Ring attractor dynamics in the Drosophila central brain

A neural heading estimate is compared with an internal goal to guide oriented navigation

Goal-directed navigation is thought to rely on the activity of head-direction cells, but how this activity guides moment-to-moment action remains poorly understood. Here we characterize how heading neurons in the Drosophila central complex guide moment-to-moment actions. We establish an innate, heading-neuron dependent, tethered navigational behavior where walking flies maintain a straight trajectory along a specific angular bearing for hundreds of body lengths. While flies perform this task, we use chemogenetics to transiently rotate their neural heading estimate and observe that the flies slow down and turn in a direction that aims to return the heading estimate to the angle it occupied prior to stimulation. These results support a working model in which the fly brain quantitatively compares an internal estimate of current heading with an internal goal heading and uses the sign and magnitude of the difference to determine which way to turn, how hard to turn, and how fast to walk forward.

The Brain Compass: A Perspective on How Self-Motion Updates the Head Direction Cell Attractor

Head direction cells form an internal compass signaling head azimuth orientation even without visual landmarks. This property is generated by a neuronal ring attractor that is updated using rotation velocity cues. The properties and origin of this velocity drive remain, however, unknown. We propose a quantitative framework whereby this drive represents a multisensory self-motion estimate computed through an internal model that uses sensory prediction errors of vestibular, visual, and somatosensory cues to improve on-line motor drive. We show how restraint-dependent strength of recurrent connections within the attractor can explain differences in head direction cell firing between free foraging and restrained passive rotation. We also summarize recent findings on how gravity influences azimuth coding, indicating that the velocity drive is not purely egocentric. Finally, we show that the internal compass may be three-dimensional and hypothesize that the additional vertical degrees of freedom use global allocentric gravity cues.

Recent Advances in the Genetic Dissection of Neural Circuits in Drosophila

Nervous systems endow animals with cognition and behavior. To understand how nervous systems control behavior, neural circuits mediating distinct functions need to be identified and characterized. With superior genetic manipulability, Drosophila is a model organism at the leading edge of neural circuit analysis. We briefly introduce the state-of-the-art genetic tools that permit precise labeling of neurons and their interconnectivity and investigating what is happening in the brain of a behaving animal and manipulating neurons to determine how behaviors are affected. Brain-wide wiring diagrams, created by light and electron microscopy, bring neural circuit analysis to a new level and scale. Studies enabled by these tools advances our understanding of the nervous system in relation to cognition and behavior.

A Flexible Model of Working Memory

Working memory is fundamental to cognition, allowing one to hold information "in mind." A defining characteristic of working memory is its flexibility: we can hold anything in mind. However, typical models of working memory rely on finely tuned, content-specific attractors to persistently maintain neural activity and therefore do not allow for the flexibility observed in behavior. Here, we present a flexible model of working memory that maintains representations through random recurrent connections between two layers of neurons: a structured "sensory" layer and a randomly connected, unstructured layer. As the interactions are untuned with respect to the content being stored, the network maintains any arbitrary input. However, in our model, this flexibility comes at a cost: the random connections overlap, leading to interference between representations and limiting the memory capacity of the network. Additionally, our model captures several other key behavioral and neurophysiological characteristics of working memory.

Diverse Food-Sensing Neurons Trigger Idiothetic Local Search in Drosophila

Foraging animals may benefit from remembering the location of a newly discovered food patch while continuing to explore nearby [1, 2]. For example, after encountering a drop of yeast or sugar, hungry flies often perform a local search [3, 4]. That is, rather than remaining on the food or simply walking away, flies execute a series of exploratory excursions during which they repeatedly depart and return to the resource. Fruit flies, Drosophila melanogaster, can perform this food-centered search behavior in the absence of external landmarks, instead relying on internal (idiothetic) cues [5]. This path-integration behavior may represent a deeply conserved navigational capacity in insects [6, 7], but its underlying neural basis remains unknown. Here, we used optogenetic activation to screen candidate cell classes and found that local searches can be initiated by diverse sensory neurons. Optogenetically induced searches resemble those triggered by actual food, are modulated by starvation state, and exhibit key features of path integration. Flies perform tightly centered searches around the fictive food site, even within a constrained maze, and they can return to the fictive food site after long excursions. Together, these results suggest that flies enact local searches in response to a wide variety of food-associated cues and that these sensory pathways may converge upon a common neural system for navigation. Using a virtual reality system, we demonstrate that local searches can be optogenetically induced in tethered flies walking on a spherical treadmill, laying the groundwork for future studies to image the brain during path integration. VIDEO ABSTRACT.

Stability of working memory in continuous attractor networks under the control of short-term plasticity

Continuous attractor models of working-memory store continuous-valued information in continuous state-spaces, but are sensitive to noise processes that degrade memory retention. Short-term synaptic plasticity of recurrent synapses has previously been shown to affect continuous attractor systems: short-term facilitation can stabilize memory retention, while short-term depression possibly increases continuous attractor volatility. Here, we present a comprehensive description of the combined effect of both short-term facilitation and depression on noise-induced memory degradation in one-dimensional continuous attractor models. Our theoretical description, applicable to rate models as well as spiking networks close to a stationary state, accurately describes the slow dynamics of stored memory positions as a combination of two processes: (i) diffusion due to variability caused by spikes; and (ii) drift due to random connectivity and neuronal heterogeneity. We find that facilitation decreases both diffusion and directed drifts, while short-term depression tends to increase both. Using mutual information, we evaluate the combined impact of short-term facilitation and depression on the ability of networks to retain stable working memory. Finally, our theory predicts the sensitivity of continuous working memory to distractor inputs and provides conditions for stability of memory.

