3.1 Electrophysiological signal types and characteristics

Electrophysiological signals are key to understanding brain activity and developing neuroprosthetics. Action potentials, local field potentials, and EEG offer different insights into neural function, from single neurons to large-scale brain activity.

Each signal type has unique characteristics in amplitude, frequency, and temporal resolution. These properties determine their applications in neuroprosthetics, from precise control of individual neurons to non-invasive brain-computer interfaces.

Electrophysiological Signal Types

Types of electrophysiological signals

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• Action potentials
  • Electrical signals generated by individual neurons when they fire
  • Represent the transmission of information along the axon from the cell body to the synapse
  • Characterized by a rapid, transient change in membrane potential from the resting state to a peak and back to the resting state
  • All-or-none response, meaning the neuron either fires an action potential or does not fire at all (threshold potential)
• Local field potentials (LFPs)
  • Represent the collective activity of a group of neurons in a localized area of the brain (cortical column)
  • Reflect the sum of synaptic activity, subthreshold membrane oscillations, and action potentials from nearby neurons
  • Provide information about the synchronous activity of neural populations and how they process and transmit information
• Electroencephalography (EEG)
  • Non-invasive recording of electrical activity from the scalp using electrodes placed on the surface of the head
  • Reflects the summation of synchronous activity from large populations of neurons in the cerebral cortex
  • Provides a global measure of brain activity with low spatial resolution but high temporal resolution (millisecond timescale)

Characteristics of electrophysiological signals

• Amplitude
  • Refers to the magnitude or strength of the electrical signal measured from the neuron or brain area
  • Measured in microvolts ($\mu V$) for EEG and LFPs or millivolts (mV) for action potentials
  • Action potentials have higher amplitudes (70-110 mV) compared to LFPs (0.5-5 mV) and EEG (5-200 $\mu V$)
• Frequency
  • Represents the number of oscillations or cycles of the electrical signal per second
  • Measured in Hertz (Hz), which is the number of cycles per second (1 Hz = 1 cycle/second)
  • EEG signals are typically categorized into frequency bands such as delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz), and gamma (30-100 Hz)
  • LFPs and action potentials contain a broad range of frequencies depending on the brain region and neuron type
• Temporal resolution
  • Refers to the ability to distinguish or separate events in time, or how precisely the timing of neural activity can be measured
  • Action potentials have the highest temporal resolution on the order of milliseconds (1-2 ms)
  • LFPs have a lower temporal resolution compared to action potentials but higher than EEG (10-100 ms)
  • EEG has the lowest temporal resolution among the three signal types due to the distance from the source (100-1000 ms)

Physiological Origins and Applications

Origins of electrophysiological signals

• Action potentials
  • Originate from the spiking activity of individual neurons when they receive enough excitatory input to reach the threshold potential
  • Provide information about the firing patterns and timing of specific neurons and how they encode and transmit information
  • Relevant for neuroprosthetic applications that require precise control or decoding of individual neuron activity (motor prostheses)
• Local field potentials
  • Arise from the collective activity of neural populations in a localized area of the brain, such as a cortical column or nucleus
  • Reflect the input-output relationships and processing within a neural network, including synaptic activity and subthreshold oscillations
  • Useful for neuroprosthetic applications that rely on the activity of neural ensembles or brain regions (sensory feedback)
• EEG
  • Generated by the synchronous activity of large populations of neurons in the cerebral cortex, primarily pyramidal cells
  • Reflects global brain states and oscillatory patterns associated with different cognitive functions and behaviors
  • Relevant for neuroprosthetic applications that target overall brain activity or require non-invasive recording (brain-computer interfaces)

Electrophysiological signals for neuroprosthetics

• Action potentials
  • Advantages:
    1. High spatial resolution allows for precise targeting and control of individual neurons
    2. High temporal resolution enables real-time decoding and encoding of neural activity
  • Limitations:
    1. Requires invasive recording techniques such as microelectrode arrays implanted in the brain
    2. Limited coverage of neural populations due to the small recording area of microelectrodes
• Local field potentials
  • Advantages:
    1. Provides information about local neural network dynamics and how ensembles of neurons process information
    2. Less invasive than single-unit recordings since the electrodes can be placed on the surface of the brain (electrocorticography)
  • Limitations:
    1. Lower spatial resolution compared to action potentials since LFPs represent the activity of many neurons
    2. May not capture the activity of individual neurons that are important for certain functions or behaviors
• EEG
  • Advantages:
    1. Non-invasive and safe for long-term use since the electrodes are placed on the scalp
    2. Provides a global measure of brain activity that can be used for monitoring and controlling neuroprosthetic devices
  • Limitations:
    1. Low spatial resolution due to the distance between the electrodes and the brain (centimeter scale)
    2. Susceptible to artifacts from muscle activity, eye movements, and electrical noise
    3. Limited to recording activity from the cerebral cortex and cannot access deeper brain structures