3rd Lecture 2024.pdf

Mælitækni og lífsmörk 2024 The Origin of Biopotentials, EEG, EOG and GSR Dr. Paolo Gargiulo, Professor  Electroencephalogram (EEG) EEG Trace; Alpha (8-13 Hz) Hans Burger (1873-1941)...

Mælitækni og lífsmörk 2024 The Origin of Biopotentials, EEG, EOG and GSR Dr. Paolo Gargiulo, Professor  Electroencephalogram (EEG) EEG Trace; Alpha (8-13 Hz) Hans Burger (1873-1941) developed electroencephalography, the graphic representation of the difference in voltage between two different 10 Hz Reference Signal cerebral locations plotted over time. He described the human alpha and beta rhythms First EEG (1926) Galvanometer; Scientific American 1880 Electroencephalogr Clin Neurophysiol. 1969;Suppl 28:37-73. https://en.wikipedia.org/wiki/Hans_Berger  EEG SIGNAL PROCESSING IN FREQUENCY DOMAIN: Power Spectral Density PSD Preprocessing: Remove artifacts Eye Blinks EMG Power Line Delta Alpha Theta Beta Low Gamma http://www.bem.fi/book/13/13.htm  What does the EEG record? Volume conduction Ions are constantly flowing in and out of neurons to maintain resting potential and propogate action potentials. Movement of like-charged ions out of numerous neighbouring neurons can create waves of electrical charge, which can push or pull electrons on scalp electrodes, creating voltage differences. In summary, the EEG signal represents the deflection of electrons on the scalp electrodes, caused by cortical “dipoles” (the summed activity within a specific area of cortex that creates a current flow).  EEG and ECoG Potentials Spikes Micro to Macro EEG Scale intracellular action potentials (IAPs) extracellular action potentials (EAPs) local field potentials (LFPs) Obien MEJ, Deligkaris K, Bullmann T, Bakkum DJ and Frey U (2015) Revealing neuronal function through microelectrode array recordings. Front. Neurosci. 8:423. doi: 10.3389/fnins.2014.00423. http://journal.frontiersin.org/article/10.3389/fnins.2014.00423/full  Why EEG? Cognitive electrophysiology memory behavior perception emotions language cognition Psychology Neuroscience Cognitive processes Functional properties of the neural network Task design Data analysis EEG improves qualitative/ EEG is direct measure of neural behavioral metrics activity  Why EEG? Millisecond time scale Direct measure of neural activity Multidimensional time space phase Cost frequency power EEG systems EEG Acquisition Electrodes: Usually made of silver (or stainless steel) – active electrodes placed on the scalp using a conductive gel or paste. Signal-to-noise ratio (impedance) reduced by light abrasion. Can have 32, 64,128, 256 electrodes. More electrodes = richer data set. Reference electrodes (arbitrarily chosen “zero level”, analogous to sea level when measuring mountain heights) commonly placed on the midline, ear lobes, nose, etc. Amplification: one pair of electrodes make up one channel on the differential amplifier, i.e. there is one amplifier per pair of electrodes. The amplifier amplifies the difference in voltage between these two electrodes, or signals (usually between 1000 and 100 000 times). This is usually the difference between an active electrode and the designated reference electrode.  10-20 Electrode Positions F = frontal, T = temporal, C = central P = Parietal Even number = right side of head, Odd number = left side The system is based on the relationship between the location of an electrode and the underlining area of the cerebral cortex http://www.bem.fi/book/13/13.htm  Montages EEG records differences in voltage: the way in which the signal is viewed can be set up in a variety of ways called montages Bipolar montage: Each waveform in the EEG represents the difference in voltage between two adjacent electrodes, e.g. ‘F3-C3’ represents the difference in voltage between channel F3 and neighbouring channel C3. This is repeated across the whole scalp through the entire array of electrodes. Reference montage: Each waveform in the EEG represents the difference in voltage between a specific active electrode and a designated reference electrode. There is no standard position for the reference, but usually a midline electrode is chosen so as not to bias the signal in any one hemisphere. Other popular reference signals include an average signal from electrodes placed on each ear lobe or mastoid. Average Reference montage: Activity from all electrodes is measured, summed and then averaged. The resulting signal is then used as a reference electrode and acts as input 2 of the amplifier. The use can specify which electrodes are to be included in this calculation. Laplacian montage: Similar to average reference, but this time the common reference is a weighted average of all the electrodes, and each channel is the difference between the given electrode and this common reference.  