The ability to transiently memorize positions in the visual field is crucial for behavior. Models and experiments have shown that such memories can be maintained in networks of cortical neurons with a continuum of possible activity states, that reflects the continuum of positions in the environment. However, the accuracy of positions stored in such networks will degrade over time due to the noisiness of neuronal signaling and imperfections of the biological substrate. Previous work in simplified models has shown that synaptic short-term plasticity could stabilize this degradation by dynamically up- or down-regulating the strength of synaptic connections, thereby “pinning down” memorized positions. Here, we present a general theory that accurately predicts the extent of this “pinning down” by short-term plasticity in a broad class of biologically plausible network models, thereby untangling the interplay of varying biological sources of noise with short-term plasticity. Importantly, our work provides a novel theoretical link from the microscopic substrate of working memory—neurons and synaptic connections—to observable behavioral correlates, for example the susceptibility to distracting stimuli.

The Central Complex as a Potential Substrate for Vector Based Navigation

Insects use path integration (PI) to maintain a home vector, but can also store and recall vector-memories that take them from home to a food location, and even allow them to take novel shortcuts between food locations. The neural circuit of the Central Complex (a brain area that receives compass and optic flow information) forms a plausible substrate for these behaviors. A recent model, grounded in neurophysiological and neuroanatomical data, can account for PI during outbound exploratory routes and the control of steering to return home. Here, we show that minor, hypothetical but neurally plausible, extensions of this model can additionally explain how insects could store and recall PI vectors to follow food-ward paths, take shortcuts, search at the feeder and re-calibrate their vector-memories with experience. In addition, a simple assumption about how one of multiple vector-memories might be chosen at any point in time can produce the development and maintenance of efficient routes between multiple locations, as observed in bees. The central complex circuitry is therefore well-suited to allow for a rich vector-based navigational repertoire.

Automated real-time quantification of group locomotor activity in Drosophila melanogaster

Recent advances in neurogenetics have highlighted Drosophila melanogaster as an exciting model to study neural circuit dynamics and complex behavior. Automated tracking methods have facilitated the study of complex behaviors via high throughput behavioral screening. Here we describe a newly developed low-cost assay capable of real-time monitoring and quantifying Drosophila group activity. This platform offers reliable real-time quantification with open source software and a user-friendly interface for data acquisition and analysis. We demonstrate the utility of this platform by characterizing ethanol-induced locomotor activity in a dose-dependent manner as well as the effects of thermo and optogenetic manipulation of ellipsoid body neurons important for ethanol-induced locomotor activity. As expected, low doses of ethanol induced an initial startle and slow ramping of group activity, whereas high doses of ethanol induced sustained group activity followed by sedation. Advanced offline processing revealed discrete behavioral features characteristic of intoxication. Thermogenetic inactivation of ellipsoid body ring neurons reduced group activity whereas optogenetic activation increased activity. Together, these data establish the fly Group Activity Monitor (flyGrAM) platform as a robust means of obtaining an online read out of group activity in response to manipulations to the environment or neural activity, with an opportunity for more advanced post-processing offline.

The insect central complex and the neural basis of navigational strategies

Oriented behaviour is present in almost all animals, indicating that it is an ancient feature that has emerged from animal brains hundreds of millions of years ago. Although many complex navigation strategies have been described, each strategy can be broken down into a series of elementary navigational decisions. In each moment in time, an animal has to compare its current heading with its desired direction and compensate for any mismatch by producing a steering response either to the right or to the left. Different from reflex-driven movements, target-directed navigation is not only initiated in response to sensory input, but also takes into account previous experience and motivational state. Once a series of elementary decisions are chained together to form one of many coherent navigation strategies, the animal can pursue a navigational target, e.g. a food source, a nest entrance or a constant flight direction during migrations. Insects show a great variety of complex navigation behaviours and, owing to their small brains, the pursuit of the neural circuits controlling navigation has made substantial progress over the last years. A brain region as ancient as insects themselves, called the central complex, has emerged as the likely navigation centre of the brain. Research across many species has shown that the central complex contains the circuitry that might comprise the neural substrate of elementary navigational decisions. Although this region is also involved in a wide range of other functions, we hypothesize in this Review that its role in mediating the animal's next move during target-directed behaviour is its ancestral function, around which other functions have been layered over the course of evolution.

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.

Every task that an animal performs, even a simple one, typically requires numerous signals to pass across complex networks of cells called neurons. These networks develop early in an animal’s life, beginning when progenitor cells called neural stem cells divide over and over to produce new cells. Specific molecular signals then induce these new cells to become different types of neurons. However, in many animals, it is poorly understood what these critical molecular signals are and how they work.

Fruit flies, for example, have a network of neurons that control how they navigate when flying. The same type of progenitor cell gives rise to at least four types of neurons in this network; these progenitor cells make an increasing amount of a protein called Eyeless as they age.

