Neural representation of current and intended task sets during sequential judgements on human faces Díaz Gutiérrez, Paloma Gilbert, Sam Arco Martín, Juan Eloy Sobrado, Alberto Ruz Cámara, María Delayed intentions Dual-sequential task PFC fMRI MVPA Engaging in a demanding activity while holding in mind another task to be performed in the near future requires the maintenance of information about both the currently-active task set and the intended one. However, little is known about how the human brain implements such action plans. While some previous studies have examined the neural representation of current task sets and others have investigated delayed intentions, to date none has examined the representation of current and intended task sets within a single experimental paradigm. In this fMRI study, we examined the neural representation of current and intended task sets, employing sequential classification tasks on human faces. Multivariate decoding analyses showed that current task sets were represented in the orbitofrontal cortex (OFC) and fusiform gyrus (FG), while intended tasks could be decoded from lateral prefrontal cortex (lPFC). Importantly, a ventromedial region in PFC/OFC contained information about both current and delayed tasks, although cross-classification between the two types of information was not possible. These results help delineate the neural representations of current and intended task sets, and highlight the importance of ventromedial PFC/OFC for maintaining task-relevant information regardless of when it is needed. 2019-12-19T11:50:44Z 2019-12-19T11:50:44Z 2019-09-20 info:eu-repo/semantics/article Díaz-Gutiérrez, P., Gilbert, S. J., Arco, J. E., Sobrado, A., & Ruz, M. (2020). Neural representation of current and intended task sets during sequential judgements on human faces. NeuroImage, 204, 116219. http://hdl.handle.net/10481/58429 10.1016/j.neuroimage.2019.116219 eng http://creativecommons.org/licenses/by-nc-nd/3.0/es/ info:eu-repo/semantics/openAccess Atribución-NoComercial-SinDerivadas 3.0 España Elsevier BV