Walking modulates speed sensitivity in Drosophila motion vision

Physically activated modes of attentional control

As we navigate through the day, our attentional control processes are constantly challenged by changing sensory information, goals, expectations, and motivations. At the same time, our bodies and brains are impacted by changes in global physiological state that can influence attentional processes. Based on converging lines of evidence from brain recordings in physically active humans and nonhumans, we propose a new framework incorporating at least two physically activated modes of attentional control in humans: altered gain control and differential neuromodulation of control networks. We discuss the implications of this framework for understanding a broader range of states and cognitive functions studied both in the laboratory and in the wild.

Theory of morphodynamic information processing: Linking sensing to behaviour

The traditional understanding of brain function has predominantly focused on chemical and electrical processes. However, new research in fruit fly (Drosophila) binocular vision reveals ultrafast photomechanical photoreceptor movements significantly enhance information processing, thereby impacting a fly's perception of its environment and behaviour. The coding advantages resulting from these mechanical processes suggest that similar physical motion-based coding strategies may affect neural communication ubiquitously. The theory of neural morphodynamics proposes that rapid biomechanical movements and microstructural changes at the level of neurons and synapses enhance the speed and efficiency of sensory information processing, intrinsic thoughts, and actions by regulating neural information in a phasic manner. We propose that morphodynamic information processing evolved to drive predictive coding, synchronising cognitive processes across neural networks to match the behavioural demands at hand effectively.

A recurrent neural circuit in Drosophila temporally sharpens visual inputs

A critical goal of vision is to detect changes in light intensity, even when these changes are blurred by the spatial resolution of the eye and the motion of the animal. Here, we describe a recurrent neural circuit in Drosophila that compensates for blur and thereby selectively enhances the perceived contrast of moving edges. Using in vivo, two-photon voltage imaging, we measured the temporal response properties of L1 and L2, two cell types that receive direct synaptic input from photoreceptors. These neurons have biphasic responses to brief flashes of light, a hallmark of cells that encode changes in stimulus intensity. However, the second phase was often much larger in area than the first, creating an unusual temporal filter. Genetic dissection revealed that recurrent neural circuitry strongly shapes the second phase of the response, informing the structure of a dynamical model. By applying this model to moving natural images, we demonstrate that rather than veridically representing stimulus changes, this temporal processing strategy systematically enhances them, amplifying and sharpening responses. Comparing the measured responses of L2 to model predictions across both artificial and natural stimuli revealed that L2 tunes its properties as the model predicts to temporally sharpen visual inputs. Since this strategy is tunable to behavioral context, generalizable to any time-varying sensory input, and implementable with a common circuit motif, we propose that it could be broadly used to selectively enhance sharp and salient changes.

Is the impact of spontaneous movements on early visual cortex species specific?

Recent studies in non-human primates do not find pronounced signals related to the animal's own body movements in the responses of neurons in the visual cortex. This is notable because such pronounced signals have been widely observed in the visual cortex of mice. Here, we discuss factors that may contribute to the differences observed between species, such as state, slow neural drift, eccentricity, and changes in retinal input. The interpretation of movement-related signals in the visual cortex also exemplifies the challenge of identifying the sources of correlated variables. Dissecting these sources is central for understanding the functional roles of movement-related signals. We suggest a functional classification of the possible sources, aimed at facilitating cross-species comparative approaches to studying the neural mechanisms of vision during natural behavior.

Temperature modulates the tuning properties of small target motion detector neurons in the dragonfly visual system

Dragonflies are poikilothermic animals with limited thermoregulation; therefore, their entire bodies, including the brain, experience a range of temperatures during their daily activities.1,2 These flying insects exhibit hunting prowess, pursuing prey or conspecifics whether in direct sunlight or under the cover of cloud.3,4 Likely to underlie these aerobatic feats are the small target motion detector (STMD) neurons.5 These visual neurons are sensitive to target contrast and tuned to the target's size and velocity, with some neurons exhibiting complex predictive and selective properties, well suited for prey interception and feeding amid swarms.3,4,6,7,8,9 Increased temperature can modulate the biochemical processes underlying neuronal processing, increasing sensitivity and quickening the responsiveness of insect photoreceptors and downstream optic flow neurons,10,11,12 while in other neuronal pathways, compensatory processes have been shown to account for temperature changes.13,14 We determined the ethological range of temperatures experienced by the dragonfly, Hemicordulia tau, in its natural environment. Across this behaviorally relevant range, we showed increased temperatures having a large 8.7-fold increase in the contrast sensitivity of STMD neurons. However, suppression of responses to larger targets was unaltered. STMD tuning for target velocities was changed remarkably, not only increasing the optimum but extending the fastest velocities encoded by an order of magnitude. These results caution against interpreting functionality underlying spike rates at constrained, experimental temperatures. Moreover, they raise intriguing new questions about how information is represented within the brain of these flying insects, given the relationship between visual stimulus parameters and neuronal activity varies so dramatically depending on current environmental conditions.

Optimization in Visual Motion Estimation

Sighted animals use visual signals to discern directional motion in their environment. Motion is not directly detected by visual neurons, and it must instead be computed from light signals that vary over space and time. This makes visual motion estimation a near universal neural computation, and decades of research have revealed much about the algorithms and mechanisms that generate directional signals. The idea that sensory systems are optimized for performance in natural environments has deeply impacted this research. In this article, we review the many ways that optimization has been used to quantitatively model visual motion estimation and reveal its underlying principles. We emphasize that no single optimization theory has dominated the literature. Instead, researchers have adeptly incorporated different computational demands and biological constraints that are pertinent to the specific brain system and animal model under study. The successes and failures of the resulting optimization models have thereby provided insights into how computational demands and biological constraints together shape neural computation.

Moving object detection based on bioinspired background subtraction

Flying insects rely mainly upon visual motion to detect and track objects. There has been a lot of research on fly inspired algorithms for object detection, but few have been developed based on visual motion alone. One of the daunting difficulties is that the neural and circuit mechanisms underlying the foreground-background segmentation are still unclear. Our previous modeling study proposed that the lobula held parallel pathways with distinct directional selectivity, each of which could retinotopically discriminate figures moving in its own preferred direction based on relative motion cues. The previous model, however, did not address how the multiple parallel pathways gave the only detection output at their common downstream. Since the preferred directions of the pathways along either horizontal or vertical axis were opposite to each other, the background moving in the opposite direction to an object also activated the corresponding lobula pathway. Indiscriminate or ungated projection from all the pathways to their downstream would mix objects with the moving background, making the previous model fail with non-stationary background. Here, we extend the previous model by proposing that the background motion-dependent gating of individual lobula projections is the key to object detection. Large-field lobula plate tangential cells are hypothesized to perform the gating to realize bioinspired background subtraction. The model is shown to be capable of implementing a robust detection of moving objects in video sequences with either a moving camera that induces translational optic flow or a static camera. The model sheds light on the potential of the concise fly algorithm in real-world applications.

