Internal representations are thought to support the generation of flexible, long-timescale behavioral patterns in both animals and artificial agents. Here, we present a novel conceptual framework for how Drosophila use their internal representation of head direction to maintain preferred headings in their surroundings, and how they learn to modify these preferences in the presence of selective thermal reinforcement. To develop the framework, we analyzed flies’ behavior in a classical operant visual learning paradigm and found that they use stochastically generated fixations and directed turns to express their heading preferences. Symmetries in the visual scene used in the paradigm allowed us to expose how flies’ probabilistic behavior in this setting is tethered to their head direction representation. We describe how flies’ ability to quickly adapt their behavior to the rules of their environment may rest on a behavioral policy whose parameters are flexible but whose form is genetically encoded in the structure of their circuits. Many of the mechanisms we outline may also be relevant for rapidly adaptive behavior driven by internal representations in other animals, including mammals.

Transcriptional promoters of mitochondrial DNA have diverged extensively in the course of mammalian evolution. Nevertheless, the transcriptional machinery and the overall mechanisms of transcriptional control and regulation seem to be conserved. We have compared the human and murine homologs of the major DNA-binding transcriptional activator, mitochondrial transcription factor 1 (mtTF1), with unexpected results. Both proteins have similar chromatographic and transcriptional properties and are the same size. Both recognize and bind sequences between -12 and -39 within their respective homologous promoters. However, the sequences that they recognize are markedly divergent; although the base pairs they contact are situated similarly or identically with respect to the transcriptional start site, sequence identity between the two species’ contact points is less than 50%. Interestingly, the two proteins are functionally interchangeable; each can bind to the heterologous light-strand promoter and can activate transcription by the heterologous mitochondrial RNA polymerase. Thus, the RNA polymerase or some as yet undetected transcription factor, rather than mTF1, may determine the strict species specificity of mitochondrial transcription. Flexible DNA sequence recognition by mtTF1, on the other hand, may be a principal facilitating mechanism for rapid control sequence evolution.

Innate vocal sounds such as laughing, screaming or crying convey one's feelings to others. In many species, including humans, scaling the amplitude and duration of vocalizations is essential for effective social communication. In mice, female scent triggers male mice to emit innate courtship ultrasonic vocalizations (USVs). However, whether mice flexibly scale their vocalizations and how neural circuits are structured to generate flexibility remain largely unknown. Here we identify mouse neurons from the lateral preoptic area (LPOA) that express oestrogen receptor 1 (LPOA neurons) and, when activated, elicit the complete repertoire of USV syllables emitted during natural courtship. Neural anatomy and functional data reveal a two-step, di-synaptic circuit motif in which primary long-range inhibitory LPOA neurons relieve a clamp of local periaqueductal grey (PAG) inhibition, enabling excitatory PAG USV-gating neurons to trigger vocalizations. We find that social context shapes a wide range of USV amplitudes and bout durations. This variability is absent when PAG neurons are stimulated directly; PAG-evoked vocalizations are time-locked to neural activity and stereotypically loud. By contrast, increasing the activity of LPOA neurons scales the amplitude of vocalizations, and delaying the recovery of the inhibition clamp prolongs USV bouts. Thus, the LPOA disinhibition motif contributes to flexible loudness and the duration and persistence of bouts, which are key aspects of effective vocal social communication.

Memory guides behavior across widely varying environments and must therefore be both sufficiently specific and general. A memory too specific will be useless in even a slightly different environment, while an overly general memory may lead to suboptimal choices. Animals successfully learn to both distinguish between very similar stimuli and generalize across cues. Rather than forming memories that strike a balance between specificity and generality, Drosophila can flexibly categorize a given stimulus into different groups depending on the options available. We asked how this flexibility manifests itself in the well-characterized learning and memory pathways of the fruit fly. We show that flexible categorization in neuronal activity as well as behavior depends on the order and identity of the perceived stimuli. Our results identify the neural correlates of flexible stimulus-categorization in the fruit fly.

Sighted animals extract motion information from visual scenes by processing spatiotemporal patterns of light falling on the retina. The dominant models for motion estimation exploit intensity correlations only between pairs of points in space and time. Moving natural scenes, however, contain more complex correlations. We found that fly and human visual systems encode the combined direction and contrast polarity of moving edges using triple correlations that enhance motion estimation in natural environments. Both species extracted triple correlations with neural substrates tuned for light or dark edges, and sensitivity to specific triple correlations was retained even as light and dark edge motion signals were combined. Thus, both species separately process light and dark image contrasts to capture motion signatures that can improve estimation accuracy. This convergence argues that statistical structures in natural scenes have greatly affected visual processing, driving a common computational strategy over 500 million years of evolution.

