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1

Homma, S., and Y. Nakajima. "Dipole-tracing analysis of human brain potentials." Journal of Neuroscience Methods 17, no. 2-3 (1986): 201. http://dx.doi.org/10.1016/0165-0270(86)90088-9.

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2

Sirevaag, Erik J., Arthur F. Kramer, Michael G. H. Coles, and Emanuel Donchin. "Resource reciprocity: An event-related brain potentials analysis." Acta Psychologica 70, no. 1 (1989): 77–97. http://dx.doi.org/10.1016/0001-6918(89)90061-9.

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3

Popivanov, D. "Time series analysis of brain potentials preceding voluntary movements." Medical & Biological Engineering & Computing 30, no. 1 (1992): 9–14. http://dx.doi.org/10.1007/bf02446187.

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4

Oostenveld, Robert, Dick F. Stegeman, Peter Praamstra, and Adriaan van Oosterom. "Brain symmetry and topographic analysis of lateralized event-related potentials." Clinical Neurophysiology 114, no. 7 (2003): 1194–202. http://dx.doi.org/10.1016/s1388-2457(03)00059-2.

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5

Licht, Robert, H. L. Hamburger, and L. H. J. Nyens. "Topographic analysis of brain potentials in dyslexic and normal children." International Journal of Psychophysiology 25, no. 1 (1997): 55. http://dx.doi.org/10.1016/s0167-8760(97)85493-1.

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6

Thesen, Thomas, and Claire Murphy. "Reliability analysis of event-related brain potentials to olfactory stimuli." Psychophysiology 39, no. 6 (2002): 733–38. http://dx.doi.org/10.1111/1469-8986.3960733.

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7

Stone, James L., Ramsis F. Ghaly, Kodanallur S. Subramanian, Peter Roccaforte, and James Kane. "Transtentorial Brain Herniation in the Monkey: Analysis of Brain Stem Auditory and Somatosensory Evoked Potentials." Neurosurgery 26, no. 1 (1990): 26–31. http://dx.doi.org/10.1227/00006123-199001000-00003.

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8

Johnson, Ray, Kurt Kreiter, Britt Russo, and John Zhu. "A spatio-temporal analysis of recognition-related event-related brain potentials." International Journal of Psychophysiology 29, no. 1 (1998): 83–104. http://dx.doi.org/10.1016/s0167-8760(98)00006-3.

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9

Locatelli, T., L. T. Mainardi, M. Cursi, G. Comi, S. Cerutti, and A. M. Bianchi. "Event-Related Brain Potentials: Laplacian Transformation for Multichannel Time-Frequency Analysis." Methods of Information in Medicine 39, no. 02 (2000): 160–63. http://dx.doi.org/10.1055/s-0038-1634272.

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Abstract:During a visual-motor task the movement strategies and the learning processes are investigated. A group of 10 normal young volunteers underwent the experiment. The EEG signal was recorded through the 10-20 acquisition system during the execution of a task after a visual input. Each subject repeated the movement several times in three different conditions: i) without knowledge of the performance; ii) with visual feedback; iii) with knowledge of the result. The signal was transformed through Laplacian operator in order to eliminate the spurious coherence and then time-variant coherence
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10

Schramm, J., T. Mokrusch, R. Fahlbusch, and A. Hochstetter. "Detailed analysis of intraoperative changes monitoring brain stem acoustic evoked potentials." Neurosurgery 22, no. 4 (1988): 694???702. http://dx.doi.org/10.1097/00006123-198804000-00013.

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11

Gibbons, Henning, and Thomas H. Rammsayer. "Current-source density analysis of slow brain potentials during time estimation." Psychophysiology 41, no. 6 (2004): 861–74. http://dx.doi.org/10.1111/j.1469-8986.2004.00246.x.

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12

Graversen, Carina, Anne Estrup Olesen, Camilla Staahl, Asbjørn Mohr Drewes, and Dario Farina. "Multivariate Analysis of Single-Sweep Evoked Brain Potentials for Pharmaco-Electroencephalography." Neuropsychobiology 71, no. 4 (2015): 241–52. http://dx.doi.org/10.1159/000375310.