A recurrent neural circuit in Drosophila deblurs visual inputs

A critical goal of vision is to detect changes in light intensity, even when these changes are blurred by the spatial resolution of the eye and the motion of the animal. Here we describe a recurrent neural circuit in Drosophila that compensates for blur and thereby selectively enhances the perceived contrast of moving edges. Using in vivo, two-photon voltage imaging, we measured the temporal response properties of L1 and L2, two cell types that receive direct synaptic input from photoreceptors. These neurons have biphasic responses to brief flashes of light, a hallmark of cells that encode changes in stimulus intensity. However, the second phase was often much larger than the first, creating an unusual temporal filter. Genetic dissection revealed that recurrent neural circuitry strongly shapes the second phase of the response, informing the structure of a dynamical model. By applying this model to moving natural images, we demonstrate that rather than veridically representing stimulus changes, this temporal processing strategy systematically enhances them, amplifying and sharpening responses. Comparing the measured responses of L2 to model predictions across both artificial and natural stimuli revealed that L2 tunes its properties as the model predicts in order to deblur images. Since this strategy is tunable to behavioral context, generalizable to any time-varying sensory input, and implementable with a common circuit motif, we propose that it could be broadly used to selectively enhance sharp and salient changes.

Mapping the neural dynamics of locomotion across the Drosophila brain

Locomotion engages widely distributed networks of neurons. However, our understanding of the spatial architecture and temporal dynamics of the networks that underpin walking remains incomplete. We use volumetric two-photon imaging to map neural activity associated with walking across the entire brain of Drosophila. We define spatially clustered neural signals selectively associated with changes in either forward or angular velocity, demonstrating that neurons with similar behavioral selectivity are clustered. These signals reveal distinct topographic maps in diverse brain regions involved in navigation, memory, sensory processing, and motor control, as well as regions not previously linked to locomotion. We identify temporal trajectories of neural activity that sweep across these maps, including signals that anticipate future movement, representing the sequential engagement of clusters with different behavioral specificities. Finally, we register these maps to a connectome and identify neural networks that we propose underlie the observed signals, setting a foundation for subsequent circuit dissection. Overall, our work suggests a spatiotemporal framework for the emergence and execution of complex walking maneuvers and links this brain-wide neural activity to single neurons and local circuits.

Neural mechanisms to incorporate visual counterevidence in self-movement estimation

In selecting appropriate behaviors, animals should weigh sensory evidence both for and against specific beliefs about the world. For instance, animals measure optic flow to estimate and control their own rotation. However, existing models of flow detection can be spuriously triggered by visual motion created by objects moving in the world. Here, we show that stationary patterns on the retina, which constitute evidence against observer rotation, suppress inappropriate stabilizing rotational behavior in the fruit fly Drosophila. In silico experiments show that artificial neural networks (ANNs) that are optimized to distinguish observer movement from external object motion similarly detect stationarity and incorporate negative evidence. Employing neural measurements and genetic manipulations, we identified components of the circuitry for stationary pattern detection, which runs parallel to the fly's local motion and optic-flow detectors. Our results show how the fly brain incorporates negative evidence to improve heading stability, exemplifying how a compact brain exploits geometrical constraints of the visual world.

A comprehensive neuroanatomical survey of the Drosophila Lobula Plate Tangential Neurons with predictions for their optic flow sensitivity

Flying insects exhibit remarkable navigational abilities controlled by their compact nervous systems. Optic flow, the pattern of changes in the visual scene induced by locomotion, is a crucial sensory cue for robust self-motion estimation, especially during rapid flight. Neurons that respond to specific, large-field optic flow patterns have been studied for decades, primarily in large flies, such as houseflies, blowflies, and hover flies. The best-known optic-flow sensitive neurons are the large tangential cells of the dipteran lobula plate, whose visual-motion responses, and to a lesser extent, their morphology, have been explored using single-neuron neurophysiology. Most of these studies have focused on the large, Horizontal and Vertical System neurons, yet the lobula plate houses a much larger set of 'optic-flow' sensitive neurons, many of which have been challenging to unambiguously identify or to reliably target for functional studies. Here we report the comprehensive reconstruction and identification of the Lobula Plate Tangential Neurons in an Electron Microscopy (EM) volume of a whole Drosophila brain. This catalog of 58 LPT neurons (per brain hemisphere) contains many neurons that are described here for the first time and provides a basis for systematic investigation of the circuitry linking self-motion to locomotion control. Leveraging computational anatomy methods, we estimated the visual motion receptive fields of these neurons and compared their tuning to the visual consequence of body rotations and translational movements. We also matched these neurons, in most cases on a one-for-one basis, to stochastically labeled cells in genetic driver lines, to the mirror-symmetric neurons in the same EM brain volume, and to neurons in an additional EM data set. Using cell matches across data sets, we analyzed the integration of optic flow patterns by neurons downstream of the LPTs and find that most central brain neurons establish sharper selectivity for global optic flow patterns than their input neurons. Furthermore, we found that self-motion information extracted from optic flow is processed in distinct regions of the central brain, pointing to diverse foci for the generation of visual behaviors.

Contrast sensitivity, visual acuity and the effect of behavioural state on optokinetic gain in fiddler crabs

Most animals rely on visual information for a variety of everyday tasks. The information available to a visual system depends in part on its spatial resolving power and contrast sensitivity. Because of their competing demands for physical space within an eye, these traits cannot simultaneously be improved without increasing overall eye size. The contrast sensitivity function is an integrated measure of visual performance that measures both resolution and contrast sensitivity. Its measurement helps us identify how different species have made a trade-off between contrast sensitivity and spatial resolution. It further allows us to identify the evolutionary drivers of sensory processing and visually mediated behaviour. Here, we measured the contrast sensitivity function of the fiddler crab Gelasimus dampieri using its optokinetic responses to wide-field moving sinusoidal intensity gratings of different orientations, spatial frequencies, contrasts and speeds. We further tested whether the behavioural state of the crabs (i.e. whether crabs are actively walking or not) affects their optokinetic gain and contrast sensitivity. Our results from a group of five crabs suggest a minimum perceived contrast of 6% and a horizontal and vertical visual acuity of 0.4 cyc deg-1 and 0.28 cyc deg-1, respectively, in the crabs' region of maximum optomotor sensitivity. Optokinetic gain increased in moving crabs compared with restrained crabs, adding another example of the importance of naturalistic approaches when studying the performance of animals.

