The Swartz Program at Harvard University seeks applicants for a postdoctoral fellow in theoretical and computational neuroscience. Based on a grant from the Swartz Foundation, a Swartz postdoctoral fellowship is available at Harvard University with a start date in the summer or fall of 2024. Postdocs join a vibrant group of theoretical and experimental neuroscientists plus theorists in allied fields at Harvard’s Center for Brain Science. The Center for Brain Science includes faculty doing research on a wide variety of topics, including neural mechanisms of rodent learning, decision-making, and sex-specific and social behaviors; reinforcement learning in rodents and humans; human motor control; behavioral and fMRI studies of human cognition; circuit mechanisms of learning and behavior in worms, larval flies, and larval zebrafish; circuit mechanisms of individual differences in flies and humans; rodent and fly olfaction; inhibitory circuit development; retinal circuits; and large-scale reconstruction of detailed brain circuitry.

During development, the complex neuronal circuitry of the brain arises from limited information contained in the genome. After the genetic code instructs the birth of neurons, the emergence of brain regions, and the formation of axon tracts, it is believed that neuronal activity plays a critical role in shaping circuits for behavior. Current AI technologies are modeled after the same principle: connections in an initial weight matrix are pruned and strengthened by activity-dependent signals until the network can sufficiently generalize a set of inputs into outputs. Here, we challenge these learning-dominated assumptions by quantifying the contribution of neuronal activity to the development of visually guided swimming behavior in larval zebrafish. Intriguingly, dark-rearing zebrafish revealed that visual experience has no effect on the emergence of the optomotor response (OMR). We then raised animals under conditions where neuronal activity was pharmacologically silenced from organogenesis onward using the sodium-channel blocker tricaine. Strikingly, after washout of the anesthetic, animals performed swim bouts and responded to visual stimuli with 75% accuracy in the OMR paradigm. After shorter periods of silenced activity OMR performance stayed above 90% accuracy, calling into question the importance and impact of classical critical periods for visual development. Detailed quantification of the emergence of functional circuit properties by brain-wide imaging experiments confirmed that neuronal circuits came ‘online’ fully tuned and without the requirement for activity-dependent plasticity. Thus, contrary to what you learned on your mother's knee, complex sensory guided behaviors can be wired up innately by activity-independent developmental mechanisms.

In most brains across the animal kingdom, brain dynamics can enter pathological states that are recognisable as epileptic seizures. Yet usually, brain operate within certain constraints given through neuronal function and synaptic coupling, that will prevent epileptic seizure dynamics from emerging. In this talk, I will bring together different approaches to identifying how networks in the broadest sense shape brain dynamics. Using illustrative examples from intracranial EEG recordings, disorders characterised by molecular disruption of a single neurotransmitter receptor type, to single-cell recordings of whole-brain activity in the larval zebrafish, I will address three key questions - (1) how does the regionally specific composition of synaptic receptors shape ongoing physiological brain activity; (2) how can disruption of this regionally specific balance result in abnormal brain dynamics; and (3) which cellular patterns underly the transition into an epileptic seizure.

I’ll give an overview of internal - or motivational - states in larval zebrafish. Specifically we will focus on the role of the Oxytocin system in regulating the detection of, and behavioral responses to, conspecifics. The appeal here is that Oxytocin has likely conserved roles across all vertebrates, including humans, and that the larval zebrafish allows us to study some of the general principles across the brain but nonetheless at cellular resolution. This allows us to propose mechanistic models of emotional states.

Animals control motor actions at multiple timescales. We use larval zebrafish and advanced optical microscopy to understand the underlying neural mechanisms. First, we examined the mechanisms of short-term motor learning by using whole-brain neural activity imaging. We found that the 5-HT system integrates the sensory outcome of actions and determines future motor patterns. Second, we established a method for recording spiking activity and membrane potential from a population of neurons during behavior. We identified putative motor command signals and internal copy signals that encode millisecond-scale details of the swimming dynamics. These results demonstrate that zebrafish provide a holistic and mechanistic understanding of the neural basis of motor control in vertebrate brains.

Behavior arises from the coordinated activity of numerous distinct brain regions. Modern experimental tools allow access to neural populations brain-wide, yet understanding such large-scale datasets necessitates scalable computational models to extract meaningful features of inter-region communication. In this talk, I will introduce Current-Based Decomposition (CURBD), an approach for inferring multi-region interactions using data-constrained recurrent neural network models. I will first show that CURBD accurately isolates inter-region currents in simulated networks with known dynamics. I will then apply CURBD to understand the brain-wide flow of information leading to behavioral state transitions in larval zebrafish. These examples will establish CURBD as a flexible, scalable framework to infer brain-wide interactions that are inaccessible from experimental measurements alone.

How can neural networks exhibit persistent activity on time scales much larger than allowed by cellular properties? We address this question in the context of larval zebrafish, a model vertebrate that is accessible to brain-scale neuronal recording and high-throughput behavioral studies. We study in particular the dynamics of a bilaterally distributed circuit, the so-called ARTR, including hundreds neurons. ARTR exhibits slow antiphasic alternations between its left and right subpopulations, which can be modulated by the water temperature, and drive the coordinated orientation of swim bouts, thus organizing the fish spatial exploration. To elucidate the mechanism leading to the slow self-oscillation, we train a network graphical model (Ising) on neural recordings. Sampling the inferred model allows us to generate synthetic oscillatory activity, whose features correctly capture the observed dynamics. A mean-field analysis of the inferred model reveals the existence several phases; activated crossing of the barriers in between those phases controls the long time scales present in the network oscillations. We show in particular how the barrier heights and the nature of the phases vary with the water temperature.

In this talk I will summarize some of our recent unpublished work on spectral coding in the larval zebrafish retina. Combining 2p imaging, hyperspectral stimulation, computational modeling and connectomics, we take a renewed look at the spectral tuning of cone photoreceptors in the live eye. We find that already cones optimally rotate natural colour space in a PCA-like fashion to disambiguate greyscale from "colour" information. We then follow this signal through the retinal layers and ultimately into the brain to explore the major spectral computations performed by the visual system at its consecutive stages. We find that by and large, zebrafish colour vision can be broken into three major spectral zones: long wavelength grey-scale-like vision, short-wavelength prey capture circuits, and spectrally diverse mid-wavelength circuits which possibly support the bulk of "true colour vision" in this tetrachromate vertebrate.

Maintaining posture is a vital challenge for all freely-moving organisms. As animals grow, their relationship to destabilizing physical forces changes. How does the nervous system deal with this ongoing challenge? Vertebrates use highly conserved vestibular reflexes to stabilize the body. We established the larval zebrafish as a new model system to understand the development of the vestibular reflexes responsible for balance. In this talk, I will begin with the biophysical challenges facing baby fish as they learn to swim. I’ll briefly review published work by David Ehrlich, Ph.D., establishing a fundamental relationship between postural stability and locomotion. The bulk of the talk will highlight unpublished work by Kyla Hamling. She discovered that a small (~50) population of molecularly-defined brainstem neurons called vestibulo-spinal cells act as a nexus for postural development. Her loss-of-function experiments show that these neurons contribute more to postural stability as animals grow older. I’ll end with brief highlights from her ongoing work examining tilt-evoked responses of these neurons using 2-photon imaging and the consequences of downstream activity in the spinal cord using single-objective light-sheet (SCAPE) microscopy