Week 3 Notes: Mind Reading (Electrophysiology)

Functional Imaging & Electrophysiology

• Comparison of Methods:
  • Electrical Methods:
  • Examples: EEG (Electroencephalography), SUA (Single Unit Activity).
  • Characteristics: Fast response times.
  • Metabolic Methods:
  • Examples: fMRI (Functional Magnetic Resonance Imaging), PET (Positron Emission Tomography).
  • Characteristics: Slower response times compared to electrical methods.

Spike Recording

• Types of Recording:
  • SUA (Single Unit Activity): Records activity from a single neuron.
  • MUA (Multiple Unit Activity): Records activity from multiple neurons.
• Recording Environments:
  • Extracellular Recording: Conducted in vivo, often in freely moving subjects.
  • Intracellular Recording: Conducted in laboratory studies, usually in controlled environments.

Neural Coding

• Types of Neural Coding:
  • Specificity Coding: One neuron corresponds to one specific concept or idea.
  • Example: "Jennifer Aniston cell" demonstrates this theory, as specific neurons fire in response to known faces or concepts.
  • Population Coding: A concept is represented by a pattern of firing across multiple neurons.

Motor System & Brain-Computer Interfaces (BCI)

• Motor Areas:
  • M1 (Primary Motor Cortex): Responsible for executing movement.
  • M2 (Secondary Motor Areas): Responsible for planning movements.
• Neuronal Firing:
  • Neurons exhibit preferred directions, meaning they fire more when the movement aligns with their favored direction of activity.
• Brain-Computer Interface Functionality:
  • BCIs use signals from these areas to control robotic limbs or digital cursors.

EEG, ECoG, and LFP

• EEG (Electroencephalography):
  • Non-invasive method using electrodes placed on the scalp.
• ECoG (Electrocorticography):
  • Invasive method that requires a direct connection to the brain surface.
• LFP (Local Field Potentials):
  • Involves deep brain recordings to capture local neural activities.

Signal Analysis

• Fourier Transform:
  • A mathematical transformation that converts signals from the time domain to the frequency domain.
• Spectrogram:
  • A visualization tool that displays how the frequency of a signal varies with time.
• Alpha Wave:
  • Typically oscillates around 10 Hz; associated with states of relaxation, often observed when a person closes their eyes.