Lesions in a songbird vocal circuit increase variability in song syntax.

Complex skills like speech and dance are composed of ordered sequences of simpler elements, but the neuronal basis for the syntactic ordering of actions is poorly understood. Birdsong is a learned vocal behavior composed of syntactically ordered syllables, controlled in part by the songbird premotor nucleus HVC (proper name). Here, we test whether one of HVC's recurrent inputs, mMAN (medial magnocellular nucleus of the anterior nidopallium), contributes to sequencing in adult male Bengalese finches (Lonchura striata domestica). Bengalese finch song includes several patterns: (1) chunks, comprising stereotyped syllable sequences; (2) branch points, where a given syllable can be followed probabilistically by multiple syllables; and (3) repeat phrases, where individual syllables are repeated variable numbers of times. We found that following bilateral lesions of mMAN, acoustic structure of syllables remained largely intact, but sequencing became more variable, as evidenced by 'breaks' in previously stereotyped chunks, increased uncertainty at branch points, and increased variability in repeat numbers. Our results show that mMAN contributes to the variable sequencing of vocal elements in Bengalese finch song and demonstrate the influence of recurrent projections to HVC. Furthermore, they highlight the utility of species with complex syntax in investigating neuronal control of ordered sequences.

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.

Discrete Evaluative and Premotor Circuits Enable Vocal Learning in Songbirds.

Virtuosic motor performance requires the ability to evaluate and modify individual gestures within a complex motor sequence. Where and how the evaluative and premotor circuits operate within the brain to enable such temporally precise learning is poorly understood. Songbirds can learn to modify individual syllables within their complex vocal sequences, providing a system for elucidating the underlying evaluative and premotor circuits. We combined behavioral and optogenetic methods to identify 2 afferents to the ventral tegmental area (VTA) that serve evaluative roles in syllable-specific learning and to establish that downstream cortico-basal ganglia circuits serve a learning role that is only premotor. Furthermore, song performance-contingent optogenetic stimulation of either VTA afferent was sufficient to drive syllable-specific learning, and these learning effects were of opposite valence. Finally, functional, anatomical, and molecular studies support the idea that these evaluative afferents bidirectionally modulate VTA dopamine neurons to enable temporally precise vocal learning.

Regulation of subcellular dendritic synapse specificity by axon guidance cues.

Neural circuit assembly occurs with subcellular precision, yet the mechanisms underlying this precision remain largely unknown. Subcellular synaptic specificity could be achieved by molecularly distinct subcellular domains that locally regulate synapse formation, or by axon guidance cues restricting access to one of several acceptable targets. We address these models using two Drosophila neurons: the dbd sensory neuron and the A08a interneuron. In wild-type larvae, dbd synapses with the A08a medial dendrite but not the A08a lateral dendrite. dbd-specific overexpression of the guidance receptors Unc-5 or Robo-2 results in lateralization of the dbd axon, which forms anatomical and functional monosynaptic connections with the A08a lateral dendrite. We conclude that axon guidance cues, not molecularly distinct dendritic arbors, are a major determinant of dbd-A08a subcellular synapse specificity.

Celestial navigation in Drosophila.

Many casual observers typecast Drosophila melanogaster as a stationary pest that lurks around fruit and wine. However, the omnipresent fruit fly, which thrives even in desert habitats, likely established and maintained its cosmopolitan status via migration over large spatial scales. To perform long-distance dispersal, flies must actively maintain a straight compass heading through the use of external orientation cues, such as those derived from the sky. In this Review, we address how D. melanogaster accomplishes long-distance navigation using celestial cues. We focus on behavioral and physiological studies indicating that fruit flies can navigate both to a pattern of linearly polarized light and to the position of the sun - the same cues utilized by more heralded insect navigators such as monarch butterflies and desert ants. In both cases, fruit flies perform menotaxis, selecting seemingly arbitrary headings that they then maintain over time. We discuss how the fly's nervous system detects and processes this sensory information to direct the steering maneuvers that underlie navigation. In particular, we highlight recent findings that compass neurons in the central complex, a set of midline neuropils, are essential for navigation. Taken together, these results suggest that fruit flies share an ancient, latent capacity for celestial navigation with other insects. Furthermore, they illustrate the potential of D. melanogaster to help us to elucidate both the cellular basis of navigation and mechanisms of directed dispersal on a landscape scale.

Temporal identity establishes columnar neuron morphology, connectivity, and function in a Drosophila navigation circuit.

