Electroencephalogram

INTRODUCTION

The electroencephalogram (EEG) is a measurement of the electrical activity in the patient's brain. This electrical activity is produced by the firing of neurons (a nerve cell) within the brain and varies from patient to patient. In 1875, English physician Richard Caton discovered the presence of electrical activity in the brain; however, it was not until German neurologist Han Berger in 1924 used his ordinary radio equipment to amplify the brain's electrical activity so he could record it on paper. He noticed that rhythmic changes in brain waves varied with the individual's state of consciousness (sleep, anesthesia, epilepsy) and that various regions of the brain do not emit the same brain wave frequency simultaneously. (http://www.bio-medical.com). The EEG was given its name by Berger who used the German term elektrenkephalogramm to describe the graphical representation of the electrical currents generated in the brain. The scientific community of Berger's time did not believe the conclusions he made and it took another five years until his conclusions could be verified through experimentation by Edgar Douglas Adrian and B.C.H Matthews. These experiments made head-waves and other scientists began studying the field and in 1936 W. Gray Walter demonstrated that this technology could be used to pinpoint a brain tumor. He used a large number of small electrodes that he pasted to the scalp and found that brain tumors caused areas of abnormal electrical activity. (Romanowski 1999) and http://www.ebme.co.uk.

The brain is the central part of the nervous system, which is the most complicated system in the body. It is an intriguing organ that has been studied right from the time of brain development in the fetus. The human brain weighs about 1.5kg in adults. The cerebrum, which forms the bulk of the brain, is divided into two hemispheres, the right hemisphere and the left hemisphere. Each hemisphere of the brain interacts with one half of the body, but for unknown reasons, it is the right side that controls the left half of the body and the left half of the brain that controls the right half of the body. However, in most people, the left hemisphere of the brain is involved in language and creativeness, while the right side of the brain is more involved in understanding and judgment. The cerebrum, which is located in the forebrain, is the largest part of the human brain and is associated with higher brain functions such as thought and action. The cerebral cortex is divided into four sections called 'lobes'. These include: the frontal lobe, parietal lobe, occipital lobe and temporal lobe. The frontal lobe is associated with reasoning, planning, parts of speech, movement and problem solving. The parietal lobe is associated with movement, orientation, recognition and perception of stimuli. The occipital lobe is associated with visual processing and the temporal lobe is associated with perception and recognition of auditory stimuli, memory and speech. (Khan 2009).

Over the years with advancements in technology EEG electrodes, amplifiers and output devices were improved and scientists learned the best places to put the electrodes and how to diagnose its conditions. They also discovered how to create electrical maps to produce an image of the brain's surface and today EEG machines have multiple channels, computer storage memories and specialized software that can create an electrical map of the brain. (Romanowski 1999). EEG has come a long way since its inception more than 100 years ago and it is used primarily in studying the properties of cerebral and neural networks in neurosciences (Michel et al. 2004). It is used to monitor the neurodevelopment and sleep patterns of infants in the intensive care unit and ultimately enable physicians to use the information to improve daily medical care (Scher 2004). The emergence of neurofeedback or EEG biofeedback has expanded the application of EEG for both cases with particular disorders or among healthy participants. EEG frequencies in neurofeedback can be controlled to influence certain cognitive performance and memory task, (Vernon et al. 2003). Interactive Brainwave Visual Analyzer (IBVA) is a form of biofeedback for the brain (neurofeedback). It's a training process of using technology to provide you with more information about what your body is doing than your ordinary senses provide. This "feedback" helps you learn to use your mind to develop greater control over your body, or, in the case of neurofeedback, your brain. IBVA detects brainwaves phasing at speeds measured in units of Hz for cycles per second between 0 and 60 Hz. It is used for sleep state and hypnosis analysis, image programming for sports training, super learning (photo reading) and for study. EEG biofeedback is effective in treating psychological disorders such as attention deficit, depression, chronic anxiety disorder, chronic alcoholics and neurological disorders like epilepsy. Patients with epilepsy that cannot be controlled by medication will often have surgery in order to remove the damaged tissue. The EEG plays an important role in localizing this tissue. Special electrodes can be inserted through the cortex or alternatively a grid of electrodes placed directly on the surface of the cortex. These recordings, often called Long Term Monitoring for Epilepsy (LTME), can be carried out for periods ranging from 24 hours to 1 week. The EEG recorded will indicate which areas of the brain should be surgically removed. (Smith n.d). Another important application of the EEG is used by anesthesiologist to monitor the depth of anesthesia. EEG measures taken during anesthesia exhibit stereotypic changes as anesthetic depth increases. These changes include complex patterns of loss of consciousness occurs (loss of responses to verbal commands and/or loss of righting reflex). As anesthetic depth increases from light surgical levels to deep anesthesia, the EEG exhibits disrupted rhythmic waveforms, high amplitude burst suppression activity, and finally, very low amplitude isoelectric or 'flat line' activity.

Quantitative EEG (QEEG) has come a long way in its relatively short life in terms of use in clinical practice. Now, as clinicians become aware of the scientific basis and power of using parametrically based measures of QEEG to assess an individual against age-matched populations, they find new ways to employ this technique. There are literally thousands of univariate electrophysiological measures that can be derived, transformed and normed into Z-scores (standard scores), to be used to indicate degrees of derivations from normal. QEEG offers a powerful application tool as a method for providing convergent evidence in the identification of clinical syndromes for individuals. Over the years, various clinicians using QEEG have attempted to establish "brain maps" to correspond with specific disorders such as learning disorders, attention deficit hyperactivity disorders (ADHD), chronic alcoholism and depression. While certain features may be associated with general types of impairments, the utilization of univariate sets of features have, to date, been unable to provide defining specific psychiatric disorders. Looking at only the univariate features without recognizing the full "space" of all deviant measures, one may not realize the particular cluster of measure that may contribute to specific disorders with distinct features. Multivariate statistical measurement sets encompass the "space" of regions by measurement, yielding distinctive complex patterns which yield greater sensitivity in discriminability. (Budzynski, Evans and Abarbanel 2008).

The basic systems of an EEG machine include data collection, storage and display. The components of these systems include electrodes, connecting wires, a computer control module and a display device. The electrodes used can be either surface or needle electrodes. Needle electrodes provide greater signal clarity because they are injected directly into the body and this in turn eliminates signal muffling caused by the skin. Surface electrodes on the other hand are disposable models such as the tab, ring and bar electrodes as well as reusable disc and finger electrodes. These electrodes may also be combined into an electrode cap that is placed directly on the head (Romanowski 2002).

EEG amplifiers convert weak signals from the brain into a more discernable signal for the output device. An amplifier may be set up as follows; a pair of electrodes detects the electrical signal from the body, wires connected to the electrodes transfer the signal to the first section of the amplifier (buffer amplifier). Here the signal is electronically stabilized and amplified by a factor of 5 - 10 and then next in line is a differential pre-amplifier that filters and amplifies the signal by a factor of 10 – 100. After passing through these amplifiers the signals are multiplied by hundreds or thousands of times. Multiple electrodes are used since the brain produces different signals at different points on the skull and the number of channels that an EEG machine has is related to the number of electrodes used. The amplifier is able to translate the different incoming signals and cancel out ones that are identical; this means that the output from the machine is actually the difference in electrical activity picked up by the two electrodes. This therefore means that the placement for each electrode is critical because the closer they are to each other the less differences in brainwaves will be recorded (Romanowski 2002).

