Berger, H., Über das Elektrenkephalogramm des Menschen (1929) Archiv Für Psychiatrie und Nervenkrankheiten, 87 (1), pp. 527-570
Loomis, A.L., Harvey, E.N., Hobart, G., Further observations on the potential rhythms of the cerebral cortex during sleep (1935) Science, 82 (2122), pp. 198-200
Morison, R.S., Bassett, D.L., Electrical activity of the thalamus and basal ganglia in decorticate cats (1945) Journal of Neurophysiology, 8 (5), pp. 309-314
Steriade, M., Thalamic origin of sleep spindles: Morison and Bassett (1945) (1995) Journal of Neurophysiology, 73 (3), pp. 921-922
Steriade, M., Nuñez, A., Amzica, F., Intracellular analysis of relations between the slow (?1 Hz) neocortical oscillation and other sleep rhythms of the electroencephalogram (1993) Journal of Neuroscience, 13 (8), pp. 3266-3283
Contreras, D., Destexhe, A., Steriade, M., Intracellular and computational characterization of the intracortical inhibitory control of synchronized thalamic inputs in vivo (1997) Journal of Neurophysiology, 78 (1), pp. 335-350
Destexhe, A., McCormick, D.A., Sejnowski, T.J., A model for 8-10 Hz spindling in interconnected thalamic relay and reticularis neurons (1993) Biophysical Journal, 65 (6), pp. 2473-2477
Destexhe, A., Contreras, D., Sejnowski, T.J., Steriade, M., A model of spindle rhythmicity in the isolated thalamic reticular nucleus (1994) Journal of Neurophysiology, 72 (2), pp. 803-818
McCormick, D.A., Bal, T., Sleep and arousal: Thalamocortical mechanisms (1997) Annual Review of Neuroscience, 20, pp. 185-215
Timofeev, I., Bazhenov, M., Mechanisms and biological role of thalamocortical oscillations (2005) Trends in Chronobiology Research, pp. 1-47. , F. Columbus, Ed. Nova Science
Timofeev, I., Bazhenov, M., Seigneur, J., Sejnowski, T., Neuronal synchronization and thalamocortical rhythms in sleep, wake and epilepsy (2012) Jasper's Basic Mechanisms of Epilepsies, , J. L. Noebels, M. Avoli, M. A. Rogawski, R. W. Olsen, and A. V. Delgado-Escueta, Eds., 4th edition
Beenhakker, M.P., Huguenard, J.R., Neurons that fire together also conspire together: Is normal sleep circuitry hijacked to generate epilepsy? (2009) Neuron, 62 (5), pp. 612-632
Lüthi, A., Sleep spindles: Where they come from, what they do (2014) Neuroscientist, 20 (3), pp. 243-256
Mölle, M., Born, J., Slow oscillations orchestrating fast oscillations and memory consolidation (2011) Progress in Brain Research, 193, pp. 93-110
Rasch, B., Born, J., About sleep's role in memory (2013) Physiological Reviews, 93 (2), pp. 681-766
Nicolas, A., Petit, D., Rompré, S., Montplaisir, J., Sleep spindle characteristics in healthy subjects of different age groups (2001) Clinical Neurophysiology, 112 (3), pp. 521-527
Martin, N., Lafortune, M., Godbout, J., Topography of agerelated changes insleep spindles (2013) Neurobiology of Aging, 34 (2), pp. 468-476
Astori, S., Wimmer, R.D., Lüthi, A., Manipulating sleep spindles-expanding views on sleep, memory, and disease (2013) Trends in Neurosciences, 36 (12), pp. 738-748
Werth, E., Achermann, P., Dijk, D.-J., Borbély, A.A., Spindle frequency activity in the sleep EEG: Individual differences and topographical distribution (1997) Electroencephalography and Clinical Neurophysiology, 103 (5), pp. 535-542
Hori, A., Kazukawa, S., Endo, M., Kurachi, M., Sleep spindles in twins (1989) Clinical EEGElectroencephalography, 20 (2), pp. 121-127
Steriade, M., Grouping of brain rhythms in corticothalamic systems (2006) Neuroscience, 137 (4), pp. 1087-1106
Sejnowski, T.J., Destexhe, A., Why do we sleep? (2000) Brain Research, 886 (1-2), pp. 208-223
Jones, E.G., The thalamic matrix and thalamocortical synchrony (2001) Trends in Neurosciences, 24 (10), pp. 595-601
