Bring your scienceto the isthmus.

How neural circuits generate diverse behaviors is a fundamental question in neuroscience. Distinct behavioral outputs may arise from either dedicated motor circuits or shared circuits operating in different functional states. Using the rich vocal repertoire of the singing mouse (Scotinomys teguina), this work identifies two distinct vocal modes—ancestral ultrasonic vocalizations used for short-range communication and loud, rhythmic songs used over long distances. Despite their acoustic and contextual differences, both modes share a sound-production mechanism, phonatory-respiratory coupling, and vocal gating from the midbrain caudolateral periaqueductal gray. Mathematical modeling and circuit perturbations show how parametric tuning of this central circuit node can produce distinct vocal modes, offering a mechanistic basis for rapid behavioral evolution in mammals.

Temporal contiguity between events—how close they occur in time—is not sufficient to explain learning. However, prominent models of reinforcement learning that are frequently fit to human and animal behavior rely on contiguity to compute values of states and actions. My postdoctoral research sought to understand whether dopamine dynamics still resemble prediction errors when temporal contiguity between events in the environment is left unchanged, but the causal relation between events is altered. Using fiber photometry and optogenetics with outcome-selective contingency degradation in rats, I found that dopamine neuron activity in the midbrain and dopamine release in the ventral striatum are best explained by a model in which dopamine triggers retrospective causal inference. These results were consistent with simulations in which phasic dopamine encodes the sum of learned contingencies between meaningful events, but inconsistent with a standard temporal-difference model in which phasic dopamine encodes a reward prediction error. Overall, this work asks us to rethink how dopamine contributes to basic mechanisms of plasticity.

Alcohol Use Disorder is defined by shared diagnostic criteria, yet individuals show strikingly diverse drinking patterns and relapse vulnerabilities. To understand how bed nucleus of the stria terminalis (BNST) function varies across individuals, we used the Structured Tracking of Alcohol Reinforcement task to phenotype mice as high, low, or compulsive ethanol drinkers. BNST activation correlated with ethanol intake, while compulsive drinkers displayed elevated BNST calcium transients during drinking despite similar intake across groups. Forced abstinence uncovered phenotype-specific adaptations: high and low drinkers reduced seeking across abstinence, whereas compulsive drinkers persisted and showed increased BNST transients during protracted abstinence. Abstinence experience itself also potentiated compulsive drinking. Together, these findings reveal that ethanol abstinence precipitates increased seeking and compulsive intake linked to dynamic, phenotype-specific BNST activity, identifying a neural correlate of relapse vulnerability and offering insight into the biological diversity of alcohol use disorder.

Body-to-brain communication influences nearly every aspect of behavior, from immediate feelings of thirst or hunger to lifelong pair bonds and mood states. Yet technical and conceptual barriers have kept the neural mechanisms underlying these effects largely unexplored. This work develops and applies new tools for studying how signals from internal organs influence neural dynamics in behaving animals, combining systems and computational neuroscience, physiology, biochemistry, and bioengineering. Mouth- and gut-to-brain signals enable the brain’s thirst system to predict changes in hydration before they occur and adjust drinking preemptively. Delayed gut-to-brain food-poisoning signals also reactivate the brain’s representation of flavors from a recent meal, providing a mechanism for learning food aversions. Together, these findings offer neural explanations for long-enigmatic elements of everyday experience while revealing general principles for how learning and motivation are instantiated in the brain.

How the brain’s wiring diagram shapes neural computation is a fundamental question in neuroscience. To test the limits of connectome-based functional predictions, I developed a sparse imaging paradigm to characterize the visual selectivity of 91 cell types in the fruit fly optic lobe. Comparing measured responses with connectome-based predictions revealed good performance for some properties, such as orientation tuning, but surprisingly poor performance for others, such as receptive-field size. Strong connections consisting of numerous input synapses exerted a disproportionately large influence on postsynaptic activity: predictions based on a neuron’s single strongest input were as accurate as models considering its full complement of inputs. Strong inputs to a given cell type were also more functionally homogeneous than expected by chance. These results reframe our understanding of structure and function in the brain and define principles for improving future connectome-based functional predictions.