EEG SYSTEM LAYOUT (www.medicalengineer.com)

Recording of the electrical activity in the brain takes place over a short period of time from where information is obtained from electrodes stationed at specific points on the patient's head. Electrodes are placed on the scalp of the head usually after preparing the scalp area by light abrasion to reduce impedance due to dead skin cells. In order for the placement of these electrodes to be consistent throughout an internationally recognized method called the "10-20 System" is followed. The 10 and the 20 gives the actual distances between adjacent electrodes. This distance can either be 10% or 20% of the total front-back or right-left distance of the skull, i.e. the nasion – inion and preauricular points respectively, http://www.neurocarelaunches.com. Specific measurements from bony landmarks (inion, nasion and preauricular point) are used to generate a system of lines, which run across the head and intersect at intervals of 10% or 20% of their total length as mentioned above. The standard set of electrodes consists of 21 recording electrodes and one ground electrode. The distance between the nasion and inion is measured along the midline and the frontopolar point, Fpz, is marked at 10% above the nasion. Frontal (Fz), central (Cz), parietal (Pz) and occipital (Oz) points are marked at intervals of 20% of the entire distance, leaving 10% for the interval between Oz and inion (see Diagram 1). The midline points Fpz and Oz routinely do not receive any electrode. The distance between two preauricular points across Cz is measured. Along this line, the transverse position for the central points C3 and C4 and the temporal points T3 and T4 are marked 20% and 40% respectively from the midline (see Diagram 2). The circumference of the head is measured form the occipital point (Oz) through temporal points T3 and T4 and the frontopolar point (Fpz). The longitudinal measurement for Fp1 is located on that circumference, 5% of the total length of the circumference to the left of Fpz. The longitudinal measurements for F7, T3, T5, O1, O2, T6, T4, F8 and Fp2 are at the distance of 10% of the circumference (see Diagram 3). An electrode is then placed on each of the two ear lobes. (Jasper 1958) and (Jasper 1983).

In order for the EEG test to be a success and the best possible results obtained the preparation the patient must undergo is very basic since only a good night sleep before the test is needed along with a grease-free head on the morning of the test. However, it can get more technical should the patient be taking any medication and information on this medication must be passed on to the doctor. An EEG test may be done in a hospital or in a doctor's office by an EEG technologist. Using the internationally recognized 10-20 system, the electrodes are placed on the patient's head and the technologist can then put the patient through a variety of different tasks such as addition/subtraction of numbers, breathing deeply and rapidly or he can ask the person to wear a goggles sending out a strobe (bright flashing light). These tasks take place normally at 15-20 second durations with 30 second breaks in between. The electrodes attached to the patient's head are connected by wires to a computer which records the electrical activity in the brain. An EEG test can last between 1-2 hours and the results obtained from it can be read by a certified doctor known as a Neurologist.

The results of an EEG test are in the form of waveforms which gives vital information about the patient. Waves can either be Alpha waves (frequency of 8 to 12 cycles per second), Beta waves (frequency of 14 to 50 cycles per second), Delta waves (frequency less than 5 cycles per second) or Theta waves (frequency of 4 to 7 cycles per second). Basic alpha waves, which originate in the cortex, can be recorded if the patient closes his eyes and put his brain "at rest" as much as possible. Beta activity is a normal activity present when the eyes are open or closed. It tends to be seen in the channels recorded from the centre or front of the head. Some drugs however, tend to increase the amount of beta activity in the EEG. Theta activity can be classified as both a normal and abnormal activity depending on the age and state of the patient. In adults it is normal if the patient is drowsy. However, it can also indicate brain dysfunction if it is seen in a patient who is alert and awake. In younger patients, theta activity may be the main activity seen in channels recorded from the back and central areas of the head. Delta activity is only normal in an adult patient if they are in a moderate to deep sleep. If it is seen at any other time it would indicate brain dysfunction. Abnormal activity may be seen in all or some channels depending on the underlying brain problem. The stroke or blow on the head. (Niedermeyer, Ernest and Lopes da Silva 2004).

ALPHA WAVES

BETA WAVES

THETA WAVES

DELTA WAVES (http://www.electropsychology.com)

Each type of wave mentioned above gives us information about the patient, for example in a normal patient we tend to observe mainly alpha or beta waves since both sides of the brain show similar patterns of electrical activity. A normal person in this case is described as one who doesn't possess any of the following diseases or injuries; head injury, neurological disease, convulsions, drug abuse, alcohol abuse, memory difficulties, confusion, depression, delusions/hallucinations and learning disabilities. If the patient is abnormal you may find two sides of the brain giving different electrical activities and this may mean there is a problem in one side of the brain caused by a brain tumor, stroke, infection or epilepsy.

EPILEPTIC SPIKES AND WAVE DISCHARGES MONITORED WITH EEG (http://www.webmd.com).

A stroke, which is a sudden disruption in blood flow to brain, caused by blockage or bleeding of a blood vessel and Epilepsy which is a nervous system disorder, can cause abnormal electrical activity in the brain and this abnormality can be seen from the results of an EEG test. Another common disease which is on the escalation presently is Alcoholism. This disease is known as alcohol dependence syndrome i.e. the most severe stage of a group of drinking problems, and the person who has this disease is known as an alcoholic. Alcohol clearly affects the brain since impairments such as difficulty in walking, blurred vision, slurred speech, slowed reaction times and impaired memory are detectable after only one or two drinks and is quickly resolved when drinking stops. We do know that heavy drinking may have extensive and far-reaching effects on the brain ranging from simple "slips" in memory to permanent and debilitating conditions that require lifetime custodial care (White 2003). According to the number 1 website for alcoholism, http://www.alcoholism.about.com, studies have shown that brains of alcoholics are smaller, lighter and shrunken when compared to that of a normal person. The cerebral cortex or gray matter in the brain controls all the complex mental activities and this is filled with neurons connected by single long fibers which make up the "hard wiring" of the brain. Heavy consumption of alcohol is particularly damaging on this "hard wiring" hence the reason why the brain becomes lighter and smaller and the alcoholic severe impairments.

SCHEMATIC DRAWING OF THE HUMAN BRAIN, SHOWING REGIONS VULNERABLE TO ALCOHOLISM-RELATED ABNORMALITIES. (http://www.elvizy.com).

Another major organ apart from the brain which alcohol affects is the liver. Long-term abusers of alcohol usually have some degree of liver damage, ranging in severity from asymptomatic and reversible fatty liver, through hepatitis and cirrhosis, to primary liver cell carcinoma, which is usually fatal. Evidence is accruing to suggest that this spectrum of disorders may be a progressive series of stages of increasing severity. Alcohol liver damage accounts for the vast majority of cases of cirrhosis in patients coming to autopsy. Further, mortality from cirrhosis is associated with national per capita levels of consumption. In North-American studies, alcoholic cirrhosis was one of the top five causes of mortality for people aged 25 to 64 years in the 1960's and 1970's. In 1992, Savolainen, Penttila and Karhunen investigated the relationship between alcohol intake and liver cirrhosis in Finland, where the per capita consumption rates doubles between 1969 and 1974. Rates of liver cirrhosis mortality rose from 4.2 to 9.7 per 100,000 between 1968 and 1988. The mortality rate from cirrhosis has been estimated as between seven and thirteen times higher in alcoholics than in those who do not drink. Although it is more common in men than in women, there is evidence that liver disease progresses more rapidly in the female alcohol abuser (Knight and Longmore 1996). Alcoholics, they say, are not like helpless victims of measles or cancer. They may have 'impaired control' but they can gain control through will-power and learning certain techniques. While the cause of alcoholism is unknown, a number of risk factors have been identified. These include; availability (Australian Aborigines illustrate the importance of availability of alcohol as a risk factor since when they were forbidden to drink there apparently was a low rate of alcohol abuse), family history (alcoholism in the family is probably the strongest predictor of alcoholism occurring in particular individuals), sex (studies have confirmed higher incidence of alcoholism in men than in women), age (alcoholism in men usually develops in the teens, twenties and thirties while in women it often develops later), geography (people living in urban or suburban areas are more often alcoholics than those living in farms or in small towns), occupation (waiters, bartenders, Dockers, musicians, authors and reporters have relatively high cirrhosis rates whereas accountants, postmen and carpenters have relatively low rates), religion (almost all Jews and Episcopalians drink, but alcoholism among Jews is uncommon and appear relatively low among Episcopalians, whereas Irish Catholics in the USA and UK have high rates of alcoholism) and school difficulty ( secondary school dropouts have a record of being irritable and melancholy and experience feelings of guilt and remorse which drives them to become alcoholics. These lose interest in life and contemplate suicide which is a common outcome of alcoholism). People who have been drinking large amounts of alcohol for long periods of time run the risk of developing serious and persistent changes in the brain. Damage may be as a result of the alcohol on the brain or may result indirectly, from a poor health status or from severe liver disease (Goodwin 2000).