Sullivan et al. have now specifically disrupted production of the Eyeless protein in the progenitor cells, and found that this altered the relative numbers of navigation neurons. The fruit flies had too many of some types of navigation neurons and too few of others. Fruit flies normally navigate in a variety of directions relative to the sun, which may allow them to disperse and find food. This was not the case in experiments where the production of Eyeless was briefly disrupted when the flies were larvae. In these experiments, the adult flies tended to head towards a bright light (that represented the sun) much more often than normal, which would presumably keep them from dispersing effectively. This was true even if the disruption of Eyeless was not long enough to change the numbers of neuron types, showing the protein is important in determining both how these navigation neurons form networks, and whether they are born at all.

A better understanding of the complexities of how healthy networks of neurons develop may give scientists more insight into what goes wrong during human developmental disorders that affect the brain. In theory, it may also someday lead to tools that can help to repair the brain if it is damaged.

Discrete attractor dynamics underlies persistent activity in the frontal cortex

Short-term memories link events separated in time, such as past sensation and future actions. Short-term memories are correlated with slow neural dynamics, including selective persistent activity, which can be maintained over seconds. In a delayed response task that requires short-term memory, neurons in the mouse anterior lateral motor cortex (ALM) show persistent activity that instructs future actions. To determine the principles that underlie this persistent activity, here we combined intracellular and extracellular electrophysiology with optogenetic perturbations and network modelling. We show that during the delay epoch, the activity of ALM neurons moved towards discrete end points that correspond to specific movement directions. These end points were robust to transient shifts in ALM activity caused by optogenetic perturbations. Perturbations occasionally switched the population dynamics to the other end point, followed by incorrect actions. Our results show that discrete attractor dynamics underlie short-term memory related to motor planning.

Origin and role of path integration in the cognitive representations of the hippocampus: computational insights into open questions

Path integration is a straightforward concept with varied connotations that are important to different disciplines concerned with navigation, such as ethology, cognitive science, robotics and neuroscience. In studying the hippocampal formation, it is fruitful to think of path integration as a computation that transforms a sense of motion into a sense of location, continuously integrated with landmark perception. Here, we review experimental evidence that path integration is intimately involved in fundamental properties of place cells and other spatial cells that are thought to support a cognitive abstraction of space in this brain system. We discuss hypotheses about the anatomical and computational origin of path integration in the well-characterized circuits of the rodent limbic system. We highlight how computational frameworks for map-building in robotics and cognitive science alike suggest an essential role for path integration in the creation of a new map in unfamiliar territory, and how this very role can help us make sense of differences in neurophysiological data from novel versus familiar and small versus large environments. Similar computational principles could be at work when the hippocampus builds certain non-spatial representations, such as time intervals or trajectories defined in a sensory stimulus space.

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.

Polarized skylight-based heading measurements: a bio-inspired approach

Many insects such as desert ants, crickets, locusts, dung beetles, bees and monarch butterflies have been found to extract their navigation cues from the regular pattern of the linearly polarized skylight. These species are equipped with ommatidia in the dorsal rim area of their compound eyes, which are sensitive to the angle of polarization of the skylight. In the polarization-based robotic vision, most of the sensors used so far comprise high-definition CCD or CMOS cameras topped with linear polarizers. Here, we present a 2-pixel polarization-sensitive visual sensor, which was strongly inspired by the dorsal rim area of desert ants' compound eyes, designed to determine the direction of polarization of the skylight. The spectral sensitivity of this minimalistic sensor, which requires no lenses, is in the ultraviolet range. Five different methods of computing the direction of polarization were implemented and tested here. Our own methods, the extended and AntBot method, outperformed the other three, giving a mean angular error of only 0.62° ± 0.40° (median: 0.24°) and 0.69° ± 0.52° (median: 0.39°), respectively (mean ± standard deviation). The results obtained in outdoor field studies show that our celestial compass gives excellent results at a very low computational cost, which makes it highly suitable for autonomous outdoor navigation purposes.

Inverse Control of Turning Behavior by Dopamine D1 Receptor Signaling in Columnar and Ring Neurons of the Central Complex in Drosophila

Action selection is a prerequisite for decision-making and a fundamental aspect to any goal-directed locomotion; it requires integration of sensory signals and internal states to translate them into action sequences. Here, we introduce a novel behavioral analysis to study neural circuits and mechanisms underlying action selection and decision-making in freely moving Drosophila. We discovered preferred patterns of motor activity and turning behavior. These patterns are impaired in FoxP mutant flies, which present an altered temporal organization of motor actions and turning behavior, reminiscent of indecisiveness. Then, focusing on central complex (CX) circuits known to integrate different sensory modalities and controlling premotor regions, we show that action sequences and turning behavior are regulated by dopamine D1-like receptor (Dop1R1) signaling. Dop1R1 inputs onto CX columnar ellipsoid body-protocerebral bridge gall (E-PG) neuron and ellipsoid body (EB) R2/R4m ring neuron circuits both negatively gate motor activity but inversely control turning behavior. Although flies deficient of D1 receptor signaling present normal turning behavior despite decreased activity, restoring Dop1R1 level in R2/R4m-specific circuitry affects the temporal organization of motor actions and turning. We finally show EB R2/R4m neurons are in contact with E-PG neurons that are thought to encode body orientation and heading direction of the fly. These findings suggest that Dop1R1 signaling in E-PG and EB R2/4 m circuits are compared against each other, thereby modulating patterns of activity and turning behavior for goal-directed locomotion.