Montages (continued) In digital EEG setups, the data is usually stored onto computer memory in reference mode, regardless of the montage used to display the data when it is being recorded. This means that “remontaging”, i.e. changing the montage either ‘on-line’ or ‘off-line’, can be done via a simple subtraction which cancels out the common reference. E.g. F3 – - F4 – Reference Reference = F3 – F4  Choosing a montage Research: Clinical: unipolar/referential bipolar same reference for all different reference for each electrodes electrode same measurement level to see localized trend in different for all electrodes scalp areas Image source: Wikipedia “10-20 system (EEG)”, google image search, and Alvarez, V., & Rossetti, A. O. (2015). Clinical use of EEG in the ICU: technical setting. Journal of clinical neurophysiology, 32(6), 481-485.  EEG Rhythms: can characteristically be broken down into different frequency bands Attenuated during movement Seen during alertness, active concentration Relaxation, closing of the eyes Control of inhibition Drowsiness, meditation, action inhibition Continuous attention, slow wave sleep Mu (8 – 13 Hz): Rest state motor neurons Gamma (30 – 100+ Hz): Cross-modal sensory processing, short-term perceptual memory  The EEG signal voltage REF 10-100µV time  The EEG signal : raw data ASA SCREENSHOT RAW SIGNAL  The EEG signal Physiological artefacts Extra-physiological artefacts (subject- related) (acquisition system- related) EOG: eye movement, blink 50 Hz power line EMG: muscular tension, movements Electromagnetic interference EKG: heartbeat Lead wire movements Respiration, tongue movement, etc. High electrode impedance, salt bridge, etc.  EEG artifacts Physiological artifacts Artifacts are signals recorded by EEG but Ocular activity not generated by brain. Some artifact may Muscle activity mimic true epileptiform abnormalities or Cardiac activity seizures. Awareness of logical topographic Perspiration field of distribution for true EEG Respiration abnormality is important in distinguishing artifact from brain waves. Physiologic Non-physiological / Technical artifacts originate from the patient and non- artifacts physiologic artifacts originate from the Electrode pop environment of the patient.” (EEG Artifacts, Cable movement Springer) Incorrect reference placement AC electrical and electromagnetic interferences Body movements  EEG preprocessing Reorganizing data : segmentation Removing/replacing bad data Cleaning data Maximize SNR 𝑠𝑖𝑔𝑛𝑎𝑙 b = max( ) 𝑛𝑜𝑖𝑠𝑒  EEG preprocessing Detection and DC offset and drift Power line noise interpolation of removal removal bad channels Detection and Removal of eye rejection of bad blinks and muscle Re-referencing epochs artifacts - ICA The EEG signal : 50Hz noise removal ASA SCREENSHOT RAW SIGNAL Notch filter fN = 50Hz The EEG signal : 50Hz noise removal ASA SCREENSHOT RAW SIGNAL Notch filter fN = 50Hz  The EEG signal : eye blink artefacts ASA SCREENSHOT RAW SIGNAL  ICA : the “cocktail party” problem Independent Component Analysis (ICA) may be used to remove/subtract artifacts embedded in the data (muscle, eye blinks, or eye movements) without removing the affected data portions. Neural activity ∑ In signal Eye blink processing, independent ∑ component analysis (ICA) is a computational method for separating a multivariate signal into additive Muscle ∑ subcomponents. Blind Source Separation (BSS) ICA : eye blink removal Muscle Eye blink  EEG Analysis Evoked Potentials (EP) stereotyped early responses time and phase-locked to the presentation of a physical stimulus Event-related Potentials (ERP) stereotyped late (?) responses time and phase-locked to stimuli, but often associated with “higher” cognitive processes, e.g. attention, expectation, memory, or top-down control evoked potential – short latencies (< 100ms) Both require averaging the – small amplitudes (< 1μV) same event over multiple – sensory processes trials (typically 100+), in order event related potential / field – longer latencies (100 – 600ms), to average out noise/random – higher amplitudes (10 – 100μV) – higher cognitive processes activity, but preserve the signal of interest. Software: EEGLAB, Brainlab, Ego…  EEG signal: analysis techniques Time Frequency/ Connectivity Power Hz ms - ERP - Network neuroscience - microstates - Spectral analysis - Source reconstruction  Time domain analyses: ERP trials Event-related potential (ERP) EEG changes that are time locked to sensory, motor or cognitive events Signal is the same across trials, noise fluctuates randomly Time domain analyses: microstates Spatial interpolation t1 time  Time domain analyses: microstates EEG microstates are: short time periods of stable scalp potential fields generated by a network of approximately simultaneously active sources. global patterns of scalp potential topographies recorded using multichannel EEG arrays that dynamically vary over time in an organized manner time 22-08-2024 (Michel, Koenig,NeuroImage, 2018) Spectral Analysis $%& 1 () x n = 𝑁 ! ! $ , 𝑋 𝑒 ' !* 𝑛 = 0.1 ….. 𝑁 − 1 !"