Diekelmann, S., Born, J., The memory function of sleep (2010) Nature Reviews Neuroscience, 11 (2), pp. 114-126
Warby, S.C., Wendt, S.L., Welinder, P., Sleep-spindle detection: Crowdsourcing and evaluating performance of experts, non-experts and automated methods (2014) Nature Methods, 11 (4), pp. 385-392
Rechtschaffen, A., Kales, A., (1968) Brain Information Service, and Brain Research Institute UoC, , Eds., A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects, US Government Printing Office, US Public Health Service
Iber, C., Ancoli-Israel, S., Chesson, A., Quan, S., (2007) The AASMManual for the Scoring of Sleep
Terminology Associated Events: Rules
IL:
2007 Technical Specifications. Westchester. The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications, , American Academy of Sleep Medicine
De Gennaro, L., Marzano, C., Fratello, F., The electroencephalographic fingerprint of sleep is genetically determined: A twin study (2008) Annals of Neurology, 64 (4), pp. 455-460
Andrillon, T., Nir, Y., Staba, R.J., Sleep spindles in humans: Insights fromintracranialEEGand unit recordings (2011) TheJournal of Neuroscience, 31 (49), pp. 17821-17834
Mölle, M., Bergmann, T.O., Marshall, L., Born, J., Fast and slow spindles during the sleep slow oscillation: Disparate coalescence and engagement inmemory processing (2011) Sleep, 34 (10), pp. 1411-1421
Nader, R.S., Smith, C.T., Correlations between adolescent processing speed and specific spindle frequencies (2015) Frontiers in Human Neuroscience, 9
De Gennaro, L., Ferrara, M., Sleep spindles: An overview (2003) Sleep Medicine Reviews, 7 (5), pp. 423-440
Schabus, M., Dang-Vu, T.T., Albouy, G., Hemodynamic cerebral correlates of sleep spindles during human non-rapid eye movement sleep (2007) Proceedings of the National Academy of Sciences of the United States of America, 104 (32), pp. 13164-13169
Ayoub, A., Aumann, D., Hörschelmann, A., Differential effects on fast and slow spindle activity, and the sleep slow oscillation in humans with carbamazepine and flunarizine to antagonize voltage-dependent Na+ and Ca2+ channel activity (2013) SLEEP, 36 (6), pp. 905-911
Schönwald, S.V., Carvalho, D.Z., De Santa-Helena, E.L., Lemke, N., Gerhardt, G.J.L., Topography-specific spindle frequency changes in obstructive sleep apnea (2012) BMC Neuroscience, 13
Dehghani, N., Cash, S.S., Halgren, E., Topographical frequency dynamics within EEG and MEG sleep spindles (2011) Clinical Neurophysiology, 122 (2), pp. 229-235
Zerouali, Y., Lina, J.-M., Sekerovic, Z., A time-frequency analysis of the dynamics of cortical networks of sleep spindles from MEG-EEG recordings (2014) Frontiers in Neuroscience, 8
Nir, Y., Staba, R.J., Andrillon, T., Regional slow waves and spindles in human sleep (2011) Neuron, 70 (1), pp. 153-169
Zygierewicz, J., Blinowska, K.J., Durka, P.J., Szelenberger, W., Niemcewicz, S., Androsiuk, W., High resolution study of sleep spindles (1999) Clinical Neurophysiology, 110 (12), pp. 2136-2147
Barthó, P., Slézia, A., Mátyás, F., Ongoing network state controls the length of sleep spindles via inhibitory activity (2014) Neuron, 82 (6), pp. 1367-1379
Bonjean, M., Baker, T., Lemieux, M., Timofeev, I., Sejnowski, T., Bazhenov, M., Corticothalamic feedback controls sleep spindle duration in vivo (2011) The Journal of Neuroscience, 31 (25), pp. 9124-9134
Kubicki, S., Meyer, C., Rohmel, J., The 4 second sleep spindle periodicity (1986) EEG EMG Z Elektroenzephalogr Elektromyogr Verwandte Geb, 17 (2), pp. 55-61
Contreras, D., Destexhe, A., Sejnowski, T.J., Steriade, M., Spatiotemporal patterns of spindle oscillations in cortex and thalamus (1997) Journal of Neuroscience, 17 (3), pp. 1179-1196
