The ElectroEncephaloGramm Cognitive Neuropsychology January 16th, 2001 Outline 1. History of the EEG 2. Biological Foundations of the EEG 3. Measuring the EEG 4. Analyzing the EEG 5. Applications of the EEG The History of the EEG 1875 Caton records brain potentials from cortex 1883 Marxow discovers evoked potentials 1929 Berger records electrical activity from the skull 1936 Gray Walter finds abnormal activity with tumors 1957 The toposcope (imaging of electrical brain activity) 1980 Color brain mapping (quantitative EEG) Hans Berger – EEG Pioneer In 1929, Hans Berger • Recorded brain activity from the closed skull • Reportet brain activity changes according to the functional state of the brain – Sleep – Hypnothesis – Pathological states (epilepsy) First EEG recorded by Berger Gray Walter – Brain Imaging In 1957, Gray Walter • Makes recordings with large numbers of electrodes • Visualizes brain activity with the toposcope • Shows that brain rhythms change according to the mental The toposcope by Gray Walter task demanded Outline 1. History of the EEG 2. Biological Foundations of the EEG 1. Brain Rhythms 2. Information Processing in the Neocortex 3. Summation Potentials 3. Measuring the EEG 4. Analyzing the EEG 5. Applications of the EEG EEG in the States of Vigilance Frequency Ranges Beta: 14 – 30 Hz Alpha: 8 – 13 Hz Theta: 5 – 7 Hz Delta: 1 – 4 Hz Alpha Rhythm Frequency: 8 – 13 Hz Amplitude: 5 – 100 microVolt Location: Occipital, Parietal State of Mind: Alert Restfulness Alpha blockade occurs when new stimulus is processed Source: oscillating thalamic pacemaker neurons Beta Rhythm Frequency: 14 – 30 Hz Amplitude: 2 – 20 microVolt Location: Frontal State of Mind: Mental Activity Reflects specific information processing between cortex and thalamus Theta Rhythm Frequency: 5 – 7 Hz Amplitude: 5 – 100 microVolt Location: Frontal, Temporal State of Mind: Sleepiness Nucleus reticularis slows oscillating thalamic neurons Therefore diminished sensory throughput to cortex Delta Rhythm Frequency: 1 – 4 Hz Amplitude: 20 – 200 microVolt Location: Variable State of Mind: Deep sleep Oscillations in Thalamus and deep cortical layers Usually inibited by ARAS (Ascending Reticular Activation System) Outline 1. History of the EEG 2. Biological Foundations of the EEG 1. Brain Rhythms 2. Information Processing in the Neocortex 3. Summation Potentials 3. Measuring the EEG 4. Analyzing the EEG 5. Applications of the EEG Cortex Structure The neocortex consists of six distinct layers I Molecular layer II External granular layer III External pyramidal layer IV Internal granular layer V Internal pyramidal layer VI Polymorphic or multiform layer Cortex Structure Layer I I Molecular layer Molekularschicht • Apical dendrites of pyramidal cells • Axons of stellate cells (parallel to cortex surface) • Few cell bodies • Local (intracortical) information exchange Cortex Structure Layer II/ III II External granular layer Äußere Körnerschicht III External pyramidal layer Äußere Pyramidenschicht • Stellate & Small Pyramidal Cells • Intercortical Information Exchange – Afferent fibers from other cortical areals enter the layers – Association (to the same hemisphere) and commisural (to the other hemisphere) fibers leave cortex (reentry at destination) Cortex Structure Layer IV IV Internal granular layer Innere Körnerschicht • Stellate cells • Afferents from Thalamus • Numerous and complex synaptic connections • Relay of thalamic information to other cortical layers • Information input layer (well developed in sensory cortex) Cortex Structure Layer V V Internal pyramidal layer Innere Pyramidenschicht • Large pyramidal cells • Projection fibers to subthalamic brain areas – Basal ganglia – Brain stem – Spinal chord • Information output layer (well developed in motor cortex) Cortex Structure Layer VI VI Multiform layer Spindelzellschicht • Neurons of various shapes (mainly fusiform) • Adjacent to white matter • Corticothalamical information exchang Cytoarchitecture Neocortex Input layers: II/IV (granular) Output layers: III/V (pyramidal) 1: heterotypical agranular cortex – Mainly pyramidal layers (output) – Primary motor cortex 5: heterotypical granular cortex – Mainly granular layers (input) – Primary sensory cortex 2-4: homotypical cortex – Association areas – All layers developed Outline 1. History of the EEG 2. Biological Foundations of the EEG 1. Brain Rhythms 2. Information Processing in the Neocortex 3. Summation Potentials 3. Measuring the EEG 4. Analyzing the EEG 5. Applications of the EEG Summation Potentials The EEG measures • not action potentials • not summation of action potentials • but summation of graded Post Synaptic Potentials (PSPs) (only pyramidal cells: dipoles between soma and apical dendrites) Outline 1. History of the EEG 2. Biological Foundations of the EEG 3. Measuring the EEG – The international 10/20 system 4. Analyzing the EEG 5. Applications of the EEG The International 10/20 System Terminology: 10/20 System Nasion: point between the forehead and the skull Inion: bump at the back of the skull Location: Frontal, Temporal, Parietal, Occipital, Central z for the central line Numbers: Even numbers (2,4,6) right hemisphere, odd (1,3,5) left EEG channels Channel: Recording from a pair of electrodes (here with a common reference: A1 – left ear) Multichannel EEG recording: up to 40 channels recorded in parallel