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At Mayfield, we work with diagnostic imaging providers in the Greater Cincinnati-Northern Kentucky region to obtain images of the brain and spine and interpret them with expertise and care. Patients and referring physicians can rest assured that we will lay the groundwork for a diagnosis of utmost accuracy. To make an appointment call Make an Appointment. How does an EEG work? Figure 1. A sample EEG recording showing a focal spike typical of a seizure.
Mayfield services In neuroscience, a picture is worth a thousand words. Health Home Treatments, Tests and Therapies. Why might I need an EEG?
There may be other reasons for your healthcare provider to recommend an EEG. What are the risks of an EEG? Certain factors or conditions may interfere with the reading of an EEG test.
These include: Low blood sugar hypoglycemia caused by fasting Body or eye movement during the tests but this will rarely, if ever, significantly interfere with the interpretation of the test Lights, especially bright or flashing ones Certain medicines, such as sedatives Drinks containing caffeine, such as coffee, cola, and tea while these drinks can occasionally alter the EEG results, this almost never interferes significantly with the interpretation of the test Oily hair or the presence of hair spray How do I get ready for an EEG?
Your healthcare provider will explain the procedure to you and you can ask questions. You will be asked to sign a consent form that gives your permission to do the procedure. Read the form carefully and ask questions if something is not clear.
Wash your hair with shampoo, but do not use a conditioner the night before the test. Do not use any hair care products, such as hairspray or gels. Tell your healthcare provider of all medicines prescription and over-the-counter and herbal supplements that you are taking. Discontinue using medicines that may interfere with the test if your healthcare provider has directed you to do so. Do not stop using medicines without first consulting your healthcare provider.
Avoid consuming any food or drinks containing caffeine for 8 to 12 hours before the test. Follow any directions your healthcare provider gives you about reducing your sleep the night before the test. Some EEG tests require that you sleep through the procedure, and some do not.
If the EEG is to be done during sleep, adults may not be allowed to sleep more than 4 or 5 hours the night before the test. Children may not be allowed to sleep for more than 5 to 7 hours the night before.
Avoid fasting the night before or the day of the procedure. Low blood sugar may influence the results. Based on your medical condition, your healthcare provider may request other specific preparations. What happens during an EEG? Generally, an EEG procedure follows this process: You will be asked to relax in a reclining chair or lie on a bed. Changing the reference electrode is similar to flooding the landscape with water.
While the sea level changes, the absolute shape of the landscape is completely unchanged. This is discussed in more detail in Michel et al. A stable electrical connection between electrode and scalp is key to recording clean EEG signals. However, dead skin cells, oily skin secretions sebum , and sweat accumulate on the scalp and constitute a wall of electrical resistance as they do not propagate electrical activity well.
EEG systems generally offer software or hardware-based quality indicators where the impedance of each electrode is visualized graphically. Green colors and low impedance values typically imply high recording quality, while red colors and high impedance values imply low recording quality. In other words: Only when impedances are low you can be absolutely sure that the recorded signal reflects the processes inside of the head rather than artefactual processes from the surroundings.
Therefore, whenever you collect EEG data, make sure that impedances are as low as possible. No hair care products should be applied hairspray, conditioner, wax or gel, for example , and hair should be completely dry. Also, instruct respondents to not wear any hair pins or clips as they will have to be removed anyway. Wet hair and other treatments will cause higher impedances. Another benefit of plainly washed hair is that you can move hair much better away from the EEG sites hair is a poor conductor.
After putting on the EEG cap and before plugging in the electrodes, you can press an alcohol-dipped Q-tip into each of the electrode sockets and rub it gently, but with purpose between two fingers.
Remember to instruct respondents to close their eyes as the evaporating alcohol can cause negative reactions to the eye. Always wait until the alcohol is completely evaporated before you proceed. Some conductive pastes are abrasive and contain pumice stone particles similar to a facial mask.
In this case, you can lower impedances massively by dipping a Q-Tip or a wooden stick with a cotton swab into the paste and then applying the paste to each of the electrode sockets.
Again, gently push down and rub the stick. Then, fill the socket with paste and put in the electrode. Instead, you can simply paste the gel into the socket. It is noteworthy not to overdo the gel application. If you apply too much gel, you might create gel bridges between neighboring electrodes, causing invalid and artefactual data that is hard or impossible to save during post-processing. Once the voltage has been picked up by the electrodes, the continuous, analog signal has to be amplified and digitized in order to be stored on a computer.
As your brain is constantly active, there are continuous fluctuations and variations of the generated voltages. EEG systems, however, take discrete snapshots of this continuous process, generating samples of data — similar to pictures taken by a camera. EEG systems differ in the sampling rate the number of samples per second they can take.
