Journal articles: 'Analysis of brain potentials'

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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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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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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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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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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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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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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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 was calculated. Different trends of the coherence function have been evidenced in subjects learning and not learning the better movement strategy. In particular, relations have been found between frontal, central and occipital electrodes in medium and high frequency ranges.

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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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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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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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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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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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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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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 influences of dipole parameters on the potential distribution of scalp surface, such as position, direction and strength, which attempts to provide an effective method to solve EEG forward problem, based on diversified head model, and also proposes a prior information to the solution to EEG inverse problem.

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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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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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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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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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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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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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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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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 the result of research there were revealed the high interconnections of latency of later components in sportsmen of both groups of examined persons at observation of significant stimuli “What” and “Where”. There was revealed the intensification of correlations of latency in frontal, central and temporal parts of the brain cortex. The correlations of amplitude of late components of biopotentials of the brain cortex were characterized with mean coefficients of interconnection mainly in sagittal central frontal and also parietal parts of cortex.

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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 visual ERP, and a slow negative shift potential associated with the auditory N100 component, varied in amplitude as processing resources were allocated to the visual or auditory channel. Both these sets of results were obtained only when stimuli were presented at a fast rate. The results suggest that intermodality divided attention influences both modality-specific and modality-nonspecific ERP components in practised subjects under high-information load conditions. The implications of the results for models of processing resources and the evaluation of mental workload are discussed.

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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 electrocorticogram and morphological markers typical of rodent seizure models were observed in the Hcn1M294L mouse. Lamotrigine exacerbated seizures and increased spiking, whereas sodium valproate reduced spiking, mirroring drug responses reported in a patient with this variant. Functional analysis in Xenopus laevis oocytes and layer V somatosensory cortical pyramidal neurons in ex vivo tissue revealed a loss of voltage dependence for the disease variant resulting in a constitutively open channel that allowed for cation ‘leak’ at depolarized membrane potentials. Consequently, Hcn1M294L layer V somatosensory cortical pyramidal neurons were significantly depolarized at rest. These neurons adapted through a depolarizing shift in action potential threshold. Despite this compensation, layer V somatosensory cortical pyramidal neurons fired action potentials more readily from rest. A similar depolarized resting potential and left-shift in rheobase was observed for CA1 hippocampal pyramidal neurons. The Hcn1M294L mouse provides insight into the pathological mechanisms underlying hyperexcitability in HCN1 developmental and epileptic encephalopathy, as well as being a preclinical model with strong construct and face validity, on which potential treatments can be tested.

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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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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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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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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 reading conditions. In combination with a recognition task, lexicality and depth of processing were varied. Left-minus-right difference ERPs optimally suited to accentuate left-lateralized language processes revealed an occipito-temporal processing negativity (210–270 ms) for all stimuli except alphanumerical strings. This asymmetry showed greater sensitivity to the combined effects of attention and lexicality than other ERPs in this time range (i.e., N170, P1, and P2). It is therefore introduced as “lexical asymmetry.”

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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 pleasant and unpleasant) gave higher cortical positivity than neutral ones, for all components. In addition, in the two latency epochs, larger positivities were found at Pz, compared to Fz and Cz, whereas Fz and Cz did not differ from each other.

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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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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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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 of faces as complex-structured stimuli and, therefore, to the presence of its distinctive organizational characteristics prior to within-category identification. In turn, the relatively late and probably more rostrally generated N250r and N400-like responses might respectively indicate processes of access and retrieval of face-related information, which is stored in long-term memory (LTM). New methods of analysis of electrophysiological and neuroanatomical data, namely, dynamic causal modeling, single-trial and time-frequency analyses, are highly recommended to advance in the knowledge of those brain mechanisms concerning face processing.

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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 active tasks during conscious resections of brain tumors. METHODS Five patients, each with an intraaxial tumor in their dominant hemisphere, underwent conscious resection of their lesion with passive mapping. The authors performed functional localization for the receptive language area, using real-time HGA mapping, by listening passively to linguistic sounds. Furthermore, single electrical pulses were delivered to the identified receptive temporal language area to detect CCEPs in the frontal lobe. All mapping results were validated by ECS, and the sensitivity and specificity were evaluated. RESULTS Linguistic HGA mapping quickly identified the language area in the temporal lobe. Electrical stimulation by linguistic HGA mapping to the identified temporal receptive language area evoked CCEPs on the frontal lobe. The combination of linguistic HGA and frontal CCEPs needed no patient cooperation or effort. In this small case series, the sensitivity and specificity were 93.8% and 89%, respectively. CONCLUSIONS The described technique allows for simple and quick functional brain mapping with higher sensitivity and specificity than ECS mapping. The authors believe that this could improve the reliability of functional brain mapping and facilitate rational and objective operations. Passive mapping also sheds light on the underlying physiological mechanisms of language in the human brain.

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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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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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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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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 stimuli with the frequency ranging from 1 to 40 Hz. As a result of the developed program the appropriate frequency of a stimulus in the EEG signal was detected and signalled.