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13

Schramm, Johannes, Thomas Mokrusch, Rudolf Fahlbusch, and Albrecht Hochstetter. "Detailed Analysis of Intraoperative Changes Monitoring Brain Stem Acoustic Evoked Potentials." Neurosurgery 22, no. 4 (1988): 694–702. http://dx.doi.org/10.1227/00006123-198804000-00013.

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14

Rawlings, Robert R., John W. Rohrbaugh, Henri Begleiter, and Michael J. Eckardt. "Spectral methods for principal components analysis of event-related brain potentials." Computers and Biomedical Research 19, no. 6 (1986): 497–507. http://dx.doi.org/10.1016/0010-4809(86)90024-8.

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15

Rawlings, Robert R., Michael J. Eckardt, and Henri Begleiter. "Multivariate spectral methods for the analysis of event-related brain potentials." Computers and Biomedical Research 21, no. 2 (1988): 117–28. http://dx.doi.org/10.1016/0010-4809(88)90020-1.

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16

Wang, Xiang Li, Shi Mei Su, and Zhi Gang Shang. "Model and Simulation of the Brain Scalp Potential Analysis." Applied Mechanics and Materials 198-199 (September 2012): 942–47. http://dx.doi.org/10.4028/www.scientific.net/amm.198-199.942.

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Based on spherical head models, this paper, by employing the finite element method (FEM), analyzes the potential distribution of the brain scalp surface and attempts to work out the electroencephalography (EEG) forward problem, in hope of finding out the impact the dipole parameters has on it. According to the electromagnetism theory, this paper discusses the general resolution of EEG, it requires electric potentials of the globe's surface, and graphically displays results of computation through finite element post-processing, which tests their effectiveness. Furthermore, it analyzes the influ
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17

Bruder, G., C. Tenke, J. Towey, et al. "Topographic analyses of brain potentials in depressed patients." Biological Psychiatry 39, no. 7 (1996): 566. http://dx.doi.org/10.1016/0006-3223(96)84173-4.

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18

Groppe, David M., Thomas P. Urbach, and Marta Kutas. "Mass univariate analysis of event-related brain potentials/fields II: Simulation studies." Psychophysiology 48, no. 12 (2011): 1726–37. http://dx.doi.org/10.1111/j.1469-8986.2011.01272.x.

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19

Begleiter, H., B. Porjesz, T. Reich, et al. "Quantitative trait loci analysis of human event-related brain potentials: P3 voltage." Electroencephalography and Clinical Neurophysiology/Evoked Potentials Section 108, no. 3 (1998): 244–50. http://dx.doi.org/10.1016/s0168-5597(98)00002-1.

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20

KRAMARENKO, ALEXANDER V., and UNER TAN. "Brief Communication VALIDITY OF SPECTRAL ANALYSIS OF EVOKED POTENTIALS IN BRAIN RESEARCH." International Journal of Neuroscience 112, no. 4 (2002): 489–99. http://dx.doi.org/10.1080/00207450290025608.

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21

Çetin, Volkan, Serhat Ozekes, and Hüseyin Selçuk Varol. "Harmonic analysis of steady-state visual evoked potentials in brain computer interfaces." Biomedical Signal Processing and Control 60 (July 2020): 101999. http://dx.doi.org/10.1016/j.bspc.2020.101999.

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22

Spielmann, Mona Isabel, Erich Schröger, Sonja A. Kotz, and Alexandra Bendixen. "Attention effects on auditory scene analysis: insights from event-related brain potentials." Psychological Research 78, no. 3 (2014): 361–78. http://dx.doi.org/10.1007/s00426-014-0547-7.

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23

Belian, T., and P. Bartsch. "Confidence analysis of single brain-stem auditory evoked potentials (BAEP) in man." International Journal of Psychophysiology 7, no. 2-4 (1989): 138. http://dx.doi.org/10.1016/0167-8760(89)90084-6.