Long-timescale anti-directional rotation in Drosophila optomotor behavior

Locomotor movements cause visual images to be displaced across the eye, a retinal slip that is counteracted by stabilizing reflexes in many animals. In insects, optomotor turning causes the animal to turn in the direction of rotating visual stimuli, thereby reducing retinal slip and stabilizing trajectories through the world. This behavior has formed the basis for extensive dissections of motion vision. Here, we report that under certain stimulus conditions, two Drosophila species, including the widely studied Drosophila melanogaster, can suppress and even reverse the optomotor turning response over several seconds. Such 'anti-directional turning' is most strongly evoked by long-lasting, high-contrast, slow-moving visual stimuli that are distinct from those that promote syn-directional optomotor turning. Anti-directional turning, like the syn-directional optomotor response, requires the local motion detecting neurons T4 and T5. A subset of lobula plate tangential cells, CH cells, show involvement in these responses. Imaging from a variety of direction-selective cells in the lobula plate shows no evidence of dynamics that match the behavior, suggesting that the observed inversion in turning direction emerges downstream of the lobula plate. Further, anti-directional turning declines with age and exposure to light. These results show that Drosophila optomotor turning behaviors contain rich, stimulus-dependent dynamics that are inconsistent with simple reflexive stabilization responses.

The spatial and temporal structure of neural activity across the fly brain

What are the spatial and temporal scales of brainwide neuronal activity? We used swept, confocally-aligned planar excitation (SCAPE) microscopy to image all cells in a large volume of the brain of adult Drosophila with high spatiotemporal resolution while flies engaged in a variety of spontaneous behaviors. This revealed neural representations of behavior on multiple spatial and temporal scales. The activity of most neurons correlated (or anticorrelated) with running and flailing over timescales that ranged from seconds to a minute. Grooming elicited a weaker global response. Significant residual activity not directly correlated with behavior was high dimensional and reflected the activity of small clusters of spatially organized neurons that may correspond to genetically defined cell types. These clusters participate in the global dynamics, indicating that neural activity reflects a combination of local and broadly distributed components. This suggests that microcircuits with highly specified functions are provided with knowledge of the larger context in which they operate.

Motor state changes escape behavior of crickets

Animals change their behavior depending on external circumstances, internal factors, and their interactions. Locomotion state is a crucial internal factor that profoundly affects sensory perception and behavior. However, studying the behavioral impacts of locomotion state in free-moving animals has been challenging due to difficulty in reproducing quantitatively identical stimuli in freely moving animals. We utilized a closed-loop controlled servosphere treadmill system, enabling unrestricted confinement and orientation of small animals, and investigated wind-induced escape behavior in freely moving crickets. When stimulated during locomotion, the crickets quickly stopped before initiating escape behavior. Moving crickets exhibited a higher probability of escape response compared to stationary crickets. The threshold for pausing response in moving crickets was also much lower than the escape response threshold. Moving crickets had delayed reaction times for escape and greater variance in movement direction compared to stationary crickets. The locomotion-related response delay may be compensated by an elevated sensitivity to airflow.

Circuits for self-motion estimation and walking control in Drosophila

The brain's evolution and operation are inextricably linked to animal movement, and critical functions, such as motor control, spatial perception, and navigation, rely on precise knowledge of body movement. Such internal estimates of self-motion emerge from the integration of mechanosensory and visual feedback with motor-related signals. Thus, this internal representation likely depends on the activity of circuits distributed across the central nervous system. However, the circuits responsible for self-motion estimation, and the exact mechanisms by which motor-sensory coordination occurs within these circuits remain poorly understood. Recent technological advances have positioned Drosophila melanogaster as an advantageous model for investigating the emergence, maintenance, and utilization of self-motion representations during naturalistic walking behaviors. In this review, I will illustrate how the adult fly is providing insights into the fundamental problems of self-motion computations and walking control, which have relevance for all animals.

Locomotion modulates olfactory learning through proprioception in C. elegans

Locomotor activities can enhance learning, but the underlying circuit and synaptic mechanisms are largely unknown. Here we show that locomotion facilitates aversive olfactory learning in C. elegans by activating mechanoreceptors in motor neurons, and transmitting the proprioceptive information thus generated to locomotion interneurons through antidromic-rectifying gap junctions. The proprioceptive information serves to regulate experience-dependent activities and functional coupling of interneurons that process olfactory sensory information to produce the learning behavior. Genetic destruction of either the mechanoreceptors in motor neurons, the rectifying gap junctions between the motor neurons and locomotion interneurons, or specific inhibitory synapses among the interneurons impairs the aversive olfactory learning. We have thus uncovered an unexpected role of proprioception in a specific learning behavior as well as the circuit, synaptic, and gene bases for this function.

Threat gates visual aversion via theta activity in Tachykinergic neurons

Animals must adapt sensory responses to an ever-changing environment for survival. Such sensory modulation is especially critical in a threatening situation, in which animals often promote aversive responses to, among others, visual stimuli. Recently, threatened Drosophila has been shown to exhibit a defensive internal state. Whether and how threatened Drosophila promotes visual aversion, however, remains elusive. Here we report that mechanical threats to Drosophila transiently gate aversion from an otherwise neutral visual object. We further identified the neuropeptide tachykinin, and a single cluster of neurons expressing it ("Tk-GAL42 ∩ Vglut neurons"), that are responsible for gating visual aversion. Calcium imaging analysis revealed that mechanical threats are encoded in Tk-GAL42 ∩ Vglut neurons as elevated activity. Remarkably, we also discovered that a visual object is encoded in Tk-GAL42 ∩ Vglut neurons as θ oscillation, which is causally linked to visual aversion. Our data reveal how a single cluster of neurons adapt organismal sensory response to a threatening situation through a neuropeptide and a combination of rate/temporal coding schemes.

Neural mechanisms to incorporate visual counterevidence in self motion estimation

In selecting appropriate behaviors, animals should weigh sensory evidence both for and against specific beliefs about the world. For instance, animals measure optic flow to estimate and control their own rotation. However, existing models of flow detection can confuse the movement of external objects with genuine self motion. Here, we show that stationary patterns on the retina, which constitute negative evidence against self rotation, are used by the fruit fly Drosophila to suppress inappropriate stabilizing rotational behavior. In silico experiments show that artificial neural networks optimized to distinguish self and world motion similarly detect stationarity and incorporate negative evidence. Employing neural measurements and genetic manipulations, we identified components of the circuitry for stationary pattern detection, which runs parallel to the fly's motion- and optic flow-detectors. Our results exemplify how the compact brain of the fly incorporates negative evidence to improve heading stability, exploiting geometrical constraints of the visual world.

