Time-Resolved Decoding of Two Processing Chains during Dual-Task Interference

The human brain exhibits fundamental limitations in multitasking. When subjects engage in a primary task, their ability to respond to a second stimulus is degraded. Two competing models of multitasking have been proposed: either cognitive resources are shared between tasks, or they are allocated to each task serially. Using a novel combination of magneto-encephalography and multivariate pattern analyses, we obtained a precise spatio-temporal decomposition of the brain processes at work during multitasking. We discovered that each task relies on a sequence of brain processes. These sequences can operate in parallel for several hundred milliseconds but beyond similar to 500 ms, they repel each other: processes evoked by the first task are shortened, while processes of the second task are either lengthened or postponed. These results contradict the resource-sharing model and further demonstrate that the serial model is incomplete. We therefore propose a new theoretical framework for the computational architecture underlying multitasking.