On August 1, 2006 the Howard Hughes Medical Institute's first stand-alone research campus opened at Janelia Farm, near Washington DC. Our mission at Janelia is to do exceptional fundamental research. Our two scientific foci are to understand the function of neural circuits and to develop synergistic imaging technologies. To achieve this we have changed many of the conventions of academic and/or industrial science. The founding director at Janelia is the well-known Drosophilist Gerry Rubin, who has been a central figure in fly molecular, developmental and genomic biology in recent decades. Not coincidentally, we at Janelia fully appreciate the potential of flies to contribute to an understanding of neuronal circuits. Our objectives are ambitious, and in the first ten months of operations at Janelia we have made some good beginnings.

We have approached the problem of reverse-engineering the flight control mechanism of the fruit fly by studying the dynamics of the responses to a visual stimulus during takeoff. Building upon a prior framework [G. Card and M. Dickinson, J. Exp. Biol., vol. 211, pp. 341-353, 2008], we seek to understand the strategies employed by the animal to stabilize attitude and orientation during these evasive, highly dynamical maneuvers. As a first step, we consider the dynamics from a gray-box perspective: examining lumped forces produced by the insect’s legs and wings. The reconstruction of the flight initiation dynamics, based on the unconstrained motion formulation for a rigid body, allows us to assess the fly’s responses to a variety of initial conditions induced by its jump. Such assessment permits refinement by using a visual tracking algorithm to extract the kinematic envelope of the wings [E. I. Fontaine, F. Zabala, M. Dickinson, and J. Burdick, "Wing and body motion during flight initiation in Drosophila revealed by automated visual tracking," submitted for publication] in order to estimate lift and drag forces [F. Zabala, M. Dickinson, and R. Murray, "Control and stability of insect flight during highly dynamical maneuvers," submitted for publication], and recording actual leg-joint kinematics and using them to estimate jump forces [F. Zabala, "A bio-inspired model for directionality control of flight initiation," to be published.]. In this paper, we present the details of our approach in a comprehensive manner, including the salient results.

This work is a synthesis of our current understanding of the mechanics, aerodynamics and visually mediated control of dragonfly and damselfly flight, with the addition of new experimental and computational data in several key areas. These are: the diversity of dragonfly wing morphologies, the aerodynamics of gliding flight, force generation in flapping flight, aerodynamic efficiency, comparative flight performance and pursuit strategies during predatory and territorial flights. New data are set in context by brief reviews covering anatomy at several scales, insect aerodynamics, neuromechanics and behaviour. We achieve a new perspective by means of a diverse range of techniques, including laser-line mapping of wing topographies, computational fluid dynamics simulations of finely detailed wing geometries, quantitative imaging using particle image velocimetry of on-wing and wake flow patterns, classical aerodynamic theory, photography in the field, infrared motion capture and multi-camera optical tracking of free flight trajectories in laboratory environments. Our comprehensive approach enables a novel synthesis of datasets and subfields that integrates many aspects of flight from the neurobiology of the compound eye, through the aeromechanical interface with the surrounding fluid, to flight performance under cruising and higher-energy behavioural modes.This article is part of the themed issue 'Moving in a moving medium: new perspectives on flight'.

Fluorescent biochemical sensors allow probing metabolic states in a living cell with high spatiotemporal dynamics. This chapter describes a method for the in situ detection of changes in NAD level in living cells using fluorescence lifetime imaging (FLIM).

Synaptic plasticity in response to changes in physiologic state is coordinated by hormonal signals across multiple neuronal cell types, but the significance and underlying mechanisms are unclear. Here, we combine cell type-specific electrophysiological, pharmacological, and optogenetic techniques to dissect neural circuits and molecular pathways controlling synaptic plasticity onto AGRP neurons, a population that regulates feeding. We find that food deprivation elevates excitatory synaptic input, which is mediated by a presynaptic positive feedback loop involving AMP-activated protein kinase. Potentiation of glutamate release was triggered by the orexigenic hormone ghrelin and exhibited hysteresis, persisting for hours after ghrelin removal. Persistent activity was reversed by the anorexigenic hormone leptin, and optogenetic photostimulation demonstrated involvement of opioid release from POMC neurons. Based on these experiments, we propose a memory storage device for physiological state constructed from bistable synapses that are flipped between two sustained activity states by transient exposure to hormones signaling energy levels. Supported by: Howard Hughes Medical Institute.