Variable but not random: temporal pattern coding in a songbird brain area necessary for song modification

Millisecond-scale motor control precedes sensorimotor learning in Bengalese finches

A key goal of the nervous system in young animals is to learn motor skills. Songbirds learn to sing as juveniles, providing a unique opportunity to identify the neural correlates of skill acquisition. Prior studies have shown that spike rate variability decreases during song acquisition, suggesting a transition from rate-based neural control to the millisecond-precise motor codes known to underlie adult vocal performance. By quantifying how the ensemble of spike patterns fired by cortical neurons (the "neural vocabulary") and the relationship between spike patterns and song acoustics (the "neural code") change during song acquisition, we quantified how vocal control changes across learning in juvenile Bengalese finches. We found that despite the expected drop in rate variability (a learning-related change in spike vocabulary), the precision of the neural code in the youngest singers is the same as in adults, with 1-2 millisecond variations in spike timing transduced into quantifiably different behaviors. In contrast, fluctuations of firing rates on longer timescales fail to affect the motor output. The consistent presence of millisecond-scale motor coding during changing levels of spike rate and behavioral variability supports the view that variability early in learning stems from deliberate motor exploration rather than imprecise motor control.

Dynamic top-down biasing implements rapid adaptive changes to individual movements

Complex behaviors depend on the coordinated activity of neural ensembles in interconnected brain areas. The behavioral function of such coordination, often measured as co-fluctuations in neural activity across areas, is poorly understood. One hypothesis is that rapidly varying co-fluctuations may be a signature of moment-by-moment task-relevant influences of one area on another. We tested this possibility for error-corrective adaptation of birdsong, a form of motor learning which has been hypothesized to depend on the top-down influence of a higher-order area, LMAN (lateral magnocellular nucleus of the anterior nidopallium), in shaping moment-by-moment output from a primary motor area, RA (robust nucleus of the arcopallium). In paired recordings of LMAN and RA in singing birds, we discovered a neural signature of a top-down influence of LMAN on RA, quantified as an LMAN-leading co-fluctuation in activity between these areas. During learning, this co-fluctuation strengthened in a premotor temporal window linked to the specific movement, sequential context, and acoustic modification associated with learning. Moreover, transient perturbation of LMAN activity specifically within this premotor window caused rapid occlusion of pitch modifications, consistent with LMAN conveying a temporally localized motor-biasing signal. Combined, our results reveal a dynamic top-down influence of LMAN on RA that varies on the rapid timescale of individual movements and is flexibly linked to contexts associated with learning. This finding indicates that inter-area co-fluctuations can be a signature of dynamic top-down influences that support complex behavior and its adaptation.

Temporal dynamics of Na/K pump mediated memory traces: insights from conductance-based models of Drosophila neurons

Sodium potassium ATPases (Na/K pumps) mediate long-lasting, dynamic cellular memories that can last tens of seconds. The mechanisms controlling the dynamics of this type of cellular memory are not well understood and can be counterintuitive. Here, we use computational modeling to examine how Na/K pumps and the ion concentration dynamics they influence shape cellular excitability. In a Drosophila larval motor neuron model, we incorporate a Na/K pump, a dynamic intracellular Na⁺ concentration, and a dynamic Na⁺ reversal potential. We probe neuronal excitability with a variety of stimuli, including step currents, ramp currents, and zap currents, then monitor the sub- and suprathreshold voltage responses on a range of time scales. We find that the interactions of a Na⁺-dependent pump current with a dynamic Na⁺ concentration and reversal potential endow the neuron with rich response properties that are absent when the role of the pump is reduced to the maintenance of constant ion concentration gradients. In particular, these dynamic pump-Na⁺ interactions contribute to spike rate adaptation and result in long-lasting excitability changes after spiking and even after sub-threshold voltage fluctuations on multiple time scales. We further show that modulation of pump properties can profoundly alter a neuron's spontaneous activity and response to stimuli by providing a mechanism for bursting oscillations. Our work has implications for experimental studies and computational modeling of the role of Na/K pumps in neuronal activity, information processing in neural circuits, and the neural control of animal behavior.