Alcoholics are not all alike since they experience different degrees of impairment and the disease has different origins for different people. Consequently, researchers have not found conclusive evidence that any one variable is solely responsible for the brain deficits found in alcoholics. Characterizing what makes some alcoholics vulnerable to brain damage whereas others are not remains the subject of active research. The good news is that most alcoholics with cognitive impairment show at least some improvement in brain structure and functioning within a year of abstinence, though some people take much longer (Bates, Bowden and Barry 2002), (Gansler 2000) and (Sullivan 2000). Clinicians must consider a variety of treatment methods to help people stop drinking and to recover from alcohol related brain impairments, and tailor these treatments to the individual patient. Development of these therapies would occur over time with advancements in technology. Brain imaging techniques are used by medical doctors so that they can monitor the course of these therapies and see how successful they are. This monitoring is important since imaging can reveal information such as structural, functional and biochemical changes in the living patient over a period of time. Promising new medications also are in the early stages of development, as researchers strive to design therapies that can help prevent alcohol's harmful effects and promote the growth of new brain cells to take the place of those that have been damaged by alcohol.

OBJECTIVES

Electroencephalogram or EEG is a tool used to image the brain while it is performing a cognitive task. This allows us to detect the location and magnitude of brain activity involved in the various types of cognitive functions we study. EEG allows us to view and record the changes in your brain activity during the time you are performing the task. Results from an EEG is extremely useful since Neurologists use this to diagnose seizure disorders (epilepsy), brain tumors, brain hemorrhage, cerebral infarct, head injury, sleep disorders and in confirming death in someone who is in a coma. (Tatum 2007).

In this research project we have narrowed the study of the EEG to examine male alcoholic and non-alcoholic patients. The general objective of this project requires us to compare EEG results obtained from testing alcoholic and non-alcoholic patients at the Eric Williams Medical Sciences Complex. An alcoholic is one who suffers from the disease known as alcoholism and cannot control how much they consume. Identification of one involves an objective assessment regarding the damage that imbibing alcohol does to the drinker's life compared with the subjective benefits the drinker perceives from consuming alcohol. While there are many cases where an alcoholic's life has been significantly and obviously damaged, there are always borderline cases that can be difficult to classify. Apart from the general objective of this research project there were many smaller tasks which had to be completed in order for us to obtain successful results and hence fulfill our main objective.

The first task of this research project entailed sourcing alcoholic and non-alcoholic volunteers to test. This was particularly important since the successfulness of this task would revolve solely around our general objective. However, once this first task was sorted out and patients were tested, from the results obtained we used analytical methods such as monopolar absolute power maps, coherence maps and chaos analysis to help us get a clearer illustration of the results and hence make the general objective much clearer.

The second objective of this project required us to have sufficient background information on the EEG, the experimental methodology when conducting an EEG (10-20 System), analytical methods used to illustrate EEG results, alcoholism, EEG on alcoholics and other general topics revolving around the area of research. In order for this to be a success the necessary books, journals, websites had to be sourced and read before any practical work commenced.

Once these two tasks were performed successfully, we then set out to obtain our general objective of analyzing and comparing EEG results of both alcoholics and non-alcoholics.

LITERATURE REVIEW

An electroencephalogram (EEG) is a test that measures and records the electrical activity of your brain by using surface biopotential electrodes. These electrodes are attached to the patient's head and hooked by wires to a computer which records the brain's electrical activity on the screen or on paper as wavy lines (waveforms). Among the basic waveforms are the alpha, beta, theta and delta rhythms. Alpha waves occur at a frequency of 8 to 12 cycles per second in a regular rhythm and are present only when you are awake but have your eyes closed. They normally disappear when you open your eyes or start concentrating mentally. Beta waves occur at a frequency of 13 to 30 cycles per second and are usually associated with the use of sedative medications. Theta waves occur at a frequency of 4 to 7 cycles per second and are most common in children and young adults. Delta waves occur at a frequency of 0.5 to 3.5 cycles per second and generally occur in young children or during deep sleep. During an EEG, typically about 20-30 minutes of activity are evaluated and special attention is paid to the basic waveforms, but brief bursts of energy and responses to stimuli, such as light are also examined, (The university of Texas medical branch, http://www.utmbhealthcare.org).

Results from an EEG test can tell a lot about the patient and is a read by a neurologist. The waves recorded can be classified as normal or abnormal. Abnormal waves can indicate medical problems, whereas different types of normal waves can indicate various states or activity levels. The value of understanding the normal EEG lies in developing the foundation to provide a clinical basis for identifying abnormality. Knowledge of normal waveform variations, variants of normal EEG that are of uncertain significance, and fluctuations of normal EEG throughout the lifecycle from youth to the aged are essential to provide an accurate impression for clinical interpretation. When abnormality is in doubt, a conservation impression of 'normal' is proper. EEG produces a graphic display of a difference in voltages from two sites of brain functions recorded over time. Extra cranial EEG provides a broad survey of the electrocerebral activity throughout both hemispheres of the brain while intracranial EEG provides focused EEG recording directly from the brain through surgically implanted electrodes that are targeted at specific regions of the brain. (Tatum 2007). Information about a diffuse or focal cerebral dysfunction, the presence of interictal epileptiform discharges (IED's), or patterns of special significance may be revealed from an abnormal EEG. For the successful interpretation of an abnormal EEG, one must first understand the criteria necessary to define normal patterns. While a normal EEG does not exclude a clinical diagnosis (i.e. epilepsy), an abnormal finding on an EEG may be supportive of a diagnosis (i.e. in epilepsy), be indicative of cerebral dysfunction (i.e. focal or generalized slowing), or have nothing to do with the reason that the study was performed (i.e. in headache). It is in the clinical application of the EEG findings that imparts the utility of EEG. (Tatum 2007). Two important applications involving EEG wave classification are diagnosis of sleep disorders and construction of brain-computer interfaces to assist disabled people with daily living tasks.

Sleep occupies roughly one-third of a person's life and is indispensable for health and well-being. Sleep apnea is a disorder characterized by a ten-second or longer pauses in breathing during sleep. A person with sleep apnea cannot self-diagnose the presence of this disorder so in order to make diagnoses for sleep disorders, physicians usually need to study patient's sleep patterns through sleep recording. A typical sleep recording has multiple channels of EEG waves coming from the electrodes placed on the subject's head. The waves from a healthy subject are stable about zero and show relatively high variability and low correlation whilst the waves from a person with sleep difficulty show less variability and higher correlation. Measuring EEG signals is a non-intrusive procedure since it does not cause any pain to the subject. Sleep staging is the pattern recognition task of classifying sleep recordings into sleep stages continuously over time and is performed by a sleep stager. These sleep stages include rapid-eye movement (REM) sleep, four levels of non-REM sleep and being awake. Sleep staging is crucial for the diagnosis and treatment of various sleep disorders. In order to make many EEG-based applications practical enough for routine use, it is necessary to achieve high accuracy in EEG wave classification. For physicians specializing in sleep disorders, improving sleep stage classification accuracy can increase both their diagnostic accuracy and the speed with which they make diagnosis. (Min and Luo. n.d).

DIAGRAM SHOWING EEG SLEEP PATTERNS, (http://www.benbest.com)

Brain-Computer interfaces (BCI's) are currently being developed to facilitate the control of computers by people who are disabled. As disabled people think about what they want to have the computer do, their thinking is classified based on their EEG waves and

corresponding instructions are automatically executed by the computer. Accurate EEG wave classification is a critical requirement for computers to receive correct instructions. There are various kinds of BCI's with the most promising one being the P300 BCI using EEG signals. This is so because of its non-invasiveness, ease of use, portability and low set-up cost. In neuroscience, P300 refers to a neutrally-evoked potential component of EEG. (Min and Luo. n.d). Quantitative EEG signal analysis involves the transformation of the EEG signal into numerical values that can be used to examine selected EEG features. Once a specific feature of the EEG has been quantified, it can be displayed using various graphical methods such as topographic mapping or spectral trend monitoring. Other applications of quantitative analysis include automated event detection, intraoperative or ICU monitoring, and source localization. Normative databases of quantitative EEG features (such as the peak alpha rhythm frequency or amount of alpha reactivity) can be used for statistical comparisons in research studies. Statistical quantitative EEG analysis is not yet considered reliable as an independent measure of abnormal brain function for clinical purposes. Topographic mapping refers to the graphical display of the distribution of a particular EEG feature over the scalp or cortical surface. Advanced forms of topographic mapping attempt to display EEG activity as it might be seen at the cortical surface by superimposing a color or gray scale image of the EEG feature onto the cortical surface image taken from the subject's MRI. More simplified forms of topographic mapping create a graphic display of an EEG feature over an imaginary head surface. All methods of topographic mapping depend heavily on montage construction. (Fisch and Spehlmann 1999).