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Freely moving Drosophila present preferred patterns of activity and turning behavior

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FoxP mutations affect temporal distribution of motor actions and turning behavior

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Central complex columnar E-PG and R2/4 m ring neurons inversely regulate turning

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Dopamine D1-like receptor signaling in R2/R4m ring neurons modulates behavior

Anticipatory Neural Activity Improves the Decoding Accuracy for Dynamic Head-Direction Signals

Insects and vertebrates harbor specific neurons that encode the animal's head direction (HD) and provide an internal compass for spatial navigation. Each HD cell fires most strongly in one preferred direction. As the animal turns its head, however, HD cells in rat anterodorsal thalamic nucleus (ADN) and other brain areas fire already before their preferred direction is reached, as if the neurons anticipated the future HD. This phenomenon has been explained at a mechanistic level, but a functional interpretation is still missing. To close this gap, we use a computational approach based on the movement statistics of male rats and a simple model for the neural responses within the ADN HD network. Network activity is read out using population vectors in a biologically plausible manner, so that only past spikes are taken into account. We find that anticipatory firing improves the representation of the present HD by reducing the motion-induced temporal bias inherent in causal decoding. The amount of anticipation observed in ADN enhances the precision of the HD compass read-out by up to 40%. More generally, our theoretical framework predicts that neural integration times not only reflect biophysical constraints, but also the statistics of behaviorally relevant stimuli; in particular, anticipatory tuning should be found wherever neurons encode sensory signals that change gradually in time.SIGNIFICANCE STATEMENT Across different brain regions, populations of noisy neurons encode dynamically changing stimuli. Decoding a time-varying stimulus from the population response involves a trade-off: For short read-out times, stimulus estimates are unreliable as the number of stochastic spikes is small; for long read-outs, estimates are biased because they lag behind the true stimulus. We show that optimal decoding of temporally correlated stimuli not only relies on finding the right read-out time window but requires neurons to anticipate future stimulus values. We apply this general framework to the rodent head-direction system and show that the experimentally observed anticipation of future head directions can be explained at a quantitative level from the neuronal tuning properties, network size, and the animal's head-movement statistics.

Learning and Its Neural Correlates in a Virtual Environment for Honeybees

The search for neural correlates of operant and observational learning requires a combination of two (experimental) conditions that are very difficult to combine: stable recording from high order neurons and free movement of the animal in a rather natural environment. We developed a virtual environment (VE) that simulates a simplified 3D world for honeybees walking stationary on an air-supported spherical treadmill. We show that honeybees perceive the stimuli in the VE as meaningful by transferring learned information from free flight to the virtual world. In search for neural correlates of learning in the VE, mushroom body extrinsic neurons were recorded over days during learning. We found changes in the neural activity specific to the rewarded and unrewarded visual stimuli. Our results suggest an involvement of the mushroom body extrinsic neurons in operant learning in the honeybee (Apis mellifera).

Neuroarchitecture of the Drosophila central complex: A catalog of nodulus and asymmetrical body neurons and a revision of the protocerebral bridge catalog

The central complex, a set of neuropils in the center of the insect brain, plays a crucial role in spatial aspects of sensory integration and motor control. Stereotyped neurons interconnect these neuropils with one another and with accessory structures. We screened over 5,000 Drosophila melanogaster GAL4 lines for expression in two neuropils, the noduli (NO) of the central complex and the asymmetrical body (AB), and used multicolor stochastic labeling to analyze the morphology, polarity, and organization of individual cells in a subset of the GAL4 lines that showed expression in these neuropils. We identified nine NO and three AB cell types and describe them here. The morphology of the NO neurons suggests that they receive input primarily in the lateral accessory lobe and send output to each of the six paired noduli. We demonstrate that the AB is a bilateral structure which exhibits asymmetry in size between the left and right bodies. We show that the AB neurons directly connect the AB to the central complex and accessory neuropils, that they target both the left and right ABs, and that one cell type preferentially innervates the right AB. We propose that the AB be considered a central complex neuropil in Drosophila. Finally, we present highly restricted GAL4 lines for most identified protocerebral bridge, NO, and AB cell types. These lines, generated using the split-GAL4 method, will facilitate anatomical studies, behavioral assays, and physiological experiments.

Functional Imaging and Optogenetics in Drosophila

Understanding how activity patterns in specific neural circuits coordinate an animal’s behavior remains a key area of neuroscience research. Genetic tools and a brain of tractable complexity make Drosophila a premier model organism for these studies. Here, we review the wealth of reagents available to map and manipulate neuronal activity with light.

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.

Building a functional connectome of the Drosophila central complex

The central complex is a highly conserved insect brain region composed of morphologically stereotyped neurons that arborize in distinctively shaped substructures. The region is implicated in a wide range of behaviors and several modeling studies have explored its circuit computations. Most studies have relied on assumptions about connectivity between neurons based on their overlap in light microscopy images. Here, we present an extensive functional connectome of Drosophila melanogaster's central complex at cell-type resolution. Using simultaneous optogenetic stimulation, calcium imaging and pharmacology, we tested the connectivity between 70 presynaptic-to-postsynaptic cell-type pairs. We identified numerous inputs to the central complex, but only a small number of output channels. Additionally, the connectivity of this highly recurrent circuit appears to be sparser than anticipated from light microscopy images. Finally, the connectivity matrix highlights the potentially critical role of a class of bottleneck interneurons. All data are provided for interactive exploration on a website.

