EEG signals are the brain's electrical whispers, revealing our mental states through distinct frequency bands. From deep sleep to intense focus, these signals paint a picture of our cognitive processes, with amplitudes and spatial patterns telling their own stories.

Understanding EEG isn't just about clean signals. It's a constant battle against artifacts, both from our bodies and the environment. Luckily, we've got tricks up our sleeves to prevent, remove, and clean up these pesky interferences, ensuring our brain's true voice shines through.

EEG Signal Characteristics

Describe the basic characteristics of EEG signals

• Frequency bands reflect different brain states and cognitive processes
  • Delta (0.5-4 Hz) associated with deep sleep and unconsciousness
  • Theta (4-8 Hz) linked to drowsiness and meditative states
  • Alpha (8-13 Hz) indicates relaxed wakefulness, often with closed eyes
  • Beta (13-30 Hz) signifies active thinking and focused attention
  • Gamma (>30 Hz) relates to complex cognitive processing and perception
• Amplitude typically ranges from 10 to 100 µV varies with electrode placement and brain activity
• Spatial resolution limited by volume conduction affected by skull and scalp tissue attenuation
• Temporal resolution high (ms range) enables real-time monitoring of rapid brain activity changes

Explain the origin of EEG signals

• Neuronal activity primarily from postsynaptic potentials in pyramidal neurons requires synchronous firing of large neuron populations
• Cortical layers III and V generate strongest signals due to perpendicular orientation to scalp surface
• Dipole model describes how positive and negative charges create detectable electrical field summation of many dipoles produces scalp EEG

EEG Artifacts

Identify common EEG artifacts and their sources

• Physiological artifacts originate from body processes
  • Eye movements (EOG) include blinks and saccades most noticeable in frontal electrodes
  • Muscle activity (EMG) from jaw clenching and facial movements introduces high-frequency contamination
  • Cardiac activity (ECG) causes regular rhythmic interference prominent near neck and ears
• Non-physiological artifacts stem from external sources
  • Power line interference introduces 50 or 60 Hz noise (location-dependent)
  • Electrode movement produces sudden voltage changes or spikes
  • Skin potentials cause slow voltage drifts due to sweating
  • Equipment-related issues arise from loose connections or faulty electrodes

Describe methods for artifact removal and prevention

• Prevention techniques focus on minimizing artifact occurrence
  1. Ensure proper electrode placement and skin preparation
  2. Implement shielding from electromagnetic interference
  3. Provide clear instructions to participants to minimize movement
• Offline artifact removal applied post-recording
  • Visual inspection and manual rejection identifies obvious artifacts
  • Independent Component Analysis (ICA) separates EEG into components allows selective removal of artifact-related components
  • Adaptive filtering uses reference signals (EOG) to subtract artifacts
• Online artifact removal processes data in real-time
  • Real-time ICA continuously separates and removes artifact components
  • Adaptive noise cancellation dynamically adjusts to remove interference
  • Regression-based methods estimate and subtract artifact contributions
• Signal processing techniques clean and enhance EEG data
  • Bandpass filtering removes specific frequency ranges (muscle activity)
  • Notch filtering targets and removes power line interference
  • Wavelet transform enables time-frequency analysis for artifact identification