Similar to oscillations, sampling rates are expressed in samples per second with the unit Hertz Hz — an EEG system with a sampling rate of Hz can take samples per second, for example. If you are interested in measurements with higher time precision, you should collect EEG data at a higher sampling rate i. If you are interested in frequency-based analyses such as prefrontal lateralization of alpha or beta bands , a sampling rate of Hz can be sufficient. Additionally to the digitization, the EEG signal is amplified.
That is the reason why EEG systems are so expensive. Some EEG systems are modular, allowing you to arbitrarily combine electrodes and different kinds of amplifiers while other EEG systems come as fixed combination of electrode grid and amplifier box. After the signals have been digitized and amplified, they are transmitted to the recording computer. This is either achieved through a wired connection via USB, for example or wirelessly e.
Wired amplifiers are still common in academic research institutions, neuroscience, and psychology labs. In contrast, commercial labs and neuromarketing agencies often use wireless EEG headsets as they allow respondents to freely move around and explore their environment without being bound to a test station at the lab. Always make sure your data is as clean as possible, meaning the collected data reflects brain activity only. Sounds simple in theory — in practice, however, there is a but.
As the electrodes will pick up electrical activity from other sources in the environment, it is important to avoid, minimize or at least control these kinds of artifacts as best as possible:. Muscle activity generates electric currents that are picked up by electrodes.
The closer the muscles are to the electrodes, the stronger their impact on the recording will be. Particularly the activity of facial muscles forehead, cheek, mouth , neck muscles and jaw musculature has severe effects on EEG recordings. Clenching should be avoided at all costs — instruct respondents to avoid chewing or tensing their jaw. As the heart is muscle, it also affects EEG data quality.
Hearts cannot be simply instructed to stop, you have to rely on signal decontamination procedures to remove ECG noise from EEG recordings. Ideally, you can monitor heart rate with an optical sensor e. Eye movements horizontal and vertical affect the electrical fields picked up by the electrodes. Vertical eye movements up-down look more sinusoidal, while horizontal eye movements right-left look more box-shaped.
The eye has a strong electromagnetic field that is established by the millions of neurons in the retina. Moving your eyes also shifts the electrical field generated by the eye ball.
Similar to eye movements, blinking interferes with brain signals quite a bit. If respondents blink while a certain stimulus is shown on screen, the EEG might not reflect the cortical processes of seeing the stimulus. As an EEG expert, you might tend to exclude this trial from the analysis since the EEG data does not contain relevant information. However, if blinking occurs non-systematically throughout the recording, attenuation based on statistical procedures such as regression and interpolation or Blind Source Separation might be more appropriate.
In this case, contaminated data portions are replaced with interpolated data using surrounding data channels or time points. Movement of an electrode or headset movements can cause severe artifacts that are visible in the affected channel or in all channels.
Reasons for this are manifold: The EEG headset becomes loose, an electrode loses contact with the socket. Particularly when impedances are poor, line noise is stronger. If the reference electrode is affected, the captured line noise is propagated to all other electrodes.
Fortunately, the cognitive frequencies of the brain are often below the 50 or 60 Hz range, allowing you to filter your data accordingly or focus on the frequencies of interest. Swaying and swinging can have strong effects on the recording.
Especially head swinging or banging changes the water distribution, which affects the electrical properties and fields generated by the brain. When it comes to EEG analysis and feature extraction, you might easily feel overwhelmed by the huge list of pre-processing steps you have to accomplish in order to get from raw signals to results. It certainly requires a certain level of expertise and experience, particularly when it comes to signal processing, artifact detection, attenuation or feature extraction.
Any of these steps require informed decisions on how to best emphasize the desired EEG processes or metrics of interest. What is a valid signal to you might be noise to anyone else. Big amplitude, slow, positive wave prominent in frontal electrodes. Swallowing artifact. Huge wave similar in all channels.
Fortunately, some modern EEG systems come with an autopilot for data processing — they take the lead and apply automated de-noising procedures or automatically generate high-level cognitive-affective metrics which can be used in order to get to conclusions much faster.
The goal of event-related EEG paradigms is to collect those brain processes which are triggered by external stimuli. Event-related EEG paradigms present stimuli repeatedly — times or more, for example. At the same time, stimuli are shown just very briefly for to ms. There is continuous and ongoing EEG activity as well as random noise completely unrelated to the onset of a stimulus continually occurring.
When you present a stimulus, you trigger stimulus-related EEG activity. In order to uncover the stimulus-related EEG data from the unrelated ongoing data, the stimulus is shown several times — 50 times or more, for example. At the end of the data collection, you will have 50 trials, which are data portions time- locked to stimulus-onset and typically range from about ms prior to stimulus onset to ms after stimulus onset.
Each trial is a time-course of data at each electrode. The selection of data portions from the continuous EEG recording is called epoching or segmentation sometimes followed by a baseline correction of each trial where the average of the EEG data before each stimulus is subtracted from the data after the stimulus.