The self as part of the sensory ecology: how behavior affects sensation from the inside out

Insects exhibit remarkable sensory and motor capabilities to successfully navigate their environment. As insects move, they activate sensory afferents. Hence, insects are inextricably part of their sensory ecology. Insects must correctly attribute self- versus external sources of sensory activation to make adaptive behavioral choices. This is achieved via corollary discharge circuits (CDCs), motor-to-sensory neuronal pathways providing predictive motor signals to sensory networks to coordinate sensory processing within the context of ongoing behavior. While CDCs provide predictive motor signals, their underlying mechanisms of action and functional consequences are diverse. Here, we describe inferred CDCs and identified corollary discharge interneurons (CDIs) in insects, highlighting their anatomical commonalities and our limited understanding of their synaptic integration into the nervous system. By using connectomics information, we demonstrate that the complexity with which identified CDIs integrate into the central nervous system (CNS) can be revealed.

Walking bumblebees see faster

The behavioural state of animals has profound effects on neuronal information processing. Locomotion changes the response properties of visual interneurons in the insect brain, but it is still unknown if it also alters the response properties of photoreceptors. Photoreceptor responses become faster at higher temperatures. It has therefore been suggested that thermoregulation in insects could improve temporal resolution in vision, but direct evidence for this idea has so far been missing. Here, we compared electroretinograms from the compound eyes of tethered bumblebees that were either sitting or walking on an air-supported ball. We found that the visual processing speed strongly increased when the bumblebees were walking. By monitoring the eye temperature during recording, we saw that the increase in response speed was in synchrony with a rise in eye temperature. By artificially heating the head, we show that the walking-induced temperature increase of the visual system is sufficient to explain the rise in processing speed. We also show that walking accelerates the visual system to the equivalent of a 14-fold increase in light intensity. We conclude that the walking-induced rise in temperature accelerates the processing of visual information-an ideal strategy to process the increased information flow during locomotion.

Visual processing in the fly, from photoreceptors to behavior

Originally a genetic model organism, the experimental use of Drosophila melanogaster has grown to include quantitative behavioral analyses, sophisticated perturbations of neuronal function, and detailed sensory physiology. A highlight of these developments can be seen in the context of vision, where pioneering studies have uncovered fundamental and generalizable principles of sensory processing. Here we begin with an overview of vision-guided behaviors and common methods for probing visual circuits. We then outline the anatomy and physiology of brain regions involved in visual processing, beginning at the sensory periphery and ending with descending motor control. Areas of focus include contrast and motion detection in the optic lobe, circuits for visual feature selectivity, computations in support of spatial navigation, and contextual associative learning. Finally, we look to the future of fly visual neuroscience and discuss promising topics for further study.

Bioinspired figure-ground discrimination via visual motion smoothing

Flies detect and track moving targets among visual clutter, and this process mainly relies on visual motion. Visual motion is analyzed or computed with the pathway from the retina to T4/T5 cells. The computation of local directional motion was formulated as an elementary movement detector (EMD) model more than half a century ago. Solving target detection or figure-ground discrimination problems can be equivalent to extracting boundaries between a target and the background based on the motion discontinuities in the output of a retinotopic array of EMDs. Individual EMDs cannot measure true velocities, however, due to their sensitivity to pattern properties such as luminance contrast and spatial frequency content. It remains unclear how local directional motion signals are further integrated to enable figure-ground discrimination. Here, we present a computational model inspired by fly motion vision. Simulations suggest that the heavily fluctuating output of an EMD array is naturally surmounted by a lobula network, which is hypothesized to be downstream of the local motion detectors and have parallel pathways with distinct directional selectivity. The lobula network carries out a spatiotemporal smoothing operation for visual motion, especially across time, enabling the segmentation of moving figures from the background. The model qualitatively reproduces experimental observations in the visually evoked response characteristics of one type of lobula columnar (LC) cell. The model is further shown to be robust to natural scene variability. Our results suggest that the lobula is involved in local motion-based target detection.

Global change in brain state during spontaneous and forced walk in Drosophila is composed of combined activity patterns of different neuron classes

Movement-correlated brain activity has been found across species and brain regions. Here, we used fast whole brain lightfield imaging in adult Drosophila to investigate the relationship between walk and brain-wide neuronal activity. We observed a global change in activity that tightly correlated with spontaneous bouts of walk. While imaging specific sets of excitatory, inhibitory, and neuromodulatory neurons highlighted their joint contribution, spatial heterogeneity in walk- and turning-induced activity allowed parsing unique responses from subregions and sometimes individual candidate neurons. For example, previously uncharacterized serotonergic neurons were inhibited during walk. While activity onset in some areas preceded walk onset exclusively in spontaneously walking animals, spontaneous and forced walk elicited similar activity in most brain regions. These data suggest a major contribution of walk and walk-related sensory or proprioceptive information to global activity of all major neuronal classes.

Long timescale anti-directional rotation in Drosophila optomotor behavior

Locomotor movements cause visual images to be displaced across the eye, a retinal slip that is counteracted by stabilizing reflexes in many animals. In insects, optomotor turning causes the animal to turn in the direction of rotating visual stimuli, thereby reducing retinal slip and stabilizing trajectories through the world. This behavior has formed the basis for extensive dissections of motion vision. Here, we report that under certain stimulus conditions, two Drosophila species, including the widely studied D. melanogaster, can suppress and even reverse the optomotor turning response over several seconds. Such "anti-directional turning" is most strongly evoked by long-lasting, high-contrast, slow-moving visual stimuli that are distinct from those that promote syn-directional optomotor turning. Anti-directional turning, like the syn-directional optomotor response, requires the local motion detecting neurons T4 and T5. A subset of lobula plate tangential cells, CH cells, show involvement in these responses. Imaging from a variety of direction-selective cells in the lobula plate shows no evidence of dynamics that match the behavior, suggesting that the observed inversion in turning direction emerges downstream of the lobula plate. Further, anti-directional turning declines with age and exposure to light. These results show that Drosophila optomotor turning behaviors contain rich, stimulus-dependent dynamics that are inconsistent with simple reflexive stabilization responses.

