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A central hypothesis in research on executive function is that controlled information processing is costly and is allocated according to the behavioral benefits it brings. However, while computational theories predict that the benefits of new information depend on prior uncertainty, the cellular effects of uncertainty on the executive network are incompletely understood. Using simultaneous recordings in monkeys, we describe several mechanisms by which the fronto-parietal network reacts to uncertainty. We show that the variance of expected rewards, independently of the value of the rewards, was encoded in single neuron and population spiking activity and local field potential (LFP) oscillations, and, importantly, asymmetrically affected fronto-parietal information transmission (measured through the coherence between spikes and LFPs). Higher uncertainty selectively enhanced information transmission from the parietal to the frontal lobe and suppressed it in the opposite direction, consistent with Bayesian principles that prioritize sensory information according to a decision maker’s prior uncertainty.

To further understand how tactile information is carried in somatosensory cortex (S1) and the thalamus (VPL), and how neuronal plasticity after neuroprosthetic stimulation affects sensory encoding, we chronically implanted microelectrode arrays across hand areas in both S1 and VPL, where neuronal activities were simultaneously recorded during tactile stimulation on the finger pad of awake monkeys. Tactile information encoded in the firing rate of individual units (rate coding) or in the synchrony of unit pairs (synchrony coding) was quantitatively assessed within the information theoretic-framework. We found that tactile information encoded in VPL was higher than that encoded in S1 for both rate coding and synchrony coding; rate coding carried greater information than synchrony coding for the same recording area. With the aim for neuroprosthetic stimulation, plasticity of the circuit was tested after 30 min of VPL electrical stimulation, where stimuli were delivered either randomly or contingent on the spiking of an S1 unit. We showed that neural encoding in VPL was more stable than in S1, which depends not only on the thalamic input but also on recurrent feedback. The percent change of mutual-information after stimulation was increased with closed-loop stimulation, but decreased with random stimulation. The underlying mechanisms during closed-loop stimulation might be spike-timing-dependent plasticity, while frequency-dependent synaptic plasticity might play a role in random stimulation. Our results suggest that VPL could be a promising target region for somatosensory stimulation with closed-loop brain-machine-interface applications.