Psy 362 exam 3
Neural Activity and Excitation/Inhibition Balance
Key Concept: Understanding neural activity through excitation/inhibition (E/I) balance.
E/I balance serves as a framework to think about neural processes in the brain.
Imbalances can lead to neurological and psychological issues.
Insomnia as a Case Study
Insomnia: Reflects neural hyperexcitability.
Treatment: Medically managed using benzodiazepines (sedatives).
Mechanism: Benzos bind to GABA receptors and enhance hyperpolarization, thereby inhibiting neuronal firing.
Dietary Factor: Excess glutamate can contribute to insomnia.
Found in foods under various names (e.g., MSG).
Aspartame: An excitotoxin linked to symptoms such as brain fog, migraines, and anxiety, especially in sensitive individuals.
Caution advised against artificial food coloring (dyes), commonly associated with increased hyperactivity in children.
Other Examples of E/I Imbalance
Conditions associated with neural hyperexcitability:
Depression
Long-COVID
Chronic Pain
Alcohol Addiction
Autism
Non-Pharmacologic Option to Restore E/I Balance
Meditation (various practices)
Yoga
Tai-Chi and Chi-Gong
Neurofeedback: Aims to increase alpha oscillations and promote relaxation.
ASMR: Assists with insomnia by enhancing alpha oscillations during episodes of "tingles".
EEG Applications: Event-Related Potentials (ERPs)
Research Focus
Question posed: How can we relate brain activation to stimuli on a moment-to-moment basis to investigate cognition (e.g., word or face processing)?
Studying the EEG signal evoked by stimuli requires methods to derive the brain's response while minimizing noise.
Noise: Refers to random oscillations in brain activity that can obscure signals from stimuli.
Original signals are often contaminated by non-stimulus-related brain activity.
Deriving Event-Related Potentials (ERPs)
Methodology: EEG epochs are averaged at stimulus onset across multiple trials.
Epoch Definition: Typically 1 second around the stimulus onset.
Experimental Setup:
Stimuli (e.g., faces, tones) presented via a computer.
Stimulus markers sent to EEG-recording computer, facilitating segmentation of EEG data into epochs.
Analysis: Epochs averaged to extract ERP signals.
Signal vs. Noise in EEG Data
Signal: Brain's consistent response to a specific stimulus (e.g., how the brain reacts to a particular face).
Noise: Random background activity (assumed artifacts from muscle movements and eye blinks have been cleaned).