Parallel motion vision pathways in the brain of a tropical bee

Spatial orientation is a prerequisite for most behaviors. In insects, the underlying neural computations take place in the central complex (CX), the brain's navigational center. In this region different streams of sensory information converge to enable context-dependent navigational decisions. Accordingly, a variety of CX input neurons deliver information about different navigation-relevant cues. In bees, direction encoding polarized light signals converge with translational optic flow signals that are suited to encode the flight speed of the animals. The continuous integration of speed and directions in the CX can be used to generate a vector memory of the bee's current position in space in relation to its nest, i.e., perform path integration. This process depends on specific, complex features of the optic flow encoding CX input neurons, but it is unknown how this information is derived from the visual periphery. Here, we thus aimed at gaining insight into how simple motion signals are reshaped upstream of the speed encoding CX input neurons to generate their complex features. Using electrophysiology and anatomical analyses of the halictic bees Megalopta genalis and Megalopta centralis, we identified a wide range of motion-sensitive neurons connecting the optic lobes with the central brain. While most neurons formed pathways with characteristics incompatible with CX speed neurons, we showed that one group of lobula projection neurons possess some physiological and anatomical features required to generate the visual responses of CX optic-flow encoding neurons. However, as these neurons cannot explain all features of CX speed cells, local interneurons of the central brain or alternative input cells from the optic lobe are additionally required to construct inputs with sufficient complexity to deliver speed signals suited for path integration in bees.

Ascending neurons convey behavioral state to integrative sensory and action selection brain regions

Knowing one's own behavioral state has long been theorized as critical for contextualizing dynamic sensory cues and identifying appropriate future behaviors. Ascending neurons (ANs) in the motor system that project to the brain are well positioned to provide such behavioral state signals. However, what ANs encode and where they convey these signals remains largely unknown. Here, through large-scale functional imaging in behaving animals and morphological quantification, we report the behavioral encoding and brain targeting of hundreds of genetically identifiable ANs in the adult fly, Drosophila melanogaster. We reveal that ANs encode behavioral states, specifically conveying self-motion to the anterior ventrolateral protocerebrum, an integrative sensory hub, as well as discrete actions to the gnathal ganglia, a locus for action selection. Additionally, AN projection patterns within the motor system are predictive of their encoding. Thus, ascending populations are well poised to inform distinct brain hubs of self-motion and ongoing behaviors and may provide an important substrate for computations that are required for adaptive behavior.

Cell types and molecular architecture of the Octopus bimaculoides visual system

Cephalopods have a remarkable visual system, with a camera-type eye and high acuity vision that they use for a wide range of sophisticated visually driven behaviors. However, the cephalopod brain is organized dramatically differently from that of vertebrates and invertebrates, and beyond neuroanatomical descriptions, little is known regarding the cell types and molecular determinants of their visual system organization. Here, we present a comprehensive single-cell molecular atlas of the octopus optic lobe, which is the primary visual processing structure in the cephalopod brain. We combined single-cell RNA sequencing with RNA fluorescence in situ hybridization to both identify putative molecular cell types and determine their anatomical and spatial organization within the optic lobe. Our results reveal six major neuronal cell classes identified by neurotransmitter/neuropeptide usage, in addition to non-neuronal and immature neuronal populations. We find that additional markers divide these neuronal classes into subtypes with distinct anatomical localizations, revealing further diversity and a detailed laminar organization within the optic lobe. We also delineate the immature neurons within this continuously growing tissue into subtypes defined by evolutionarily conserved developmental genes as well as novel cephalopod- and octopus-specific genes. Together, these findings outline the organizational logic of the octopus visual system, based on functional determinants, laminar identity, and developmental markers/pathways. The resulting atlas presented here details the "parts list" for neural circuits used for vision in octopus, providing a platform for investigations into the development and function of the octopus visual system as well as the evolution of visual processing.

Muscles that move the retina augment compound eye vision in Drosophila

Most animals have compound eyes, with tens to thousands of lenses attached rigidly to the exoskeleton. A natural assumption is that all of these species must resort to moving either their head or their body to actively change their visual input. However, classic anatomy has revealed that flies have muscles poised to move their retinas under the stable lenses of each compound eye1-3. Here we show that Drosophila use their retinal muscles to smoothly track visual motion, which helps to stabilize the retinal image, and also to perform small saccades when viewing a stationary scene. We show that when the retina moves, visual receptive fields shift accordingly, and that even the smallest retinal saccades activate visual neurons. Using a head-fixed behavioural paradigm, we find that Drosophila perform binocular, vergence movements of their retinas-which could enhance depth perception-when crossing gaps, and impairing the physiology of retinal motor neurons alters gap-crossing trajectories during free behaviour. That flies evolved an ability to actuate their retinas suggests that moving the eye independently of the head is broadly paramount for animals. The similarities of smooth and saccadic movements of the Drosophila retina and the vertebrate eye highlight a notable example of convergent evolution.

Visual and motor signatures of locomotion dynamically shape a population code for feature detection in Drosophila

Natural vision is dynamic: as an animal moves, its visual input changes dramatically. How can the visual system reliably extract local features from an input dominated by self-generated signals? In Drosophila, diverse local visual features are represented by a group of projection neurons with distinct tuning properties. Here, we describe a connectome-based volumetric imaging strategy to measure visually evoked neural activity across this population. We show that local visual features are jointly represented across the population, and a shared gain factor improves trial-to-trial coding fidelity. A subset of these neurons, tuned to small objects, is modulated by two independent signals associated with self-movement, a motor-related signal, and a visual motion signal associated with rotation of the animal. These two inputs adjust the sensitivity of these feature detectors across the locomotor cycle, selectively reducing their gain during saccades and restoring it during intersaccadic intervals. This work reveals a strategy for reliable feature detection during locomotion.

State-dependent pupil dilation rapidly shifts visual feature selectivity

To increase computational flexibility, the processing of sensory inputs changes with behavioural context. In the visual system, active behavioural states characterized by motor activity and pupil dilation1,2 enhance sensory responses, but typically leave the preferred stimuli of neurons unchanged2-9. Here we find that behavioural state also modulates stimulus selectivity in the mouse visual cortex in the context of coloured natural scenes. Using population imaging in behaving mice, pharmacology and deep neural network modelling, we identified a rapid shift in colour selectivity towards ultraviolet stimuli during an active behavioural state. This was exclusively caused by state-dependent pupil dilation, which resulted in a dynamic switch from rod to cone photoreceptors, thereby extending their role beyond night and day vision. The change in tuning facilitated the decoding of ethological stimuli, such as aerial predators against the twilight sky10. For decades, studies in neuroscience and cognitive science have used pupil dilation as an indirect measure of brain state. Our data suggest that, in addition, state-dependent pupil dilation itself tunes visual representations to behavioural demands by differentially recruiting rods and cones on fast timescales.

