The Electro Encephalo Gramm Cognitive Neuropsychology January 16

The Electro. Encephalo. Gramm Cognitive Neuropsychology January 16 th, 2001

Outline 1. 2. 3. 4. 5. History of the EEG Biological Foundations of the EEG Measuring the EEG Analyzing the EEG 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 The toposcope by Gray Walter 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 task demanded

Outline 1. History of the EEG 2. Biological Foundations of the EEG 1. 2. 3. 4. 5. Brain Rhythms Information Processing in the Neocortex Summation Potentials Measuring the EEG Analyzing the EEG 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: Amplitude: Location: State of Mind: 8 – 13 Hz 5 – 100 micro. Volt Occipital, Parietal Alert Restfulness Alpha blockade occurs when new stimulus is processed Source: oscillating thalamic pacemaker neurons

Beta Rhythm Frequency: Amplitude: Location: State of Mind: 14 – 30 Hz 2 – 20 micro. Volt Frontal Mental Activity Reflects specific information processing between cortex and thalamus

Theta Rhythm Frequency: Amplitude: Location: State of Mind: 5 – 7 Hz 5 – 100 micro. Volt Frontal, Temporal Sleepiness Nucleus reticularis slows oscillating thalamic neurons Therefore diminished sensory throughput to cortex

Delta Rhythm Frequency: Amplitude: Location: State of Mind: 1 – 4 Hz 20 – 200 micro. Volt Variable 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. 2. 3. 4. 5. Brain Rhythms Information Processing in the Neocortex Summation Potentials Measuring the EEG Analyzing the EEG 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. 2. 3. 4. 5. Brain Rhythms Information Processing in the Neocortex Summation Potentials Measuring the EEG Analyzing the EEG 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. 2. 3. History of the EEG Biological Foundations of the EEG 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: Inion: Location: Numbers: point between the forehead and the skull bump at the back of the skull Frontal, Temporal, Parietal, Occipital, Central z for the central line 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: A 1 – 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. 2. 3. 4. History of the EEG Biological Foundations of the EEG Measuring the EEG Analyzing the EEG 1. 2. 3. Event Related Potentials Spectral Analysis 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 • N 400: Semantic mismatch marker • P 600: 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. 2. 3. 4. 5. History of the EEG Biological Foundations of the EEG Measuring the EEG Analyzing the EEG 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 glued to the scalp according to the international 10/20 -placement system. Data were recorded against the average signals of both earlobes ((A 1 + A 2) /2) which turned out to be the most suitable reference for coherence analysis. The electrooculogram (EOG) was recorded from two electrodes located at the left later outer cantus and above the right eye. Electrode impedance did not exceed 8 kΩ and signal bandpass was 0. 3 – 35 Hz. Data were simultaneously monitored by an inkwriter system and digitally sampled at 256 Hz to be stored on hard disk. After recording, the EEG data were screened for artefacts (eye blinks, horizontal and vertical eye movements, muscle activities) by visual inspection on a monitor and on paper. These two methods allowed a very reliable exclusion of the artefacts. Impedance did not exceed 8 kΩ and signal bandpass was 0. 3 – 35 Hz. Data were simultaneously monitored by an inkwriter system and digitally sampled at 256 Hz to be stored on hard disk. After recording, the EEG data were screened for artefacts (eye blinks, horizontal and vertical eye movements, muscle activities) by visual inspection on a monitor and on paper. These two methods allowed a very reliable exclusion of the artefacts.

Methods Section 2 EEG was recorded during memorization of the different lists of nouns and during four interspersed resting periods with eyes open lasting one minute each. According to the behavioral results epochs of recalled and of not recalled ones were selected for further analysis. The beginning of each noun was marked by a trigger and the following 1 s EEG epoch was Fourier-transformed. All 1 -s artefact-free epochs of the resting EEG were also Fouriertransformed. On the average, per subject, 16 4 epochs for recalled nouns auditorily presented were analysed, 28 5 for not recalled nouns auditorily presented, 7 2 for recalled nuons visually presented, 14 4 for not recalled nouns visually presented and 198 45 for the resting EEG. Then averaged power spectra and cross-power spectra were computed for each subject. According to the 19 elctrode positions, 19 averaged power spectra were computed. Cross power spectra were computed between all possible pairs, which yielded 171 values per frequency.

Methods Section 3 To reduce the large data set the adjacent spectral values vere averaged to obtain broadband parameters for the following frequency bands: delta-1 (1 – 2 Hz), delta-2 (3 – 4 Hz), theta (5 – 7 Hz), alpha-1 (8 – 10 Hz), alpha-2 (11 – 12 Hz), and beta-1 (13 – 18 Hz). Finally, 19 mean amplitudes (square root of power) per frequency band were computed 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. Since it has been demonstrated that, especially, lower EEG frequencies were correlated with memory processes, we predominantely investigated lower frequency bands in the present study. The division into distinct, well-selected frequency bands was made since several studies point at their different functional role during cognitive processing.

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. 2. 3. 4. 5. History of the EEG Biological Foundations of the EEG Measuring the EEG Analyzing the EEG Applications of the EEG Thank you for your attention!