In-Depth Notes on EEG Concepts and Applications

Introduction to EEG

• Electroencephalography (EEG) is a method to measure the electrical activity of the brain through electrodes placed on the scalp.
• EEG primarily reflects the activity of the cerebral cortex which covers older brain structures like the limbic system and brainstem.
• Deep brain regions require implanted electrodes for detailed assessment.

Measuring Brain Activity with EEG

• EEG reflects the cumulative electrical activity of numerous neurons, particularly cortical pyramidal cells which are aligned perpendicularly to the cortical surface.
• When these neurons receive similar inputs, their synchronous electrical changes—postsynaptic potentials—combine to produce detectable signals on the scalp.
• EEG mainly tracks larger regions of activation with neurons needing to be synchronized for effective detection.
• Typical EEG rhythms include:
  • Alpha waves (8-12 Hz): Awake relaxed state, synchronized activity.
  • Beta waves (13-30 Hz): Awake attentive state, cognitive activity, desynchronized.
  • Gamma waves (30-80 Hz): Integration of stimuli.
  • Delta waves (1-5 Hz): Deep sleep or high mental activity.
  • Theta waves (4-8 Hz): Deep sleep or attention periods.

EEG Recording Techniques

• Simple measurements can be made using a pair of electrodes and a ground electrode, measuring voltage differences.
• International 10-20 System: A standard for electrode placement (prefrontal, frontal, parietal, occipital, temporal, and central) to ensure consistency in studies.
• Challenges: The EEG signal is weak; amplification (up to a million times) is necessary.
• EEG is sensitive to artifacts generated by muscle movements, eye blinks, and external electrical sources.

Signal Analysis

• The EEG signal is generally recorded in the 0 to 100 Hz domain with a sampling rate of 500-1000 Hz.
• Electrode preparation involves skin cleansing (alcohol rub) and potentially slight abrasion to enhance signal clarity.
• Fast Fourier Transform: A common method for analyzing EEG data—it decomposes signals into constituent frequency components for better understanding.

Spatial Analysis and Source Localization

• Analyzing the spatial aspects of EEG activity requires multiple electrodes.
• Source localization methods allow the identification of the origin of brain activity in 3D models, combining EEG with other imaging technologies like fMRI for higher spatial accuracy.

Event-Related Potentials (ERP)

• ERP refers to the brain's electrical response to specific stimuli measured through electrodes.
• Examples of ERP components:
  • P1 (P100): Positive deflection after 65-100 ms, driven by the visual cortex.
  • N1: Larger negative deflection peaking at 150-200 ms.
  • P2 (P200): A large positive wave after 150-250 ms, can also have centro-frontal components.
• Responses show attentional influences on components (especially P1 and N1).
• Auditory processing is quicker than visual, influencing reaction times (auditory: 140-160 ms, visual: 180-200 ms).

Classification of ERP Components

• Early components (before P1) indicate non-cortical processing and are generated in subcortical regions (e.g., brainstem-evoked responses).
• Exogenous components: Fast responses determined by stimulus characteristics within first 100 ms.
• Endogenous components: Reflect higher processing levels; P300 wave (~300 ms) is notable here.

EEG Applications in Psychological Research

• EEG is utilized in various fields: sleep studies, activation, conditioning, hypnosis, and emotional responses.
• Research areas for ERP include attention, perception, and the processing of visual/auditory stimuli.

Conclusion

• EEG serves as a vital tool in psychology and neuroscience for investigating brain function and understanding complex neural processes.