The DOI matches its Crossref record; 141 of the 154 references it cites were found in a registry or an index.
Memory processes, brain oscillations and EEG synchronization
Abstract
This article tries to integrate results in memory research from divergent disciplines such as cognitive psychology, neuroanatomy, and neurophysiology. The integrating link is seen in more recent findings that provide strong arguments for the assumption that oscillations are a basic form of communication between cortical cell assemblies. It is assumed that synchronous oscillations of large cell assemblies--termed type 1 synchronization--reflect a resting state or possibly even a state of functional inhibition. On the other hand, during mental activity, when different neuronal networks may start to oscillate with different frequencies, each network may still oscillate synchronously (this is termed type 2 synchronization), but as a consequence, the large scale type 1 oscillation disappears. It is argued that these different types of synchronization can be observed in the scalp EEG by calculating event-related power changes within comparatively narrow but individually adjusted frequency bands. Experimental findings are discussed which support the hypothesis that short-term (episodic) memory demands lead to a synchronization (increase in band power) in the theta band, whereas long-term (semantic) memory demands lead to a task-specific desynchronization (decrease or suppression of power) in the upper alpha band. Based on these and other findings, a new memory model is proposed that is described on three levels: cognitive, anatomical and neurophysiological. It is suggested that short-term (episodic) memory processes are reflected by oscillations in an anterior limbic system, whereas long-term (semantic) memory processes are reflected by oscillations in a posterior-thalamic system. Oscillations in these frequency bands possibly provide the basis for encoding, accessing, and retrieving cortical codes that are stored in the form of widely distributed but intensely interconnected cell assemblies.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“the theta rhythm is directly connected with some areas engaged in memory processing and, in particular, it represents an EEG marker of hippocampal activity”
From The Functional Role of Dreaming in Emotional Processes (2019) · cites this paper as Klimesch, 1996
In the citing paper
“Theta rhythm may be considered as the local field potential (LFP) that represents an electrophysiological marker of hippocampal activity (Rutishauser et al., 2010), both during awake behavior and REM sleep (Klimesch, 1996; Cantero et al., 2003).”
From EEG oscillations during sleep and dream recall: state- or trait-like individual differences? (2015) · cites this paper as Klimesch, 1996
Citations
Cites
Hebb, D. O. (2005) · doi:10.4324/9781410612403 · Cited by 9,825
LOSS OF RECENT MEMORY AFTER BILATERAL HIPPOCAMPAL LESIONS
Scoville, W. B., & Milner, B. (1957) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.20.1.11 · Cited by 7,322
indicated, N. A. (1950) · Journal of Consulting Psychology · doi:10.1037/h0049612 · Cited by 6,984
The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat
O'Keefe, J., & Dostrovsky, J. (1971) · Brain Research · doi:10.1016/0006-8993(71)90358-1 · Cited by 6,151
Controlled and automatic human information processing: I. Detection, search, and attention.
Schneider, W., & Shiffrin, R. M. (1977) · Psychological Review · doi:10.1037/0033-295x.84.1.1 · Cited by 5,902
Memory and the hippocampus: A synthesis from findings with rats, monkeys, and humans.
