Dynamic Capacity Allocation in Motor-Cognitive Dual-Tasking - probed by Semantic Auditory Stimuli
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Human performance in multitasking situations is constrained by limited processing capacity, requiring dynamic allocation of cognitive and motor resources across simultaneously executed tasks. The present work investigates adaptive capacity allocation during motor-cognitive dual- and triple-task performance using semantically loaded auditory probe stimuli. Building on classical capacity theories, multiple resource models, and structural bottleneck approaches, a two-dimensional time-regime model is proposed that integrates both temporal processing demands and accuracy-related resource allocation.Across a series of experiments, participants performed combinations of a continuous motor tracking task, a cognitive calculation task, and an auditory reaction time task under varying task-load conditions. Performance was assessed using reaction time and error, calculation time and error, motor time lag, and motor accuracy measures. In addition, semantically meaningful auditory stimuli were introduced to examine content-specific interference effects on ongoing task performance. Event-related analyses further differentiated interference patterns across distinct temporal regions of interest before, during, and after stimulus processing.
Results consistently demonstrated performance decrements during multitasking compared to single-task conditions, particularly reflected in prolonged reaction times, increased motor delays, and reduced motor precision. However, error rates often remained comparatively stable, suggesting adaptive redistribution of processing capacity to preserve task accuracy. Semantic stimuli affected reaction times and cognitive processing, while motor performance showed both interference and compensatory stabilization effects depending on task demands and processing phase. Event-related analyses revealed that performance impairments were temporally dynamic rather than constant, supporting the assumption of flexible resource allocation across task phases.
The findings support the proposed time-regime model, according to which tasks operating under flexible temporal constraints are prolonged to maintain accuracy, whereas tasks with fixed temporal requirements are more susceptible to interference and performance breakdown. The findings contribute to a deeper understanding of cognitive-motor interference mechanisms and offer a framework for investigating real-world multitasking behavior in domains such as driving, sports, rehabilitation, and human-machine interaction.