同一樣嘅腦電圖數據可以有好多種唔同方法呈現,而每一款呈現數據嘅方法叫做一個裝配(montage)。例如係最常用嘅連環式裝配(sequential montage)噉,會畫好多條線出嚟,每條線嘅 Y 軸代表咗某兩條電極之間嘅電壓差(例如「Fp1-F3」嗰條線嘅 Y 軸代表「Fp1」同「F3」嗰兩個位嘅電壓差),而 X 軸代表時間-於是每一條線都會俾睇嗰個人見到個頭某一個特定嘅區域嘅電壓值隨時間嘅變化[24]。
Mu 波(mu wave,當中嘅 mu 讀做 miu1)係一種頻率喺 8 至 13 Hz 之間嘅腦電波,喺感覺運動皮層(sensorimotor cortex)嗰度會探測到。感覺運動皮層呢個腦區域專門管嗰個人嘅郁動,而淨係喺呢個區先會搵到嘅 mu 波係一特殊嘅 alpha 波,同鏡神經細胞(mirror neuron)嘅活動好關係密切[82]。
Mu 波最出名嘅係能夠預測鏡神經細胞嘅活動。正常人嘅腦喺望到其他人郁動嗰陣會出現 mu 壓低(mu suppression;指 mu 波強度下跌)嘅情況,而 mu 壓低反映感覺運動皮層入面嗰啲鏡神經細胞喺度活躍緊。鏡神經細胞係一種特殊神經細胞,專門幫一個人模仿其他人嘅行為同動作,例如係自動噉模仿其他人嘅表情,對於同人溝通嚟講好緊要[82][83]。所以如果一個人個腦喺望其他人郁嗰陣冇 mu 壓低嘅情況出現,噉表示佢唔曉做模仿其他人嘅表情等嘅嘢-所以 mu 壓低嘅異常同自閉症呢啲令患者唔識同人相處嘅病有好大啦掕[84]。
舉個例,已知自閉症係一種搞到患者唔識同人相處嘅心理病。研究者搵若干個受診斷有自閉症嘅人返嚟做受試者(用心理測驗斷定咗有自閉症);然後佢哋要求呢啲受試者睇一啲影片,呢啲影片當中某啲展示其他人身體嘅郁動,某啲展示死物,一路俾佢哋睇一路用腦電圖量度佢哋嘅腦活動;然後做統計分析,比較呢啲受試者嘅腦電活動同一般人嘅,結果發現,自閉症患者同一般人一樣,喺做動作嗰陣會有 mu 壓低(mu suppression)嘅現象,而一般人喺睇其他人做動作嗰陣都會有 mu 壓低,但自閉症患者喺睇其他人做動作嗰陣冇 mu 壓低。呢份研究提供咗兩樣重要嘅資訊:
量度 mu 壓低可以幫手診斷自閉症;
Mu 壓低反映鏡神經細胞嘅活動,所以呢個結果表示,自閉症嘅機制涉及鏡神經細胞活動異常;即係表示,描述自閉症嘅理論模型一定要考慮鏡神經細胞嘅作用[84]。
腦電圖腦機介面技術仲可以用嚟製作新型嘅遊戲:喺最廣義上,一隻電子遊戲係一個電腦程式,會接收由玩家俾嘅輸入,按玩家輸入改變遊戲狀態,並且將遊戲狀態嘅改變作為輸出俾玩家睇,等玩家可以由探索遊戲世界當中得到樂趣。喺廿同廿一世紀初,玩家輸入都係通過遊戲控制器-有若干個掣俾玩家撳-嚟得到嘅,不過 2010 年代開始,就有遊戲製作方面嘅專業人士開始研究俾玩家通過「諗嘢」嚟俾輸入:想像一部遊戲機,部機駁住咗個腦電圖量度器,並且能夠按探測到嘅腦電規律控制遊戲狀態[註 10],簡單例子:探測到規律 A 就當玩家想攻擊,而探測到規律 B 就當玩家想防守-假設玩家能夠控制自己嘅腦電活動,就會達到「玩家可以靠諗嘢控制隻遊戲」嘅效果[101]。
Niedermeyer E.; da Silva F.L. (2004). Electroencephalography: Basic Principles, Clinical Applications, and Related Fields. Lippincott Williams & Wilkins.
