EEG Signal Processing and Machine Learning. Saeid Sanei

EEG Signal Processing and Machine Learning - Saeid Sanei


Скачать книгу
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.

      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.

      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.

Schematic illustration of 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.

      Following the generation of an IPSP, there is an overflow of cations from the nerve cell or an inflow of anions into the nerve cell. This flow ultimately causes a change in potential along the nerve cell membrane. Primary transmembranous currents generate secondary ional currents along the cell membranes in the intracellular and extracellular space. The portion of these currents that flow through the extracellular space is directly responsible for the generation of field potentials. These field potentials, usually with less than 100 Hz frequency, are called EEGs when there are no changes in the signal average and called DC potential if there are slow drifts in the average signals, which may mask the actual EEG signals. A combination of EEG and DC potentials is often observed for some abnormalities in the brain such as seizure (induced by pentylenetetrazol), hypercapnia, and asphyxia [22]. We next focus on the nature of APs.

Schematic illustration of an example of an AP.

      The conduction velocity of APs lies between 1 and 100 m s−1. APs are initiated by many different types of stimuli; sensory nerves respond to many types of stimuli, such as: chemical, light, electricity, pressure, touch, and stretching. Conversely, the nerves within the CNS (brain and spinal cord) are mostly stimulated by chemical activity at synapses.

      A stimulus must be above a threshold level to set off an AP. Very weak stimuli cause a small local electrical disturbance, but do not produce a transmitted AP. As soon as the stimulus strength goes above the threshold, an AP appears and travels down the nerve.

      For a human being the amplitude


Скачать книгу