We read with interest the article “Learning Curve and Fatigue Effect of Flicker Defined Form Perimetry,” by Lamparter and associates. The authors investigated the learning effect of the relatively new flicker defined form perimetry and found a significant improvement in different perimetric indices between the first 3 tests performed by inexperienced healthy subjects.

As they state, the learning effect has been demonstrated in both normal and glaucomatous patients tested with conventional as well as nonconventional perimetric techniques. Reviewing the existing literature about this topic, we found that data about learning effect currently are available for standard automated perimetry, short-wavelength automated perimetry (SWAP), frequency doubling technology, Rarebit perimetry, and now flicker defined form perimetry. Similar results have been found for standard automated perimetry, frequency doubling technology, Rarebit perimetry, and flicker defined form perimetry, with a learning effect occurring between the first and the second or the third session; conversely, SWAP has shown the occurrence of a learning effect also at the fifth session. Interestingly, SWAP is the only technique based on colored stimuli (blue dots on a yellow background), whereas the others use differently structured, uncolored stimuli (single white dots on a white screen, black and white striped squares on a white screen, a couple of white dots on a black screen, black and white dots on a mean luminance background). As already suggested by Wild and associates, it is plausible that chromatic discrimination may represent an additional factor influencing the perimetric learning effect.

The pathway for the interpretation of colors has been reported to be separate from those responsible for object identification, confirmed by evidence indicating that color and orientation selectivity are mutually exclusive and that form vision depends primarily on achromatic information.

Indeed, patients with visual agnosia may maintain the ability to identify the color of objects, whereas patients with cerebral achromatopsia may have normal visual acuity and contrast sensitivity. Recent studies in primate primary visual cortex have challenged the view that color and form are represented by distinct neuronal populations. Johnson and associates suggested that S-cones contributes to both chromatic and achromatic visual functions and that the conjoint representation of color and form is a fundamental property of cortical processing. Regardless of the exact mechanisms involved in these processes, it therefore is plausible that the detection of stimuli requiring both object and color identification (thus involving 2 separate pathways, different cortical processing, or both) implies higher training than object identification alone. This may be particularly true taking into account the possibly relevant fatigue effect induced by SWAP. Fogagnolo and associates recently reported a mild learning effect in standard automated perimetry–experienced patients tested with a Swedish interactive threshold algorithm program adapted to SWAP and the ability to reduce the examination duration by approximately 70%. However, the authors argued that learning effect in patients tested with this strategy who are naïve to perimetry may be higher.

Further studies should be performed to clarify this issue that, in our opinion, should be taken into account when developing new perimetric techniques.