Squire, L. R. (1992) · Psychological Review · doi:10.1037/0033-295x.99.2.195 · Cited by 5,376
Baddeley, A. (1992) · Science · doi:10.1126/science.1736359 · Cited by 5,258
Über das Elektrenkephalogramm des Menschen
Berger, H. (1929) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/bf01797193 · Cited by 4,266
Gray, C. M., König, P., Engel, A. K., & Singer, W. (1989) · Nature · doi:10.1038/338334a0 · Cited by 4,183
Handbook of perception and human performance
Boff, K. R., Kaufman, L., & Thomas, J. P. (1986) · Wiley eBooks · Cited by 4,033
Research works printed but not linked: 4
- Gray, 1987, Stimulus-dependent neuronal oscillations in the cat visual cortex area 17, Neuroscience (Suppl.), 22, 434
- Klimesch, 1988, Die Suchzeit für episodische und semantische Information, Sprache Kogn., 7, 129
- Klimesch, 1990, Alpha frequency and memory performance, J. Psychophysiol., 4, 381
- Pulvermueller, 1994, Brain rhythms, cell assemblies and cognition: Evidence from the processing of words and pseudowords, Psycoloquy.94.5.48. brain-rhythms, 1.pulvermueller
Cited by
Sorted by citations
Items 401–500 of 916
Daams, M., Schuitema, I., van Dijk, B. W., Broeder, E. V. D., Veerman, A. J. P., van den Bos, C., & de Sonneville, L. M. J. (2012) · BMC Neurology · doi:10.1186/1471-2377-12-84 · Cited by 32
Roesmann, K., Terrighena, E. L., Chan, C. C. H., Junghoefer, M., & Lee, T. M. C. (2018) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2018.00412 · Cited by 32
González-Hernández, J. A., Cedeño, I., Pita-Alcorta, C., Galán, L., Aubert, E., & Figueredo-Rodríguez, P. (2003) · International Journal of Psychophysiology · doi:10.1016/s0167-8760(03)00019-9 · Cited by 32
Boxum, M., Voetterl, H., van Dijk, H., Gordon, E., DeBeus, R. J., Arnold, L. E., & Arns, M. (2024) · Applied Psychophysiology and Biofeedback · doi:10.1007/s10484-024-09649-y · Cited by 31
The Influence of Exercise on Cognitive Performance in Normobaric Hypoxia
Seo, Y., Burns, K. J., Fennell, C., Kim, J., Gunstad, J., Glickman, E. L., & McDaniel, J. (2015) · High Altitude Medicine & Biology · doi:10.1089/ham.2015.0027 · Cited by 31
A practical review of electroencephalography’s value to consumer research
McInnes, A. N., Sung, B., & Hooshmand, R. (2022) · International Journal of Market Research · doi:10.1177/14707853221112622 · Cited by 37
Kamarajan, C., Pandey, A. K., Chorlian, D. B., Manz, N., Stimus, A. T., Anokhin, A. P., Bauer, L. O., Kuperman, S., Kramer, J., Bucholz, K. K., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0142659 · Cited by 34
Macroscopic entrainment of periodically forced oscillatory ensembles
Popovych, O. V., & Tass, P. A. (2010) · Progress in Biophysics and Molecular Biology · doi:10.1016/j.pbiomolbio.2010.09.018 · Cited by 30
Detecting and comparing brain activity in short program comprehension using EEG
Yeh, M. K. ‐., Gopstein, D., Yu, Y., & Zhuang, Y. (2017) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie.2017.8190486 · Cited by 30
Smit, D. J. A., Andreassen, O. A., Boomsma, D. I., Burwell, S. J., Chorlian, D. B., de Geus, E. J. C., Elvsåshagen, T., Gordon, R. L., Harper, J., Hegerl, U., et al. (2021) · Brain and Behavior · doi:10.1002/brb3.2188 · Cited by 34
Design spaces and EEG frequency band power in constrained and open design
Vieira, S. L. D. S., Benedek, M., Gero, J. S., Li, S., & Cascini, G. (2022) · International Journal of Design Creativity and Innovation · doi:10.1080/21650349.2022.2048697 · Cited by 30
Ricci, G., Crescenzio, F. D., Santhosh, S., Magosso, E., & Ursino, M. (2022) · Scientific Reports · doi:10.1038/s41598-022-14747-0 · Cited by 30