DIAGRAM SHOWING AN EEG TOPOGRAPHIC MAP, (http://www.cerebromente.org)

Automated event detection is a form of quantitative analysis in which certain signal characteristics are used to classify an EEG change. It is most commonly applied to the detection of electrographic seizures during epilepsy monitoring. Intraoperative EEG monitoring is performed using continuous routine EEG visual inspection alone or in combination with quantitative EEG monitoring. The most common application of intraoperative EEG monitoring is for carotid endarterectomy surgery. Thresholds for EEG changes at different levels of cerebral blood flow are used to alert the surgeon to the need to either shunt the patient or increase blood pressure. Continuous EEG and video monitoring is used to verify the presence of a seizure disorder, classify seizure type in patients with epilepsy and localize the epileptogenic zone (the area of the brain that must be removed in order to control seizures). The EEG signal can be acquired by radiotelemetry (using a radio transmitter worn by the patient) or by cable telemetry (via a lightweight cable directly attached to the patient). Systems that record the video in a digital format provide much faster access for review of events than those using videotape. In general, all patients with medically intractable epilepsy (e.g. vagus nerve stimulator implantation or brown surgery) should undergo epilepsy monitoring. (Fisch and Spehlmann 1999). Some other forms of quantitative analysis include Power Spectral Density (PSD), Chaos Analysis and Tsallis entropy. Power spectral density (PSD) is the frequency response of a random or periodic signal and tells us where the average power is distributed as a function of frequency. Intuitively, the spectral density captures the frequency content of a stochastic process and helps identify periodicities. In electroencephalography, the signal is usually a wave and the spectral density of the wave when multiplied by an appropriate factor, will give the power carried by the wave and this gives us the power spectral density (PSD) of the signal. This method of analysis can be used in many instances such as for patients with epileptic seizures. Epileptic seizures are characterized by various events of electrical activity which may rapidly change with time and may exhibit different frequency content. Studies have shown that seizure patients have a decreased power at high frequencies (8.25-30 Hz) relative to lower frequencies (0.25-8 Hz). It has also shown that there is an observed change of power spectrum in alpha frequency (8-12 Hz) and structural changes in EEG frequency composition just before the occurrence of spike during seizure.(Magosso et al. 2008).

DIAGRAM SHOWING POWER SPECTRAL DENSITY ANALYSING AN EEG WAVEFORM, (http://www.mathworks.cn).

Tsallis entropy is a generalization of the standard Boltzmann – Gibbs entropy and is defined as:

Constantino Tsallis is a physicist who came up with this solution based on the idea of maximum entropy. Tsallis entropy permits us to estimate the large-scale, long-term behavior of a system that is built up from a variety of spatially separated long-scale, short-term dynamics. The Tsallis entropy measure has proven to be useful on the analysis of some aspects of EEG signals. As for the methodology, no spectral entropies are used since the probability distribution is evaluated from the signal amplitudes. The ensuing entropic quantifier is useful for studying and detecting morphological changes such as spikes. (Murray and Tsallis 2004). EEG exhibits diversified time variations which is a weak and complicated signal compared to speech or the EEG fluctuations. There exists many ambiguous factors in the quantification of EEG data and careful deliberations are required in the direct analysis of the original EEG signal. Chaos analysis, which is a method for determining the statistical self affinity of a signal, is applied to EEG by decomposing the data into the real and imaginary parts at each frequency. By this approach, the band-limitation problem in EEG measurement can be avoided and the existence of the chaos in the fluctuation of EEG frequency component is verified. As a result of analysis, the maximum Lyapunov index is positive for most of the frequency components. Thus, it is shown that the fluctuations of the real and the imaginary parts at each frequency have the chaotic property. In other words, it is estimated that EEG is composed of a large number of frequency components with the chaotic property. (Masao 1999). Chaos analysis entails the use of the correlation dimension which gives a measure of the complexity of the underlying attractor of the system. (http://www.tm.tfh-wildau.de)

Alcoholism, in common and historic usage, refers to any condition that result in the continued consumption of alcoholic beverages, despite health problems and negative social consequences. Studies indicate that the proportion of men with alcohol dependence is higher than the proportion of women, 7% and 2.5% respectively, although women are more vulnerable to long-term consequences of alcoholism. The National Institute on Alcohol Abuse and Alcoholism researchers has identified five subtypes of alcoholics from a study of 1,484 people who met diagnostic criteria for alcohol dependence. These five types of alcoholics includes young adult alcoholics (31.5%), young antisocial alcoholics (21%) – most in mid 20's and more than half comes from families with alcoholism, functional alcoholics (18.5%) – middle aged, well-educated with stables jobs and families, intermediate familial alcoholics (19%) – middle aged with about half from families with multigeneral alcoholism and almost half have had clinical depression and 20% have bipolar disorder and the final type of alcoholics are the chronic severe alcoholics (9%) – mostly middle-aged individuals who had early onset of drinking and alcohol problems. (Moss et al. 2007) and (National Institute of Health 2007). Alcoholism facts are important to know since alcoholism is a type of drug addiction. Alcoholism facts include facts of alcohol such as physical and psychological dependence. Alcohol acts as a depressant on the central nervous system and this can lead to a decrease of activity, anxiety, tension and inhibitions. A fact of alcoholism is that alcohol affects other body systems as well. Gastrointestinal tract irritation can happen with erosion of the esophagus and stomach linings, causing nausea, vomiting and even bleeding. Additional alcoholism facts are that vitamins will not be absorbed properly, which can lead to nutritional deficiencies if alcohol use continues. Liver disease may develop and can lead to cirrhosis. The muscles of the heart may be affected and sexual dysfunction may occur in men causing problems with erections while women can cease having monthly periods. (Goodwin 2000).

Substance use disorders (SUDs) include disorders related to the taking of a drug of abuse (including alcohol), and represent the most common psychiatric conditions that can result in serious impairments in cognition and behavior. Many persons with SUDs have comorbid conditions that need to be considered in designing a treatment plan that incorporates neurotherapy. These include conditions such as Mild Traumatic Brain Injury (MIBI) or Attention – Deficit Hyperactivity disorder (ADHD), which may require separate neurofeedback treatment for those specific conditions either preceding neurofeedback treatment for addition, or incorporated into it. There are also conditions such as affective disorders and anxiety disorders that occur commonly in SUDs that may respond well to neurofeedback protocols for addictive disorders. These conditions may require separate assessments during the course of therapy to determine response and the need for changing protocols or adding other treatments i.e. medications or psychotherapy to integrate into the treatment plan. Acute and chronic drug abuse results in significant alteration of the brain activity detectable with quantitative electroencephalographic (QEEG) methods. The treatment of addictive disorders by EEG biofeedback was first popularized by the work of Eugene Peniston and became popularly known as the Peniston protocol. This approach employed independent auditory feedback of two slow brain conditions to produce a hypnagogic state. The patient was taught prior to neurofeedback to use what amounts to success imagery (of sobriety, refusing offer of alcohol, living confident and happy) as they drifted down into an alpha-theta state. Repeated sessions resulted in long-term abstinence, and changes in personality testing. (Budzynski, Evans and Abarbanel 2008).