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24

Romaniuk, Alona, Tеtiana Shevchuk, Tеtiana Poruchynska, Oleksandr Zhuravlov, and Oksana Usova. "THE CORRELATIVE ANALYSIS OF AMPLITUDE-TEMPORAL CHARACTERISTICS OF EVOKED POTENTIALS OF BRAIN CORTEX IN SPORTSMEN." EUREKA: Life Sciences 2 (March 31, 2017): 51–58. http://dx.doi.org/10.21303/2504-5695.2017.00309.

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The article considers the correlative analysis of amplitude-temporal characteristics of evoked potentials of brain cortex in sportsmen of playing kinds of sport and athletes at perception and processing of significant information “What” and “Where” in the brain cortex. The method of electroencephalography (Р300 methodology) was used to study the evoked potentials of the brain cortex. The statistical processing of data was realized using the statistical package MedStat. Kendall coefficient of correlation was used depending on data distribution, different from the normal values distribution. In
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25

Parasuraman, Raja. "Event-Related Brain Potentials and Intermodal Divided Attention." Proceedings of the Human Factors Society Annual Meeting 29, no. 10 (1985): 971–75. http://dx.doi.org/10.1177/154193128502901016.

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Attention allocation to visual and auditory channels under high-information load was examined by recording event-related brain potentials (ERPs). Ten subjects monitored an audiovisual display of intermittent 2-degree circles presented centrally and 1000-Hz tones presented binaurally. Subjects had to detect targets in both channels while dividing attention to ecah channel in varying proportions. Each subject had a minimum of 20 hours practice at the task. POC analysis indicated a tradeoff in processing resources between the visual and auditory channels. The N160 and P250 components of the visua
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26

Bleakley, Lauren E., Chaseley E. McKenzie, Ming S. Soh, et al. "Cation leak underlies neuronal excitability in an HCN1 developmental and epileptic encephalopathy." Brain 144, no. 7 (2021): 2060–73. http://dx.doi.org/10.1093/brain/awab145.

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Abstract Pathogenic variants in HCN1 are associated with developmental and epileptic encephalopathies. The recurrent de novo HCN1 M305L pathogenic variant is associated with severe developmental impairment and drug-resistant epilepsy. We engineered the homologue Hcn1 M294L heterozygous knock-in (Hcn1M294L) mouse to explore the disease mechanism underlying an HCN1 developmental and epileptic encephalopathy. The Hcn1M294L mouse recapitulated the phenotypic features of patients with the HCN1 M305L variant, including spontaneous seizures and a learning deficit. Active epileptiform spiking on the e
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27

Weiss, T. "Dipole analysis of laser evoked brain potentials (LEP) to painful and nonpainful stimuli." Electroencephalography and Clinical Neurophysiology 103, no. 1 (1997): 179. http://dx.doi.org/10.1016/s0013-4694(97)88843-1.

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28

Holcomb, Phillip J., and Jane E. Anderson. "Cross-modal semantic priming: A time-course analysis using event-related brain potentials." Language and Cognitive Processes 8, no. 4 (1993): 379–411. http://dx.doi.org/10.1080/01690969308407583.

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29

Holcomb, Phillip J., Sharon A. Coffey, and Helen J. Neville. "Visual and auditory sentence processing: A developmental analysis using event‐related brain potentials." Developmental Neuropsychology 8, no. 2-3 (1992): 203–41. http://dx.doi.org/10.1080/87565649209540525.

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30

Koppehele-Gossel, Judith, Robert Schnuerch, and Henning Gibbons. "Lexical Processing as Revealed by Lateralized Event-Related Brain Potentials." Journal of Psychophysiology 33, no. 3 (2019): 148–64. http://dx.doi.org/10.1027/0269-8803/a000218.