Clapp, W. C., Muthukumaraswamy, S. D., Hamm, J. P., Teyler, T. J., & Kirk, I. J. (2006) · Neuroscience Letters · doi:10.1016/j.neulet.2005.12.081 · Cited by 30
EEG-rhythm dynamics during a 2-back working memory task and performance
Tsoneva, T., Baldo, D., Lema, V., & Garcia‐Molina, G. (2011) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2011.6090952 · Cited by 30
Event-Related Oscillations in Alcoholism Research: A Review
Pandey, A. K., & Rangaswamy, M. (2012) · Journal of Addiction Research & Therapy · doi:10.4172/2155-6105.s7-001 · Cited by 31
Jhung, K., Cho, S., Jang, J.-H., Park, J. Y., Shin, D., Kim, K. R., Lee, E. M., Cho, K., & An, S. K. (2012) · Neuroscience Letters · doi:10.1016/j.neulet.2012.11.051 · Cited by 30
Alpha rhythm slowing in a modified thalamo-cortico-thalamic model related with Alzheimer’s disease
Li, X., Yang, X., & Sun, Z. (2020) · PLoS ONE · doi:10.1371/journal.pone.0229950 · Cited by 31
Hertrich, I., Kirsten, M., Tiemann, S., Beck, S., Wühle, A., Ackermann, H., & Rolke, B. (2015) · Brain and Language · doi:10.1016/j.bandl.2015.06.005 · Cited by 29
Age effects on EEG correlates of the Wisconsin Card Sorting Test
Dias, N. S., Ferreira, D., Reis, J. S., Jacinto, L., Fernandes, L., Pinho, F., Festa, J., Pereira, M., Afonso, N., Santos, N. C., et al. (2015) · Physiological Reports · doi:10.14814/phy2.12390 · Cited by 29
Vecchio, F., Pellicciari, M. C., Miraglia, F., Brignani, D., Miniussi, C., & Rossini, P. M. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.01.051 · Cited by 29
Knott, V., & Fisher, D. J. (2007) · Experimental and Clinical Psychopharmacology · doi:10.1037/1064-1297.15.4.368 · Cited by 29
Vecchio, F., Percio, C. D., Marzano, N., Fiore, A., Toràn, G., Aschieri, P., Gallamini, M., Cabras, J., Rossini, P. M., Babiloni, C., et al. (2008) · Behavioral Neuroscience · doi:10.1037/0735-7044.122.4.917 · Cited by 29
EEG synchronization upon reward in man
Hallschmid, M. (2002) · Clinical Neurophysiology · doi:10.1016/s1388-2457(02)00142-6 · Cited by 29
Zentai, N., Csathó, Á., Trunk, A., Fiocchi, S., Parazzini, M., Ravazzani, P., Thuróczy, G., & Hernádi, I. (2015) · Radiation Research · doi:10.1667/rr13896.1 · Cited by 29
Weber, E., & Doppelmayr, M. M. (2016) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2016.11.002 · Cited by 29
Exercise-induced changes in EEG alpha power depend on frequency band definition mode
Gutmann, B., Hülsdünker, T., Mierau, J., Strüder, H. K., & Mierau, A. (2017) · Neuroscience Letters · doi:10.1016/j.neulet.2017.10.033 · Cited by 29
Analysis of the dynamical behaviour of the EEG rhythms during a test of sustained attention
Molteni, E., Bianchi, A. M., Butti, M., Reni, G., & Zucca, C. (2007) · Conference proceedings · doi:10.1109/iembs.2007.4352535 · Cited by 29
Mechanisms behind hazard perception of warning signs: An EEG study
Zhu, L., Ma, Q., Bai, X., & Hu, L. (2020) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2020.02.001 · Cited by 28
Müller, H., Baumeister, J., Bardal, E. M., Vereijken, B., & Skjæret-Maroni, N. (2023) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2023.1143859 · Cited by 28
Dynamics of Sensorimotor Oscillations in a Motor Task
Pfurtscheller, G., & Neuper, C. (2009) · The frontiers collection · doi:10.1007/978-3-642-02091-9_3 · Cited by 28
Naruse, Y., Matani, A., Miyawaki, Y., & Okada, M. (2009) · Human Brain Mapping · doi:10.1002/hbm.20899 · Cited by 28
The effect of temperamental traits on event-related potentials, heart rate and reaction time
Pascalis, V. D., Strelau, J., & Zawadzki, B. (1999) · Personality and Individual Differences · doi:10.1016/s0191-8869(98)00151-2 · Cited by 29