Learning by imitation is the foundation for verbal and musical expression, but its neural basis remains obscure. A juvenile male zebra finch imitates an adult tutor through a song-specialized cortico-basal ganglia circuit, providing a powerful system for locating the synaptic substrates of imitative motor learning. Combining a computational framework for quantifying song learning with synapse-specific optogenetic and chemogenetic manipulations, we identified the cortico-basal ganglia synapses that drive the acquisition and expression of rapid vocal changes and characterized the hours-long timescale over which those changes consolidate. Transiently augmenting postsynaptic activity in the basal ganglia briefly accelerated learning and persistently altered song. These results identify the synaptic locus that enables a juvenile songbird to learn to sing and reveal the circuit logic and behavioral timescales of imitative learning.

Anthropogenic change is creating environments enriched in toxic chemicals, including arsenic-contaminated drinking water. To understand biological resilience, we study Tokorhabditis tufae, a culturable nematode isolated from arsenic-rich Mono Lake. Unlike most nematodes, T. tufae hatches its progeny internally and gives birth to live young. Pharmacology and immunostaining reveal distinct neurobiological control of live birth, with changes that support egg retention and internal hatching. Gestation protects progeny from toxins until they are born in a stress-resistant dauer stage, and developing progeny transition from quiescence to a mobile state that facilitates birth through their own movement. These findings suggest that adaptation to an extreme environment involves coordinated neurobiological, physiological, and behavioral changes. Ongoing international collaborations are establishing T. tufae as a model for studying how neural circuits and behaviors evolve in contaminated environments.

Flexible visuospatial behavior requires transforming sensory input into stable, internally maintained action plans, a process thought to involve posterior parietal cortex. We recorded spiking activity and local field potentials from areas CIP and V3A in rhesus macaques performing memory-guided and visually guided saccade tasks. A brief, task-specific transient of beta-band synchronization emerged after target offset during memory-guided trials but was absent during visually guided behavior. It appeared earlier in CIP than V3A, predicted subsequent saccade accuracy, and preceded a sustained increase in induced beta power that also scaled with performance. Visually guided trials instead showed sustained beta suppression related to accuracy. Across tasks, beta dynamics showed a push–pull organization: suppression accompanied externally driven orienting, while enhancement accompanied endogenous maintenance. We propose that transient beta synchronization marks a hierarchical control signal that reconfigures network states for stable, internally guided action.

The ability to generalize learning across contexts is essential for navigating the world. We used calcium imaging to monitor hippocampal neurons as animals performed a conditioning task across multiple spatial contexts, asking whether cells could preserve task information even as their spatial encoding remapped. Dimensionality-reduction and machine-learning methods revealed that task-related neural representations remained stable while place-cell representations changed, producing similar embedding geometries across contexts. These patterns were consistent not only within individual animals but also across animals, suggesting a shared “neural syntax” in the hippocampus. The findings bridge memory and navigation research by showing how the hippocampus maintains cognitive consistency across different spatial environments, and suggest a common neural framework with broad implications for understanding memory, learning, and related cognitive processes.

Aggression is a fundamental social behavior used to gain and defend resources, territories, and mates. To explore its genetic basis, we leveraged Siamese fighting fish, which have been selectively bred for fighting for more than 700 generations. Controlled visual stimuli, including custom fish animations and 3D-printed models, quantified the markedly increased aggressive displays and biting attacks of fighting betta. Population-genetic analyses identified a strong selection signal centered on the neuroligin 1 gene. Although no coding differences were found between fighting and wild fish, fighting betta express two to four times less nlgn1 mRNA and show distinct spatial expression patterns during development. CRISPR/Cas9-mediated knockout fish will help establish nlgn1’s role in aggression and its mechanism of action. This work provides insight into the molecular, genetic, and neuronal mechanisms of aggressive behavior and the evolution of social behavior.