Participants with Electrodes EEG in clinical diagnostics EEG in scientific research Outline 1. History of the EEG 2. Biological Foundations of the EEG 3. Measuring the EEG 4. Analyzing the EEG 1. Event Related Potentials 2. Spectral Analysis 3. Topographical Mapping 5. Applications of the EEG Event Related Potentials • Averaging of trials following a stimulus • Noise reduction: The noise decreases by the squareroot of the number of trials • Far field potentials require up to 1000 measurements • Assumption: no habituation occurs (participants don‘t get used to stimulation) Language specific ERP Components • N400: Semantic mismatch marker • P600: Syntactic mismatch marker Example Sentences: Correct (Baseline): The cats won't eat the food Mary gives them. Semantic mismatch: The cats won't bake the food Mary gives them. Syntactic mismatch: The cats won't eating the food Mary gives them. Semantic and syntactic mismatch: The cats won't baking the food Mary gives them. EEG Spectral Analysis • Fast Fourier Transform seperates spontaneous EEG signal to component frequencies and amplitudes • Restriction: high frequency resolution demands long (in the range of seconds) analysis windows Topographical Maps Topographical maps plot EEG data on a map of the brain. Data is interpolated between electrodes. Usual data plotted: • ERP maps – potential changes • Spectral maps – frequency changes • Statistical maps – comparison of measurements Outline 1. History of the EEG 2. Biological Foundations of the EEG 3. Measuring the EEG 4. Analyzing the EEG 5. Applications of the EEG Weiss, Rappelsberger (2000) Long-range EEG synchronization during word encoding correlates with successful memory performance Methods Section 1 A set of 19 gold-cup electrodes was After recording, the EEG data were glued to the scalp according to the screened for artefacts (eye blinks, international 10/20-placement horizontal and vertical eye movements, system. Data were recorded against muscle activities) by visual inspection the average signals of both earlobes on a monitor and on paper. These two ((A1 + A2) /2) which turned out to be methods allowed a very reliable the most suitable reference for exclusion of the artefacts. Impedance coherence analysis. The did not exceed 8 kΩ and signal electrooculogram (EOG) was bandpass was 0.3 –35 Hz. Data were recorded from two electrodes located simultaneously monitored by an ink- at the left later outer cantus and above writer system and digitally sampled at the right eye. Electrode impedance did 256 Hz to be stored on hard disk. After not exceed 8 kΩ and signal bandpass recording, the EEG data were was 0.3 –35 Hz. Data were screened for artefacts (eye blinks, simultaneously monitored by an ink- horizontal and vertical eye movements, writer system and digitally sampled at muscle activities) by visual inspection 256 Hz to be stored on hard disk. on a monitor and on paper. These two methods allowed a very reliable exclusion of the artefacts. Methods Section 2 EEG was recorded during nouns auditorily presented, 7 2 memorization of the different lists for recalled nuons visually of nouns and during four presented, 14 4 for not recalled interspersed resting periods with nouns visually presented and 198 eyes open lasting one minute 45 for the resting EEG. Then each. According to the behavioral averaged power spectra and results epochs of recalled and of cross-power spectra were not recalled ones were selected for computed for each subject. further analysis. The beginning of According to the 19 elctrode each noun was marked by a trigger positions, 19 averaged power and the following 1 s EEG epoch spectra were computed. Cross was Fourier-transformed. All 1-s power spectra were computed. artefact-free epochs of the resting Cross power spectra were EEG were also Fourier- computed between all possible transformed. On the average, per pairs, which yielded 171 values per subject, 16 4 epochs for recalled frequency. nouns auditorily presented were analysed, 28 5 for not recalled Methods Section 3 To reduce the large data set the Since it has been demonstrated adjacent spectral values vere that, especially, lower EEG averaged to obtain broadband frequencies were correlated with parameters for the following memory processes, we frequency bands: delta-1 (1 – 2 predominantely investigated lower Hz), delta-2 (3 – 4 Hz), theta (5 – 7 frequency bands in the present Hz), alpha-1 (8 – 10 Hz), alpha-2 study. The division into distinct, (11 – 12 Hz), and beta-1 (13 – 18 well-selected frequency bands was Hz). Finally, 19 mean amplitudes made since several studies point at (square root of power) per their different functional role during frequency band were computed cognitive processing. and the normalization of the 171 cross-power spectra yielded 171 coherence values per frequency band. Grand mean values were obtained by averaging amplitude and coherence values across subjects. Coherence Map A coherence map plots differences in coherence between recalled and not recalled nouns. Results • Overall increase of coherence for recalled vs. not recalled nouns • Long range synchronization of frontal and temporal/parietal neuronal assemblies increases for recalled nouns. Outline 1. History of the EEG 2. Biological Foundations of the EEG 3. Measuring the EEG 4. Analyzing the EEG 5. Applications of the EEG Thank you for your attention!