Dear Editor:
In 1875, Richard Caton published the first study of electrical activity of animal brains. In 1924, Hans Berger extended Caton's work to the measurement of human electrical potentials, with the published results appearing in Archiv forschung Psychiatrie in 1929. In his pioneering writings, Berger noted, “We see in the electroencephalogram a concomitant phenomenon of the continuous nerve processes, which take place in the brain, exactly as the electrocardiogram represents a concomitant phenomenon of the contractions of the individual segments of the heart.”1,2
Since its early role in the 1920s, electroencephalogram (EEG) technology has evolved and currently has many applications, including heterogeneous conditions within psychiatric, neurologic, neuropsychological, metabolic syndromes, and research.3–10 The EEG is an essential study of patients with seizures and those suspected of having seizures. The EEG records spontaneous electrical activity retrieved from the cerebral cortex, measured as scalp potentials. Tracings of EEG potentials occur as horizontal waves and vertical spikes, with localized complexes. This activity reflects the currents that flow in the extracellular space and these in turn reflect the summated effects of interdependent reciprocal activating excitatory and inhibitory synaptic potentials that occur at the level of the neuron.11 Vertical organization of the electrical influences is in keeping with the idea that the evolutional design of the cortex rests upon complex interconnections among the large number of mosaic-like vertical columnar units.
Abnormal EEGs are usually found in epilepsy, but many patients with seizures have normal EEGs. The exact percentage varies depending on the seizure type and frequency, the circumstances under which the EEG is obtained, and the number of EEGs performed.12 A single EEG recording can show a normal pattern in as many as 20 percent of patients with absence seizures and 40 percent of those with grand mal epilepsy, although these percentages may be reduced with repeated recordings.13 In a study of 782 abnormal EEGs, the EEG demonstrated specificity of 40.7 percent for brain injury, 27.9 percent for craniocerebral trauma, 27.2 percent for infectious etiology, and 4.2 percent for congenital metabolic disease.14 EEGs suffer low predictive value and inaccuracies of parameter estimation due to uncertainties in the conductivities of tissue, dissimilarities among individuals, and over simplified models that are insufficient to represent the complexity of the physiology and physics involved in the human brain.15,16
Vectors are not uncommon in physiologic systems, and their arithmetic is different from scalar events, which involves magnitude only. Vector quantities include displacement, velocity, and force. Displacement represents a change in position that can be used to estimate destination. Velocity incorporates speed and its direction. Force is responsible for all changes that occur in motion. The direction as well as the magnitude of a force must be known to determine its source, and to estimate its cause and effect. Often the best way to analyze a biological problem is to resolve it into its arithmetic components.17
Physiological vector analysis has long been utilized in fields of clinical medicine. Electrocardiograms, which through Einthoven's triangle, create a summated cardiac vector.18 Additionally, cardiologists are experimenting with velocity vector mapping as an alternative to isochronal maps to infer patterns in the cardiac activation sequence during ablation procedures.19 The recording of three-dimensional eye position utilizing rotation vectors has become the accepted standard in oculomotor research.20
Approximately one percent of the people in the world suffer from epilepsy and 30 percent of epileptics are not aided by medication.21 Detection, sensitivity, and specificity of seizure occurrence and type remain an inexact science despite the technological advancements of EEG multidimensional analysis.
The intention of this paper is to offer a theoretical statement on the nature, purpose, and clinical advantage of vectored EEGs. We believe that integrative analysis of multivariate neurodynamic schemes of the brain on the basis of linear conversion of nonlinear wave and spike formations into an algorithmic representative vector has the potential of improving diagnostic specificity, and treatment localization and efficacy. It is our hope that research will lead to the development of models to bridge the gap between classical correlation and interpretative analyses to a more quantifiable endpoint that embraces the clarity of physics as it applies to biological systems.