The emergence and influence of internal states

Animal behavior is shaped by a variety of "internal states"-partially hidden variables that profoundly shape perception, cognition, and action. The neural basis of internal states, such as fear, arousal, hunger, motivation, aggression, and many others, is a prominent focus of research efforts across animal phyla. Internal states can be inferred from changes in behavior, physiology, and neural dynamics and are characterized by properties such as pleiotropy, persistence, scalability, generalizability, and valence. To date, it remains unclear how internal states and their properties are generated by nervous systems. Here, we review recent progress, which has been driven by advances in behavioral quantification, cellular manipulations, and neural population recordings. We synthesize research implicating defined subsets of state-inducing cell types, widespread changes in neural activity, and neuromodulation in the formation and updating of internal states. In addition to highlighting the significance of these findings, our review advocates for new approaches to clarify the underpinnings of internal brain states across the animal kingdom.

Chronic exposure to insecticides impairs honeybee optomotor behaviour

Honeybees use wide-field visual motion information to calculate the distance they have flown from the hive, and this information is communicated to conspecifics during the waggle dance. Seed treatment insecticides, including neonicotinoids and novel insecticides like sulfoxaflor, display detrimental effects on wild and managed bees, even when present at sublethal quantities. These effects include deficits in flight navigation and homing ability, and decreased survival of exposed worker bees. Neonicotinoid insecticides disrupt visual motion detection in the locust, resulting in impaired escape behaviors, but it had not previously been shown whether seed treatment insecticides disrupt wide-field motion detection in the honeybee. Here, we show that sublethal exposure to two commonly used insecticides, imidacloprid (a neonicotinoid) and sulfoxaflor, results in impaired optomotor behavior in the honeybee. This behavioral effect correlates with altered stress and detoxification gene expression in the brain. Exposure to sulfoxaflor led to sparse increases in neuronal apoptosis, localized primarily in the optic lobes, however there was no effect of imidacloprid. We propose that exposure to cholinergic insecticides disrupts the honeybee's ability to accurately encode wide-field visual motion, resulting in impaired optomotor behaviors. These findings provide a novel explanation for previously described effects of neonicotinoid insecticides on navigation and link these effects to sulfoxaflor for which there is a gap in scientific knowledge.

Not so spontaneous: Multi-dimensional representations of behaviors and context in sensory areas

Sensory areas are spontaneously active in the absence of sensory stimuli. This spontaneous activity has long been studied; however, its functional role remains largely unknown. Recent advances in technology, allowing large-scale neural recordings in the awake and behaving animal, have transformed our understanding of spontaneous activity. Studies using these recordings have discovered high-dimensional spontaneous activity patterns, correlation between spontaneous activity and behavior, and dissimilarity between spontaneous and sensory-driven activity patterns. These findings are supported by evidence from developing animals, where a transition toward these characteristics is observed as the circuit matures, as well as by evidence from mature animals across species. These newly revealed characteristics call for the formulation of a new role for spontaneous activity in neural sensory computation.

Impact of walking speed and motion adaptation on optokinetic nystagmus-like head movements in the blowfly Calliphora

The optokinetic nystagmus is a gaze-stabilizing mechanism reducing motion blur by rapid eye rotations against the direction of visual motion, followed by slower syndirectional eye movements minimizing retinal slip speed. Flies control their gaze through head turns controlled by neck motor neurons receiving input directly, or via descending neurons, from well-characterized directional-selective interneurons sensitive to visual wide-field motion. Locomotion increases the gain and speed sensitivity of these interneurons, while visual motion adaptation in walking animals has the opposite effects. To find out whether flies perform an optokinetic nystagmus, and how it may be affected by locomotion and visual motion adaptation, we recorded head movements of blowflies on a trackball stimulated by progressive and rotational visual motion. Flies flexibly responded to rotational stimuli with optokinetic nystagmus-like head movements, independent of their locomotor state. The temporal frequency tuning of these movements, though matching that of the upstream directional-selective interneurons, was only mildly modulated by walking speed or visual motion adaptation. Our results suggest flies flexibly control their gaze to compensate for rotational wide-field motion by a mechanism similar to an optokinetic nystagmus. Surprisingly, the mechanism is less state-dependent than the response properties of directional-selective interneurons providing input to the neck motor system.

Walking strides direct rapid and flexible recruitment of visual circuits for course control in Drosophila

Flexible mapping between activity in sensory systems and movement parameters is a hallmark of motor control. This flexibility depends on the continuous comparison of short-term postural dynamics and the longer-term goals of an animal, thereby necessitating neural mechanisms that can operate across multiple timescales. To understand how such body-brain interactions emerge across timescales to control movement, we performed whole-cell patch recordings from visual neurons involved in course control in Drosophila. We show that the activity of leg mechanosensory cells, propagating via specific ascending neurons, is critical for stride-by-stride steering adjustments driven by the visual circuit, and, at longer timescales, it provides information about the moving body's state to flexibly recruit the visual circuit for course control. Thus, our findings demonstrate the presence of an elegant stride-based mechanism operating at multiple timescales for context-dependent course control. We propose that this mechanism functions as a general basis for the adaptive control of locomotion.

Natural behavior is the language of the brain

The breadth and complexity of natural behaviors inspires awe. Understanding how our perceptions, actions, and internal thoughts arise from evolved circuits in the brain has motivated neuroscientists for generations. Researchers have traditionally approached this question by focusing on stereotyped behaviors, either natural or trained, in a limited number of model species. This approach has allowed for the isolation and systematic study of specific brain operations, which has greatly advanced our understanding of the circuits involved. At the same time, the emphasis on experimental reductionism has left most aspects of the natural behaviors that have shaped the evolution of the brain largely unexplored. However, emerging technologies and analytical tools make it possible to comprehensively link natural behaviors to neural activity across a broad range of ethological contexts and timescales, heralding new modes of neuroscience focused on natural behaviors. Here we describe a three-part roadmap that aims to leverage the wealth of behaviors in their naturally occurring distributions, linking their variance with that of underlying neural processes to understand how the brain is able to successfully navigate the everyday challenges of animals' social and ecological landscapes. To achieve this aim, experimenters must harness one challenge faced by all neurobiological systems, namely variability, in order to gain new insights into the language of the brain.

From Photons to Behaviors: Neural Implementations of Visual Behaviors in Drosophila

Neural implementations of visual behaviors in Drosophila have been dissected intensively in the past couple of decades. The availability of premiere genetic toolkits, behavioral assays in tethered or freely moving conditions, and advances in connectomics have permitted the understanding of the physiological and anatomical details of the nervous system underlying complex visual behaviors. In this review, we describe recent advances on how various features of a visual scene are detected by the Drosophila visual system and how the neural circuits process these signals and elicit an appropriate behavioral response. Special emphasis was laid on the neural circuits that detect visual features such as brightness, color, local motion, optic flow, and translating or approaching visual objects, which would be important for behaviors such as phototaxis, optomotor response, attraction (or aversion) to moving objects, navigation, and visual learning. This review offers an integrative framework for how the fly brain detects visual features and orchestrates an appropriate behavioral response.

