An EEG dataset for structured auditory sequence processing with Morse code sounds

Abstract Auditory processing of structured sound sequences requires information to be integrated across time while preserving sequence content and order, allowing different properties of the same auditory input to guide different behavioral decisions. Yet openly available human EEG resources remain limited for studying explicitly structured auditory sequences processed under different decision rules within the same participants. Here we present MorseEEG-ATP, a two-task EEG dataset from 32 Morse-naïve adults who listened to the same set of 78 single-character Morse-code sounds while performing dot-count and first–last matching tasks. The dataset combines shared auditory input with distinct decision rules, enabling investigation of sequence-level temporal and structural variation, task-associated EEG and behavioral features, and cross-task correspondence and generalization. It includes continuous BIDS-organized EEG, trial-level behavioral and event records, auditory stimuli and metadata, baseline-preprocessed derivatives, and analysis code. Technical validation demonstrates consistent behavioral task engagement, characterizes EEG preprocessing yield, identifies consistent stimulus-marker-locked EEG responses, and provides exploratory evidence of EEG spectral variation associated with individual differences in task performance.