, and Jian-Hua Sun. "On the Scale Interactions that Dominate the Maintenance of a Persistent Heavy Rainfall Event: A Piecewise Energy Analysis." Journal of the Atmospheric Sciences 75, no. 3 (March 1, 2018): 907–25. http://dx.doi.org/10.1175/jas-d-17-0294.1.

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Анотація:
Abstract Persistent heavy rainfall events (PHREs) are the product of the combined effects of multiscale systems. A PHRE that occurred during the 2016 mei-yu season was selected to further the understanding of the scale interactions accounting for the persistence of this type of event. The scale interactions were analyzed quantitatively using a piecewise energy budget based on temporal scale separation. Results show that the strongest interactions between the precipitation-related eddy flow and its background circulation (BC) occur in the mid- to lower troposphere, where a significant downscale kinetic energy (KE) cascade alone dominates eddy flow persistence. An obvious upscale KE cascade (i.e., a feedback effect) appears in the mid- to upper troposphere but has a negligible effect on the BC. Overall, within the precipitation region, the downscale KE cascade is primarily dependent on BC signals with shorter periods, whereas the upscale KE cascade is more dependent on BC signals with longer periods. Thus, the BC has asymmetric effects on the KE cascades. The most significant BC signal as determined via wavelet analysis [i.e., quasi-biweekly (10–18 days) oscillations in this event] does not play the leading role in the downscale KE cascade. Instead, the quasi-weekly oscillations provide the maximum amount of energy for eddy flow maintenance. Semi-idealized simulations of various BC signals show similar results: precipitation and the intensities of lower-level shear lines and transversal troughs (both of which are closely related to the precipitation-related eddy flow) are more sensitive to the quasi-weekly oscillation than to the quasi-biweekly oscillation.
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47

Aktürk, Tuba, Ümmühan İşoğlu-Alkaç, Lütfü Hanoğlu, and Bahar Güntekin. "Age related differences in the recognition of facial expression: Evidence from EEG event-related brain oscillations." International Journal of Psychophysiology 147 (January 2020): 244–56. http://dx.doi.org/10.1016/j.ijpsycho.2019.11.013.

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48

Hall, Mei-Hua, Kevin M. Spencer, Katja Schulze, Colm McDonald, Sridevi Kalidindi, Eugenia Kravariti, Fergus Kane, et al. "The genetic and environmental influences of event-related gamma oscillations on bipolar disorder." Bipolar Disorders 13, no. 3 (May 2011): 260–71. http://dx.doi.org/10.1111/j.1399-5618.2011.00925.x.

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49

Criado, Jose R., Ian R. Gizer, Wendy S. Slutske, Evie Phillips, and Cindy L. Ehlers. "Event-related oscillations to affective stimuli: Heritability, linkage and relationship to externalizing disorders." Journal of Psychiatric Research 46, no. 2 (February 2012): 256–63. http://dx.doi.org/10.1016/j.jpsychires.2011.10.017.

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50

Levy, Ron, Andres M. Lozano, Anthony E. Lang, and Jonathan O. Dostrovsky. "Event-related desynchronization of motor cortical oscillations in patients with multiple system atrophy." Experimental Brain Research 206, no. 1 (June 10, 2010): 1–13. http://dx.doi.org/10.1007/s00221-010-2312-5.

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