Visual Energy

Introduction to Visual Energy: Rationale and Application
(Supplementary methods)
by Erik Nylen
Updated 12/15/2009

In Goldmann Kinetic Perimetry, the target used for mapping a patient’s visual field has three main properties:

Size (mm^2)
Relative Intensity (dB)
Velocity (deg/s)

The kinetic energy of a moving object is commonly described in the form

where m = mass, and v = velocity. Using the kinetic energy of an object with mass as our analog, we can calculate the mass of our target as it’s area*intensity (the same way for calculating mass from density and volume).

Substituting these values, the energy of the target is

where A = area of the target, I = target intensity, and v = velocity. The units of the target is in

since both millimeters and degrees are units of length, degrees can be selected as the unit of length, giving

where C is the conversion constant between millimeters and degrees. Though units of energy typically only contain the second power of length, not the fourth. This is in an indicator that the units of target are actually in energy*area.

For example, the energy*area of a I2e target moving at 5 deg/s is

whereas the V4e has an energy-area of

This value of E is one measure of kinetic energy of the target stimulus. Kinetic perimetry maps the potential energy of activating the minimum number of photoisomerizations required for conscious detection. For any closed energy system, potential energy is inversely related to kinetic energy. Applied to the retina, little potential energy is required to detect a large, bright stimulus. Conversely, a large amount of potential energy is required to detect a small, dim stimulus. Moreover, moving an object from an undetected region of visual space into a detectable region indeed serves to activate the energy needed for observation. Under the assumption that the Goldmann paradigm is a closed, linear system, we can then easily calculate the potential energy of the retina.

Electroretinography is also an estimate of potential energy. ERG measures the total change in potential across the globe. Reported are single values, in uV, for scotopic, photopic, and flicker response to light stimuli. Subject attention and willingness to participate is not an issue in this test, as can be in perimetry. However, artifact and noise often hinder the clinician’s use and interpretation of the data. Moreover, ERG can often report paradoxically normal values for an individuals who have clearly reduced or scotomatous visual fields.

Using Goldmann Kinetic Perimetry, a discrete series of isopter values are established for each patient. Isopter detection areas are then weighted uniformly, giving a baseline potential energy of detection. Integrating over the entire visual field yields a baseline Goldmann Visual Energy. Normalizing to age matched controls, a subject’s normalized Visual Energy can be calculated. This normalized Visual Energy estimates the total amount of functional vision in subjects. Improvements on the resolution of this estimate could be made by testing more isopters in Goldmann Visual Field recordings, or by fitting an appropriate Hill of Vision model to account for the gradient of photoreceptor densities between isopters. Higher resolution in perimetry and functional model fitting will provide for a more detailed description of Visual Energy. Just as functional magnetic resonance imaging is limited by temporal and spatial resolution, as well as patient cooperation in lengthy tests, our test is held only to the precise data we collect. However, this baseline calculation serves as a suitable estimate of visual function.

The Visual Energy is used here as a measure of visual function in a cohort of patients, each with two molecularly confirmed mutations in ABCA4. We show here how the baseline measure of Visual Energy provides a framework for classifying disease severity. We then use this measure to show how various mutations in ABCA4 can cause different degrees of vision loss.