Saeid Sanei - EEG Signal Processing and Machine Learning
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EEG Signal Processing and Machine Learning: краткое содержание, описание и аннотация
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During the 1930s, the first EEG recording of sleep spindles was undertaken by Berger. He then reported the effect of hypoxia on the human brain, the nature of several diffuse and localized brain disorders, and gave an inkling of epileptic discharges [8]. During this time another group established in Berlin‐Buch and led by Kornmüller, provided more precise recording of the EEG [9]. Berger was also interested in cerebral localization and particularly in the localization of brain tumours. He also found some correlation between mental activities and the changes in the EEG signals.
Toennies (1902–1970) from the group in Berlin built the first biological amplifier for the recording of brain potentials. A differential amplifier for recording of EEGs was later produced by the Rockefeller foundation in 1932.
The importance of multichannel recordings and using a large number of electrodes to cover a wider brain region was recognized by Kornmüller [10]. The first EEG work focusing on epileptic manifestation, and the first demonstration of epileptic spikes was presented by Fischer and Lowenbach [11, 12].
In England, W. Gray Walter became the pioneer of clinical EEG. He discovered the foci of slow brain activity (delta waves), which initiated enormous clinical interest in the diagnosis of brain abnormalities. In Brussels, Fredric Bremer (1892–1982) discovered the influence of afferent signals on the state of vigilance [13].
Research activities related to EEGs started in North America in around 1934. In this year, Hallowell Davis illustrated a good alpha rhythm for himself. A cathode ray oscilloscope was used around this date by the group in St. Louis University in Washington, in the study of peripheral nerve potentials. The work on human EEGs started at Harvard in Boston and the University of Iowa in the 1930s. The study of epileptic seizure developed by Fredric Gibbs was the major work on EEGs during these years, as the realm of epileptic seizure disorders was the domain of their greatest effectiveness. Epileptology may be divided historically into two periods [14]: before and after the advent of EEG. Gibbs and Lennox applied the idea of Fischer based on his studies about picrotoxin and its effect on the cortical EEG in animals to human epileptology. Berger [15] showed a few examples of paroxysmal EEG discharges in a case of presumed petit mal attacks and during a focal motor seizure in a patient with general paresis.
As the other great pioneers of EEG in North America, Hallowell Davis, Herbert H. Jasper, Frederic A. Gibbs, William Lennox, and Alfred L. Loomis were the earliest investigators of the nature of EEG during human sleep. Alfred L. Loomis, E. Newton Harvey, and Garret A. Hobart were the first who mathematically studied the human sleep EEG patterns and the stages of sleep. At McGill University, Herbert Jasper studied the related behavioural disorder before he found his niche in basic and clinical epileptology [16].
The American EEG Society was founded in 1947 and the first international EEG Congress was held in London, United Kingdom around this time. While the EEG studies in Germany were still limited to Berlin, Japan gained attention by the work of Motokawa, a researcher of EEG rhythms [17]. During these years the neurophysiologists demonstrated the thalamocortical relationship through anatomical methods. This leads to the development of the concept of centrencephalic epilepsy [18, 30].
Throughout the 1950s the work on EEGs expanded in many different places. During this time surgical operation for removing the epileptic foci became popular and the book entitled Epilepsy and the Functional Anatomy of the Human Brain (Jasper and Penfield) was published. During this time microelectrodes were invented. They were made of metals such as tungsten or glass, filled with electrolytes such as potassium chloride, with diameters of less than 3 μm.
Depth EEG of a human was first obtained with implanted intracerebral electrodes by Mayer and Hayne (1948). Invention of intracellular microelectrode technology revolutionized this method and was used in the spinal cord by Brock et al. in 1952, and in the cortex by Phillips in 1961.
Analysis of EEG signals started during the early days of EEG measurement. Berger assisted by Dietch (1932) applied Fourier analysis to EEG sequences which was rapidly developed during the 1950s. Analysis of sleep disorders with EEGs started its development in the 1950s through the work of Kleitman at the University of Chicago.
In the 1960s the analysis of EEGs of full‐term and premature newborns began its development [19]. Investigation of evoked potentials (EPs), especially visual EPs, as commonly used for monitoring mental illnesses, progressed during the 1970s.
The history of EEG however has been a continuous process which started from the early 1300s and has brought daily development of clinical, experimental, and computational studies for discovery, recognition, diagnosis, and treatment of a vast number of neurological and physiological brain abnormalities as well as the rest of human central nervous system (CNS). At this time, EEGs are recorded invasively and noninvasively using fully computerized systems. The EEG machines are equipped with many signal processing tools, delicate and accurate measurement electrodes, and enough memory for very‐long‐term recordings of several hours. EEG or MEG machines may be integrated with other neuroimaging system such as fMRI. Very delicate needle‐type electrodes can also be used for recording the EEGs from over the cortex (electrocorticogram), and thereby avoid the attenuation and nonlinearity effects induced by the skull. We next proceed to describe the nature of neural activities within the human brain.
1.3 Neural Activities
The CNS generally consists of nerve cells and glia cells, which are located between neurons. Each nerve cell consists of axons, dendrites, and cell bodies. Nerve cells respond to stimuli and transmit information over long distances. A nerve cell body has a single nucleus and contains most of the nerve cell metabolism especially that related to protein synthesis. The proteins created in the cell body are delivered to other parts of the nerve. An axon is a long cylinder, which transmits an electrical impulse and can be several metres long in vertebrates (giraffe axons go from the head to the tip of spine). In humans the length can be a percentage of a millimetre to more than a metre. An axonal transport system for delivering proteins to the ends of the cell exists and the transport system has ‘molecular motors’ which ride upon tubulin rails.
Dendrites are connected to either the axons or dendrites of other cells and receive impulses from other nerves or relay the signals to other nerves. In the human brain each nerve is connected to approximately 10 000 other nerves, mostly through dendritic connections.
The activities in the CNS are mainly related to the synaptic currents transferred between the junctions (called synapses) of axons and dendrites, or dendrites and dendrites of cells. A potential of 60–70 mV with negative polarity may be recorded under the membrane of the cell body. This potential changes with variations in synaptic activities. If an action potential (AP) travels along the fibre, which ends in an excitatory synapse, an excitatory post‐synaptic potential (EPSP) occurs in the following neuron. If two APs travel along the same fibre over a short distance, there will be a summation of EPSPs producing an AP on the post‐synaptic neuron providing a certain threshold of membrane potential is reached. If the fibre ends in an inhibitory synapse, then hyperpolarization will occur, indicating an inhibitory post‐synaptic potential (IPSP) [20, 21]. Figure 1.3shows the above activities schematically.

Figure 1.3 The neuron membrane potential changes and current flow during synaptic activation recorded by means of intracellular microelectrodes. APs in the excitatory and inhibitory presynaptic fibre respectively lead to EPSP and IPSP in the post‐synaptic neuron.
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