The insect central complex (CX) is a conserved brain region containing 60 + neuronal subtypes, several of which contribute to navigation. It is not known how CX neuronal diversity is generated or how developmental origin of subtypes relates to function. We mapped the developmental origin of four key CX subtypes and found that neurons with similar origin have similar axon/dendrite targeting. Moreover, we found that the temporal transcription factor (TTF) Eyeless/Pax6 regulates the development of two recurrently-connected CX subtypes: Eyeless loss simultaneously produces ectopic P-EN neurons with normal axon/dendrite projections, and reduces the number of E-PG neurons. Furthermore, transient loss of Eyeless during development impairs adult flies' capacity to perform celestial navigation. We conclude that neurons with similar developmental origin have similar connectivity, that Eyeless maintains equal E-PG and P-EN neuron number, and that Eyeless is required for the development of circuits that control adult navigation.

Sun Navigation Requires Compass Neurons in Drosophila.

Despite their small brains, insects can navigate over long distances by orienting using visual landmarks [1], skylight polarization [2-9], and sun position [3, 4, 6, 10]. Although Drosophila are not generally renowned for their navigational abilities, mark-and-recapture experiments in Death Valley revealed that they can fly nearly 15 km in a single evening [11]. To accomplish such feats on available energy reserves [12], flies would have to maintain relatively straight headings, relying on celestial cues [13]. Cues such as sun position and polarized light are likely integrated throughout the sensory-motor pathway [14], including the highly conserved central complex [4, 15, 16]. Recently, a group of Drosophila central complex cells (E-PG neurons) have been shown to function as an internal compass [17-19], similar to mammalian head-direction cells [20]. Using an array of genetic tools, we set out to test whether flies can navigate using the sun and to identify the role of E-PG cells in this behavior. Using a flight simulator, we found that Drosophila adopt arbitrary headings with respect to a simulated sun, thus performing menotaxis, and individuals remember their heading preference between successive flights-even over several hours. Imaging experiments performed on flying animals revealed that the E-PG cells track sun stimulus motion. When these neurons are silenced, flies no longer adopt and maintain arbitrary headings relative to the sun stimulus but instead exhibit frontal phototaxis. Thus, without the compass system, flies lose the ability to execute menotaxis and revert to a simpler, reflexive behavior.

Flying Drosophilamelanogaster maintain arbitrary but stable headings relative to the angle of polarized light.

Animals must use external cues to maintain a straight course over long distances. In this study, we investigated how the fruit fly Drosophila melanogaster selects and maintains a flight heading relative to the axis of linearly polarized light, a visual cue produced by the atmospheric scattering of sunlight. To track flies' headings over extended periods, we used a flight simulator that coupled the angular velocity of dorsally presented polarized light to the stroke amplitude difference of the animals' wings. In the simulator, most flies actively maintained a stable heading relative to the axis of polarized light for the duration of 15 min flights. We found that individuals selected arbitrary, unpredictable headings relative to the polarization axis, which demonstrates that D. melanogaster can perform proportional navigation using a polarized light pattern. When flies flew in two consecutive bouts separated by a 5 min gap, the two flight headings were correlated, suggesting individuals retain a memory of their chosen heading. We found that adding a polarized light pattern to a light intensity gradient enhanced flies' orientation ability, suggesting D. melanogaster use a combination of cues to navigate. For both polarized light and intensity cues, flies' capacity to maintain a stable heading gradually increased over several minutes from the onset of flight. Our findings are consistent with a model in which each individual initially orients haphazardly but then settles on a heading which is maintained via a self-reinforcing process. This may be a general dispersal strategy for animals with no target destination.

Variable sequencing is actively maintained in a well learned motor skill.

Variation in sequencing of actions occurs in many natural behaviors, yet how such variation is maintained is poorly understood. We investigated maintenance of sequence variation in adult Bengalese finch song, a learned skill with rendition-to-rendition variation in the sequencing of discrete syllables (i.e., syllable "b" might transition to "c" with 70% probability and to "d" with 30% probability). We found that probabilities of transitions ordinarily remain stable but could be modified by delivering aversive noise bursts following one transition (e.g., "b→c") but not the alternative (e.g., "b→d"). Such differential reinforcement induced gradual, adaptive decreases in probabilities of targeted transitions and compensatory increases in alternative transitions. Thus, the normal stability of transition probabilities does not reflect hardwired premotor circuitry. While all variable transitions could be modified by differential reinforcement, some were less readily modified than others; these were cases that exhibited more alternation between possible transitions than predicted by chance (i.e., "b→d " would tend to follow "b→c " and vice versa). These history-dependent transitions were less modifiable than more stochastic transitions. Similarly, highly stereotyped transitions (which are completely predictable) were not modifiable. This suggests that stochastically generated variability is crucial for sequence modification. Finally, we found that, when reinforcement ceased, birds gradually restored transition probabilities to their baseline values. Hence, the nervous system retains a representation of baseline probabilities and has the impetus to restore them. Together, our results indicate that variable sequencing in a motor skill can reflect an end point of learning that is stably maintained via continual self-monitoring.