With regards,
Jim Sondecker, BS, MS
M. Smith, MD
D. Robinson, DO
Stockton, California
References
- 1.Brazier MAB. A history of the electrical activity of the brain: The first half-century. New York, NY: Macmillan; 1961. [Google Scholar]
- 2.Finger S. Origins of neuroscience: A history of explorations into brain function. New York, NY: Oxford University Press; 1994. pp. 41–2. [Google Scholar]
- 3.Spoor MT, Sutherland FR. The evolution of the concept of brain death. Ann R Coll Physicians Surg Can. 1995;28(1):30–4. [PubMed] [Google Scholar]
- 4.Ortiz N, Annoni JM, Trojan D, Alberque C, Eytan A. Persistent severe depressive episode with mood-congruent psychotic features associated with left temporal ischemia. Cogn Behav Neurol. 2004;17(3):157–62. doi: 10.1097/01.wnn.0000140168.25333.2b. [DOI] [PubMed] [Google Scholar]
- 5.Sanchez-Valle R, Nos C, YagÃe J, et al. Clinical and genetic features of human prion diseases in Catalonia: 1993-2002. Eur J Neurol. 2004;11(10):649–55. doi: 10.1111/j.1468-1331.2004.00967.x. [DOI] [PubMed] [Google Scholar]
- 6.Stefan H. How to diagnose and treat epilepsy. MMW Fortschr Med. 2004;146(2):41–4. 46. [PubMed] [Google Scholar]
- 7.Stern B, Glicksohn J, Stern M, Myslobodsky MS. Profiles of patients with a history of mild head injury. Int J Neurosci. 2004;114(9):1223–37. doi: 10.1080/00207450490475742. [DOI] [PubMed] [Google Scholar]
- 8.Morino M, Ishibashi K, Hara M. Surgical treatment of temporal lobe epilepsy associated with subcortical ectopic gray matter under the guidance of intraoperative electrocorticography. Seizure. 2004;13(7):470–4. doi: 10.1016/j.seizure.2003.09.013. [DOI] [PubMed] [Google Scholar]
- 9.Consales G, De Gaudio AR. Sepsis associated encephalopathy. Minerva Anestesiol. 71;2005;(1-2):39–52. [PubMed] [Google Scholar]
- 10.Achermann P, BorbÃly AA. Mathematical models of sleep regulation. Front Biosci. 2003;8:s683–93. doi: 10.2741/1064. [DOI] [PubMed] [Google Scholar]
- 11.Kybic J, Clerc M, Abboud T, et al. A common formalism for the integral formulations of the forward EEG problem. IEEE Trans Med Imaging. 2005;24(1):12–28. doi: 10.1109/tmi.2004.837363. [DOI] [PubMed] [Google Scholar]
- 12.Rowland LP. Merritt's Textbook of Neurology. Eighth Edition. Lea & Febiger London: 1989. pp. P780–804. [Google Scholar]
- 13.American EEG Society. Guidelines in EEG and evoked potentials. J Clin Neurophysiol. 1986;3(suppl 1):1. [PubMed] [Google Scholar]
- 14.Niedermeyer E, DaSilva FL. Electroencephalography, Third Edition. Baltimore, MD: Urban and Schwarzenberg; 1977. [Google Scholar]
- 15.Zifkin BG. The electroencephalogram as a screening tool in pilot applicants. Epilepsy Behav. 2005;6(1):17–20. doi: 10.1016/j.yebeh.2004.10.001. [DOI] [PubMed] [Google Scholar]
- 16.GutiÃrrez D, Nehorai A, Muravchik CH. Estimating brain conductivities and dipole source signals with EEG arrays. IEEE Trans Biomed Eng. 2004;51(12):2113–22. doi: 10.1109/TBME.2004.836507. [DOI] [PubMed] [Google Scholar]
- 17.Arthur Beiser., editor. Physics. Fourth Edition. Menlo Park, CA: Benjamin/Cummings; 1986. pp. 1–11. [Google Scholar]
- 18.William F Ganong., editor. Review of Medical Physiology. 17th Edition. Norwalk, CT: Appleton & Lange; 1995. pp. 498–504. [Google Scholar]
- 19.Fitzgerald TN, Brooks DH, Triedman JK. Identification of cardiac rhythm features by mathematical analysis of vector fields. IEEE Trans Biomed Eng. 2005;52(1):19–29. doi: 10.1109/TBME.2004.839636. [DOI] [PubMed] [Google Scholar]
- 20.Haslwanter T. Mathematics of three-dimensional eye rotations. Vision Res. 1995;35(12):1727–39. doi: 10.1016/0042-6989(94)00257-m. [DOI] [PubMed] [Google Scholar]
- 21.Adeli H, Zhou Z, Dadmehr N. Analysis of EEG records in an epileptic patient using wavelet transform. J Neurosci Methods. 2003;123(1):69–87. doi: 10.1016/s0165-0270(02)00340-0. [DOI] [PubMed] [Google Scholar]