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Runnova A, Selskii A, Kiselev A, Shamionov R, Parsamyan R, Zhuravlev M. Changes in EEG Alpha Activity during Attention Control in Patients: Association with Sleep Disorders. J Pers Med 2021; 11:jpm11070601. [PMID: 34201953 PMCID: PMC8307584 DOI: 10.3390/jpm11070601] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 06/22/2021] [Accepted: 06/23/2021] [Indexed: 11/25/2022] Open
Abstract
We aimed to assess which quantitative EEG changes during daytime testing in patients with sleep disorder (primary insomnia and excessive daytime sleepiness groups). All experimental study participants were subjected to a long-term test for maintaining attention to sound stimuli, and their EEGs were recorded and then processed, using wavelet analysis, in order to estimate the power and frequency structure of alpha activity. In healthy subjects, the maximum increase in the alpha rhythm occurred near 9 Hz. Patients with primary insomnia were characterized by an increase in the amplitude of the alpha rhythm near 11 Hz. For subjects with sleep disorders, an increase in the amplitude of the alpha rhythm was observed in the entire frequency range (7.5–12.5 Hz), with a maximum increase at 9–10 Hz. Significant differences (p≤0.001) for changes in the alpha rhythm dynamics in the course of performing the attention test were observed in the frequency range of 7.5–10.5 Hz between the control group and patients with sleep disorders. The ratios of the alpha rhythm power values for passive stages with closed eyes before and after active stage were significantly different among the groups of healthy sleep volunteers, patients with primary insomnia, and patients with impaired sleep hygiene within the range of 9.5 to 12.5 Hz. The results of the current study supported the notion of a 24-h hyperarousal in primary insomnia.
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Affiliation(s)
- Anastasiya Runnova
- Department of Basic Research in Neurocardiology, Institute of Cardiological Research, Saratov State Medical University Named after V.I. Razumovsky, B. Kazachaya Str., 112, 410012 Saratov, Russia; (A.R.); (A.S.); (A.K.); (R.P.)
- Institute of Physics, Saratov State University, Astrakhanskaya Str., 83, 410012 Saratov, Russia
| | - Anton Selskii
- Department of Basic Research in Neurocardiology, Institute of Cardiological Research, Saratov State Medical University Named after V.I. Razumovsky, B. Kazachaya Str., 112, 410012 Saratov, Russia; (A.R.); (A.S.); (A.K.); (R.P.)
- Institute of Physics, Saratov State University, Astrakhanskaya Str., 83, 410012 Saratov, Russia
| | - Anton Kiselev
- Department of Basic Research in Neurocardiology, Institute of Cardiological Research, Saratov State Medical University Named after V.I. Razumovsky, B. Kazachaya Str., 112, 410012 Saratov, Russia; (A.R.); (A.S.); (A.K.); (R.P.)
- National Medical Research Center for Therapy and Preventive Medicine, 10, Petroverigsky per., 101953 Moscow, Russia
| | - Rail Shamionov
- Faculty of Psychological, Pedagogical and Special Education, Saratov State University, Astrakhanskaya Str., 83, 410012 Saratov, Russia;
| | - Ruzanna Parsamyan
- Department of Basic Research in Neurocardiology, Institute of Cardiological Research, Saratov State Medical University Named after V.I. Razumovsky, B. Kazachaya Str., 112, 410012 Saratov, Russia; (A.R.); (A.S.); (A.K.); (R.P.)
| | - Maksim Zhuravlev
- Department of Basic Research in Neurocardiology, Institute of Cardiological Research, Saratov State Medical University Named after V.I. Razumovsky, B. Kazachaya Str., 112, 410012 Saratov, Russia; (A.R.); (A.S.); (A.K.); (R.P.)
- Institute of Physics, Saratov State University, Astrakhanskaya Str., 83, 410012 Saratov, Russia
- Correspondence:
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Zani A. From Correlational Signs to Markers. Current Trends in Neuroelectric Research on Visual Attentional Processing. Brain Sci 2020; 10:E350. [PMID: 32517167 PMCID: PMC7348763 DOI: 10.3390/brainsci10060350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Accepted: 06/03/2020] [Indexed: 11/30/2022] Open
Abstract
Traditionally, electroencephalographic (EEG) and event-related brain potentials (ERPs) research on visual attentional processing attempted to account for mental processes in conceptual terms without reference to the way in which they were physically realized by the anatomical structures and physiological processes of the human brain. The brain science level of analysis, in contrast, attempted to explain the brain as an information processing system and to explain mental events in terms of brain processes. Somehow overcoming the separation between the two abovementioned levels of analysis, the cognitive neuroscience level considered how information was represented and processed in the brain. Neurofunctional processing takes place in a fraction of a second. Hence, the very high time resolution and the reliable sensitivity of EEG and ERPs in detecting fast functional changes in brain activity provided advantages over hemodynamic imaging techniques such as positron emission tomography (PET) or functional magnetic resonance imaging (fMRI), as well as over behavioral measures. However, volume conduction and lack of three-dimensionality limited applications of EEG and ERPs per se more than hemodynamic techniques for revealing locations in which brain processing occurs. These limits could only be overcome by subtraction methods for isolating attentional effects that might endure over time in EEG and may be riding even over several different ERP components, and by intracerebral single and distributed electric source analyses as well as the combining of these signals with high-spatial resolution hemodynamic signals (fMRI), both in healthy individuals and clinical patients. In my view, the articles of the Special Issue concerned with "ERP and EEG Markers of Brain Visual Attentional Processing" of the present journal Brain Sciences provide very good examples of all these levels of analysis.
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Affiliation(s)
- Alberto Zani
- School of Psychology, Vita Salute San Raffaele University, 20132 Milan, Italy
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