Rapid and reversible manipulations of neural activity in behaving animals are transforming our understanding of brain function. An important assumption underlying much of this work is that evoked behavioural changes reflect the function of the manipulated circuits. We show that this assumption is problematic because it disregards indirect effects on the independent functions of downstream circuits. Transient inactivations of motor cortex in rats and nucleus interface (Nif) in songbirds severely degraded task-specific movement patterns and courtship songs, respectively, which are learned skills that recover spontaneously after permanent lesions of the same areas. We resolve this discrepancy in songbirds, showing that Nif silencing acutely affects the function of HVC, a downstream song control nucleus. Paralleling song recovery, the off-target effects resolved within days of Nif lesions, a recovery consistent with homeostatic regulation of neural activity in HVC. These results have implications for interpreting transient circuit manipulations and for understanding recovery after brain lesions.

Executing a motor skill requires the brain to control which muscles to activate at what times. How these aspects of control - motor implementation and timing - are acquired, and whether the learning processes underlying them differ, is not well understood. To address this we used a reinforcement learning paradigm to independently manipulate both spectral and temporal features of birdsong, a complex learned motor sequence, while recording and perturbing activity in underlying circuits. Our results uncovered a striking dissociation in how neural circuits underlie learning in the two domains. The basal ganglia was required for modifying spectral, but not temporal structure. This functional dissociation extended to the descending motor pathway, where recordings from a premotor cortex analogue nucleus reflected changes to temporal, but not spectral structure. Our results reveal a strategy in which the nervous system employs different and largely independent circuits to learn distinct aspects of a motor skill.

The acquisition of complex motor sequences often proceeds through trial-and-error learning, requiring the deliberate exploration of motor actions and the concomitant evaluation of the resulting performance. Songbirds learn their song in this manner, producing highly variable vocalizations as juveniles. As the song improves, vocal variability is gradually reduced until it is all but eliminated in adult birds. In the present study we examine how the motor program underlying such a complex motor behavior evolves during learning by recording from the robust nucleus of the arcopallium (RA), a motor cortex analog brain region. In young birds, neurons in RA exhibited highly variable firing patterns that throughout development became more precise, sparse, and bursty. We further explored how the developing motor program in RA is shaped by its two main inputs: LMAN, the output nucleus of a basal ganglia-forebrain circuit, and HVC, a premotor nucleus. Pharmacological inactivation of LMAN during singing made the song-aligned firing patterns of RA neurons adultlike in their stereotypy without dramatically affecting the spike statistics or the overall firing patterns. Removing the input from HVC, on the other hand, resulted in a complete loss of stereotypy of both the song and the underlying motor program. Thus our results show that a basal ganglia-forebrain circuit drives motor exploration required for trial-and-error learning by adding variability to the developing motor program. As learning proceeds and the motor circuits mature, the relative contribution of LMAN is reduced, allowing the premotor input from HVC to drive an increasingly stereotyped song.

3D printing allows rapid fabrication of complex objects from digital designs. One 3D-printing process, direct laser writing, polymerises a lightsensitive material by steering a focused laser beam through the shape of the object to be created. The highest-resolution direct laser writing systems use a femtosecond laser to effect two-photon polymerisation. The focal (polymerisation) point is steered over the shape of the desired object with mechanised stages or galvanometer-controlled mirrors. Here we report a new high-resolution direct laser writing system that employs a resonant mirror scanner to achieve a significant increase in printing speed over galvanometer-or piezo-based methods while maintaining resolution on the order of a micron. This printer is based on a software modification to a commerically available resonant-scanning two-photon microscope. We demonstrate the complete process chain from hardware configuration and control software to the printing of objects of approximately 400 × 400 × 350 µm, and validate performance with objective benchmarks.Released under an open-source license, this work makes micro-scale 3D printing available the large community of two-photon microscope users, and paves the way toward widespread availability of precision-printed devices.Comments: Corresponding author: BWP (bwpearre@bu.edu). TJG and TMO contributed equally to this work.Conflict-of-Interest statement: TJG is an employee of Neuralink Inc.