Vogler, E. C., Flynn, D. T., Busciglio, F., Bohannan, R. C., Tran, A., Mahavongtrakul, M., & Busciglio, J. A. (2017). Low cost electrode assembly for EEG recordings in mice. Frontiers in neuroscience, 11.
Pirttimäki, T., Salo, R. A., Shatillo, A., Kettunen, M. I., Paasonen, J., Sierra, A., ... & Pitkänen, A. (2016). Implantable RF-coil with multiple electrodes for long-term EEG-fMRI monitoring in rodents. Journal of neuroscience methods, 274, 154-163.
Chen, A. H., Zhou, Y., Gong, H. Q., & Liang, P. J. (2004). Firing rates and dynamic correlated activities of ganglion cells both contribute to retinal information processing. Brain research, 1017(1-2), 13-20.
Light, G. A., Williams, L. E., Minow, F., Sprock, J., Rissling, A., Sharp, R., ... & Braff, D. L. (2010). Electroencephalography (EEG) and event‐related potentials (ERPs) with human participants. Current protocols in neuroscience, 52(1), 6-25.
De Vos, M., Kroesen, M., Emkes, R., & Debener, S. (2014). P300 speller BCI with a mobile EEG system: comparison to a traditional amplifier. Journal of neural engineering, 11(3), 036008.
Wolpaw, J. R., & McFarland, D. J. (2004). Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. Proceedings of the National Academy of Sciences of the United States of America, 101(51), 17849-17854.
Li, R., & Principe, J. C. (2006, August). Blinking artifact removal in cognitive EEG data using ICA. In 2006 International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 5273-5276). IEEE.
Albert, B., Zhang, J., Noyvirt, A., Setchi, R., Sjaaheim, H., Velikova, S., & Strisland, F. (2016, July). Automatic EEG processing for the early diagnosis of traumatic brain injury. In 2016 World Automation Congress (WAC) (pp. 1-6). IEEE.
Makeig, S. (1993). Auditory event-related dynamics of the EEG spectrum and effects of exposure to tones. Electroencephalogr Clin Neurophysiol, 86:283–93.
Delorme, A., & Makeig, S. (2004). EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of neuroscience methods, 134(1), 9-21.
Jung, T. P., Humphries, C., Lee, T. W., Makeig, S., McKeown, M. J., Iragui, V., & Sejnowski, T. J. (1998, August). Removing electroencephalographic artifacts: comparison between ICA and PCA. In Neural Networks for Signal Processing VIII, 1998. Proceedings of the 1998 IEEE Signal Processing Society Workshop (pp. 63-72). IEEE.
Acharya, U. R., Sree, S. V., Alvin, A. P. C., & Suri, J. S. (2012). Use of principal component analysis for automatic classification of epileptic EEG activities in wavelet framework. Expert Systems with Applications, 39(10), 9072-9078.
Fitzgibbon, Sean P; Powers, David M W; Pope, Kenneth J; Clark, C Richard (2007). "Removal of EEG noise and artifact using blind source separation". Journal of Clinical Neurophysiology. 24 (3): 232–243.
Shackman, Alexander J.; McMenamin, Brenton W.; Maxwell, Jeffrey S.; Greischar, Lawrence L.; Davidson, Richard J. (2010). "Identifying robust and sensitive frequency bands for interrogating neural oscillations". NeuroImage. 51 (4): 1319–33.
Joyce, Carrie A.; Gorodnitsky, Irina F.; Kutas, Marta (2004). "Automatic removal of eye movement and blink artifacts from EEG data using blind component separation". Psychophysiology. 41 (2): 313–25.
Lorens, S. A., & Darrow, C. W. (1962). Eye movements, EEG, GSR and EKG during mental multiplication. Electroencephalography and Clinical Neurophysiology, 14(5), 739-746.