Since the method worked well for alcoholics, it has been tried in subjects with mixed substance dependence and stimulant dependence – but with limited success until the work of Scott and Kaiser. They described treating stimulant abusing subjects with attention deficit type EEG biofeedback protocols, followed by the Peniston protocol, with substantial improvement in program retention and long-term abstinence rates. This approach has become known widely as the Scott-Kaiser modification (of the Peniston protocol). A third approach to neurofeedback in substance use disorders is to use QEEG- guided neurofeedback, although the efficacy of the method has not been studied as extensively. (Budzynski, Evans and Abarbanel 2008). EEG studies of the effects of alcohol can be divided into four topics: 1) the effects of acute administration of alcohol; 2) changes associated with chronic experimental administration of alcohol; 3) the effects of chronic alcohol abuse and 4) EEG concomitants of tolerance and abrupt withdrawal. The effects of acute alcohol ingestion on EEG rhythms parallel changes in the affective state and level of arousal of the subject. All vary as a function of both dosage and the rate of increase in blood alcohol level (BAL) over time. Begleiter and Platz (1972) reviewed the early literature and reached several conclusions. The percentage of alpha time is increased, as in the abundance of alpha. There is increased synchronization of the EEG pattern, greater stability of component waveforms with less dispersion and slowing in the dominant alpha frequency. EEG changes appear slight even in the presence of marked changes in mood and behavior. The findings that have emerged from the study of abstinent chronic alcoholic patients have been much less consistent and subject to numerous sources of error. In general, from these finds it can be concluded that definite and severe EEG abnormalities occur only in chronic alcoholics with clinically obvious signs of neurological deterioration. In those studies where percentage of alpha time and characteristics of the alpha rhythm have been shown to differ between non-deteriorated alcohol abusers and normals, it has not been possible to demonstrate that this was independent of the withdrawal process. One trend to emerge from this research, however, was the severity and advancing stage of the alcohol problem. (Knight and Longmore 1994). Electroencephalographic alterations have been described in alcoholic patients mainly in beta and alpha bands. Decreased power in slow bands in alcoholic patients may be an indicator of chronic brain damage, while increase in beta band may be related to various factors suggesting cortical hyperexcitability. Abnormalities in resting EEG have high heritable traits and are often associated with a predisposition to alcoholism development. The studies on the effects of alcohol dependence on EEG coherence can be summarized as lower frontal alpha and slow-beta coherence in alcohol-dependent patients with some topographical coherence abnormality differences between alcohol-dependent males and females. (Budzynski, Evans and Abarbanel 2008).A number of studies have identified sources of inter-individual variation in the EEG response to alcohol which may be genetic and related to a heightened future risk for alcoholism. For example, Ehlers and colleagues (1988) examined EEG activity before and after alcohol administration in 48 Native American Mission men. These men were assigned to groups based upon two hypothesized risk factors for future alcoholism; (1) the presence versus absence of a family history of alcoholism and (2) a higher versus lower degree of Native American ancestry. The results revealed that men at higher risk due to a higher degree of Native American ancestry exhibited a smaller increase in slow alpha activity following alcohol administration that men with <50% Native American ancestry. In a parallel analysis, high risk men with a family history of alcoholism were likewise found to exhibit a smaller increase in slow alpha activity following alcohol administration than their lower-risk, family history negative counterparts. From these results it can be seen that the EEG effects of Native American Heritage and a family history of alcoholism appears to be similar. (Kaufman 2001). In 1993 another case study was looked at when the electroencephalographic activity in 78, nonalcoholic men, 21-25 year old, at higher versus lower risk for future alcoholism based upon the presence versus absence of a family history of alcohol dependence as well as one other risk factor, namely, the presence versus absence of a personal diagnosis of Antisocial Personality Disorder (ASDP) (Bauer and Hesselbrock, 1993) was examined. The four groups of subjects were compared at baseline and at multiple time points following administration of a placebo beer and an alcoholic (0.32g/kg) beer. The EEG differences among the groups varied as a function of condition and time. For instance, at baseline, the EEGs of subjects with both risk factors for alcohol abuse contained significantly faster beta activity than the EEGs of subjects with either one or no risk factors. However, after subjects consumed the placebo beer, the interaction disappeared and was replaced by a main effect of family history (FH-pos > FH-neg) on fast alpha (10.9-12.5Hz) power. The FH effect remained until blood alcohol concentrations began to rise 10 minutes after subjects drank the alcohol beer. At that time, fast alpha activity in the family history positive group declined markedly to the same level as the FH-neg group. These demonstrations of a significant EEG response to a placebo and enhanced electroencephalographic sensitivity to the effects of a rising blood alcohol level, among high risk, FH-positive subjects agree with findings reported by Pollock and colleagues 1983, 1986. (Kaufman 2001). Certain limitations are associated with the EEG as a clinical diagnostic tool; these also apply to research data derived from it. As many as 15% of asymptomatic patients have abnormal EEG readings and the proportion of abnormal readings is even higher among populations with functional psychiatric disorders. Furthermore, the absence of an abnormal EEG record does not guarantee the absence of neuropathology. The accuracy of localization of the site of abnormality is variable and the EEG record may be affected by a range of factors unrelated to neuropathology such as blood sugar level. Despite these limitations, application of the EEG to the study of alcohol abuse has made a significant contribution to our understanding. Access to an ongoing record of the neuro-electrical activity of the brain has enabled exploration of the relationships between alcohol ingestion, subjective states, behavioral changes and electrical activity.

APPARATUS AND METHOD

In order for the end product of this research project to be a success we had to ensure all the fine details of the relevant methods put forward were up to mark and carried out precisely. The experimental and analytical methods were bulky and of extreme importance in obtaining our final objective but it were the smaller and less straight forward tasks of equal importance which had to be carried out first. This included sourcing and preparing both alcoholic and non-alcoholic patients for testing and acquainting ourselves with the machines in the Physiology lab at the Eric Williams Medical Sciences Complex.

EXPERIMENTAL METHODOLOGY:

Sourcing Patient:

The participation of patients in this study was entirely voluntary so obtaining people who were deemed suitable enough for testing would be a challenge. We set out performing this task by phoning friends whom we considered were suitable to test (i.e. those who never consumed alcohol before and those who consume it frequently and who have been doing so for many years now). Apart from just putting forward the question of whether he (since we narrowed out research to males only) would be interested in performing an EEG test, we found it necessary to brief the patient on relevant literature about the EEG (since many did not know what it entailed) as well as present them with a consent form stating the purpose of the study, the procedure and a protection for patients rights section where a signature from them would be needed. Both the literature and consent form worked hand in hand in our benefit since the volunteer saw the high level of knowledge and professionalism we possessed. Even though many friends turned down the offer, we still managed to allocate a handful for both alcoholic and non-alcoholic groupings. Still not satisfied with that turnout and being as ambitious as were are, we decided to visit rehab centers along the east-west corridor hoping they would lend a hand in our research. Frequent visits were made to both Mt. St Benedict rehabilitation center and Caura hospital rehab center where meetings were held with people in high authority. Our gesture was put forward at both centers and a positive feedback was given from Mt.St Benedict providing a letter be presented to them. The letter was prepared by our project supervisor at the department of Physics, University of the West Indies, St Augustine, and we presented it to the head at the rehab center who indicated there would be no problem in acquiring volunteers providing a batch of alcoholics were admitted in the coming weeks. Follow up phone calls were made over two months and in the last week of testing we were able to obtain one volunteer from the center for testing.

After sourcing our volunteers, under the guidance of our supervisor we were given a thorough briefing on the experimental apparatus. Close attention had to be paid since we had set our goals at making our general objective as clear as possible and also because of the high cost of the machine in front of us (cost in excess of US$100,000.00) which would result in us being extremely careful when handling all apparatus. When proper knowledge of all the equipment was gained, it was now down to the serious matter of testing our patients.

Preparing/ Testing Patient:

Respective meeting times were organized with our volunteers and transport was provided by us, the project students, to and from Mt. Hope hospital. Before testing patients we indicated to them that a proper night's rest the night before the test along with grease-free hair on the morning of the test were pre-requisites in obtaining successful results from the EEG. The first step in the testing of the patients required the volunteer to sign the consent form and fill out a form ticking "yes" or "no" to different medical diseases present on the sheet. The patient's information (name, date-of-birth [month/day/year], patient ID, Physician, technician, medication/s, history [left or right handed] was entered into the computer and saved for future reference. This was followed by obtaining the impedance screen which would show the impedance at the different points on the patient's head as obtained from the internationally recognized "10-20" method for electrode placement. An ideal impedance was one less than 5Kohms even though we tried to get it below 2Kohms. The international 10-20 system of electrode placement as described thoroughly in the introduction provides for uniform coverage of the entire scalp. It uses the distances between bony landmarks of the head to generate a system of lines which run across the head and intersect at intervals of 10% or 20% of their total length. The use of the 10-20 system assures symmetrical, reproducible electrode placements and allows a more accurate comparison of EEGs from the same patient and from different patients, recorded at the same or different laboratories. (Fisch and Spehlmann 1999). After obtaining the impedance screen, the patient was asked to sit on a chair where using a measuring tape we measured and marked out the electrode areas (using a marker) following the relevant steps from the 10-20 method. After obtaining these twenty one (21) points on the patient's head we then performed the task of attaching the electrodes to the respective electrode areas. Prior to this we first had to clean these areas using a TEN20 gel in a rigorous manner so as to remove the marker prints as well as clean the scalp properly to achieve a very low impedance. Upon cleaning an individual spot, a small amount of a conductive paste was placed in the "cup" of the electrode located on one end and this was then pressed onto the spot which was just been cleaned. This TEN20 conductive paste has adhesive qualities to hold electrodes in place and it plays the role of acting as a conductor to generate electricity from the scalp to the electrode. A cotton ball was then placed on top the cup of the electrode to ensure it doesn't move while the other end was inserted into the Cadwell easy writer 32 channels EEG amplifier which was connected to the computer. This method of cleaning followed by attaching the electrodes to the scalp was performed for all 21 locations on the head and an additional two electrodes were connected to both ear lobes as reference electrodes.