Ktonas, P.Y., Paparrigopoulos, T., Monoyiou, E.A., Bergiannaki, J.D., Soldatos, C.R., Sleep spindle incidence dynamics: A pilot study based on a Markovian analysis (2000) Sleep, 23 (3), pp. 419-423
Bonjean, M., Baker, T., Bazhenov, M., Cash, S., Halgren, E., Sejnowski, T., Interactions between core and matrix thalamocortical projections in human sleep spindle synchronization (2012) Journal of Neuroscience, 32 (15), pp. 5250-5263
Kopell, N., Ermentrout, G.B., Whittington, M.A., Traub, R.D., Gamma rhythms and beta rhythms have different synchronization properties (2000) Proceedings of TheNationalAcademy of Sciences of the United States of America, 97 (4), pp. 1867-1872
Rosanova, M., Casali, A., Bellina, V., Resta, F., Mariotti, M., Massimini, M., Natural frequencies of human corticothalamic circuits (2009) Journal of Neuroscience, 29 (24), pp. 7679-7685
Anderer, P., Klösch, G., Gruber, G., Low-resolution brain electromagnetic tomography revealed simultaneously active frontal and parietal sleep spindle sources in the human cortex (2001) Neuroscience, 103 (3), pp. 581-592
Manshanden, I., De Munck, J.C., Simon, N.R., Lopes da Silva, F.H., Source localization of MEG sleep spindles and the relation to sources of alpha band rhythms (2002) Clinical Neurophysiology, 113 (12), pp. 1937-1947
Urakami, Y., Relationships between sleep spindles and activities of cerebral cortex as determined by simultaneous EEG and MEGrecording (2008) Journal of ClinicalNeurophysiology, 25 (1), pp. 13-24
Dehghani, N., Cash, S.S., Rossetti, A.O., Chen, C.C., Halgren, E., Magnetoencephalography demonstrates multiple asynchronous generators during human sleep spindles (2010) Journal of Neurophysiology, 104 (1), pp. 179-188
Dehghani, N., Cash, S.S., Chen, C.C., Divergent cortical generators of MEG and EEG during human sleep spindles suggested by distributed source modeling (2010) PLoS ONE, 5 (7)
Jones, E.G., Viewpoint: The core and matrix of thalamic organization (1998) Neuroscience, 85 (2), pp. 331-345
Jones, E.G., Thalamic circuitry and thalamocortical synchrony (2002) Philosophical Transactions of the Royal Society B: Biological Sciences, 357 (1428), pp. 1659-1673
Srinivasan, R., Nunez, P.L., Tucker, D.M., Silberstein, R.B., Cadusch, P.J., Spatial sampling and filtering of EEG with spline laplacians to estimate cortical potentials (1996) Brain Topography, 8 (4), pp. 355-366
Burle, B., Spieser, L., Roger, C., Casini, L., Hasbroucq, T., Vidal, F., Spatial and temporal resolutions of EEG: Is it really black and white A scalp current density view (2015) International Journal of Psychophysiology, 97 (3), pp. 210-220
Cox, R., Hofman, W.F., De Boer, M., Talamini, L.M., Local sleep spindle modulations in relation to specific memory cues (2014) NeuroImage, 99, pp. 103-110
Vyazovskiy, V.V., Riedner, B.A., Cirelli, C., Tononi, G., Sleep homeostasis and cortical synchronization: II. Alocal field potential study of sleep slowwaves in the rat (2007) Sleep, 30 (12), pp. 1631-1642
Crunelli, V., Errington, A.C., Hughes, S.W., Tóth, T.I., The thalamic low-threshold Ca2+ potential: A key determinant of the local and global dynamics of the slow (<1 Hz) sleep oscillation in thalamocortical networks (2011) Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 369 (1952), pp. 3820-3839
Staresina, B.P., Bergmann, T.O., Bonnefond, M., Hierarchical nesting of slow oscillations, spindles and ripples in the human hippocampus during sleep (2015) Nature Neuroscience, 18 (11), pp. 1679-1686
Buzsàki, G., Czopf, J., Kondàkor, I., Björklund, A., Gage, F.H., Cellular activity of intracerebrally transplanted fetal hippocampus during behavior (1987) Neuroscience, 22 (3), pp. 871-883