Barry, W; Jones, GM (1965). "Influence of Eye Lid Movement Upon Electro-Oculographic Recording of Vertical Eye Movements". Aerospace medicine. 36: 855–8.
Iwasaki, Masaki; Kellinghaus, Christoph; Alexopoulos, Andreas V.; Burgess, Richard C.; Kumar, Arun N.; Han, Yanning H.; Lüders, Hans O.; Leigh, R. John (2005). "Effects of eyelid closure, blinks, and eye movements on the electroencephalogram". Clinical Neurophysiology. 116 (4): 878–85.
Nam, Y., Zhao, Q., Cichocki, A., & Choi, S. (2010, November). A tongue-machine interface: Detection of tongue positions by glossokinetic potentials. In International Conference on Neural Information Processing (pp. 34-41). Springer, Berlin, Heidelberg.
Adeli, Hojjat; Zhou, Ziqin; Dadmehr, Nahid (February 2003). "Analysis of EEG records in an epileptic patient using wavelet transform". Journal of Neuroscience Methods. 123 (1): 69–87.
Hirose, G., Saeki, M., Kosoegawa, H., Takado, M., Yamamoto, T., & Tada, A. (1981). Delta waves in the EEGs of patients with intracerebral hemorrhage. Archives of neurology, 38(3), 170-175.
Clarke, A. R., Barry, R. J., McCarthy, R., & Selikowitz, M. (1998). EEG analysis in attention-deficit/hyperactivity disorder: a comparative study of two subtypes. Psychiatry research, 81(1), 19-29.
Park, J., Xu, L., Sridhar, V., Chi, M., & Cauwenberghs, G. (2011, August). Wireless dry EEG for drowsiness detection. In 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 3298-3301). IEEE.
Kurt, M. B., Sezgin, N., Akin, M., Kirbas, G., & Bayram, M. (2009). The ANN-based computing of drowsy level. Expert Systems with Applications, 36(2), 2534-2542.
Gargiulo, G., Bifulco, P., Calvo, R. A., Cesarelli, M., Jin, C., & van Schaik, A. (2008, November). A mobile EEG system with dry electrodes. In Biomedical Circuits and Systems Conference, 2008. BioCAS 2008. IEEE (pp. 273-276). IEEE.
Kisley, Michael A.; Cornwell, Zoe M. (2006). "Gamma and beta neural activity evoked during a sensory gating paradigm: Effects of auditory, somatosensory and cross-modal stimulation". Clinical Neurophysiology. 117 (11): 2549–63.
Jensen, O., Kaiser, J., & Lachaux, J. P. (2007). Human gamma-frequency oscillations associated with attention and memory. Trends in neurosciences, 30(7), 317-324.
Başar, E. (2013). A review of gamma oscillations in healthy subjects and in cognitive impairment. International Journal of Psychophysiology, 90(2), 99-117.
Recommendations for the Practice of Clinical Neurophysiology: Guidelines of the International Federation of Clinical Physiology (EEG Suppl. 52) Editors: G. Deuschl and A. Eisen q 1999 International Federation of Clinical Neurophysiology. All rights reserved. Published by Elsevier Science B.V.
Likowski, K. U., Mühlberger, A., Gerdes, A., Wieser, M. J., Pauli, P., & Weyers, P. (2012). Facial mimicry and the mirror neuron system: simultaneous acquisition of facial electromyography and functional magnetic resonance imaging. Frontiers in Human Neuroscience, 6, 214.
Oberman, Lindsay M.; Hubbard, Edward M.; McCleery, Joseph P.; Altschuler, Eric L.; Ramachandran, Vilayanur S.; Pineda, Jaime A. (2005). "EEG evidence for mirror neuron dysfunction in autism spectrum disorders". Cognitive Brain Research. 24 (2): 190–8.
Warnke, A.; Remschmidt, H.; Hennighausen, K. (1994). "Verbal information processing in dyslexia--data from a follow-up experiment of neuro-psychological aspects and EEG". Acta paedopsychiatrica. 56 (3): 203–208.
Freunberger, R., Klimiesch, W., Doppelmayr, M & Holler, Y. (2007). Visual P2 component is related to theta phase-locking. Neuroscience Letters, 426, 181-186.
