The role of timing in shaping information processing in neural systems

Biological sensory systems encode environmental information through large populations of receptors whose activity reaches the brain as parallel spike trains. Understanding how these signals are transformed and which stimulus features are most meaningful to the organism is a central challenge in neuroscience. This dissertation illustrates a comprehensive, data‑driven framework for analyzing relationships between stimuli and their neural representations, complementing traditional hypothesis‑driven approaches. Stimulus sets and neural responses are characterized either categorically or within continuous similarity spaces, and analytical methods are adapted or developed to quantify input–output relationships. Across the datasets examined, stimulus timing consistently emerged as a key feature governing neural encoding.