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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 volumetric magnetic resonance imaging, and framed stereotaxy was used to implant an electrode parallel to the axis of the gyrus by using an oblique anterolateral-posteromedial trajectory. Intraoperative evoked potentials from auditory stimuli were recorded from multiple electrode contacts. Postoperatively, stimulation of each electrode was performed and participants were asked to describe the percept. Audiometric analysis was performed for 2 participants during subthreshold stimulation. RESULTS: Sounds presented to the contralateral and ipsilateral ears produced evoked potentials in HG electrodes in all participants intraoperatively. Stimulation produced a reproducible sensation of sound in all participants with perceived volume proportional to amplitude. Four participants reported distinct sounds when different electrodes were stimulated, with more medial contacts producing tones perceived as higher in pitch. Stimulation was not associated with adverse audiometric effects. There were no complications of electrode implantation. CONCLUSION: Direct anatomic targeting with physiological verification can be used to implant electrodes directly into primary auditory cortex. If deep brain stimulation proves effective for intractable tinnitus, this technique may be useful to assist with electrode implantation.

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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-peak intervals, were calculated. It is shown that unilateral traumatic damage of the motor cortex area and underlying regions in rats does not signifi cantly reduce the number of VEP peaks. However, in most of the animals, the N1 component was absent in the area of damage.In comparison with healthy rats, traumatized rats demonstrated an increased latency of N1 and N3 peaks on the 3rd day after the operation followed by their return to normal values on the 7th day. In addition, traumatized rats showed a higher P2 amplitude in regions remote from the traumatized cortex area on the 3rd day; however, the P2 amplitude was lower in the injury area on the 7th day. The obtained results indicate that the registration and analysis of VEP can be used for localizing the traumatized area and to analyse the dynamics of the brain functional state in rats with brain trauma.

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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 stimulation on the fractal structure of EEG signal. On comparison between different conditions, 14-Hz steady-state visual evoked potentials (SSVEPs), previously shown to trigger an optimal brain response, exhibited the greatest influence on the complexity of the EEG signal. On the other hand, we observed the lowest complexity of EEG signal in the post-stimulation rest period. Statistical analysis confirmed significant differences in the fractal structure of the EEG signal between rest and different stimulation conditions. These findings demonstrate for the first time a direct relationship between the efficiency of brain processing and the complexity of the measured EEG signal, which could be employed for objective assessment and classification in various experimental paradigms.

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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 of evoked potentials in subjects of different groups by channels was carried out in accordance with the Wilcoxon test. Demonstrated for which channels the results significantly differ between the two groups of subjects. The sequence of evoked potential analysis demonstrated in the article suits for adjusting the settings of the “brain-computer” systems for a particular subject and allows to select channels used in further BCI training efficiently.

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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 with Hilbert transform, is first employed to provide time-frequency power spectra for neural data. Such power spectra are typically sparse and of high resolution, that is, there usually exist many zero values, which result in numerical problems for directly computing coherence. Hence, we propose to add random noise onto the spectra, making coherence calculation feasible. Furthermore, a statistical randomization procedure is designed to cancel out the effect of the added noise. Computer simulations are first performed to verify the effectiveness of NAIC. Local field potentials collected from visual cortex of macaque monkey while performing a generalized flash suppression task are then used to demonstrate the usefulness of our NAIC method to provide highresolution time-frequency coherence measure for connectivity analysis of neural data.

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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 region was improved with multichannel compared with single-channel waveforms. In visual cortex, unsupervised clustering identified the canonical regular-spiking (RS) and fast-spiking (FS) classes but also indicated a subclass of RS units with unidirectional backpropagating action potentials (BAPs). Moreover, BAPs were observed in many hippocampal RS cells. Overall, waveform analysis of spikes from high-density probes aids neuron identification and can reveal dendritic backpropagation. NEW & NOTEWORTHY It is challenging to identify neuron types with extracellular electrophysiology in vivo. We show that spatiotemporal action potentials measured on high-density electrode arrays can capture cell type-specific morphoelectrical properties, allowing classification of neurons across brain structures and within the cortex. Moreover, backpropagating action potentials are reliably detected in vivo from subpopulations of cortical and hippocampal neurons. Together, these results enhance the utility of dense extracellular electrophysiology for cell-type interrogation of brain network function.

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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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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 recorded from 62 EEG channels. The EEG signals were recorded as EPs elicited by painful electrical stimulations in the oesophagus with an intensity corresponding to the individual pain detection threshold. The EPs from all channels and subjects were decomposed simultaneously by a temporal matching pursuit (TMP) algorithm with Gabor atoms. Results Amplitude and phase features were classified by a support vector machine (SVM) to discriminate patients from healthy volunteers. A classification performance of 93.1% (P<0.001) was obtained when applying a majority voting scheme to the 3 best performing channels (FC4, C1, and C6) and including features from 2 atoms. The most discriminative features were determined by the slope coefficients from the SVM decision rule, which identified the biomarkers as delayed latency of the first atom (N2–P2 complex) and decreased amplitude of the second atom (NI–P1 complex). Conclusion The combination of TMP and SVM is a novel approach to classify two study populations, which may provide a new objective tool to identify biomarkers from various chronic pain populations.

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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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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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Journal articles on the topic 'Analysis of brain potentials'

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