PICTURE SHOW ING ELECTRODES PLACED INTO CADWELL AMPLIFIER

When all electrodes were attached to the patient's head (as shown in diagram below), he was then slowly helped up from the chair and onto the patient's bed before which we placed a goggles over his eyes. A final electrode which played the role of the ground was then attached to an area slightly above the wrist and away from the palm of the hand. The next step entailed us giving the patient a briefing as to what we expected from him. We made it clear that there should be no talking, no moving, no tense jaw bites, no tense body and finally eyes should remain close throughout the duration of the experiment. We then explained the role of the goggles and the bright strobe it emits and we told the patient to remain as relaxed as possible when we emit the bright strobe. Then finally we explained the cumulative task in which the patient was asked to keep on subtracting 7 starting from 200 for a period of 15 seconds. We indicated to them that the subtractions should only proceed on our word and should cease as well on our word. Once they understood the instructions put forward to them we reclined the bed slightly, switched off the lights and started the experiment.

PICTURE SHOWING ELECTRODES AFTER CONNECTED TO PATIENT'S HEAD

The impedance button on the EEG machine was pressed to remove the impedance diagram from the screen. We then pressed the calibration button and visually observed the calibrated waves on the screen to ensure it was constant. Once this satisfied our taste, we hit the "run" button and this signaled the start off the experimental readings. For the first couple of seconds we observed the waves and ensured there wasn't too much noise visible (dark black lines). If some electrodes were seen to be giving noisy recordings, we stopped the experiment, reclined the bed so the patient can lie flat on his back, checked the impedance screen to ensure impedances remained within our range and then started back the experiment. Once we were happy with the waves present, we then either started emitting the bright strobe from the goggles or initiated the counting task. The strobe was flashed for 20 seconds with 30 second interval breaks in between while the patient was asked to count mentally for 15 seconds followed by a 30 second break in between. The purpose of the counting was to keep the patient alert and was mainly used when sleeping waves were detected on the screen from the EEG. Twelve (12) readings for both flash and count were obtained for each patient. When these readings were obtained this signaled the end of the experiment and the bed was adjusted to an upright position while the goggles were carefully removed from the patient's eyes. Since the electrodes were very fragile they were handled with care while being removed one by one from the patient's head. The information was saved on the computer system until we needed it for analysis.

PICTURE SHOWING ENTIRE EEG SETUP

ANALYTICAL METHODOLOGY:

On completion of the experimental methodology as described above we then set about analyzing the EEG data using the Neurometric Analysis System. Neurometric analysis of the EEG permits objective classification of both the nature of the abnormality and its magnitude. It provides a sound, extensively test data selection and analysis method, rigorously defined and accurate statistical evaluations relative to validated normals and the largest clinical QEEG database in the world. In Neurometrics, each extracted feature is subjected to a statistical evaluation, and compared to the distribution of values of the same features observed in normative (reference) database using multivariate statistical procedures. (Shuttlesworth 1999).

Our first task in analyzing the results of each patient was to transfer all their information to the "nx" program we were using and save it. Once this was completed we then chose a patient to analyze, clicked on "view EEG reading" and the results of the EEG test came up on the screen. The next step entailed us going through the entire test and highlighting a minimum of 2 minutes and 2 seconds of proper waveforms which we would use for the analysis. Since this experiment consisted of three parts; resting stage, counting stage and flashing light stage; we had to obtain 2 minutes and 2 seconds of information for each stage in every patient. We did each stage separately, obtaining the relevant maps and tables for it before going on to the next stage and obtaining the relevant information for that stage. We gathered maps and tables for both the monopolar absolute power () and the monopolar coherence of the EEG spectral bands. Power spectral density is described by the absolute power, expressed as or picowatts (pW) contained in the four common EEG frequency bands: delta (1.5 to 3.0 Hz), theta (3.0 to 7.5 Hz), alpha (7.5 to 13.0 Hz) and beta (13.0 to 20 Hz). The power at each electrode site for each frequency is measured and the total absolute power is the sum of the power values in each frequency band. (Schurr and Rigor 1990). The absolute coherence on the other hand gives a reflection of the joint variation in electrical activity between homologous electrode pairs. These measures are similar to an estimate of shared variance, meaning that power fluctuations in one hemisphere can be reliably used to predict power fluctuations in the other hemisphere. (Shuttlesworth 1999). When these maps and tables were saved and printed we then viewed the highlighted section of the waves we chose and removed some of it so that we only had 52 seconds of information left from the initial 2 minutes and 2 seconds. The information was saved and used to run in a special program in order to obtain the correlation dimension for the chaos analysis. Chaos analysis, which is a method for determining the statistical self affinity of a signal, is applied to EEG by decomposing the data into the real and imaginary parts at each frequency. The correlation dimension gives a measure of complexity for the underlying attractor of the system (http://www.tm.tfh-wildau.de). By this approach, the band-limitation problem in EEG measurement can be avoided and the existence of the chaos in the fluctuation of EEG frequency component is verified. As a result of analysis, the maximum Lyapunov index is positive for most of the frequency components. Thus, it is shown that the fluctuations of the real and the imaginary parts at each frequency have the chaotic property. In other words, it is estimated that EEG is composed of a large number of frequency components with the chaotic property. (Masao 1999). We kept a high degree of professionalism when performing both the experimental and analytical methods in this research project since we always had our minds set on accomplishing our main goal of making our general objective as clear and precise as possible.

Electrode

Time →

Fp1

-10.64

-7.42

-8.12

2.52

-7.00

-7.28

-4.90

-4.20

-0.56

Fp2

6.02

7.28

-6.16

-5.74

0.28

-10.92

-8.26

-2.10

-0.28

F3

-11.20

-10.08

-3.22

0.98

-4.06

-3.78

0.84

-3.92

2.52

F4

1.26

11.76

-0.56

-2.10

-5.60

-6.02

-3.36

2.38

-5.32

C3

-11.62

-8.40

0.28

-5.04

-2.38

-4.06

-4.48

-4.90

-2.38

C4

-8.40

-7.14

3.36

-4.90

-6.86

-4.06

-4.76

-2.52

-15.40

P3

-6.30

-11.20

5.88

-4.62

5.32

2.10

6.44

1.54

5.18

P4

0.42

-3.22

0.14

4.48

-2.66

0.00

2.94

4.76

-6.30

O1

-6.44

-1.68

2.10

-5.18

1.40

-5.04

0.70

-3.50

-6.44

O2

7.28

2.38

4.62

-1.96

-2.94

-1.40

-2.94

-1.68

-0.56

F7

-3.50

-6.30

2.66

-4.76

3.64

-4.20

-0.28

-1.40

0.56

F8

24.78

-4.20

-5.04

-2.66

-0.70

2.10

-0.14

-1.12

-5.32

T3

-9.80

-9.52

-4.90

-4.90

-4.20

-5.60

-1.40

-5.18

-2.38

T4

-25.34

-11.06

6.16

-2.94

-5.04

-4.34

-4.48

-1.96

-3.78

T5

0.98

5.88

2.38

2.80

5.32

-0.84

0.28

1.40

1.54

T6

16.52

4.62

2.94

-1.82

5.74

8.68

3.36

1.12

-4.34

Fz

4.62

-4.34

-7.42

-0.42

-1.68

-2.52

-3.78

-1.68

-4.20

Cz

-1.68

-2.24

-3.22

-3.36

3.36

0.98

0.42

0.14

3.08

Pz

0.14

-1.54

-4.90

-0.70

-4.90

-0.14

-3.64

-1.12

-13.58

Oz

-18.06

-7.70

-10.22

-0.84

-0.14

-0.42

-1.12

-3.78

-19.74

Fpz

-0.14

2.80

-5.32

-4.34

0.00

-7.84

-3.50

1.54

-7.42

TABLE 1:

Table 1 indicates a data matrix for 0.1 second for the chaos analysis. This is the information obtained for 0.1 second for all relevant electrodes and information was obtained for 52 seconds for each chaos analysis.