Mölle, M., Marshall, L., Gais, S., Born, J., Grouping of spindle activity during slow oscillations in human non-rapid eye movement sleep (2002) The Journal of Neuroscience, 22 (24), pp. 10941-10947
Clemens, Z., Mölle, M., Eross, L., Fine-tuned coupling between human parahippocampal ripples and sleep spindles (2011) European Journal of Neuroscience, 33 (3), pp. 511-520
Sullivan, D., Mizuseki, K., Sorgi, A., Buzsáki, G., Comparison of sleep spindles and theta oscillations in the hippocampus (2014) The Journal of Neuroscience, 34 (2), pp. 662-674
Massimini, M., Huber, R., Ferrarelli, F., Hill, S., Tononi, G., The sleep slow oscillation as a traveling wave (2004) The Journal of Neuroscience, 24 (31), pp. 6862-6870
Dijk, D.-J., Hayes, B., Czeisler, C.A., Dynamics of electroencephalographic sleep spindles and slow wave activity in men: Effect of sleep deprivation (1993) Brain Research, 626 (1-2), pp. 190-199
Himanen, S.-L., Virkkala, J., Huhtala, H., Hasan, J., Spindle frequencies in sleep EEG show U-shape within first four NREM sleep episodes (2002) Journal of Sleep Research, 11 (1), pp. 35-42
Malow, B.A., Carney, P.R., Kushwaha, R., Bowes, R.J., Hippocampal sleep spindles revisited: Physiologic or epileptic activity? (1999) Clinical Neurophysiology, 110 (4), pp. 687-693
Nakabayashi, T., Uchida, S., Maehara, T., Absence of sleep spindles in humanmedial and basal temporal lobes (2001) Psychiatry and Clinical Neurosciences, 55 (1), pp. 57-65
Dang-Vu, T.T., Schabus, M., Desseilles, M., Sterpenich, V., Bonjean, M., Maquet, P., Functional neuroimaging insights into the physiology of human sleep (2010) Sleep, 33 (12), pp. 1589-1603
Dang-Vu, T.T., Neuronal oscillations in sleep: Insights from functional neuroimaging (2012) NeuroMolecular Medicine, 14 (3), pp. 154-167
Gumenyuk, V., Roth, T., Moran, J.E., Cortical locations of maximal spindle activity: Magnetoencephalography (MEG) study (2009) Journal of Sleep Research, 18 (2), pp. 245-253
Duman, F., Erdamar, A., Erogul, O., Telatar, Z., Yetkin, S., Efficient sleep spindle detection algorithm with decision tree (2009) Expert Systems with Applications, 36 (6), pp. 9980-9985
Daubechies, I., Lu, J., Wu, H.-T., Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool (2011) Applied and Computational Harmonic Analysis, 30 (2), pp. 243-261
Jmail, N., Gavaret, M., Wendling, F., A comparison of methods for separation of transient and oscillatory signals in EEG (2011) Journal of Neuroscience Methods, 199 (2), pp. 273-289
Parekh, A., Selesnick, I.W., Rapoport, D.M., Ayappa, I., Sleep spindle detection using time-frequency sparsity (2014) Proceedings of the IEEE Signal Processing InMedicine and Biology Symposium (SPMB '14), pp. 1-6. , IEEE, Philadelphia, Pa, USA, December
Wamsley, E.J., Tucker, M.A., Shinn, A.K., Reduced sleep spindles and spindle coherence in schizophrenia: Mechanisms of impaired memory consolidation? (2012) Biological Psychiatry, 71 (2), pp. 154-161
Wendt, S.L., Christensen, J.A., Kempfner, J., Leonthin, H.L., Jennum, P., Sorensen, H.B., Validation of a novel automatic sleep spindle detector with high performance during sleep in middle aged subjects (2012) Proceedings of TheAnnual International Conference of the IEEE Engineering InMedicine and Biology Society, pp. 4250-4253. , San Diego, Calif, USA, August-September
Bódizs, R., Körmendi, J., Rigó, P., Lázár, A.S., The individual adjustment method of sleep spindle analysis: Methodological improvements and roots in the fingerprint paradigm (2009) Journal of Neuroscience Methods, 178 (1), pp. 205-213
Gais, S., Mölle, M., Helms, K., Born, J., Learning-dependent increases in sleep spindle density (2002) Journal of Neuroscience, 22 (15), pp. 6830-6834
