Environmental noise, GABA, and the auditory brain across the lifespan: A mechanistic gap analysis

Environmental noise has been associated with altered auditory physiology, impaired speech perception, and adverse developmental outcomes, yet the causal mechanisms connecting these observations remain incompletely established. This review applies the Mechanistic Gap Index (MGI), a quantitative framework for evaluating individual causal transitions, to proposed pathways involving environmental noise, cochlear synaptopathy, GABAergic inhibition, neural encoding, and auditory development. Eight relationships yielded a mean MGI of 0.75, with four critical evidentiary bottlenecks. Application of the same scoring criteria to a more established auditory-training mechanism yielded an MGI of 0.33, providing a preliminary comparison of mechanistic completeness. Beyond identifying missing causal links, we propose extending the MGI in four directions: prioritizing experiments capable of closing specific gaps; investigating long-range causal relationships between apparently disconnected biological observations; identifying overlooked intermediate mechanisms concealed within unsupported causal transitions; and iteratively refining causal pathways as new evidence emerges. Importantly, a high-gap transition may reflect not only insufficient evidence but also an incompletely specified mechanism containing unidentified intermediate processes. Decomposing such transitions could reveal experimentally supported connections and isolate the specific missing steps required for causal closure. Prospective measures of mechanistic gain, longitudinal MGI assessment, and a complementary measure of mechanistic resolution could further support this approach. Although these extensions require independent validation, the proposed advance is to transform the MGI from a descriptive assessment of evidentiary gaps into an iterative framework for experimental prioritization, mechanistic reconstruction, and causal discovery.