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Abstract. Neurocognitive models of written-word processing from low-level perceptual up to semantic analysis include the notion of a strongly left-lateralized posterior-to-anterior stream of activation. Two left-lateralized components in the event-related brain potential (ERP), N170 and temporo-parietal PSA (posterior semantic asymmetry; peak at 300 ms), have been suggested to reflect sublexical analysis and semantic processing, respectively. However, for intermediate processing steps, such as lexical access, no posterior left-lateralized ERP signature has yet been observed under single-word r
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31

Mini, Alessio, Daniela Palomba, Alessandro Angrilli, and Stefano Bravi. "Emotional Information Processing and Visual Evoked Brain Potentials." Perceptual and Motor Skills 83, no. 1 (1996): 143–52. http://dx.doi.org/10.2466/pms.1996.83.1.143.

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Visual evoked potentials to emotional slides presented for 2 sec. were investigated in 13 subjects. 73 emotional slides (pleasant, unpleasant, and neutral) were selected from a standardized set of photographic slides, the 1988 International Affective Picture System of Lang, Öhman, and Vaitl. Visual evoked potentials were recorded from three head locations, frontal, central and parietal (Fz, Cz, and Pz). Analyses were performed in the two latency ranges: 300–400 msec. and 400–500 msec. Analyses showed an arousal effect, as indicated by a quadratic trend, indicating that emotional slides (both p
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32

Bromm, Burkhart. "Laser Evoked Brain Potentials in the Assessment of Pain: Methods, Applications, Brain Source Analyses." PAIN RESEARCH 12, no. 2 (1997): 41–57. http://dx.doi.org/10.11154/pain.12.41.

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33

Molnár, Márk. "Chaos in induced rhythms of the brain – the value of ERP studies." Behavioral and Brain Sciences 19, no. 2 (1996): 305. http://dx.doi.org/10.1017/s0140525x00042795.

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AbstractEvent-related potentials (ERPs) – neglected almost entirely by Wright & Liley – allow objective investigation of information processing in the brain. The application of chaos theory to such an analysis broadens this possibility. Through the use of the point correlation dimension (PD2) accurate dimensional analysis of different Event-Related Potential components such as the P3 wave is possible.
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34

Olivares, Ela I., Jaime Iglesias, Cristina Saavedra, Nelson J. Trujillo-Barreto, and Mitchell Valdés-Sosa. "Brain Signals of Face Processing as Revealed by Event-Related Potentials." Behavioural Neurology 2015 (2015): 1–16. http://dx.doi.org/10.1155/2015/514361.

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We analyze the functional significance of different event-related potentials (ERPs) as electrophysiological indices of face perception and face recognition, according to cognitive and neurofunctional models of face processing. Initially, the processing of faces seems to be supported by early extrastriate occipital cortices and revealed by modulations of the occipital P1. This early response is thought to reflect the detection of certain primary structural aspects indicating the presencegrosso modoof a face within the visual field. The posterior-temporal N170 is more sensitive to the detection
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35

Tamura, Yukie, Hiroshi Ogawa, Christoph Kapeller, et al. "Passive language mapping combining real-time oscillation analysis with cortico-cortical evoked potentials for awake craniotomy." Journal of Neurosurgery 125, no. 6 (2016): 1580–88. http://dx.doi.org/10.3171/2015.4.jns15193.

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OBJECTIVE Electrocortical stimulation (ECS) is the gold standard for functional brain mapping; however, precise functional mapping is still difficult in patients with language deficits. High gamma activity (HGA) between 80 and 140 Hz on electrocorticography is assumed to reflect localized cortical processing, whereas the cortico-cortical evoked potential (CCEP) can reflect bidirectional responses evoked by monophasic pulse stimuli to the language cortices when there is no patient cooperation. The authors propose the use of “passive” mapping by combining HGA mapping and CCEP recording without a
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36

Groppe, David M., Thomas P. Urbach, and Marta Kutas. "Mass univariate analysis of event-related brain potentials/fields I: A critical tutorial review." Psychophysiology 48, no. 12 (2011): 1711–25. http://dx.doi.org/10.1111/j.1469-8986.2011.01273.x.

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37

Dien, Joseph, Gwen A. Frishkoff, Arleen Cerbone, and Don M. Tucker. "Parametric analysis of event-related potentials in semantic comprehension: evidence for parallel brain mechanisms." Cognitive Brain Research 15, no. 2 (2003): 137–53. http://dx.doi.org/10.1016/s0926-6410(02)00147-7.