Huupponen, E., Värri, A., Himanen, S.-L., Hasan, J., Lehtokangas, M., Saarinen, J., Optimization of sigma amplitude threshold in sleep spindle detection (2000) Journal of Sleep Research, 9 (4), pp. 327-334
Devuyst, S., Dutoit, T., Didier, J.F., Automatic sleep spindle detection in patients with sleep disorders (2006) Proceedings of the 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS '06), pp. 3883-3886. , New York, NY, USA, September
Nonclercq, A., Urbain, C., Verheulpen, D., Decaestecker, C., Van Bogaert, P., Peigneux, P., Sleep spindle detection through amplitude-frequency normal modelling (2013) Journal of Neuroscience Methods, 214 (2), pp. 192-203
Kabir, M.M., Tafreshi, R., Boivin, D.B., Haddad, N., Enhanced automated sleep spindle detection algorithm based on synchrosqueezing (2015) Medical and Biological Engineering and Computing, 53 (7), pp. 635-644
Clemens, Z., Fabó, D., Halász, P., Overnight verbal memory retention correlates with the number of sleep spindles (2005) Neuroscience, 132 (2), pp. 529-535
Ray, L.B., Fogel, S.M., Smith, C.T., Peters, K.R., Validating an automated sleep spindle detection algorithm using an individualized approach (2010) Journal of Sleep Research, 19 (2), pp. 374-378
Coppieters, D., Muto, V., Gaggioni, G., Automatic artifacts and arousals detection in whole-night sleep EEG recordings (2016) Journal of Neuroscience Methods, 258, pp. 124-133
João, C., Manuel, O., Arnaldo, B., Teresa, P., An automatic sleep spindle detector based on WT, STFT and WMSD (2012) Proceedings of World Academy of Science, Engineering and Technology (2070-3740), 68, pp. 2154-2157
Schimicek, P., Zeitlhofer, J., Anderer, P., Saletu, B., Automatic sleep-spindle detection procedure: Aspects of reliability and validity (1994) Clinical EEG Electroencephalography, 25 (1), pp. 26-29
Held, C.M., Causa, L., Estévez, P., Dual approach for automated sleep spindles detection within EEG background activity in infant polysomnograms (2004) Proceedings of the 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC '04), 1, pp. 566-569. , San Francisco, Calif, USA, September
Ventouras, E.M., Monoyiou, E.A., Ktonas, P.Y., Sleep spindle detection using artificial neural networks trained with filtered time-domain EEG: A feasibility study (2005) Computer Methods and Programs in Biomedicine, 78 (3), pp. 191-207
Ferrarelli, F., Huber, R., Peterson, M.J., Reduced sleep spindle activity in schizophrenia patients (2007) American Journal of Psychiatry, 164 (3), pp. 483-492
Bódizs, R., Kis, T., Lázár, A.S., Prediction of generalmental ability based on neural oscillation measures of sleep (2005) Journal of Sleep Research, 14 (3), pp. 285-292
Ahmed, B., Redissi, A., Tafreshi, R., An automatic sleep spindle detector based on wavelets and the teager energy operator (2009) Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 2596-2599. , IEEE, Minneapolis, Minn, USA, September
Mallat, S.G., A theory for multiresolution signal decomposition: The wavelet representation (1989) IEEE Transactions on Pattern Analysis and Machine Intelligence, 11 (7), pp. 674-693
Kaiser, J.F., Some useful properties of Teager's energy operators (1993) Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '93), 3, pp. 149-152. , IEEE Computer Society, Minneapolis, Minn, USA, April
Huupponen, E., AdnHasan, V.J.A., Himanen, S.L., Lehtokangas, M., Saarinen, J., Fuzzy reasoning based sleep spindle detection (1999) Proceedings of the 1999 Finnish Signal Processing Symposium, pp. 94-97. , H. Saarnisaari and M. Juntti, Eds
Huupponen, E., Gómez-Herrero, G., Saastamoinen, A., Värri, A., Hasan, J., Himanen, S.-L., Development and comparison of four sleep spindle detection methods (2007) Artificial Intelligence in Medicine, 40 (3), pp. 157-170
