Limitations and suggestions for reporting interactions with spatial frequency
A limitation is that we do not know why groups differed in acuity; thus, it is not yet clear whether it is appropriate to match groups on acuity in the way we have done. On the one hand, at least one study has found that people with schizophrenia less often visit an optometrist (Viertiö et al., 2007; see also, Silverstein & Rosen, 2015), suggesting that poor contrast sensitivity at higher spatial frequencies may arise from not having appropriate eyewear (Zemon et al., 2020; Keri et al., 2002). This possibility should be taken seriously because optical blur within the “normal” 20/20 range can diminish sensitivity to Gabor elements with a frequency as low as four cycles/degree (Keane et al., 2022). On the other hand, people with anti-NMDA receptor encephalitis– a condition that symptomatically resembles schizophrenia and that attacks the same receptor that is commonly implicated in schizophrenia (Beck et al., 2020; Singh et al., 2022)–have worse acuity than matched controls, especially for more severe bouts of the infection (Brandt et al., 2016). Thus, either uncorrected refractive error, neural factors, or some combination could worsen contrast sensitivity deficits at higher spatial frequencies in schizophrenia. The same conclusion may hold for other special populations. For example, individuals of advanced age may have impaired acuity due to a combination of neural factors and optical under-correction (La Fleur & Salthouse, 2014; Liou et al., 1999).
Interactions with spatial frequency can be properly reported in a few ways. First, as may already be obvious, log-transforms can approximate homoscedastic, normal distributions, and generalized estimating equations may provide an even better way to model such data (Prekár & Brabec, 2018; Feng et al., 2014). Boxplots or histograms could reveal unexpected data distributions (such as those in Fig. 1B). To avoid confounds with optical blur, an optometrist could measure and correct acuity beforehand so that all subjects have their best corrected visual acuity at the time of testing (BCVA). Note that some investigators mistakenly use the term “BCVA” to refer to habitual acuity rather than optimal acuity (Elliot, 2016). However, only the latter can remove confounds associated with refractive error since many individuals with contacts or glasses will have out-of-date prescriptions. If groups cannot be matched on BCVA, this would be informative as it would indicate a neural origin to poor acuity and argue against any further matching based on acuity. If providing optimal correction to every subject is impractical, refractive error could instead be quantified with an auto-refractor. Portable auto-refractors generate spherical equivalent refractive error estimates that are similar to those of subjective refraction and retinoscopy with or without cycloplegia (Ciuffreda & Rosenfeld, 2015). In this approach, subjects with excessive refractive error could be excluded (e.g., >0.5 diopters, roughly equivalent to 20/30 vision), and subject groups could then be matched on refractive error in a post-hoc analysis, if not in the overall sample. Either way, refractive error must be considered before interpreting interactions with spatial frequency.