Diagnosing Autism Spectrum Disorders Based on EEG Analysis: a Survey
Hashemian, M., & Pourghassem, H. (2014) · Neurophysiology · doi:10.1007/s11062-014-9427-4 · Cited by 28
Rütsche, B., Hauser, T. U., Jäncke, L., & Grabner, R. H. (2015) · PLoS ONE · doi:10.1371/journal.pone.0120665 · Cited by 28
Survey on Physiological Computing in Human–Robot Collaboration
Savur, C., & Sahin, F. (2023) · Machines · doi:10.3390/machines11050536 · Cited by 27
Heib, D. P. J., Hoedlmoser, K., Anderer, P., Gruber, G., Zeitlhofer, J., & Schabus, M. (2015) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00804 · Cited by 34
Vecchio, F., Miraglia, F., Quaranta, D., Lacidogna, G., Marra, C., & Rossini, P. M. (2018) · Journal of Alzheimer s Disease · doi:10.3233/jad-180342 · Cited by 27
Functional brain connectivity during exposure to the scale and color of interior built environments
Bower, I. S., Hill, A. T., & Enticott, P. G. (2022) · Human Brain Mapping · doi:10.1002/hbm.26061 · Cited by 31
Cortical sources of resting-state EEG rhythms are abnormal in naïve HIV subjects
Babiloni, C., Vecchio, F., Buffo, P., Onorati, P., Muratori, C., Ferracuti, S., Roma, P., Battuello, M., Donato, N., Pellegrini, P. P. P., et al. (2012) · Clinical Neurophysiology · doi:10.1016/j.clinph.2012.06.002 · Cited by 27
Do You Know What I Mean? Brain Oscillations and the Understanding of Communicative Intentions
Brunetti, M., Zappasodi, F., Marzetti, L., Perrucci, M. G., Cirillo, S., Romani, G. L., Pizzella, V., & Aureli, T. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00036 · Cited by 28
STRUCTURAL ORGANIZATION OF FUNCTIONAL NETWORKS FROM EEG SIGNALS DURING MOTOR LEARNING TASKS
Fallani, F. D. V., Baluch, F., Astolfi, L., Subramanian, D., Zouridakis, G., & Babiloni, F. (2010) · International Journal of Bifurcation and Chaos · doi:10.1142/s0218127410026198 · Cited by 27
Shadows of music–language interaction on low frequency brain oscillatory patterns
Carrus, E., Koelsch, S., & Bhattacharya, J. (2011) · Brain and Language · doi:10.1016/j.bandl.2011.05.009 · Cited by 27
Altered task‐related modulation of long‐range connectivity in children with autism
Pillai, A. S., McAuliffe, D., Lakshmanan, B. M., Mostofsky, S. H., Crone, N. E., & Ewen, J. B. (2017) · Autism Research · doi:10.1002/aur.1858 · Cited by 27
Intelligence related differences in induced brain activity during the performance of memory tasks
Jaušovec, N., & Jaušovec, K. (2003) · Personality and Individual Differences · doi:10.1016/s0191-8869(03)00120-x · Cited by 27
Human alpha rhythms during visual delayed choice reaction time tasks: A magnetoencephalography study
Babiloni, C., Babiloni, F., Carducci, F., Cincotti, F., Percio, C. D., Penna, S. D., Franciotti, R., Pignotti, S., Pizzella, V., Rossini, P. M., et al. (2004) · Human Brain Mapping · doi:10.1002/hbm.20079 · Cited by 27
Synchrony and Complexity in State-Related EEG Networks: An Application of Spectral Graph Theory
Ghaderi, A. H., Baltaretu, B. R., Andevari, M. N., Bharmauria, V., & Balcı, F. (2020) · Neural Computation · doi:10.1162/neco_a_01327 · Cited by 28
Neural Oscillations in Aversively Motivated Behavior
Totty, M. S., & Maren, S. (2022) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2022.936036 · Cited by 28
Ajjimaporn, A., Noppongsakit, P., Ramyarangsi, P., Siripornpanich, V., & chaunchaiyakul, R. C. (2022) · Physiology & Behavior · doi:10.1016/j.physbeh.2022.113955 · Cited by 30
Nawaz, R., Wood, G. M. D. O., Nisar, H., & Yap, V. V. (2023) · Bioengineering · doi:10.3390/bioengineering10020200 · Cited by 26