Integration and multiplexing of positional and contextual information by the hippocampal network

The hippocampus is known to store cognitive representations, or maps, that encode both positional and contextual information, critical for episodic memories and functional behavior. How path integration and contextual cues are dynamically combined and processed by the hippocampus to maintain these representations accurate over time remains unclear. To answer this question, we propose a two-way data analysis and modeling approach to CA3 multi-electrode recordings of a moving rat submitted to rapid changes of contextual (light) cues, triggering back-and-forth instabitilies between two cognitive representations (“teleportation” experiment of Jezek et al). We develop a dual neural activity decoder, capable of independently identifying the recalled cognitive map at high temporal resolution (comparable to theta cycle) and the position of the rodent given a map. Remarkably, position can be reconstructed at any time with an accuracy comparable to fixed-context periods, even during highly unstable periods. These findings provide evidence for the capability of the hippocampal neural activity to maintain an accurate encoding of spatial and contextual variables, while one of these variables undergoes rapid changes independently of the other. To explain this result we introduce an attractor neural network model for the hippocampal activity that process inputs from external cues and the path integrator. Our model allows us to make predictions on the frequency of the cognitive map instability, its duration, and the detailed nature of the place-cell population activity, which are validated by a further analysis of the data. Our work therefore sheds light on the mechanisms by which the hippocampal network achieves and updates multi-dimensional neural representations from various input streams.

As an animal moves in space and receives external sensory inputs, it must dynamically maintain the representations of its position and environment at all times. How the hippocampus, the brain area crucial for spatial representations, achieves this task, and manages possible conflicts between different inputs remains unclear. We propose here a comprehensive attractor neural network-based model of the hippocampus and of its multiple input streams (including self-motion). We show that this model is capable of maintaining faithful representations of positional and contextual information, and resolves conflicts by adapting internal representations to match external cues. Model predictions are confirmed by the detailed analysis of hippocampal recordings of a rat submitted to quickly varying and conflicting contextual inputs.

Multiple Representations of Space by the Cockroach, Periplaneta americana

When cockroaches are trained to a visual–olfactory cue pairing using the antennal projection response (APR), they can form different memories for the location of a visual cue. A series of experiments, each examining memory for the spatial location of a visual cue, were performed using restrained cockroaches. The first group of experiments involved training cockroaches to associate a visual cue (CS—green LED) with an odor cue (US) in the presence or absence of a second visual reference cue (white LED). These experiments revealed that cockroaches have at least two forms of spatial memory. First, it was found that during learning, the movements of the antennae in response to the odor influenced the cockroaches’ memory. If they use only one antenna, cockroaches form a memory that results in an APR being elicited to the CS irrespective of its location in space. When using both antennae, the cockroaches resulting memory leads to an APR to the CS that is spatially confined to within 15° of the trained position. This memory represents an egocentric spatial representation. Second, the cockroaches simultaneously formed a memory for the angular spatial relationships between two visual cues when trained in the presence of a second visual reference cue. This training provided the cockroaches an allocentric representation or visual snapshot of the environment. If both egocentric and the visual snapshot were available to the cockroach to localize the learned cue, the visual snapshot determined the behavioral response in this assay. Finally, the split-brain assay was used to characterize the cockroach’s ability to establish a memory for the angular relationship between two visual cues with half a brain. Split-brain cockroaches were trained to unilaterally associate a pair of visual cues (CS—green LED and reference—white LED) with an odor cue (US). Split-brain cockroaches learned the general arrangement of the visual cues (i.e., the green LED is right of the white LED), but not the precise angular relationship. These experiments provide new insight into spatial memory processes in the cockroach.

Building a heading signal from anatomically defined neuron types in the Drosophila central complex

A network of a few hundred neurons in the Drosophila central complex carries an estimate of the fly's heading in the world, akin to the mammalian head-direction system. Here we describe how anatomically defined neuronal classes in this network are poised to implement specific sub-processes for building and updating this population-level heading signal. The computations we describe in the fly central complex strongly resemble those posited to exist in the mammalian brain, in computational models for building head-direction signals. By linking circuit anatomy to navigational physiology, the Drosophila central complex should provide a detailed example of how a heading signal is built.

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.

Interspike interval analysis and spikelets in presubicular head-direction cells

Head-direction (HD) neurons are thought to provide the mammalian brain with an internal sense of direction. These cells, which selectively increase their firing when the animal's head points in a specific direction, use the spike rate to encode HD with a high signal-to-noise ratio. In the present work, we analyzed spike train features of presubicular HD cells recorded juxtacellularly in passively rotated rats. We found that HD neurons could be classified into two groups on the basis of their propensity to fire spikes at short interspike intervals. "Bursty" neurons displayed distinct spike waveforms and were weakly but significantly more modulated by HD compared with "nonbursty" cells. In a subset of HD neurons, we observed the occurrence of spikelets, small-amplitude "spike-like" events, whose HD tuning was highly correlated to that of the co-recorded juxtacellular spikes. Bursty and nonbursty HD cells, as well as spikelets, were also observed in freely moving animals during natural behavior. We speculate that spike bursts and spikelets might contribute to presubicular HD coding by enhancing its accuracy and transmission reliability to downstream targets. NEW & NOTEWORTHY We provide evidence that presubicular head-direction (HD) cells can be classified into two classes (bursty and nonbursty) on the basis of their propensity to fire spikes at short interspike intervals. Bursty cells displayed distinct electrophysiological properties and stronger directional tuning compared with nonbursty neurons. We also provide evidence for the occurrence of spikelets in a subset of HD cells. These electrophysiological features (spike bursts and spikelets) might contribute to the precision and robustness of the presubicular HD code.