Covert skill learning in a cortical-basal ganglia circuit.

We learn complex skills such as speech and dance through a gradual process of trial and error. Cortical-basal ganglia circuits have an important yet unresolved function in this trial-and-error skill learning; influential 'actor-critic' models propose that basal ganglia circuits generate a variety of behaviours during training and learn to implement the successful behaviours in their repertoire. Here we show that the anterior forebrain pathway (AFP), a cortical-basal ganglia circuit, contributes to skill learning even when it does not contribute to such 'exploratory' variation in behavioural performance during training. Blocking the output of the AFP while training Bengalese finches to modify their songs prevented the gradual improvement that normally occurs in this complex skill during training. However, unblocking the output of the AFP after training caused an immediate transition from naive performance to excellent performance, indicating that the AFP covertly gained the ability to implement learned skill performance without contributing to skill practice. In contrast, inactivating the output nucleus of the AFP during training completely prevented learning, indicating that learning requires activity within the AFP during training. Our results suggest a revised model of skill learning: basal ganglia circuits can monitor the consequences of behavioural variation produced by other brain regions and then direct those brain regions to implement more successful behaviours. The ability of the AFP to identify successful performances generated by other brain regions indicates that basal ganglia circuits receive a detailed efference copy of premotor activity in those regions. The capacity of the AFP to implement successful performances that were initially produced by other brain regions indicates precise functional connections between basal ganglia circuits and the motor regions that directly control performance.

Mechanisms and time course of vocal learning and consolidation in the adult songbird.

In songbirds, the basal ganglia outflow nucleus LMAN is a cortical analog that is required for several forms of song plasticity and learning. Moreover, in adults, inactivating LMAN can reverse the initial expression of learning driven via aversive reinforcement. In the present study, we investigated how LMAN contributes to both reinforcement-driven learning and a self-driven recovery process in adult Bengalese finches. We first drove changes in the fundamental frequency of targeted song syllables and compared the effects of inactivating LMAN with the effects of interfering with N-methyl-d-aspartate (NMDA) receptor-dependent transmission from LMAN to one of its principal targets, the song premotor nucleus RA. Inactivating LMAN and blocking NMDA receptors in RA caused indistinguishable reversions in the expression of learning, indicating that LMAN contributes to learning through NMDA receptor-mediated glutamatergic transmission to RA. We next assessed how LMAN's role evolves over time by maintaining learned changes to song while periodically inactivating LMAN. The expression of learning consolidated to become LMAN independent over multiple days, indicating that this form of consolidation is not completed over one night, as previously suggested, and instead may occur gradually during singing. Subsequent cessation of reinforcement was followed by a gradual self-driven recovery of original song structure, indicating that consolidation does not correspond with the lasting retention of changes to song. Finally, for self-driven recovery, as for reinforcement-driven learning, LMAN was required for the expression of initial, but not later, changes to song. Our results indicate that NMDA receptor-dependent transmission from LMAN to RA plays an essential role in the initial expression of two distinct forms of vocal learning and that this role gradually wanes over a multiday process of consolidation. The results support an emerging view that cortical-basal ganglia circuits can direct the initial expression of learning via top-down influences on primary motor circuitry.

Learning the microstructure of successful behavior.

Reinforcement signals indicating success or failure are known to alter the probability of selecting between distinct actions. However, successful performance of many motor skills, such as speech articulation, also requires learning behavioral trajectories that vary continuously over time. Here, we investigated how temporally discrete reinforcement signals shape a continuous behavioral trajectory, the fundamental frequency of adult Bengalese finch song. We provided reinforcement contingent on fundamental frequency performance only at one point in the song. Learned changes to fundamental frequency were maximal at this point, but also extended both earlier and later in the fundamental frequency trajectory. A simple principle predicted the detailed structure of learning: birds learned to produce the average of the behavioral trajectories associated with successful outcomes. This learning rule accurately predicted the structure of learning at a millisecond timescale, demonstrating that the nervous system records fine-grained details of successful behavior and uses this information to guide learning.