Lim, C., Barragan, J. A., Farrow, J. M., Wachs, J. P., Sundaram, C. P., & Yu, D. (2023) · Sensors · doi:10.3390/s23094354 · Cited by 29
Electrophysiological CNS-processes related to associative learning in humans
Christoffersen, G. R. J., & Schachtman, T. R. (2015) · Behavioural Brain Research · doi:10.1016/j.bbr.2015.09.011 · Cited by 26
Sumich, A. L., Matsudaira, T., Gow, R. V., Ibrahimovic, A., Ghebremeskel, K., Crawford, M. A., & Taylor, E. (2009) · Neuropharmacology · doi:10.1016/j.neuropharm.2009.07.024 · Cited by 27
EEG frequency analysis of cortical brain activities induced by effect of light touch
Ishigaki, T., Ueta, K., Imai, R., & Morioka, S. (2016) · Experimental Brain Research · doi:10.1007/s00221-015-4545-9 · Cited by 26
Incorporating biometric data in models of consumer choice
Huseynov, S., Kassas, B., Segovia, M. S., & Palma, M. A. (2018) · Applied Economics · doi:10.1080/00036846.2018.1527460 · Cited by 27
Babiloni, C., Ferri, R., Noce, G., Lizio, R., Lopez, S., Soricelli, A., Nobili, F. M., Arnaldi, D., Famà, F., Orzi, F., et al. (2020) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2020.08.012 · Cited by 25
Oscillatory correlates of autobiographical memory
Knyazev, G. G., Savostyanov, A. N., Bocharov, A. V., Дорошева, Е. А., Tamozhnikov, S. S., & Сапрыгин, А. Е. (2014) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2014.12.006 · Cited by 28
Lee, T., Yu, Y. W. ‐., Hong, C., Tsai, S., Wu, H., & Chen, T. (2011) · Brain Research · doi:10.1016/j.brainres.2010.12.073 · Cited by 26
Weisz, N., & Schlittmeier, S. J. (2005) · Cerebral Cortex · doi:10.1093/cercor/bhj051 · Cited by 25
Prolongation of alpha oscillations in auditory oddball paradigm
Öniz, A., & Başar, E. (2008) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2008.10.003 · Cited by 25
Rod Driven Frequency Entrainment and Resonance Phenomena
Salchow-Hömmen, C., Strohmeier, D., Klee, S., Jannek, D., Schiecke, K., Witte, H., Nehorai, A., & Haueisen, J. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00413 · Cited by 25
Egsgaard, L. L., Wang, L., & Arendt‐Nielsen, L. (2008) · Experimental Brain Research · doi:10.1007/s00221-008-1632-1 · Cited by 25
John, A. R., Singh, A. K., Do, T., Eidels, A., Nalivaiko, E., Gavgani, A. M., Brown, S. D., Bennett, M. S., Lal, S., Simpson, A. M., et al. (2022) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2022.3157446 · Cited by 24
da Silva, A. L. C. D. L., Costa, A. P. C. S., & de Almeida, A. T. (2022) · International Transactions in Operational Research · doi:10.1111/itor.13210 · Cited by 24
A Framework to Support Automated Classification and Labeling of Brain Electromagnetic Patterns
Frishkoff, G. A., Frank, R. M., Rong, J., Dou, D., Dien, J., & Halderman, L. K. (2007) · Computational Intelligence and Neuroscience · doi:10.1155/2007/14567 · Cited by 24
Longitudinal study of EEG frequency maturation and power changes in children on the Russian North
Si, S., Shemyakina, N. V., Nagornova, Z. V., & Bekshaev, S. S. (2014) · International Journal of Developmental Neuroscience · doi:10.1016/j.ijdevneu.2014.08.012 · Cited by 24
Stability of Synchronous Solutions in a Directed Kuramoto-Oscillator Network With a Pacemaker
Rao, P., Li, X., & OGORZAŁEK, M. J. (2017) · IEEE Transactions on Circuits & Systems II Express Briefs · doi:10.1109/tcsii.2017.2679216 · Cited by 24
Serrien, D. J., Fisher, R. J., & Brown, P. (2003) · Experimental Brain Research · doi:10.1007/s00221-003-1578-2 · Cited by 24
Capotosto, P., Perrucci, M. G., Brunetti, M., Gratta, C. D., Doppelmayr, M. M., Grabner, R. H., Klimesch, W., Neubauer, A. C., Neuper, C., & Pfurtscheller, G. (2009) · Behavioural Brain Research · doi:10.1016/j.bbr.2009.07.032 · Cited by 23