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38

Machinskaya, R. I., E. V. Krupskaya, and A. V. Kurgansky. "Functional brain organization of global and local visual perception: Analysis of event-related potentials." Human Physiology 36, no. 5 (2010): 518–34. http://dx.doi.org/10.1134/s036211971005004x.

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39

Kostyunina, M. B., and A. Posada. "Wavelet analysis and its application in investigation of brain potentials during verbal task solving." Biophysics 57, no. 4 (2012): 556–61. http://dx.doi.org/10.1134/s0006350912040082.

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40

Nawrocka, Agata, and Marcin Nawrocki. "The Application of Visual Evoked Potentials in Brain-Computer Interface." Solid State Phenomena 208 (September 2013): 102–8. http://dx.doi.org/10.4028/www.scientific.net/ssp.208.102.

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The article presents the concept of a universal BCI system based on the detection of Steady-State Visual Evoked Potentials (SSVEP). One of the possibilities of its application involves, for example, the visual keyboard which makes it possible to enter data (alphanumeric characters) into the computer without using muscles. The first part discusses the construction and the principle of operation of BCI interfaces and next the most frequently used evoked potentials are presented. An application allowing for an analysis of the EEG signal of a person subject to effect of the photostimulator using s
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41

Donovan, Chris, Jennifer Sweet, Matthew Eccher, et al. "Deep Brain Stimulation of Heschl Gyrus." Neurosurgery 77, no. 6 (2015): 940–47. http://dx.doi.org/10.1227/neu.0000000000000969.

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BACKGROUND: Tinnitus is a source of considerable morbidity, and neuromodulation has been shown to be a potential treatment option. However, the location of the primary auditory cortex within Heschl gyrus in the temporal operculum presents challenges for targeting and electrode implantation. OBJECTIVE: To determine whether anatomic targeting with intraoperative verification using evoked potentials can be used to implant electrodes directly into the Heschl gyrus (HG). METHODS: Nine patients undergoing stereo-electroencephalogram evaluation for epilepsy were enrolled. HG was directly targeted on
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42

Sysoev, Yu I., R. T. Chernyakov, R. D. Idiyatullin, et al. "Changes of Visually Evoked Potentials in Rats after Brain Trauma." Journal Biomed, no. 2 (June 10, 2020): 68–77. http://dx.doi.org/10.33647/2074-5982-16-2-68-77.

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In this study, we compared visually evoked potentials (VEP) in healthy rats and rats following traumatic brain injury. Traumatic brain injury was modelled by the method of controlled cortical impact. The electrical activity of the brain cortex was registered using nichrome electrodes. Responses in primary and secon dary motor cortex areas, as well as in the area of primary sensory cortex over the hippocampus, were evoked by 3 Hz white light fl ashes on the 3rd and 7th day after the operation. The latencies and amplitudes of N1, P2, N2, P3 и N3, as well as the duration and amplitudes of inter-p
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43

NAMAZI, HAMIDREZA, TIRDAD SEIFI ALA, and HOVAGIM BAKARDJIAN. "DECODING OF STEADY-STATE VISUAL EVOKED POTENTIALS BY FRACTAL ANALYSIS OF THE ELECTROENCEPHALOGRAPHIC (EEG) SIGNAL." Fractals 26, no. 06 (2018): 1850092. http://dx.doi.org/10.1142/s0218348x18500925.

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Analysis of the brain response to different types of external stimuli has always been one of the major research areas in behavioral neuroscience. The electroencephalography (EEG) technique combined with different signal analysis approaches has been especially successful in revealing the detailed dynamic properties of the neural response to exogenous stimulation. In this analysis, we evaluated the nonlinear structure of the EEG signal using fractal theory in rest and visual stimulation (checkerboard reversal at 8, 14 and 28[Formula: see text]Hz). Our analysis showed a significant influence of s
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44

Selskii, Anton, Maksim Zhuravlev, Anastasiia Runnova, Elena Grinina, Marina Konovalova, and Rail Shamionov. "A study of changes in cognitive evoked potentials in persons with visual impairment." E3S Web of Conferences 273 (2021): 10051. http://dx.doi.org/10.1051/e3sconf/202127310051.