Role of the head-direction signal in spatial tasks: when and how does it guide behavior?

Since their discovery, mammalian head-direction (HD) cells have been extensively researched in terms of sensory origins, external cue control, and circuitry. However, the relationship of HD cells to behavior is not yet fully understood. In the current review, we examine the anatomical clues for information flow in the HD circuit and an emerging body of evidence that links neural activity of HD cells and spatial orientation. We hypothesize from results obtained in spatial orientation tasks involving HD cells that when properly aligned with available external cues, the HD signal could be used for guiding rats to a goal location. However, contradictory inputs from separate sensory systems may reduce the influence of the HD signal such that animals are able to switch between this and other systems according to their impact on behavior.

Testing the Efficacy of Single-Cell Stimulation in Biasing Presubicular Head Direction Activity

To support navigation, the firing of head direction (HD) neurons must be tightly anchored to the external space. Indeed, inputs from external landmarks can rapidly reset the preferred direction of HD cells. Landmark stimuli have often been simulated as excitatory inputs from "visual cells" (encoding landmark information) to the HD attractor network; when excitatory visual inputs are sufficiently strong, preferred directions switch abruptly to the landmark location. In the present work, we tested whether mimicking such inputs via juxtacellular stimulation would be sufficient for shifting the tuning of individual presubicular HD cells recorded in passively rotated male rats. We recorded 81 HD cells in a cue-rich environment, and evoked spikes trains outside of their preferred direction (distance range, 11-178°). We found that HD tuning was remarkably resistant to activity manipulations. Even strong stimulations, which induced seconds-long spike trains, failed to induce a detectable shift in directional tuning. HD tuning curves before and after stimulation remained highly correlated, indicating that postsynaptic activation alone is insufficient for modifying HD output. Our data are thus consistent with the predicted stability of an HD attractor network when anchored to external landmarks. A small spiking bias at the stimulus direction could only be observed in a visually deprived environment in which both average firing rates and directional tuning were markedly reduced. Based on this evidence, we speculate that, when attractor dynamics become unstable (e.g., under disorientation), the output of HD neurons could be more efficiently controlled by strong biasing stimuli.SIGNIFICANCE STATEMENT The activity of head direction (HD) cells is thought to provide the mammalian brain with an internal sense of direction. To support navigation, the firing of HD neurons must be anchored to external landmarks, a process thought to be supported by associative plasticity within the HD system. Here, we investigated these plasticity mechanisms by juxtacellular stimulation of single HD neurons in vivo in awake rats. We found that HD coding is strongly resistant to external manipulations of spiking activity. Only in a visually deprived environment was juxtacellular stimulation able to induce a small activity bias in single presubicular neurons. We propose that juxtacellular stimulation can bias HD tuning only when competing anchoring inputs are reduced or not available.

Self-Organized Attractor Dynamics in the Developing Head Direction Circuit

Head direction (HD) cells are neurons found in an extended cortical and subcortical network that signal the orientation of an animal’s head relative to its environment [1, 2, 3]. They are a fundamental component of the wider circuit of spatially responsive hippocampal formation neurons that make up the neural cognitive map of space [4]. During post-natal development, HD cells are the first among spatially modulated neurons in the hippocampal circuit to exhibit mature firing properties [5, 6], but before eye opening, HD cell responses in rat pups have low directional information and are directionally unstable [7, 8]. Using Bayesian decoding of HD cell ensemble activity recorded in the anterodorsal thalamic nucleus (ADN), we characterize this instability and identify its source: under-signaling of angular head velocity, which incompletely shifts the directional signal in proportion to head turns. We find evidence that geometric cues (the corners of a square environment) can be used to mitigate this under-signaling and, thereby, stabilize the directional signal even before eye opening. Crucially, even when directional firing cannot be stabilized, ensembles of unstable HD cells show short-timescale (1–10 s) temporal and spatial couplings consistent with an adult-like HD network. The HD network is widely modeled as a continuous attractor whose output is one coherent activity peak, updated during movement by angular head velocity signals and anchored by landmark cues [9, 10, 11]. Our findings present strong evidence for this model, and they demonstrate that the required network circuitry is in place and functional early during development, independent of reference to landmark information.