Self-citationRole of the occipito-temporal theta rhythm in hand visual identification
Moreau, Q., Parrotta, E., Era, V., Martelli, M., & Candidi, M. (2019) · Journal of Neurophysiology · doi:10.1152/jn.00267.2019 · Cited by 23
The effects of brand familiarity and product category in brand extension: An ERP study
Ma, Q., Wang, M., & Qian, D. (2020) · Neuroscience Research · doi:10.1016/j.neures.2020.06.010 · Cited by 23
The Semantic Object Retrieval Test (SORT) in Normal Aging and Alzheimer Disease
Kraut, M. A., Cherry, B. J., Pitcock, J. A., Vestal, L., Henderson, V. W., & Hart, J. (2006) · Cognitive and Behavioral Neurology · doi:10.1097/01.wnn.0000213922.41008.22 · Cited by 23
Dimpfel, W., Schombert, L., & Biller, A. (2016) · Advances in Alzheimer s Disease · doi:10.4236/aad.2016.51001 · Cited by 23
Vecchio, F., Miraglia, F., Alù, F., Judica, E., Cotelli, M., Pellicciari, M. C., & Rossini, P. M. (2021) · Brain Connectivity · doi:10.1089/brain.2020.0824 · Cited by 23
Kolev, V., Rosso, O. A., & Yordanova, J. (2001) · Neuroreport · doi:10.1097/00001756-200109170-00008 · Cited by 23
EEG foundation models: a critical review of current progress and future directions
Kuruppu, G., Wagh, N., Křemen, V., & Varatharajah, Y. (2026) · Journal of Neural Engineering · doi:10.1088/1741-2552/ae4455 · Cited by 44
Default Mode Network and Neural Phase Synchronization in Healthy Aging: A Resting State EEG Study
Chow, R., Rabi, R., Paracha, S., Hasher, L., Anderson, N. D., & Alain, C. (2022) · Neuroscience · doi:10.1016/j.neuroscience.2022.01.008 · Cited by 23
Delay modulates spectral correlates in the human EEG of non-verbal auditory working memory
Peterson, D. A., & Thaut, M. H. (2002) · Neuroscience Letters · doi:10.1016/s0304-3940(02)00429-9 · Cited by 22
Zinn, M. L., Zinn, M. A., & Jason, L. A. (2016) · Applied Psychophysiology and Biofeedback · doi:10.1007/s10484-016-9331-3 · Cited by 22
Braun, V., Sokoliuk, R., & Hanslmayr, S. (2017) · Brain stimulation · doi:10.1016/j.brs.2017.04.129 · Cited by 22
Varga, N. L., & Manns, J. R. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118600 · Cited by 23
Marks, V. S., Saboo, K., Topçu, Ç., Lech, M., Thayib, T. P., Nejedlý, P., Křemen, V., Worrell, G. A., & Kucewicz, M. T. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118637 · Cited by 22
Pre-stimulus alpha power affects vertex N2–P2 potentials evoked by noxious stimuli
Babiloni, C., Percio, C. D., Brancucci, A., Capotosto, P., Pera, D. L., Marzano, N., Valeriani, M., Romani, G. L., Arendt‐Nielsen, L., & Rossini, P. M. (2007) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2007.09.009 · Cited by 22
Magnetic stimulation selectively affects pre-stimulus EEG microstates
Croce, P., Zappasodi, F., Spadone, S., & Capotosto, P. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.04.061 · Cited by 22
Altered states of consciousness: Processed EEG in mental disease
Spiegel, A., Tonner, P. H., & Renna, M. (2006) · Best practice & research. Clinical anaesthesiology · doi:10.1016/j.bpa.2005.07.010 · Cited by 22
Decoding the neural signatures of valence and arousal from portable EEG headset
Garg, N., Garg, R., Anand, A. J., & Baths, V. (2022) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2022.1051463 · Cited by 21
Babiloni, C., Buffo, P., Vecchio, F., Onorati, P., Muratori, C., Ferracuti, S., Roma, P., Battuello, M., Donato, N., Noce, G., et al. (2014) · Clinical Neurophysiology · doi:10.1016/j.clinph.2014.01.024 · Cited by 21
Aurtenetxe, S., Castellanos, N. P., Moratti, S., Bajo, R., Gil, P., Beitia, G., del Pozo, F., & Maestú, F. (2012) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2012.11.008 · Cited by 22
