[Reward processing of the basal ganglia--reward function of pedunculopontine tegmental nucleus]

We address the role of neuronal activity in the pathways of the brainstem-midbrain circuit in reward and the basis for the hypothesis that this circuit provides advantages over previous reinforcement learning theories. Several lines of evidence support the reward-based learning theory proposing that midbrain dopamine (DA) neurons emit a teaching signal (the reward prediction error signal) to control synaptic plasticity of the projection area. However, the underlying mechanism of the location and manner in which the reward prediction error signal is computed remains unclear. Since the pedunculopontine tegmental nucleus (PPTN) in the brainstem is one of the strongest excitatory input sources to DA neurons, we hypothesized that the PPTN may play an important role in activating the DA neurons and reinforce learning by relaying necessary signals for reward prediction error computation to those neurons. To investigate the involvement of PPTN neurons in reward prediction error computation, we employed a visually guided saccade task while recording the neuronal activity in monkeys. Here, we predict that PPTN neurons may relay the excitatory component of tonic reward prediction and phasic primary reward signals, and derive a new computational theory of reward prediction error in DA neurons.