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Non-visual cues can anchor head direction (HD) cells in pre-eye-opening rat pups

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Internal network dynamics are preserved even when the HD representation is unstable

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Angular velocity under-signaling drives instability, which is mitigated by corners

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Circuit architecture develops even before any landmarks can stabilize HD responses

Recurrent Circuitry for Balancing Sleep Need and Sleep

Sleep-promoting neurons in the dorsal fan-shaped body (dFB) of Drosophila are integral to sleep homeostasis, but how these cells impose sleep on the organism is unknown. We report that dFB neurons communicate via inhibitory transmitters, including allatostatin-A (AstA), with interneurons connecting the superior arch with the ellipsoid body of the central complex. These "helicon cells" express the galanin receptor homolog AstA-R1, respond to visual input, gate locomotion, and are inhibited by AstA, suggesting that dFB neurons promote rest by suppressing visually guided movement. Sleep changes caused by enhanced or diminished allatostatinergic transmission from dFB neurons and by inhibition or optogenetic stimulation of helicon cells support this notion. Helicon cells provide excitation to R2 neurons of the ellipsoid body, whose activity-dependent plasticity signals rising sleep pressure to the dFB. By virtue of this autoregulatory loop, dFB-mediated inhibition interrupts processes that incur a sleep debt, allowing restorative sleep to rebalance the books. VIDEO ABSTRACT.

Unraveling the neural basis of insect navigation

One of the defining features of animals is their ability to navigate their environment. Using behavioral experiments this topic has been under intense investigation for nearly a century. In insects, this work has largely focused on the remarkable homing abilities of ants and bees. More recently, the neural basis of navigation shifted into the focus of attention. Starting with revealing the neurons that process the sensory signals used for navigation, in particular polarized skylight, migratory locusts became the key species for delineating navigation-relevant regions of the insect brain. Over the last years, this work was used as a basis for research in the fruit fly Drosophila and extraordinary progress has been made in illuminating the neural underpinnings of navigational processes. With increasingly detailed understanding of navigation circuits, we can begin to ask whether there is a fundamentally shared concept underlying all navigation behavior across insects. This review highlights recent advances and puts them into the context of the behavioral work on ants and bees, as well as the circuits involved in polarized-light processing. A region of the insect brain called the central complex emerges as the common substrate for guiding navigation and its highly organized neuroarchitecture provides a framework for future investigations potentially suited to explain all insect navigation behavior at the level of identified neurons.

Neural Coding: Bumps on the Move

By meticulously deconstructing the Drosophila head-direction neural circuit, two recent studies have revealed the mechanism of how the fly's body rotations are translated into a continuously updated internal compass representation.

An Anatomically Constrained Model for Path Integration in the Bee Brain

Path integration is a widespread navigational strategy in which directional changes and distance covered are continuously integrated on an outward journey, enabling a straight-line return to home. Bees use vision for this task-a celestial-cue-based visual compass and an optic-flow-based visual odometer-but the underlying neural integration mechanisms are unknown. Using intracellular electrophysiology, we show that polarized-light-based compass neurons and optic-flow-based speed-encoding neurons converge in the central complex of the bee brain, and through block-face electron microscopy, we identify potential integrator cells. Based on plausible output targets for these cells, we propose a complete circuit for path integration and steering in the central complex, with anatomically identified neurons suggested for each processing step. The resulting model circuit is thus fully constrained biologically and provides a functional interpretation for many previously unexplained architectural features of the central complex. Moreover, we show that the receptive fields of the newly discovered speed neurons can support path integration for the holonomic motion (i.e., a ground velocity that is not precisely aligned with body orientation) typical of bee flight, a feature not captured in any previously proposed model of path integration. In a broader context, the model circuit presented provides a general mechanism for producing steering signals by comparing current and desired headings-suggesting a more basic function for central complex connectivity, from which path integration may have evolved.

Neocortical dynamics during whisker-based sensory discrimination in head-restrained mice

A fundamental task frequently encountered by brains is to rapidly and reliably discriminate between sensory stimuli of the same modality, be it distinct auditory sounds, odors, visual patterns, or tactile textures. A key mammalian brain structure involved in discrimination behavior is the neocortex. Sensory processing not only involves the respective primary sensory area, which is crucial for perceptual detection, but additionally relies on cortico-cortical communication among several regions including higher-order sensory areas as well as frontal cortical areas. It remains elusive how these regions exchange information to process neural representations of distinct stimuli to bring about a decision and initiate appropriate behavioral responses. Likewise, it is poorly understood how these neural computations are conjured during task learning. In this review, we discuss recent studies investigating cortical dynamics during discrimination behaviors that utilize head-fixed behavioral tasks in combination with in vivo electrophysiology, two-photon calcium imaging, and cell-type-specific targeting. We particularly focus on information flow in distinct cortico-cortical pathways when mice use their whiskers to discriminate between different objects or different locations. Within the primary and secondary somatosensory cortices (S1 and S2, respectively) as well as vibrissae motor cortex (M1), intermingled functional representations of touch, whisking, and licking were found, which partially re-organized during discrimination learning. These findings provide first glimpses of cortico-cortical communication but emphasize that for understanding the complete process of discrimination it will be crucial to elucidate the details of how neural processing is coordinated across brain-wide neuronal networks including the S1-S2-M1 triangle and cortical areas beyond.

