Flexible spike timing of layer 5 neurons during dynamic beta oscillation shifts in rat prefrontal cortex.

Human brain oscillations occur in different frequency bands that have been linked to different behaviours and cognitive processes. Even within specific frequency bands such as the beta- (14-30 Hz) or gamma-band (30-100 Hz), oscillations fluctuate in frequency and amplitude. Such frequency fluctuations most probably reflect changing states of neuronal network activity, as brain oscillations arise from the correlated synchronized activity of large numbers of neurons. However, the neuronal mechanisms governing the dynamic nature of amplitude and frequency fluctuations within frequency bands remain elusive. Here we show that in acute slices of rat prefrontal cortex (PFC), carbachol-induced oscillations in the beta-band show frequency and amplitude fluctuations. Fast and slow non-harmonic frequencies are distributed differentially over superficial and deep cortical layers, with fast frequencies being present in layer 3, while layer 6 only showed slow oscillation frequencies. Layer 5 pyramidal cells and interneurons experience both fast and slow frequencies and they time their spiking with respect to the dominant frequency. Frequency and phase information is encoded and relayed in the layer 5 network through timed excitatory and inhibitory synaptic transmission. Our data indicate that frequency fluctuations in the beta-band reflect synchronized activity in different cortical subnetworks, that both influence spike timing of output layer 5 neurons. Thus, amplitude and frequency fluctuations within frequency bands may reflect activity in distinct cortical neuronal subnetworks that may process information in a parallel fashion.

Anticipatory reward signals in ventral striatal neurons of behaving rats.

It has been proposed that the striatum plays a crucial role in learning to select appropriate actions, optimizing rewards according to the principles of 'Actor-Critic' models of trial-and-error learning. The ventral striatum (VS), as Critic, would employ a temporal difference (TD) learning algorithm to predict rewards and drive dopaminergic neurons. This study examined this model's adequacy for VS responses to multiple rewards in rats. The respective arms of a plus-maze provided rewards of varying magnitudes; multiple rewards were provided at 1-s intervals while the rat stood still. Neurons discharged phasically prior to each reward, during both initial approach and immobile waiting, demonstrating that this signal is predictive and not simply motor-related. In different neurons, responses could be greater for early, middle or late droplets in the sequence. Strikingly, this activity often reappeared after the final reward, as if in anticipation of yet another. In contrast, previous TD learning models show decremental reward-prediction profiles during reward consumption due to a temporal-order signal introduced to reproduce accurate timing in dopaminergic reward-prediction error signals. To resolve this inconsistency in a biologically plausible manner, we adapted the TD learning model such that input information is nonhomogeneously distributed among different neurons. By suppressing reward temporal-order signals and varying richness of spatial and visual input information, the model reproduced the experimental data. This validates the feasibility of a TD-learning architecture where different groups of neurons participate in solving the task based on varied input information.

Neural coding of reward magnitude in the orbitofrontal cortex of the rat during a five-odor olfactory discrimination task.

The orbitofrontal cortex (OBFc) has been suggested to code the motivational value of environmental stimuli and to use this information for the flexible guidance of goal-directed behavior. To examine whether information regarding reward prediction is quantitatively represented in the rat OBFc, neural activity was recorded during an olfactory discrimination "go"/"no-go" task in which five different odor stimuli were predictive for various amounts of reward or an aversive reinforcer. Neural correlates related to both actual and expected reward magnitude were observed. Responses related to reward expectation occurred during the execution of the behavioral response toward the reward site and within a waiting period prior to reinforcement delivery. About one-half of these neurons demonstrated differential firing toward the different reward sizes. These data provide new and strong evidence that reward expectancy, regardless of reward magnitude, is coded by neurons of the rat OBFc, and are indicative for representation of quantitative information concerning expected reward. Moreover, neural correlates of reward expectancy appear to be distributed across both motor and nonmotor phases of the task.

Neurons in hippocampal afferent zones of rat striatum parse routes into multi-pace segments during maze navigation.

Hippocampal 'place' neurons discharge when rats occupy specific regions within an environment. This finding is a cornerstone of the theory of the hippocampus as a cognitive map of space. But for navigation, representations of current position must be implemented by signals concerning where to go next, and how to get there. In recordings in hippocampal output structures associated with the motor system (nucleus accumbens and ventromedial caudate nucleus) in rats solving a plus-maze, neurons fired continuously from the moment the rat left one location until it arrived at the next goal site, or at an intermediate place, such as the maze centre. While other studies have shown discharges during reward approach behaviours, this is the first demonstration of activity corresponding to the parsing of complex routes into sequences of movements between landmarks, similar to the lists of instructions we often employ to communicate directions to follow between points on a map. As these cells fired during a series of several paces or re-orientation movements, perhaps this is homologous to 'chunking'. The temporal overlaps in the activity profiles of the individual neurons provide a possible substrate to successively trigger movements required to arrive at the goal. These hippocampally informed, and in some cases, spatially selective responses support the view of the ventral striatum as an interface between limbic and motor systems, permitting contextual representations to have an impact on fundamental action sequences for goal-directed behaviour.

Learning-related changes in response patterns of prefrontal neurons during instrumental conditioning.

A crucial aspect of organizing goal-directed behavior is the ability to form neural representations of relationships between environmental stimuli, actions and reinforcement. Very little is known yet about the neural encoding of response-reward relationships, a process which is deemed essential for purposeful behavior. To investigate this, tetrode recordings were made in the medial prefrontal cortex (PFC) of rats performing a Go-NoGo task. After task acquisition, a subset of neurons showed a sustained change in firing during the rewarded action sequence that was triggered by a specific visual cue. When these changes were monitored in the course of learning, they were seen to develop in parallel with the behavioral learning curve and were highly sensitive to a switch in reward contingencies. These sustained changes correlated with the reward-associated action sequence, not with sensory or reward-predicting properties of the cue or individual motor acts per se. This novel type of neural plasticity may contribute to the formation of response-reinforcer associations and of behavioral strategies for guiding goal-directed action.