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Graded Potential

Graded Potential

Graded potentials are localized fluctuations in the cell membrane's electrical charge, commonly found in the dendrites of neurons. The magnitude of these potential changes depends on the strength of the initiating stimulus. In a membrane at its resting potential, a graded potential signifies a voltage shift either above -70 mV or below -70 mV.
Graded potentials fall into two categories: depolarizing and hyperpolarizing. Depolarizing graded potentials typically occur when sodium (Na+) or...

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Related Experiment Video

Updated: May 21, 2025

Objectively Assessing Sports Concussion Utilizing Visual Evoked Potentials

Objectively Assessing Sports Concussion Utilizing Visual Evoked Potentials

Published on: April 27, 2021

Measuring contrast processing in the visual system using the steady state visually evoked potential (SSVEP).

Alex R Wade¹, Daniel H Baker¹

¹Department of Psychology and York Biomedical Research Institute, University of York, UK.

Vision Research

|May 3, 2025

Summary

This summary is machine-generated.

Steady-state visually-evoked potentials (SSVEPs) offer a robust method for studying human contrast processing. This review details how SSVEPs have been utilized over 70 years to understand visual perception, incorporating interactive models.

Keywords:

Contrast EEG SSVEP VEP Vision

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Last Updated: May 21, 2025

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Area of Science:

Visual Neuroscience
Sensory Perception
Human Vision

Background:

Contrast processing is fundamental to the early visual system.
Understanding how factors like spatial/temporal frequency, age, and clinical conditions affect contrast perception has been a long-standing goal in vision science.
The steady-state visually-evoked potential (SSVEP) technique has been a productive experimental approach.

Purpose of the Study:

To review the application of SSVEPs in studying human visual contrast processing over the past 70 years.
To provide an interactive learning aid for modeling and analyzing SSVEPs.
To highlight the advantages of SSVEPs, including high signal-to-noise ratio and unambiguous output measures.

Main Methods:

Utilizing frequency-tagged contrast-modulated inputs presented at defined frequencies and phases.
Analyzing brain's electrical signals in the temporal frequency domain using SSVEPs.
Employing mathematical models and embedded code for illustration of key modeling and analysis steps.

Main Results:

SSVEPs provide a high signal-to-noise ratio (SNR) for measuring visual responses.
The technique allows for unambiguous output measures in contrast processing studies.
SSVEPs facilitate the analysis of interactions between stimulus components within a mathematical framework.

Conclusions:

SSVEPs are a valuable and versatile tool for investigating human contrast processing.
The integration of interactive models enhances the understanding and application of SSVEP analysis.
This work serves as both a comprehensive review and a practical guide for researchers in vision science.