# Fourier transform %&' )* 𝑋! = # x n 𝑒 &( % !" "#$  Welch’s periodogram Welch method is carried out by dividing the time signal into successive overlapping segments, FFT is computed in each window and the PSD is then computed as an average of FFTs over all windows, which reduces the variance of the individual power measurements (Mike X Cohen, Analyzing Neural Time Series Data: Theory and Practice, Jan. 2014) Network neuroscience Structural: focuses on the physical pathways, by describing the anatomical connections between different areas of the brain (Binary, undirected). Functional: focuses on the statistical relationships between distributed cortical areas, i.e., determines metrics of statistical dependence (Weighted, Undirected). Effective: allows the determination of the causality of the relationship between two areas. It can combine statistical coupling of the signals with anatomical information on the brain physical structure (Weighted, Directed).  EEG Analysis Grand mean ERP in response to Evoked Response / Event – related potential visual oddball paradigm – subjects are asked to react when they see a rare occurrence amongst a series of common stimuli, e.g. rotating arms of a clock It produces a stereotyped evoked response over parieto-central electrodes at around 300ms (termed P300 component) that is largest after seeing the rare target stimulus Rangaswamy & Porjesz. From event-related potentials to oscillations. Alcohol Research & Health, 2008  Frequency Domain: P300 Language (12-30 Hz) (3-7 Hz) Theta Memory PSD distribution associated to the RARE stimulus Beta LowGamma (30-50 Hz) Visual Ramon et al.; Epilepsy &Behavior, 14, 54-59, 2009  The Forward and Inverse Problems 1. Forward modelling generates expected signal 2. Compare model to actual recorded signal 3. Use difference between the two to work backwards and refine understanding of where signal comes from Forward Modelling: 1. Dipolar source models – can explain many configurations of electrical current caused by groups of neurones and measured at ~ 2cm 2. Volume conductor models – modelling effects of cranial anatomy (simpler for MEG).  EOG Electro-Oculogram, Eye movement In the 1920's, it was discovered that by placing electrodes on the skin in the region of the eyes, one could record electrical activity which changed in synchrony with movements of the eye in the head. It was initially believed that these potentials reflected the action potentials in the muscles that are responsible for moving the eyes in the orbit. eye movements can be detected by placing However, it is now generally agreed that these electrodes on the skin in the area of the head electrical potentials are generated by the permanent around the eyes. Vertical movements of the potential difference which exists between the cornea eyes are best measured by placing the and the ocular fundus (cornea-retinal potential, 10- electrodes on the lids, while horizontal eye 30mV: the cornea being positive). movements can be best measured by placing the electrodes on the external canthi (the bone on the side of the eye).  EOG Electro-Oculogram, Eye movement EOG, electrooculography is an electrophysiological method in which DC potentials are registered. The DC potential is dependent on the position of the eye, and is of particular interest, for instance, when the eyelids are closed (REM sleep). As a a rapid movement of the eye between fixation points. DC recording method, EOG tends to be prone to drift that makes the spatial localization of the point of gaze problematic. It is also sensitive to facial muscle activity and electrical interference.  EOG Electro-Oculogram, Eye movement OG voltages are higher than EEG signals. Since the eye is outside of the skull structure, there is no bone to attenuate signal. The cornea (front) has a positive polarity. The retina (back) has a negative polarity. EOG placement (LOC and ROC) is on the outer canthus of the eye, offset 1 centimeter below During REM sleep the eyes move rapidly under the eyelids and this produces rapid conjugate eye movements appear as (LOC) and 1 centimeter above (ROC) the out of phase signal deflections horizon. EOG picks up the inherent voltage of the eye. During eyes-open wakefulness, sharp deflections in the EOG tracing may indicate the presence of eye blinks.  GSR Galvanic Skin Response increased sympathetic activity (sympathetic arousal) elevates heart rate, blood pressure, and sweating, as well as redirects blood from the intestinal reservoir toward skeletal muscles, lungs, heart, and brain in preparation for motor action Galvanic Skin Response (GSR) is an “electrodermal” signature of the sympathetic nervous innervation of the skin. GSR can be measured on the skin surface and predominantly reflects the unopposed action of sudomotor Galvanic Skin Response (GSR) measure is sympathetic nerves on secretory channels of represented at the top followed by Blood eccrine sweat glands: enhanced porosity Pressure (BP) and Respiratory Rate (RR) increases electrical conductance. gland measures. innervation, measured by GSR, and brain states of affective and cognitive arousal.  GSR Galvanic Skin Response GSR is a signal used often in “lie detectors,” since GSR amplitude reacts sensitively to emotional provocation, salient thoughts, and attentional demand. Correspondingly, this effect exemplifies the direct coupling between sympathetic sweat gland innervation, measured by GSR, and brain states of affective and cognitive arousal.