Our knowledge about neural mechanisms underlying decision making is largely based on experiments that involved few options. However, it is more common in daily life to choose between many options, in which processing choice information selectively is particularly important. The current study examined whether the dorsolateral prefrontal cortex (dlPFC) and posterior parietal cortex (PPC) are of particular importance to multiple-option decision making. Sixty-eight participants received anodal high definition-transcranial direct current stimulation (HD-tDCS) to focally enhance dlPFC or PPC in a double-blind sham-controlled design. Participants then performed a multiple-option decision making task. We found longer fixations on poorer options were related to less optimal decisions. Interestingly, this negative impact was attenuated after applying anodal HD-tDCS over dlPFC, especially in choices with many options. This suggests that dlPFC has a causal role in filtering choice-irrelevant information. In contrast, these effects were absent after participants received anodal HD-tDCS over PPC. Instead, the choices made by these participants were more biased towards the best options presented on the side contralateral to the stimulation. This suggests PPC has a causal role in value-based spatial selection. To conclude, the dlPFC has a role in filtering undesirable options, whereas the PPC emphasizes the desirable contralateral options.

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When foraging for food, animals must track the sensory events of their environment and their own actions over time. Memory of these sensorimotor events is crucial for learning the values of different options and foraging policies 1. To investigate the role of the medial prefrontal cortex (mPFC) in foraging behavior, we conducted experiments on mice using foraging tasks that required integration of past oro-sensory rewards and past choices. We found that the mPFC selectively represents sensorimotor events, which organize into a spatiotemporal map encoding location and temporal delay of past rewards and choices relative to the animal's current epoch in time. These representations of sensorimotor events, which we refer to as sensorimotor state representations, play a critical role in foraging behavior. Inactivation of the mPFC affected the integration of past rewards and choices into the mice's decisions, leading to a decrease in reward harvesting efficiency, particularly for longer temporal delays. Behavioral models that compute values and policy failed to capture the representations in mPFC. Our results suggest that the mPFC plays a critical role in representing sensorimotor states independently of value and policy computations. This highlights the importance of considering sensorimotor state representation in the mPFC in understanding foraging behavior.