Functional reallocation of sensory processing resources caused by long-term neural adaptation to altered optics

The eye’s optics are a major determinant of visual perception. Elucidating how long-term exposure to optical defects affects visual processing is key to understanding the capacity for, and limits of, sensory plasticity. Here, we show evidence of functional reallocation of sensory processing resources following long-term exposure to poor optical quality. Using adaptive optics to bypass all optical defects, we assessed visual processing in neurotypically-developed adults with healthy eyes and with keratoconus – a corneal disease causing severe optical aberrations. Under fully-corrected optical conditions, keratoconus patients showed altered contrast sensitivity, with impaired sensitivity for fine spatial details and better-than-typical sensitivity for coarse spatial details. Both gains and losses in sensitivity were more pronounced in patients experiencing poorer optical quality in their daily life and mediated by changes in signal enhancement mechanisms. These findings show that adult neural processing adapts to better match the changes in sensory inputs caused by long-term exposure to altered optics.


Sample-size estimation
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Replicates
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Statistical reporting
• Statistical analysis methods should be described and justified • Raw data should be presented in figures whenever informative to do so (typically when N per group is less than 10) • For each experiment, you should identify the statistical tests used, exact values of N, definitions of center, methods of multiple test correction, and dispersion and precision measures (e.g., mean, median, SD, SEM, confidence intervals; and, for the major substantive results, a measure of effect size (e.g., Pearson's r, Cohen's d) • Report exact p-values wherever possible alongside the summary statistics and 95% confidence intervals. These should be reported for all key questions and not only when the p-value is less than 0.05.
Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: (For large datasets, or papers with a very large number of statistical tests, you may upload a single table file with tests, Ns, etc., with reference to sections in the manuscript.)

Group allocation
All information regarding the amount of data collected is detailed in the Material and Methods for each experiment. No data was excluded. As indicated in the manuscript (e.g., p.8), the results of the visual acuity (VA) experiment replicated previous findings (Sabesan & Yoon, 2009). Multiple threshold estimates were collected for each observer, with low variability observed within a given observer. For the qCSF experiment, we collected multiple qCSF runs for each observer to reliably estimate contrast sensitivity across a wide spatial frequency (SF) range. The reliability and efficiency of the qCSF method has been well characterized (e.g., Lesmes et al., 2010;Hou et al., 2010;2016). Moreover, as mentioned (p.12), the results of the equivalent noise paradigm experiment replicated the main findings of the qCSF experiment (i.e., impaired contrast sensitivity at high SFs and better sensitivity at low SFs), despite differences in stimulus and experimental design. Finally, we also indicate that our results replicate previous studies (e.g., Sabesan et al., 2007;Sabesan et al., 2016;Sabesan & Yoon, 2009;Sabesan, Zheleznyak & Yoon, 2012;Zheleznyak et al., 2016) showing that adaptive optics correction can effectively maintain aberrationfree optical quality during visual testing (p.4, 20).
Individual estimates are shown for each experiment (e.g., Fig.2 ,4,5,7,8 3 • Indicate how samples were allocated into experimental groups (in the case of clinical studies, please specify allocation to treatment method); if randomization was used, please also state if restricted randomization was applied • Indicate if masking was used during group allocation, data collection and/or data analysis Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: Additional data files ("source data") • We encourage you to upload relevant additional data files, such as numerical data that are represented as a graph in a figure, or as a summary table • Where provided, these should be in the most useful format, and they can be uploaded as "Source data" files linked to a main figure or table • Include model definition files including the full list of parameters used • Include code used for data analysis (e.g., R, MatLab) • Avoid stating that data files are "available upon request" Please indicate the figures or tables for which source data files have been provided: All observers were screened by one of our ophthalmologists to ensure they could participate in our study (see p.19). Patients diagnosed with keratoconus were allocated to the keratoconus group, and observers with typical 'healthy' optics were allocated to the typical-control group. No masking was used.
All data will be made available on OSF and indicated in the manuscript before publication of the final version.