Abstract Neural signal shapes convey significant information about their generating processes. In this study, we introduce a data-driven methodology to identify sensory and behaviourally-relevant traces within neural responses. We present a phenomenological model that characterises temporal variations in intracranial EEG using eight interpretable parameters: peak time, peak intensity, initial and final baselines, accumulation and depletion period, and their respective concavities.