Neural Circuits Underlying Behavioral Flexibility: Insights From Drosophila

Behavioral flexibility is critical to survival. Animals must adapt their behavioral responses based on changes in the environmental context, internal state, or experience. Studies in Drosophila melanogaster have provided insight into the neural circuit mechanisms underlying behavioral flexibility. Here we discuss how Drosophila behavior is modulated by internal and behavioral state, environmental context, and learning. We describe general principles of neural circuit organization and modulation that underlie behavioral flexibility, principles that are likely to extend to other species.

Spatial tuning of translational optic flow responses in hawkmoths of varying body size

To safely navigate their environment, flying insects rely on visual cues, such as optic flow. Which cues insects can extract from their environment depends closely on the spatial and temporal response properties of their visual system. These in turn can vary between individuals that differ in body size. How optic flow-based flight control depends on the spatial structure of visual cues, and how this relationship scales with body size, has previously been investigated in insects with apposition compound eyes. Here, we characterised the visual flight control response limits and their relationship to body size in an insect with superposition compound eyes: the hummingbird hawkmoth Macroglossum stellatarum. We used the hawkmoths’ centring response in a flight tunnel as a readout for their reception of translational optic flow stimuli of different spatial frequencies. We show that their responses cut off at different spatial frequencies when translational optic flow was presented on either one, or both tunnel walls. Combined with differences in flight speed, this suggests that their flight control was primarily limited by their temporal rather than spatial resolution. We also observed strong individual differences in flight performance, but no correlation between the spatial response cutoffs and body or eye size.

Flexible filtering by neural inputs supports motion computation across states and stimuli

Sensory systems flexibly adapt their processing properties across a wide range of environmental and behavioral conditions. Such variable processing complicates attempts to extract a mechanistic understanding of sensory computations. This is evident in the highly constrained, canonical Drosophila motion detection circuit, where the core computation underlying direction selectivity is still debated despite extensive studies. Here we measured the filtering properties of neural inputs to the OFF motion-detecting T5 cell in Drosophila. We report state- and stimulus-dependent changes in the shape of these signals, which become more biphasic under specific conditions. Summing these inputs within the framework of a connectomic-constrained model of the circuit demonstrates that these shapes are sufficient to explain T5 responses to various motion stimuli. Thus, our stimulus- and state-dependent measurements reconcile motion computation with the anatomy of the circuit. These findings provide a clear example of how a basic circuit supports flexible sensory computation.

Flight-induced compass representation in the monarch butterfly heading network

For navigation, animals use a robust internal compass. Compass navigation is crucial for long-distance migrating animals like monarch butterflies, which use the sun to navigate over 4,000 km to their overwintering sites every fall. Sun-compass neurons of the central complex have only been recorded in immobile butterflies, and experimental evidence for encoding the animal's heading in these neurons is still missing. Although the activity of central-complex neurons exhibits a locomotor-dependent modulation in many insects, the function of such modulations remains unexplored. Here, we developed tetrode recordings from tethered flying monarch butterflies to reveal how flight modulates heading representation. We found that, during flight, heading-direction neurons change their tuning, transforming the central-complex network to function as a global compass. This compass is characterized by the dominance of processing steering feedback and allows for robust heading representation even under unreliable visual scenarios, an ideal strategy for maintaining a migratory heading over enormous distances.

Nonlinear, neuronal adaptation in insect vision models improves target discrimination within repetitively moving backgrounds

Neurons which respond selectively to small moving targets, even against a cluttered background, have been identified in several insect species. To investigate what underlies these robust and highly selective responses, researchers have probed the neuronal circuitry in target-detecting, visual pathways. Observations in flies reveal nonlinear adaptation over time, composed of a fast onset and gradual decay. This adaptive processing is seen in both of the independent, parallel pathways encoding either luminance increments (ON channel) or decrements (OFF channel). The functional significance of this adaptive phenomenon has not been determined from physiological studies, though the asymmetrical time course suggests a role in suppressing responses to repetitive stimuli. We tested this possibility by comparing an implementation of fast adaptation against alternatives, using a model of insect 'elementary small target motion detectors'. We conducted target-detecting simulations on various natural backgrounds, that were shifted via several movement profiles (and target velocities). Using performance metrics, we confirmed that the fast adaptation observed in neuronal systems enhances target detection against a repetitively moving background. Such background movement would be encountered via natural ego-motion as the insect travels through the world. These findings show that this form of nonlinear, fast-adaptation (suitably implementable via cellular biophysics) plays a role analogous to background subtraction techniques in conventional computer vision.

Fast tuning of posture control by visual feedback underlies gaze stabilization in walking Drosophila

Locomotion requires a balance between mechanical stability and movement flexibility to achieve behavioral goals despite noisy neuromuscular systems, but rarely is it considered how this balance is orchestrated. We combined virtual reality tools with quantitative analysis of behavior to examine how Drosophila uses self-generated visual information (reafferent visual feedback) to control gaze during exploratory walking. We found that flies execute distinct motor programs coordinated across the body to maximize gaze stability. However, the presence of inherent variability in leg placement relative to the body jeopardizes fine control of gaze due to posture-stabilizing adjustments that lead to unintended changes in course direction. Surprisingly, whereas visual feedback is dispensable for head-body coordination, we found that self-generated visual signals tune postural reflexes to rapidly prevent turns rather than to promote compensatory rotations, a long-standing idea for visually guided course control. Together, these findings support a model in which visual feedback orchestrates the interplay between posture and gaze stability in a manner that is both goal dependent and motor-context specific.

The physiological basis for contrast opponency in motion computation in Drosophila

In Drosophila, direction-selective neurons implement a mechanism of motion computation similar to cortical neurons, using contrast-opponent receptive fields with ON and OFF subfields. It is not clear how the presynaptic circuitry of direction-selective neurons in the OFF pathway supports this computation if all major inputs are OFF-rectified neurons. Here, we reveal the biological substrate for motion computation in the OFF pathway. Three interneurons, Tm2, Tm9 and CT1, provide information about ON stimuli to the OFF direction-selective neuron T5 across its receptive field, supporting a contrast-opponent receptive field organization. Consistent with its prominent role in motion detection, variability in Tm9 receptive field properties transfers to T5, and calcium decrements in Tm9 in response to ON stimuli persist across behavioral states, while spatial tuning is sharpened by active behavior. Together, our work shows how a key neuronal computation is implemented by its constituent neuronal circuit elements to ensure direction selectivity.