After the exclusion of epochs containing artifacts or the correction of data due to blinking, for example , the remaining epochs are averaged sample by sample, resulting in an average time-course of EEG data. By averaging the EEG time-courses of all trials, only the stimulus-related EEG activity survives while the unrelated random background noise is attenuated the more repetitions you complete, the cleaner the event-related EEG data will be.
The remaining average EEG waveform is the event-related potential , which reflects the average stimulus-related EEG activity as triggered by a specific stimulus. Research has identified ERPs for all sensory modalities — vision, touch and sound, olfaction and haptic stimuli. All of these sensory stimuli trigger event-related EEG activity.
You have the choice: You can plot ERPs either as time-course time-locked to stimulus onset or as sequence of voltage maps that change their distribution characteristics over time dependent on stimulus properties or different internal states. Dependent on where the voltages are strongest positive and negative poles , you can infer which brain regions are active at a given time.
Often, scientists compare ERPs of different experimental conditions — ERPs elicited by face stimuli compared to houses, for example.
Alternatively, you can compare ERPs of different respondent groups — children suffering from Autism spectrum disorder vs. In both situations, your analysis focuses on the differences in ERP latency, amplitude or topographic distribution at certain time-points time-locked to stimulus onset between conditions. As you cannot get an ERP from a single stimulus presentation the EEG data will contain both stimulus-related and stimulus- unrelated aspects , you need to repeat the presentation think of repetitions or more.
Event-related paradigms assume that the EEG data of each single trial is precisely time-locked to stimulus-onset. This requires that any stimulus onset markers must have been sent precisely in the moment of stimulus presentation. Whenever there is a randomly varying delay between the onset marker and the actual onset of a stimulus, the exact time-locking of the EEG data to stimulus onset cannot be guaranteed.
As a result, the average ERP waveform might be washed out or vanishes completely because the single trials were not perfectly aligned to the respective stimulus onsets.
The only way to be absolutely sure about the actual stimulus onset on screen, for example, is to attach a photodiode on the stimulus presentation screen and store its brightness levels with the other data. Whenever a stimulus appears on screen, the photodiode signal changes, allowing you to properly align the data to the true stimulus onset instead of a potentially incorrect onset marker.
You can find more details on collecting and analyzing ERP paradigms in Luck ERP designs are limited to a specific set of brain activity triggered by sensory stimuli. However, the brain is a continuous oscillator and generates rhythmic activity even in the complete absence of stimuli — during sleep, for example.
In order to tap into the brain activity that drives our behavior, our thoughts, motivations and emotions, a different analytic approach is required, which is based on the analysis of frequencies. What are the major frequencies that are contributing to the brain mix? How do these frequencies vary dependent on changes in internal states or environmental factors? You learned before that the brain generates primarily low frequencies between 1 and 80 Hz.
These can be classified into specific frequency bands such as delta, theta, alpha, beta and gamma and associated with brain processes in specific regions underlying attention, cognition and emotion. Compared to ERPs, frequency analyses are more closely linked to physiological processes and brain structures.
Another benefit of frequency analyses is that much less data is required to arrive at conclusions. However, frequency-based analyses come with a cost: In contrast to ERP designs that allow insights into millisecond changes of voltages, frequency-based EEG measures have much less time precision. Frequency-based analyses are recommended whenever testing time is limited and your analysis is not about the precise timing of stimulus-related activity but rather about the general mental, affective or cognitive state of the respondent.
Frequency analyses are particularly useful in studies of cognitive-affective states — when EEG is measured while respondents attend to media content, reflect on the quality of products or food, or navigate websites or software interfaces, for example. Some of the most widely used terms in frequency analysis is power, which reflects the strength of a specific frequency in the signal.
Higher power means that the EEG signal contains a specific frequency to a larger extent. You could also say that the EEG signal is driven by a specific frequency.
If you would like to get started with frequency-based analysis, find yourself a respondent and run one of the oldest and most replicated EEG experiments:. Eyes open. Record EEG data for 2 minutes from respondents and simply instruct them to keep their eyes open they are certainly allowed to blink. Eyes closed. Record EEG data for another 2 minutes and instruct respondents to close their eyes and focus on their inner thoughts and mental images. When you analyze both conditions separately with an FFT and extract the frequencies underlying the spontaneous EEG data, you will likely notice that the condition eyes closed shows a higher frequency power in the alpha band 8 — 12 Hz in occipital channels compared to the condition eyes open.
This effect of reduced alpha power when opening the eyes is called alpha blocking and has been initially described by Hans Berger in Over the last decades, frequency-based analyses of EEG data have become much more sophisticated.
One of the more advanced frequency-based metrics is frontal asymmetry, or frontal lateralization. Researchers have consistently found that higher band power in left vs. Additionally, larger left-frontal band power may serve as an index of engagement-related emotions such as joy, while larger right-frontal band power might indicate negative emotional states disgust, fear or sadness, for example.
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