DISCUSSION OF RESULTS

Alcoholism is a disorder of great destructive power. The damage it causes falls not only on alcoholics themselves but on their families and friends as well. Such a serious and widespread problem demands to be studied, yet our general knowledge about alcoholism is astonishing. Experts who have studied alcohol abuse doubt that any such entity as alcoholism exists. The reason is that alcoholism has an unstable, chameleon-like quality that makes it difficult to pin down at any given time. To be trusted, information should come from meticulously conducted long-term prospective studies in which individuals are selected for study before they develop problems with alcohol and then followed for many years. In the search for answers about alcoholism, longitudinal study offers many advantages. For one thing, since alcoholism is a chronic affliction, both its victims and the nature of their disability change over time. Thus, a cross-sectional view of an alcoholic's life will never adequately capture the nature of the disorder. Second, alcoholism is a malady about which there are no black and white answers, and longitudinal study is far better suited than cross-sectional study to elucidate clinical "grays". Third, unlike most habits and conditions, alcoholism has direct, as well as indirect, effects upon the central nervous system. Alcoholism affects personality and perceptions about the past so markedly that the true facts of an alcoholic's life can often be discovered only by prospective study. (Vaillant 1995).

Alcohol on the brain:

There are many adverse effects of alcohol on the brain namely it contracts brain tissue, depresses the central nervous system and destroys brain cells. Brain cells are different to many other cells in the body since they do not regenerate. Therefore heavy consumption of alcohol over long periods of time can cause serious problems with both cognitive and memory tasks since there would be fewer brain cells. When alcohol reaches the brain it interacts with receptors on some cells which results in interference in communication between nerve cells. It enhances the inhibitory GABA and weakens the excitatory neurotransmitter glutamine thus increasing the effect of making the person feel sluggish or lazy. (http://www.bloodalcohol.info).

Monopolar Absolute Power:

The monopolar absolute power, expressed in terms of picowatts or microvolts squared, is an expression of the average amplitude of EEG within a given frequency band. Monopolar measures assess the power recorded at a specific electrode site, with the power ranges defined in terms of the traditionally accepted EEG frequency bands of delta, theta, alpha and beta. (Shuttlesworth 1999). In this research project we tested the monopolar absolute powers of both alcoholics and non-alcoholics during the three stages; resting, flashing and counting. During the resting stage for alcoholics (FIG 1A) we observed alpha waves being dominant with a power of approximately 15.0 while beta, delta and theta waves were all low power. For the non-alcoholic (FIG 1B) we observed both alpha and beta waves being dominant with a power of 25.0 on average throughout and a slightly higher power of approximately 35.0 uV^2 around the occipital lobe (O1 and O2). Generally during the resting stage, alpha waves tend to dominate in a normal person and this was proven when we observed its dominance being more prominent in the non-alcoholic as compared to the alcoholic. The presence of the moderate-high power beta waves in the non-alcoholics indicates the high level of alertness even though they were in the resting stage. In alcoholics, the low power beta indicates the lack of alertness. This fact goes to show one of the many effects alcohol has on the brain, that being its ability to not respond or be alert to events as quickly as a non-alcoholic. From the line graphs plotted, FIG 7A and FIG 7B, a clear indication that non-alcoholics possess a greater overall power than alcoholics during this stage is seen. Also visible from the graphs are that peaks are observed for all brain waves for both groups in the vicinity of the O1 electrode (Occipital Lobe). The occipital lobe is responsible for visual processing and the peaks in this lobe are present as a result of eye lids not being completely opaque since its skin is the thinnest in the body, (Gladstone et al. 2002) resulting in light still entering the eye even if it is completely shut and in a resting state. The small amount of light entering the eye would be processed in the occipital lobe resulting in peaks present in the lobe.

The next stage entailed us sending off a bright strobe into the patient's right eye and again we observed notable differences in the results. FIG 2A illustrates the topographic map showing absolute power during this flashing stage for an alcoholic. We observed low power alpha waves, low-medium power beta waves (medium power around O1 and O2 electrodes), medium power theta waves in O1 and O2 electrodes and medium to high power delta waves in and around Fp1 and Fp2. However, for the non-alcoholics (FIG 2B) we observed medium-high power alpha waves in and around O1 and O2 and extremely high power beta waves in and around O1 and O2. Generally, in a normal person, beta waves are dominant during arousal and due to the flashing strobe this dominance of beta waves was expected to be seen in and around the Occipital lobe (O1 and O2). This was what we exactly saw FIG 2B illustrating for the non-alcoholic. The power of the beta waves in this region in the alcoholic was basically low to medium which again illustrated the alcoholic's ability to not be as alert to relevant events. What was prominent in the alcoholic's topographic map was the dominance of delta waves which are of the slowest frequency and greatest amplitude. This proved the fact that the alcoholics were slow in responding to the flash since delta waves in a normal person are normally dominant when the person is in a deep, dreamless sleep. The medium power alpha waves present in the non-alcoholic symbolizes the fact that they still expressed a high degree of relaxation/reflection during the flash. Graphs 8A and 8B illustrate once again the dominance in total overall power present in the non-alcoholics. A proper representation of the dominance in beta waves during this stage is clearly seen from the both graphs, however, one thing which is similar though is the presence of peaks, even though of different powers, at the O1 electrode. This again is due to the fact that the eye lid isn't completely opaque and light from the flash still enters the eye and is being processed in the occipital lobe of the brain since as mentioned before, visual processing takes place here.

The third and final stage which we tested to obtain results for the absolute power was the counting stage. Generally for this stage, which includes a high degree of arousal, we would expect beta waves to be dominant and we would expect to see this dominance mainly in the occipital lobe and frontal lobe since it deals with problem solving. FIG 3B illustrates this for the non-alcoholics in that we see beta waves being dominant in and around the O1 and O2 electrodes with moderate to high power. However, we observe in the beta frequency that the absolute power in the frontal lobe (Fp1 and Fp2) is low whereas the power in this lobe with the theta frequency is moderate to high for the non-alcoholic. Since the counting task took place in periods of 15 seconds with 20 second breaks in between, the patient would have been able to get accustomed to it and hence since it would become normal to the patient this would have been likely to result in the presence of the high power theta waves. From FIG 3A which illustrates the absolute power during this counting stage for alcoholics we can observe moderate power beta waves in both occipital and frontal lobes while we also see low to moderate power alpha and delta waves as well. The dominance of both the alpha and delta waves in these lobes indicates that even though the patient was counting the brain was basically in a "relaxed" or "non-aroused" state due to the effect of alcohol again. Low power beta waves in the alcoholic as compared to the high power beta waves in the non-alcoholic in the occipital lobe was once again due to the lack of alertness or lack of effectiveness in the brain of the alcoholic. Graphs 9A and 9B provide clearer indication for these differences. Peaks of obviously different intensities in both graphs are observed in both Fp1 and O1 electrodes (frontal and occipital respectively) since these lobes are responsible for problem solving and visual processing respectively. We see both alpha and beta waves being dominant in non-alcoholics as compared to the alpha and beta waves in the alcoholics. Since these two waves depend highly on the level of rest and arousal respectively, it is generally expected to notice lower levels of these both factors in the alcoholic since the response of the brain is very small. Once again we see the total overall power being dominant in the non-alcoholic meaning the effective use of one's brain which hasn't in any way been affected by alcohol abuse (alcoholism) is greater than one's brain which has been abused by alcohol (alcoholic).