Shafiei, S. B., Elsayed, A. S., Hussein, A. A., Iqbal, U. H., & Guru, K. A. (2020) · IEEE Access · doi:10.1109/access.2020.3036751 · Cited by 21
Vecchio, F., Nucci, L., Pappalettera, C., Miraglia, F., Iacoviello, D., & Rossini, P. M. (2022) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac9c96 · Cited by 21
Predictive coding in visual search as revealed by cross-frequency EEG phase synchronization
Sauseng, P., Conci, M., Wild, B., & Geyer, T. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.01655 · Cited by 21
Heritability and “environmentability” of electroencephalogram in infants: The twin study
Orekhova, E. V., Stroganova, T. A., Posikera, I. N., & Malykh, S. B. (2003) · Psychophysiology · doi:10.1111/1469-8986.00073 · Cited by 21
New advances in EEG and cognition
Gruzelier, J. H. (1996) · International Journal of Psychophysiology · doi:10.1016/s0167-8760(96)00069-4 · Cited by 21
Babiloni, C., Lopez, S., Noce, G., Ferri, R., Panerai, S., Catania, V., Soricelli, A., Salvatore, M., Nobili, F. M., Arnaldi, D., et al. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad300 · Cited by 20
Wiggert, N., Wilhelm, F. H., Boger, S., Georgii, C., Klimesch, W., & Blechert, J. (2016) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsw128 · Cited by 21
Self-citationCrk, I., & Kluthe, T. (2016) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2016.7591752 · Cited by 20
Sailamul, P., Jang, J., & Paik, S. (2017) · Journal of Computational Neuroscience · doi:10.1007/s10827-017-0657-5 · Cited by 20
Synchronizing and Desynchronizing Neural Populations through Phase Distribution Control
Monga, B., Froyland, G., & Moehlis, J. (2018) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.23919/acc.2018.8431114 · Cited by 20
Alcohol-induced alterations in ERD/ERS during an auditory memory task
Krause, C. M., Aromäki, A. S., Sillanmäki, L. H., Åström, T., Alanko, K., Salonen, E., & Peltola, O. (2002) · Alcohol · doi:10.1016/s0741-8329(01)00204-x · Cited by 20
Bonfiglio, L., Sello, S., Carboncini, M. C., Arrighi, P., André, P., & Rossi, B. (2011) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2011.01.002 · Cited by 20
Brain Oscillatory Correlates of Visual Short-Term Memory Errors
Mapelli, I., & Özkurt, T. E. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2019.00033 · Cited by 20
Metadata
- Authors
- Klimesch, W.
- Affiliations
- University of Salzburg (AT)
- Corresponding author
- Klimesch, Wolfgang
- ORCID
- Klimesch, Wolfgang
- Venue
- International Journal of Psychophysiology
- Publisher
- Elsevier BV
- Published
- 1996-11
- Volume
- 24
- Issue
- 1-2
- Pages
- 61-100
- ISSN
- 0167-8760 (ISSN-L)
- OpenAlex
- W2051134452
- Cited by
- 923
- References
- 154
- Citations by year
- 2026: 15 · 2025: 24 · 2024: 18 · 2023: 33 · 2022: 37 · 2021: 41 · 2020: 50 · 2019: 36 · 2018: 27 · 2017: 56 · 2016: 37 · 2015: 38 · 2014: 48 · 2013: 27 · 2012: 44
- FWCI
- 9.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Psychophysiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Keywords
- memory processes, neural oscillations, EEG synchronization, episodic memory, semantic memory, theta band, alpha band, resting state, functional inhibition, memory models, memory encoding and retrieval
- MeSH terms
- Alpha Rhythm, Attention, Brain, Cerebral Cortex, Cortical Synchronization, Electroencephalography, Evoked Potentials, Hippocampus, Humans, Memory, Models, Neurological, Psychomotor Performance, Semantics, Thalamus, Theta Rhythm, Visual Perception
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review