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In this work we have used psychophysiological assessments of the human brain electrical activity according to the classical neurological method for calculating the evoked potential. The experiment was designed to extraction cognitive evoked potentials. Taking into account the characteristic components, the temporal dynamics of the EEG data channels was investigated. This approach allows one to consistently assess the distribution of all components of the evoked potential on the subject's head map. Based on the results of evoked potentials processing, a statistical comparison of the components
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45

Hu, Meng, and Hualou Liang. "Noise-Assisted Instantaneous Coherence Analysis of Brain Connectivity." Computational Intelligence and Neuroscience 2012 (2012): 1–12. http://dx.doi.org/10.1155/2012/275073.

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Characterizing brain connectivity between neural signals is key to understanding brain function. Current measures such as coherence heavily rely on Fourier or wavelet transform, which inevitably assume the signal stationarity and place severe limits on its time-frequency resolution. Here we addressed these issues by introducing a noise-assisted instantaneous coherence (NAIC) measure based on multivariate mode empirical decomposition (MEMD) coupled with Hilbert transform to achieve high-resolution time frequency representation of neural coherence. In our method, fully data-driven MEMD, together
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46

Jia, Xiaoxuan, Joshua H. Siegle, Corbett Bennett, et al. "High-density extracellular probes reveal dendritic backpropagation and facilitate neuron classification." Journal of Neurophysiology 121, no. 5 (2019): 1831–47. http://dx.doi.org/10.1152/jn.00680.2018.

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Different neuron types serve distinct roles in neural processing. Extracellular electrical recordings are extensively used to study brain function but are typically blind to cell identity. Morphoelectrical properties of neurons measured on spatially dense electrode arrays have the potential to distinguish neuron types. We used high-density silicon probes to record from cortical and subcortical regions of the mouse brain. Extracellular waveforms of each neuron were detected across many channels and showed distinct spatiotemporal profiles among brain regions. Classification of neurons by brain r
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47

Fischer, C., J. Luaute, M. Kandel, F. Dailler, and D. Mrlet. "W4.4 ERPs and sensory evoked potentials in severe comatose brain injury patients. A multivariate analysis." Clinical Neurophysiology 122 (June 2011): S15. http://dx.doi.org/10.1016/s1388-2457(11)60051-5.

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48

Graversen, Carina, Christina Brock, Jens Brøndum Frøkjær, Georg Dimcevski, Dario Farina, and Asbjørn Mohr Drewes. "Multivariate pattern analysis of evoked brain potentials by temporal matching pursuit and support vector machine." Scandinavian Journal of Pain 3, no. 3 (2012): 194. http://dx.doi.org/10.1016/j.sjpain.2012.05.057.

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Abstract Background/aims Electroencephalography (EEG) recorded as evoked brain potentials (EPs) reflects the cortical processing to an external event. This approach is often used to study the altered response to acute pain in chronic pain patients compared to healthy volunteers. However, discrimination of the responses from the study populations is a non-trivial task, which calls for improved objective methods. Methods To develop and validate a new methodology, we analyzed data from 16 type-1 diabetes mellitus patients and 15 age and gender matched volunteers, by means of brain activity record
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49

Wu, Xiaopei, Bangyan Zhou, Zhao Lv, and Chao Zhang. "To Explore the Potentials of Independent Component Analysis in Brain-Computer Interface of Motor Imagery." IEEE Journal of Biomedical and Health Informatics 24, no. 3 (2020): 775–87. http://dx.doi.org/10.1109/jbhi.2019.2922976.

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50

Bromm, Burkhart, and Andrew C. N. Chen. "Brain electrical source analysis of laser evoked potentials in response to painful trigeminal nerve stimulation." Electroencephalography and Clinical Neurophysiology 95, no. 1 (1995): 14–26. http://dx.doi.org/10.1016/0013-4694(95)00032-t.

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