Absolute Coherence:

Coherence measures give us a reflection of the joint variation in electrical activity between homologous electrode pairs. Coherence functions measure waveform similarity as a function of frequency. These measures are similar to an estimate of shared variance, which is an expression of the percentage of time that power fluctuations in one hemisphere can be reliably used to predict power fluctuations in the other hemisphere. Hypercoherent relationships exist when the moment to moment fluctuations in the EEG power in one hemisphere are reliably statistically associated with power fluctuations in the other. A hypocoherent relationship exists when it is not possible to predict power fluctuations from one hemisphere to the other; that is, they are out of synchrony with each other. (Shuttlesworth 1999). Generally, what is expected with absolute coherence was what we saw from the topographic maps and graphs and this was that the interhemispheric coherence scores from homologous brain sites are generally greater for alcoholics in the slower frequencies (delta and theta brain waves) but greater for non-alcoholics in the higher frequencies (beta and alpha brain waves) (Coutin-Churchman et al. 2006). FIG 4 (A&B) which illustrates topographic maps for the absolute coherence of alcoholics and non-alcoholics respectively for the resting stage gives us a perfect indication of this deduction. In Fig 4A we observe the highly coherent theta waves around O1 and O2 while in Fig 4B we observe the highly coherent beta waves in and around Fp1 and Fp2. This observation goes to show the dominance of the slow frequency waves in alcoholics which illustrate a lack of alertness as compared to the dominance of the higher frequency beta waves in non-alcoholics who possess greater alertness and awareness. The topographic maps from Fig 4 A&B indicate the high coherence of both theta and beta waves but what it didn't indicate was the dominance of alpha waves in the Fp1-Fp2 electrodes in both groups as seen in graphs 10A and 10B. Dominance of slower frequency waves in alcoholics and higher frequency waves in non-alcoholics was expected and was obviously seen, however, since this was the resting stage and the patient's eyes were closed and body's relaxed then it was obvious that alpha waves would be dominant and highly coherent, more so in the non-alcoholic than the alcoholic.

Chaos Analysis:

Chaos analysis, which is a method for determining the statistical self affinity of a signal, is applied to EEG by decomposing the data into real and imaginary parts at each frequency. The correlation dimension, being one of the characteristic invariants of non-linear system dynamics, gives a measure of complexity for the underlying attractor of the system. The equation for the correlation integral is given by:

Where H is the Heaviside step function. The determination of the correlation dimension of EEG recordings from subjects has been proven useful since it has been reported that the dimension increases with the level of mental activity. A dimension in the vicinity of 10 is normally reported for patients involved in a mental task. (Sarbadhikari 2005). Graph 15 illustrates this deduction since it can clearly be seen that non-alcoholics, who tend to have a greater mental activity as proven from the analysis by absolute monopolar power, possess a greater correlation dimension as compared to alcoholics during this counting stage. Large variations of correlation dimension between the two groups in this stage are observed in the frontal electrodes (Fp1, F7 and F8) which are all located in the frontal lobe where problem solving takes place. The dominance of the correlation dimension of non-alcoholics over alcoholics is clearly depicted here.

A less random dynamical behavior (correlation dimension) indicates less information processing in the brain due to the hyper-synchronization of the EEG. (Kannathal et al. 2005).Graph 13 illustrates the resting stage and again here we observe non-alcoholics having generally a higher correlation dimension than alcoholics. This indicates that the level of electrical activity in the brain of the non-alcoholic is greater than that for the alcoholic which results in the greater degree of alertness that the non-alcoholic possesses. In graph 14 we however experience the opposite since in this case the alcoholic possessed a high correlation dimension in general over the non-alcoholic. The non-alcoholic dominated in the occipital and frontal lobes which are the lobes required for visual processing and mental activity respectively. This dominance by the non-alcoholic in these lobes during this flashing stage indicates that there response/level of alertness to the flash was greater than the alcoholic. The dominance by the alcoholics throughout the other electrode sites indicates that they were not necessarily as relaxed at these sites as compared to the non-alcoholic. This represents that during relevant stages (in this case the flashing stage), the non-alcoholic was more alert at the electrode sites which were important in processing the information as compared to the non-alcoholic. At the sites which were not needed to process relevant information the non-alcoholic was more relaxed than the alcoholic. This showed that the alcoholic's brain isn't as coordinated and effective as compared to the non-alcoholic, who showed greater levels of alertness when it was needed at the respective sites.

CONCLUSION

Just as a tree is known by its fruit, alcoholism is known by its problems. Alcohol calories may result in overweight, things may be said while drinking which should not be said at any other time, a minor traffic offense may have major consequences in the case of a breathalyzer test. So problems, yes, but alcoholism? The verdict lies in the hands of the observer. Moderate drinkers may at times be more indulgent but seeing these things don't happen frequently, does this make the person an alcoholic? If not, what basically is the major characteristic of an alcoholic? The answer to this is based on the vulnerability of the person. Being vulnerable to alcohol results in the ability to not say "no" and this in turn results in the frequent consumption of it, which basically is the major characteristic of an alcoholic. The volume of alcohol a person consumes is a small factor which is over-shadowed by the frequency in which the person does it and this is the major difference between a moderate drinker and an alcoholic. (Goodwin 2000). Being the type of disease it is, alcoholism has many adverse effects on all major organs of the body namely the brain.

The main objective of this experiment entailed the analysis and comparison of EEG data of alcoholics and non-alcoholics. Several alcoholic and non-alcoholic volunteers were obtained and EEG tests were performed on each individual to obtain this necessary data. From an EEG test we obtain electrical signals from the brain via electrodes attached to the surface of the head. The brain, which is the center of the nervous system, controls all organ systems of the body by either activating muscles or by causing secretion of chemicals such as hormones. The main significances of this research project required us to observe the effects which alcohol has on one's brain by comparing the EEG results of the alcoholic with that of the non-alcoholic. Three analytical methods which include; power spectral density, absolute coherence and chaos analysis were used to portray these EEG results so that we could have gotten a better picture of the major differences.

Basically, all three methods in their own sense gave us the same conclusion, that being alcoholics were generally less alert than non-alcoholics. EEG power is a trait marker for alcoholism and from this analytical method what we generally observed was that non-alcoholics possessed a greater overall power than alcoholics which simply meant that the effect use of the non-alcoholic's brain was greater than the effective use of the alcoholic's. We can also conclude that the higher frequency alpha and beta waves are more dominant in the non-alcoholic as compared to the alcoholic and this is due to their greater level of alertness. Speculation can therefore be made that decreases in EEG power are a morbid effect of long term alcohol abuse. From the absolute coherence we basically observed that the higher frequency alpha and beta waves were generally more dominant in the non-alcoholic resulting in their high level of alertness, as compared to the dominance of the lower frequency theta and delta waves in the alcoholic. What conclusion can be drawn from this observation was that in the non-alcoholic there was dysfunctional brain connectivity generally in the slower frequency waves while the alcoholics experienced the dysfunctional brain connectivity in the higher frequency waves. Apart from this general conclusion, from the graphs plotted for all three stages we observed that alcoholics possessed somewhat of a high absolute coherence in the alpha frequency. From the chaos analysis which involves the correlation dimension since it is one of the characteristic invariants of non-linear system dynamics, we observed a similar trend. Since the correlation dimension increases with the level of mental activity, we observed that non-alcoholics generally possess a higher dimension since the effective use of their brain is greater than that of an alcoholic. Generally it can be concluded that cognitive and mental activity is associated with a higher correlation dimension in the EEG. This implies that the correlation dimension is a sensitive parameter in the analysis of electrical brain activity.

Alcoholism is a type of drug addiction and it can affect a person economically, socially and as we saw from this project, mentally. The mental effect of alcohol is very disturbing since the brain is the control center for all the organ systems in the body. The EEG test is very useful in diagnosing this disease in a patient since it deals directly with electrical activity in the brain. It is known that 75% of the EEG is inherited and since alcoholism is a genetic disease, the EEG test is very useful in diagnosing a patient who possesses these genetic traits. Apart from the mental effect of alcoholism, it is a major social, economic and public health problem. Alcohol is involved in more than half of all accidental deaths and almost half of all traffic deaths. It also acts as a depressant and accounts for a high percentage of family break ups and suicides.

George Washington, in his letter to Thomas Green, dated March 31st, 1789 stated, "An aching head and trembling limbs, which are inevitable effects of drinking, disincline the hands from work" (http://www.notable-quotes.com). From this research project, the mental effects which we saw alcohol having on the brain can surely decrease productivity in a nation striving for excellence. The invention of the EEG has been remarkable for it can be used in many aspects of neurology in this present day.

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- http://www.notable-quotes.com

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