Coles, Michael G.H.; Michael D. Rugg (1996). "Event-related brain potentials: an introduction". Electrophysiology of Mind互聯網檔案館嘅歸檔,歸檔日期2016年3月3號,. (PDF). Oxford Scholarship Online Monographs. pp. 1–27.
Krusienski, D. J. D., Sellers, E. E. W., Cabestaing, F., Bayoudh, S., McFarland, D. J., Vaughan, T. M., et al. A comparison of classification techniques for the P300 Speller. Journal of Neural Engineering. 2006; 3(4): 299-305
Näätänen, R., & Alho, K. (1995). Mismatch negativity-a unique measure of sensory processing in audition. International Journal of Neuroscience, 80(1-4), 317-337.
Britton, J. W., Frey, L. C., Hopp, J. L., Korb, P., Koubeissi, M. Z., Lievens, W. E., ... & St, E. L. (2016). Electroencephalography (EEG): An introductory text and atlas of normal and abnormal findings in adults, children, and infants. American Epilepsy Society, Chicago.
Gronseth, G. S.; Greenberg, M. K. (1995). "The utility of the electroencephalogram in the evaluation of patients presenting with headache: A review of the literature". Neurology. 45 (7): 1263–1267.
Coben, R., Clarke, A. R., Hudspeth, W., & Barry, R. J. (2008). EEG power and coherence in autistic spectrum disorder. Clinical neurophysiology, 119(5), 1002-1009.
Rossi, P. G., Parmeggiani, A., Bach, V., Santucci, M., & Visconti, P. (1995). EEG features and epilepsy in patients with autism. Brain and Development, 17(3), 169-174.
Rowe, D. L., Robinson, P. A., & Gordon, E. (2005). Stimulant drug action in attention deficit hyperactivity disorder (ADHD): inference of neurophysiological mechanisms via quantitative modelling. Clinical neurophysiology, 116(2), 324-335.
Stein, A., Yotam, Y., Puzis, R., Shani, G., & Taieb-Maimon, M. (2018). EEG-triggered dynamic difficulty adjustment for multiplayer games. Entertainment computing, 25, 14-25.
Vespa, Paul M.; Nenov, Val; Nuwer, Marc R. (1999). "Continuous EEG Monitoring in the Intensive Care Unit: Early Findings and Clinical Efficacy". Journal of Clinical Neurophysiology. 16 (1): 1–13.
Hämäläinen, Matti; Hari, Riitta; Ilmoniemi, Risto J.; Knuutila, Jukka; Lounasmaa, Olli V. (1993). "Magnetoencephalography-theory, instrumentation, and applications to noninvasive studies of the working human brain". Reviews of Modern Physics. 65 (2): 413–97.
O'Regan, S; Faul, S; Marnane, W (2010). "Automatic detection of EEG artifacts arising from head movements". 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology. pp. 6353–6.
Kondylis, Efstathios D. (2014). "Detection Of High-Frequency Oscillations By Hybrid Depth Electrodes In Standard Clinical Intracranial EEG Recordings". Frontiers in Neurology. 5: 1–10.
Coenen, Anton; Edward Fine; Oksana Zayachkivska (2014). "Adolf Beck: A Forgotten Pioneer In Electroencephalography". Journal of the History of the Neurosciences. 23 (3): 276–286.
Haas, L F (2003). "Hans Berger (1873-1941), Richard Caton (1842-1926), and electroencephalography". Journal of Neurology, Neurosurgery & Psychiatry. 74 (1): 9.
S. Bozinovski, M. Sestakov, L. Bozinovska: Using EEG alpha rhythm to control a mobile robot, In G. Harris, C. Walker (eds.) Proc. IEEE Annual Conference of Medical and Biological Society, p. 1515-1516, New Orleans, 1988.
S. Bozinovski: Mobile robot trajectory control: From fixed rails to direct bioelectric control, In O. Kaynak (ed.) Proc. IEEE Workshop on Intelligent Motion Control, p. 63-67, Istanbul, 1990.