Estévez, P.A., Zilleruelo-Ramos, R., Hernández, R., Causa, L., Held, C.M., Sleep spindle detection by using merge neural gas (2007) Proceedings of the 6th International Workshop on Self-Organizing Maps (WSOM '07), , Bielefeld University, January
Mporas, I., Korvesis, P., Zacharaki, E., Megalooikonomou, V., Sleep spindle detection in EEG signals combining HMMs and SVMs (2013) Engineering Applications of Neural Networks, 384, pp. 138-145. , L. Iliadis, H. Papadopoulos, and C. Jayne, Eds. of Communications in Computer and Information Science Springer, Berlin, Germany
Görür, D., Halici, U., Aydin, H., Ongun, G., Ozgen, F., Leblebicioglu, K., Sleep spindles detection using short time Fourier transform and neural networks (2002) Proceedings of the International Joint Conference on Neural Networks (IJCNN '02), 2, pp. 1631-1636. , IEEE, Honolulu, Hawaii, USA, May
Schönwald, S.V., De Santa-Helena, E.L., Rossatto, R., Chaves, M.L.F., Gerhardt, G.J.L., Benchmarking matching pursuit to find sleep spindles (2006) Journal of NeuroscienceMethods, 156 (1-2), pp. 314-321
Durka, P.J., Malinowska, U., Zieleniewska, M., O'Reilly, C., Rózánski, P.T., Zygierewicz, J., Spindles in Svarog: Framework and software for parametrization of EEG transients (2015) Frontiers in Human Neuroscience, 9
Ray, L.B., Sockeel, S., Soon, M., Expert and crowdsourced validation of an individualized sleep spindle detection method employing complex demodulation and individualized normalization (2015) Frontiers in Human Neuroscience, 9
Causa, L., Held, C.M., Causa, J., Automated sleepspindle detection in healthy children polysomnograms (2010) IEEE Transactions on Biomedical Engineering, 57 (9), pp. 2135-2146
Durka, P., (2007) Matching Pursuit and Unification in EEG Analysis, , Artech House, Boston, Mass, USA
Brockmeier, A.J., Principe, J.C., Learning recurrent waveforms within EEGs (2016) IEEE Transactions on Biomedical Engineering, 63 (1), pp. 43-54
Liang, H., Bressler, S.L., Desimone, R., Fries, P., Empirical mode decomposition: A method for analyzing neural data (2005) Neurocomputing, 65-66, pp. 801-807
Huang, N.E., Shen, Z., Long, S.R., The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis (1998) Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 454 (1971), pp. 903-995
Dragomiretskiy, K., Zosso, D., Variational mode decomposition (2014) IEEE Transactions on Signal Processing, 62 (3), pp. 531-544
Huang, N.E., Wu, Z., A review onHilbert-Huang transform: Method and its applications to geophysical studies (2008) Reviews of Geophysics, 46 (2)
Yoo, S.K., Kang, H.C., Amplitude and phase analysis of EEG signal by complex demodulation (2013) International Journal of Medical, Health, Biomedical, Bioengineering and Pharmaceutical Engineering, 7 (10), pp. 648-651
Draganova, R., Popivanov, D., Assessment of EEG frequency dynamics using complex demodulation (1999) Physiological Research, 48 (2), pp. 157-165
Huupponen, E., De Clercq, W., Gómez-Herrero, G., Determination of dominant simulated spindle frequency with different methods (2006) Journal of NeuroscienceMethods, 156 (1-2), pp. 275-283
Ktonas, P.Y., Golemati, S., Xanthopoulos, P., Timefrequency analysis methods to quantify the time-varying microstructure of sleep EEG spindles: Possibility for dementia biomarkers? (2009) Journal of Neuroscience Methods, 185 (1), pp. 133-142
Babadi, B., McKinney, S.M., Tarokh, V., Ellenbogen, J.M., DiBa: A data-driven Bayesian algorithm for sleep spindle detection (2012) IEEE Transactions on Bio-Medical Engineering, 59 (2), pp. 483-493
