Beta reactivity, prospective facilitation of executive processing, and its dependence on dopaminergic therapy in Parkinson's disease

Oscillations and the basal ganglia: motor control and beyond

Oscillations form a ubiquitous feature of the central nervous system. Evidence is accruing from cortical and sub-cortical recordings that these rhythms may be functionally important, although the precise details of their roles remain unclear. The basal ganglia share this predilection for rhythmic activity which, as we see in Parkinson's disease, becomes further enhanced in the dopamine depleted state. While certain cortical rhythms appear to penetrate the basal ganglia, others are transformed or blocked. Here, we discuss the functional association of oscillations in the basal ganglia and their relationship with cortical activity. We further explore the neural underpinnings of such oscillatory activity, including the important balance to be struck between facilitating information transmission and limiting information coding capacity. Finally, we introduce the notion that synchronised oscillatory activity can be broadly categorised as immutability promoting rhythms that reinforce incumbent processes, and mutability promoting rhythms that favour novel processing.

Beta-band amplitude oscillations in the human internal globus pallidus support the encoding of sequence boundaries during initial sensorimotor sequence learning

Sequential behavior characterizes both simple everyday tasks, such as getting dressed, and complex skills, such as music performance. The basal ganglia (BG) play an important role in the learning of motor sequences. To study the contribution of the human BG to the initial encoding of sequence boundaries, we recorded local field potentials in the sensorimotor area of the internal globus pallidus (GPi) during the early acquisition of sensorimotor sequences in patients undergoing deep brain stimulation for dystonia. We demonstrated an anticipatory modulation of pallidal beta-band neuronal oscillations that was specific to sequence boundaries, as compared to within-sequence elements, and independent of both the movement parameters and the initiation/termination of ongoing movement. The modulation at sequence boundaries emerged with training, in parallel with skill learning, and correlated with the degree of long-range temporal correlations (LRTC) in the dynamics of ongoing beta-band amplitude oscillations. The implication is that LRTC of beta-band oscillations in the sensorimotor GPi might facilitate the emergence of beta power modulations by the sequence boundaries in parallel with sequence learning. Taken together, the results reveal the oscillatory mechanisms in the human BG that contribute at an initial learning phase to the hierarchical organization of sequential behavior as reflected in the formation of boundary-delimited representations of action sequences.

Synchronous oscillatory neural ensembles for rules in the prefrontal cortex

Intelligent behavior requires acquiring and following rules. Rules define how our behavior should fit different situations. To understand its neural mechanisms, we simultaneously recorded from multiple electrodes in dorsolateral prefrontal cortex (PFC) while monkeys switched between two rules (respond to color versus orientation). We found evidence that oscillatory synchronization of local field potentials (LFPs) formed neural ensembles representing the rules: there were rule-specific increases in synchrony at "beta" (19-40 Hz) frequencies between electrodes. In addition, individual PFC neurons synchronized to the LFP ensemble corresponding to the current rule (color versus orientation). Furthermore, the ensemble encoding the behaviorally dominant orientation rule showed increased "alpha" (6-16 Hz) synchrony when preparing to apply the alternative (weaker) color rule. This suggests that beta-frequency synchrony selects the relevant rule ensemble, while alpha-frequency synchrony deselects a stronger, but currently irrelevant, ensemble. Synchrony may act to dynamically shape task-relevant neural ensembles out of larger, overlapping circuits.