Recurrent network dynamics reconciles visual motion segmentation and integration

In sensory systems, a range of computational rules are presumed to be implemented by neuronal subpopulations with different tuning functions. For instance, in primate cortical area MT, different classes of direction-selective cells have been identified and related either to motion integration, segmentation or transparency. Still, how such different tuning properties are constructed is unclear. The dominant theoretical viewpoint based on a linear-nonlinear feed-forward cascade does not account for their complex temporal dynamics and their versatility when facing different input statistics. Here, we demonstrate that a recurrent network model of visual motion processing can reconcile these different properties. Using a ring network, we show how excitatory and inhibitory interactions can implement different computational rules such as vector averaging, winner-take-all or superposition. The model also captures ordered temporal transitions between these behaviors. In particular, depending on the inhibition regime the network can switch from motion integration to segmentation, thus being able to compute either a single pattern motion or to superpose multiple inputs as in motion transparency. We thus demonstrate that recurrent architectures can adaptively give rise to different cortical computational regimes depending upon the input statistics, from sensory flow integration to segmentation.

Parallel encoding of recent visual experience and self-motion during navigation in Drosophila

Animal navigation requires multiple types of information for decisions on directional heading. We identified neural processing channels that encode multiple cues during navigational decision-making in Drosophila melanogaster. In a flight simulator, we found that flies made directional choices on the basis of the location of a recently presented landmark. This experience-guided navigation was impaired by silencing neurons in the bulb (BU), a region in the central brain. Two-photon calcium imaging during flight revealed that the dorsal part of the BU encodes the location of a recent landmark, whereas the ventral part of the BU tracks self-motion reflecting turns. Photolabeling-based circuit tracing indicated that these functional compartments of the BU constitute adjacent, yet distinct, anatomical pathways that both enter the navigation center. Thus, the fly's navigation system organizes multiple types of information in parallel channels, which may compactly transmit signals without interference for decision-making during flight.

In silico Interrogation of Insect Central Complex Suggests Computational Roles for the Ellipsoid Body in Spatial Navigation

The central complex in the insect brain is a composite of midline neuropils involved in processing sensory cues and mediating behavioral outputs to orchestrate spatial navigation. Despite recent advances, however, the neural mechanisms underlying sensory integration and motor action selections have remained largely elusive. In particular, it is not yet understood how the central complex exploits sensory inputs to realize motor functions associated with spatial navigation. Here we report an in silico interrogation of central complex-mediated spatial navigation with a special emphasis on the ellipsoid body. Based on known connectivity and function, we developed a computational model to test how the local connectome of the central complex can mediate sensorimotor integration to guide different forms of behavioral outputs. Our simulations show integration of multiple sensory sources can be effectively performed in the ellipsoid body. This processed information is used to trigger continuous sequences of action selections resulting in self-motion, obstacle avoidance and the navigation of simulated environments of varying complexity. The motor responses to perceived sensory stimuli can be stored in the neural structure of the central complex to simulate navigation relying on a collective of guidance cues, akin to sensory-driven innate or habitual behaviors. By comparing behaviors under different conditions of accessible sources of input information, we show the simulated insect computes visual inputs and body posture to estimate its position in space. Finally, we tested whether the local connectome of the central complex might also allow the flexibility required to recall an intentional behavioral sequence, among different courses of actions. Our simulations suggest that the central complex can encode combined representations of motor and spatial information to pursue a goal and thus successfully guide orientation behavior. Together, the observed computational features identify central complex circuitry, and especially the ellipsoid body, as a key neural correlate involved in spatial navigation.

Angular velocity integration in a fly heading circuit

Many animals maintain an internal representation of their heading as they move through their surroundings. Such a compass representation was recently discovered in a neural population in the Drosophila melanogaster central complex, a brain region implicated in spatial navigation. Here, we use two-photon calcium imaging and electrophysiology in head-fixed walking flies to identify a different neural population that conjunctively encodes heading and angular velocity, and is excited selectively by turns in either the clockwise or counterclockwise direction. We show how these mirror-symmetric turn responses combine with the neurons' connectivity to the compass neurons to create an elegant mechanism for updating the fly's heading representation when the animal turns in darkness. This mechanism, which employs recurrent loops with an angular shift, bears a resemblance to those proposed in theoretical models for rodent head direction cells. Our results provide a striking example of structure matching function for a broadly relevant computation.

Integration of celestial compass cues in the central complex of the locust brain

Many insects rely on celestial compass cues such as the polarization pattern of the sky for spatial orientation. In the desert locust, the central complex (CX) houses multiple sets of neurons, sensitive to the oscillation plane of polarized light and, thus, likely acts as an internal polarization compass. We investigated whether other sky compass cues like direct sunlight or the chromatic gradient of the sky might contribute to this compass. We recorded from polarization-sensitive CX neurons while an unpolarized green or UV light spot was moved around the head of the animal. All types of neuron that were sensitive to the plane of polarization (E-vector) above the animal also responded to the unpolarized light spots in an azimuth-dependent way. The tuning to the unpolarized light spots was independent of wavelength, suggesting that the neurons encode solar azimuth based on direct sunlight and not on the sky chromatic gradient. Two cell types represented the natural 90°-relationship between solar azimuth and zenithal E-vector orientation, providing evidence to suggest that solar azimuth information supports the internal polarization compass. Most neurons showed advances in their tuning to the E-vector and the unpolarized light spots dependent on rotation direction, consistent with anticipatory signaling. The amplitude of responses and its variability were dependent on the level of background firing, possibly indicating different internal states. The integration of polarization and solar azimuth information strongly suggests that besides the polarization pattern of the sky, direct sunlight might be an important cue for sky compass navigation in the locust.