Movements, embodiment and the emergence of decisions. Insights from insect navigation

We readily infer that animals make decisions, but what this implies is usually not clearly defined. The notion of 'decision-making' ultimately stems from human introspection, and is thus loaded with anthropomorphic assumptions. Notably, the decision is made internally, is based on information, and precedes the goal directed behaviour. Also, making a decision implies that 'something' did it, thus hints at the presence of a cognitive mind, whose existence is independent of the decision itself. This view may convey some truth, but here I take the opposite stance. Using examples from research in insect navigation, this essay highlights how apparent decisions can emerge without a brain, how actions can precede information or how sophisticated goal directed behaviours can be implemented without neural decisions. This perspective requires us to shake off the idea that behaviour is a consequence of the brain; and embrace the concept that movements arise from - as much as participate in - distributed interactions between various computational centres - including the body - that reverberate in closed-loop with the environment. From this perspective we may start to picture how a cognitive mind can be the consequence, rather than the cause, of such neural and body movements.

Sensitivity to expression levels underlies differential dominance of a putative null allele of the Drosophila tβh gene in behavioral phenotypes

The biogenic amine octopamine (OA) and its precursor tyramine (TA) are involved in controlling a plethora of different physiological and behavioral processes. The tyramine-β-hydroxylase (tβh) gene encodes the enzyme catalyzing the last synthesis step from TA to OA. Here, we report differential dominance (from recessive to overdominant) of the putative null tβh^nM18 allele in 2 behavioral measures in Buridan’s paradigm (walking speed and stripe deviation) and in proboscis extension (sugar sensitivity) in the fruit fly Drosophila melanogaster. The behavioral analysis of transgenic tβh expression experiments in mutant and wild-type flies as well as of OA and TA receptor mutants revealed a complex interaction of both aminergic systems. Our analysis suggests that the different neuronal networks responsible for the 3 phenotypes show differential sensitivity to tβh gene expression levels. The evidence suggests that this sensitivity is brought about by a TA/OA opponent system modulating the involved neuronal circuits. This conclusion has important implications for standard transgenic techniques commonly used in functional genetics.

Differential dominance occurs when genes associated with several phenotypes (pleiotropic genes) show different modes of inheritance (e.g., recessive, dominant or overdominant) depending on the phenotype. This study reveals that differential sensitivity to gene expression levels can mediate differential dominance, which can be a significant challenge for standard transgenic techniques commonly used to elucidate gene function.

Visuo-Motor Feedback Modulates Neural Activities in the Medulla of the Honeybee, Apis mellifera

Behavioral and internal-state modulation of sensory processing has been described in several organisms. In insects, visual neurons in the optic lobe are modulated by locomotion, but the degree to which visual-motor feedback modulates these neurons remains unclear. Moreover, it also remains unknown whether self-generated and externally generated visual motion are processed differently. Here, we implemented a virtual reality system that allowed fine-scale control over visual stimulation in relation to animal motion, in combination with multichannel recording of neural activity in the medulla of a female honeybee (Apis mellifera). We found that this activity was modulated by locomotion, although, in most cases, only when the bee had behavioral control over the visual stimulus (i.e., in a closed-loop system). Moreover, closed-loop control modulated a third of the recorded neurons, and the application of octopamine (OA) evoked similar changes in neural responses that were observed in a closed loop. Additionally, in a subset of modulated neurons, fixation on a visual stimulus was preceded by an increase in firing rate. To further explore the relationship between neuromodulation and adaptive control of the visual environment of the bee, we modified motor gain sensitivity while locally injecting an OA receptor antagonist into the medulla. Whereas female honeybees were tuned to a motor gain of -2 to 2 (between the heading of the bee and its visual feedback), local disruption of the OA pathway in the medulla abolished this tuning, resulting in similar low levels of response across levels of motor gain. Our results show that behavioral control modulates neural activity in the medulla and ultimately impacts behavior.SIGNIFICANCE STATEMENT When moving, an animal generates the motion of the visual scene over its retina. We asked whether self-generated and externally generated optic flow are processed differently in the insect medulla. Our results show that closed-loop control of the visual stimulus modulates neural activity as early as the medulla and ultimately impacts behavior. Moreover, blocking octopaminergic modulation further disrupted object-tracking responses. Our results suggest that the medulla is an important site for context-dependent processing of visual information and that placing the animal in a closed-loop environment may be essential to understanding its visual cognition and processing.

The lobula plate is exclusive to insects

Just one superorder of insects is known to possess a neuronal network that mediates extremely rapid reactions in flight in response to changes in optic flow. Research on the identity and functional organization of this network has over the course of almost half a century focused exclusively on the order Diptera, a member of the approximately 300-million-year-old clade Holometabola defined by its mode of development. However, it has been broadly claimed that the pivotal neuropil containing the network, the lobula plate, originated in the Cambrian before the divergence of Hexapoda and Crustacea from a mandibulate ancestor. This essay defines the traits that designate the lobula plate and argues against a homologue in Crustacea. It proposes that the origin of the lobula plate is relatively recent and may relate to the origin of flight.

Overground Walking Decreases Alpha Activity and Entrains Eye Movements in Humans

Experiments in animal models have shown that running increases neuronal activity in early visual areas in light as well as in darkness. This suggests that visual processing is influenced by locomotion independent of visual input. Combining mobile electroencephalography, motion- and eye-tracking, we investigated the influence of overground free walking on cortical alpha activity (~10 Hz) and eye movements in healthy humans. Alpha activity has been considered a valuable marker of inhibition of sensory processing and shown to negatively correlate with neuronal firing rates. We found that walking led to a decrease in alpha activity over occipital cortex compared to standing. This decrease was present during walking in darkness as well as during light. Importantly, eye movements could not explain the change in alpha activity. Nevertheless, we found that walking and eye related movements were linked. While the blink rate increased with increasing walking speed independent of light or darkness, saccade rate was only significantly linked to walking speed in the light. Pupil size, on the other hand, was larger during darkness than during light, but only showed a modulation by walking in darkness. Analyzing the effect of walking with respect to the stride cycle, we further found that blinks and saccades preferentially occurred during the double support phase of walking. Alpha power, as shown previously, was lower during the swing phase than during the double support phase. We however could exclude the possibility that the alpha modulation was introduced by a walking movement induced change in electrode impedance. Overall, our work indicates that the human visual system is influenced by the current locomotion state of the body. This influence affects eye movement pattern as well as neuronal activity in sensory areas and might form part of an implicit strategy to optimally extract sensory information during locomotion.