{"doi":"10.1101/2025.07.25.25331915","title":"A Practical Introduction to Wavelet Analysis in Electroretinography","abstract":"Purpose: To provide a conceptual understanding of the continuous and discrete wavelet transforms (CWT, DWT) for clinical electroretinography (ERG) analysis, and how these methods uncover time-frequency features that complement traditional time-domain analysis. Methods: A technical overview without the use of mathematical formula describing the basics of CWT and DWT and implementation considerations. We also review an example of four standard ISCEV ERG recordings from a healthy male (between 30-34 years of age) and a male (between 15-19 years of age) with complete congenital stationary night blindness (CSNB). Results: Wavelet analysis uncovered time-frequency signatures absent in raw traces. In light-adapted flicker, the normal ERG showed a ~30 Hz response with harmonics up to 90 Hz, whereas CSNB was largely attenuated. For LA 3 and dark-adapted flashes, normal CWTs concentrated energy < 100 Hz between 0.04-0.08 s, while CSNB demonstrated lowered or almost absent energy profiles in comparison. DWT indices exhibited a similar pattern, with normal recordings demonstrating high energy responses early in the 7, 15, and 29 Hz frequency bands, while CSNB registered markedly lower values. Conclusions: CWT and DWT provide complementary and objective insight into ERG responses. Open-source MATLAB toolkit and step-by-step tutorial provided herein lower technical barriers and enable use by the broader community.","journal":"medRxiv","year":2025,"id":558591,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9595,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":537664,"name":"David S. Lalush","orcid":"0000-0002-7240-929X","position":1,"is_corresponding":false},{"id":475252,"name":"J. Jason McAnany","orcid":"0000-0003-1192-3487","position":2,"is_corresponding":false},{"id":528996,"name":"Brett G. Jeffrey","orcid":"0000-0001-9549-0644","position":3,"is_corresponding":false},{"id":4026,"name":"Melissa A Haendel","orcid":"0000-0001-9114-8737","position":4,"is_corresponding":false},{"id":1369338,"name":"Yousif J. Shwetar","orcid":"0000-0002-0587-4693","position":0,"is_corresponding":true}],"reference_count":19,"raw_metadata":null,"created_at":"2026-07-19T02:55:25.969263Z","pmid":"40778145","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}