This study investigates how contextual cues and prior evidence guide human goal-directed behavior, focusing on the neurophysiological mechanisms underlying the integration of contextual information into actions. Using intracranial electroencephalography (iEEG), the researchers demonstrate that increasing uncertainty shifts brain processing from purely oscillatory to a mixed regime involving ramping dynamics. Oscillatory and ramping dynamics reflect dissociable signatures, likely contributing differently to the encoding and transfer of cognitive variables in a cue-guided motor task. The results suggest that prefrontal activity encodes rules and actions in distinct subspaces, while theta oscillations synchronize the prefrontal-motor network to guide action execution. Human decisions depend on prior evidence and contextual cues. The active sensing framework posits that the brain uses its inherent rhythmic structure as an energy-efficient mechanism for temporal predictions. This framework predicts that the brain switches from a rhythmic to a continuous, energy-costly processing mode when less prior evidence is available. Active sensing also implies that synchronization of endogenous oscillations is crucial for inter-areal information transfer. Recent work in non-human primates has shown that sensorimotor cortex and adjacent areas encode high-level contextual information in neural population codes. However, population coding and neural oscillations, two key signatures of coordinated population activity, have mainly been studied in isolation. In this study, the researchers tested how high-level contextual information is flexibly integrated into actions in humans. They specifically examined whether principles of the active sensing framework apply to prefrontal-motor interactions when context is rule-based. They also aimed to determine the population correlates of rhythmic and continuous processing modes. The study used iEEG from patients with epilepsy to record activity in prefrontal and motor cortex during a cue-guided motor task. The results showed that context was encoded in distinct subspaces by the prefrontal cortex, while theta oscillations mediated communication between prefrontal and motor cortex to guide context-dependent actions. The study found that ramping dynamics in the prefrontal cortex were modulated by predictive context, while oscillatory dynamics in the motor cortex were not. These findings suggest that ramping dynamics in the prefrontal cortex dissociate states of uncertainty, while neural oscillations may dynamically coordinate prefrontal-motor network interactions in a context-dependent manner. The results also indicate that theta oscillations temporally coordinate action-encoding subspaces in the prefrontal-motor network, mediating the cross-regional generalization of action plans. Collectively, the results reveal how continuous ramping dynamics and oscillatory synchrony jointly support rule-guided human behavior.This study investigates how contextual cues and prior evidence guide human goal-directed behavior, focusing on the neurophysiological mechanisms underlying the integration of contextual information into actions. Using intracranial electroencephalography (iEEG), the researchers demonstrate that increasing uncertainty shifts brain processing from purely oscillatory to a mixed regime involving ramping dynamics. Oscillatory and ramping dynamics reflect dissociable signatures, likely contributing differently to the encoding and transfer of cognitive variables in a cue-guided motor task. The results suggest that prefrontal activity encodes rules and actions in distinct subspaces, while theta oscillations synchronize the prefrontal-motor network to guide action execution. Human decisions depend on prior evidence and contextual cues. The active sensing framework posits that the brain uses its inherent rhythmic structure as an energy-efficient mechanism for temporal predictions. This framework predicts that the brain switches from a rhythmic to a continuous, energy-costly processing mode when less prior evidence is available. Active sensing also implies that synchronization of endogenous oscillations is crucial for inter-areal information transfer. Recent work in non-human primates has shown that sensorimotor cortex and adjacent areas encode high-level contextual information in neural population codes. However, population coding and neural oscillations, two key signatures of coordinated population activity, have mainly been studied in isolation. In this study, the researchers tested how high-level contextual information is flexibly integrated into actions in humans. They specifically examined whether principles of the active sensing framework apply to prefrontal-motor interactions when context is rule-based. They also aimed to determine the population correlates of rhythmic and continuous processing modes. The study used iEEG from patients with epilepsy to record activity in prefrontal and motor cortex during a cue-guided motor task. The results showed that context was encoded in distinct subspaces by the prefrontal cortex, while theta oscillations mediated communication between prefrontal and motor cortex to guide context-dependent actions. The study found that ramping dynamics in the prefrontal cortex were modulated by predictive context, while oscillatory dynamics in the motor cortex were not. These findings suggest that ramping dynamics in the prefrontal cortex dissociate states of uncertainty, while neural oscillations may dynamically coordinate prefrontal-motor network interactions in a context-dependent manner. The results also indicate that theta oscillations temporally coordinate action-encoding subspaces in the prefrontal-motor network, mediating the cross-regional generalization of action plans. Collectively, the results reveal how continuous ramping dynamics and oscillatory synchrony jointly support rule-guided human behavior.