Görür, D., Halici, U., Aydin, H., Ongun, G., Ozgen, F., Leblebicioglu, K., Sleep spindles detection using autoregressive modeling (2003) Proceedings of the International Conference on Artificial Neural Networks (ICANN '03), pp. 26-29
Acir, N., GüzeliŞ, C., Automatic recognition of sleep spindles in EEG by using artificial neural networks (2004) Expert Systems with Applications, 27 (3), pp. 451-458
Achermann, P., Olbrich, E., Oscillatory events in the human sleep EEG-detection and properties (2004) Neurocomputing, 58-60, pp. 129-135
Olbrich, E., Achermann, P., Analysis of oscillatory patterns in the human sleep EEG using a novel detection algorithm (2005) Journal of Sleep Research, 14 (4), pp. 337-346
Stewart, S., Ivy, M.A., Anslyn, E.V., The use of principal component analysis and discriminant analysis in differential sensing routines (2014) Chemical Society Reviews, 43 (1), pp. 70-84
Da Costa, J.C., Ortigueira, M.D., Batista, A., ARMA modelling of sleep spindles (2011) Technological Innovation for Sustainability, 349, pp. 341-348. , L. M. Camarinha-Matos, Ed. of IFIP Advances in Information and Communication Technology Springer, Berlin, Germany
Caldas, D.C.J., Ortigueira, M., Batista, A., Paiva, T., ARMA modelling for sleep disorders diagnose (2013) Technological Innovation for the Internet of Things: 4th IFIP WG 5. 5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2013, 394, pp. 271-278. , Costa de Caparica, Portugal, April 15-17, 2013. Proceedings, L. Camarinha-Matos, S. Tomic, P. GraÇa, and T. Paiva, Eds. of IFIP Advances in Information and Communication Technology, Springer, Berlin, Germany
Müller, K.-R., Mika, S., Rätsch, G., Tsuda, K., Schölkopf, B., An introduction to kernel-based learning algorithms (2001) IEEE Transactions on Neural Networks, 12 (2), pp. 181-201
Ktonas, P.Y., Ventouras, E.-C., Automated detection of sleep spindles in the scalp EEG and estimation of their intracranial current sources: Comments on techniques and on related experimental and clinical studies (2014) Frontiers in Human Neuroscience, 8
Schabus, M., Dang-Vu, T.T., Heib, D.P.J., The fate of incoming stimuli duringNREMsleep is determined by spindles and the phase of the slowoscillation (2012) Frontiers InNeurology, 3. , Article ID Article 40
Dang-Vu, T.T., Salimi, A., Boucetta, S., Sleep spindles predict stress-related increases in sleep disturbances (2015) Frontiers in Human Neuroscience, 9, p. 68
Manoach, D.S., Pan, J.Q., Purcell, S.M., Stickgold, R., Reduced sleep spindles in schizophrenia: A treatable endophenotype that links risk genes to impaired cognition? (2015) Biological Psychiatry
Cajochen, C., Münch, M., Knoblauch, V., Blatter, K., Wirz-Justice, A., Age-related changes in the circadian and homeostatic regulation of human sleep (2006) Chronobiology International, 23 (1-2), pp. 461-474
O'Reilly, C., Nielsen, T., Automatic sleep spindle detection: Benchmarking with fine temporal resolution using open science tools (2015) Frontiers in Human Neuroscience, 9
Devuyst, S., Dutoit, T., Stenuit, P., Kerkhofs, M., Automatic sleep spindles detection-overview and development of a standard proposal assessment method (2011) Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 1713-1716. , Boston, Mass, USA, August-September
O'Reilly, C., Gosselin, N., Carrier, J., Nielsen, T., Montreal archive of sleep studies: An open-access resource for instrument benchmarking and exploratory research (2014) Journal of Sleep Research, 23 (6), pp. 628-635
Wilson, G., Aruliah, D.A., Brown, C.T., Best practices for scientific computing (2014) PLoS Biology, 12 (1), pp. 1-7
Owens, B., DATA SHARING. Montreal institute going 'open' to accelerate science (2016) Science, 351 (6271), p. 329