The Drosophila visual system: From neural circuits to behavior

A Bio-Inspired Visual Neural Model for Robustly and Steadily Detecting Motion Directions of Translating Objects Against Variable Contrast in the Figure-Ground and Noise Interference

(1) Background: At present, the bio-inspired visual neural models have made significant achievements in detecting the motion direction of the translating object. Variable contrast in the figure-ground and environmental noise interference, however, have a strong influence on the existing model. The responses of the lobula plate tangential cell (LPTC) neurons of Drosophila are robust and stable in the face of variable contrast in the figure-ground and environmental noise interference, which provides an excellent paradigm for addressing these challenges. (2) Methods: To resolve these challenges, we propose a bio-inspired visual neural model, which consists of four stages. Firstly, the photoreceptors (R1-R6) are utilized to perceive the change in luminance. Secondly, the change in luminance is divided into parallel ON and OFF pathways based on the lamina monopolar cell (LMC), and the spatial denoising and the spatio-temporal lateral inhibition (LI) mechanisms can suppress environmental noise and improve motion boundaries, respectively. Thirdly, the non-linear instantaneous feedback mechanism in divisive contrast normalization is adopted to reduce local contrast sensitivity; further, the parallel ON and OFF contrast pathways are activated. Finally, the parallel motion and contrast pathways converge on the LPTC in the lobula complex. (3) Results: By comparing numerous experimental simulations with state-of-the-art (SotA) bio-inspired models, we can draw four conclusions. Firstly, the effectiveness of the contrast neural computation and the spatial denoising mechanism is verified by the ablation study. Secondly, this model can robustly detect the motion direction of the translating object against variable contrast in the figure-ground and environmental noise interference. Specifically, the average detection success rate of the proposed bio-inspired model under the pure and real-world complex noise datasets was increased by 5.38% and 5.30%. Thirdly, this model can effectively reduce the fluctuation in this model response against variable contrast in the figure-ground and environmental noise interference, which shows the stability of this model; specifically, the average inter-quartile range of the coefficient of variation in the proposed bio-inspired model under the pure and real-world complex noise datasets was reduced by 38.77% and 47.84%, respectively. The average decline ratio of the sum of the coefficient of variation in the proposed bio-inspired model under the pure and real-world complex noise datasets was 57.03% and 67.47%, respectively. Finally, the robustness and stability of this model are further verified by comparing other early visual pre-processing mechanisms and engineering denoising methods. (4) Conclusions: This model can robustly and steadily detect the motion direction of the translating object under variable contrast in the figure-ground and environmental noise interference.

X-Tracker: Automated Analysis of Xenopus Tadpole Visual Avoidance Behavior

Xenopus laevis tadpoles exhibit an avoidance behavior when they encounter a moving visual stimulus. A visual avoidance event occurs when a moving object approaches the eye of a free-swimming animal at an approximately 90-degree angle and the animal turns in response to the encounter. Analysis of this behavior requires tracking both the free-swimming animal and the moving visual stimulus both prior to and after the encounter. Previous automated tracking software does not discriminate the moving animal from the moving stimulus, requiring time-consuming manual analysis. Here we present X-Tracker, an automated behavior tracking code that can detect and discriminate moving visual stimuli and free-swimming animals and score encounters and avoidance events. X-Tracker is as accurate as human analysis without the human time commitment. We also present software improvements to our previous visual stimulus presentation and image capture that optimize videos for automated analysis, and hardware improvements that increase the number of animal-stimulus encounters. X-Tracker is a high throughput, unbiased, and significant time-saving analysis system that will greatly facilitate visual avoidance behavior analysis of Xenopus laevis tadpoles, and potentially other free-swimming organisms. The tool is available at https://github.com/ClineLab/Tadpole-Behavior-Automation.

A single photoreceptor splits perception and entrainment by cotransmission

Vision enables both image-forming perception, driven by a contrast-based pathway, and unconscious non-image-forming circadian photoentrainment, driven by an irradiance-based pathway1,2. Although two distinct photoreceptor populations are specialized for each visual task3-6, image-forming photoreceptors can additionally contribute to photoentrainment of the circadian clock in different species7-15. However, it is unknown how the image-forming photoreceptor pathway can functionally implement the segregation of irradiance signals required for circadian photoentrainment from contrast signals required for image perception. Here we report that the Drosophila R8 photoreceptor separates image-forming and irradiance signals by co-transmitting two neurotransmitters, histamine and acetylcholine. This segregation is further established postsynaptically by histamine-receptor-expressing unicolumnar retinotopic neurons and acetylcholine-receptor-expressing multicolumnar integration neurons. The acetylcholine transmission from R8 photoreceptors is sustained by an autocrine negative feedback of the cotransmitted histamine during the light phase of light-dark cycles. At the behavioural level, elimination of histamine and acetylcholine transmission impairs R8-driven motion detection and circadian photoentrainment, respectively. Thus, a single type of photoreceptor can achieve the dichotomy of visual perception and circadian photoentrainment as early as the first visual synapses, revealing a simple yet robust mechanism to segregate and translate distinct sensory features into different animal behaviours.

Organization of an Ascending Circuit that Conveys Flight Motor State

Natural behaviors are a coordinated symphony of motor acts which drive self-induced or reafferent sensory activation. Single sensors only signal presence and magnitude of a sensory cue; they cannot disambiguate exafferent (externally-induced) from reafferent sources. Nevertheless, animals readily differentiate between these sources of sensory signals to make appropriate decisions and initiate adaptive behavioral outcomes. This is mediated by predictive motor signaling mechanisms, which emanate from motor control pathways to sensory processing pathways, but how predictive motor signaling circuits function at the cellular and synaptic level is poorly understood. We use a variety of techniques, including connectomics from both male and female electron microscopy volumes, transcriptomics, neuroanatomical, physiological and behavioral approaches to resolve the network architecture of two pairs of ascending histaminergic neurons (AHNs), which putatively provide predictive motor signals to several sensory and motor neuropil. Both AHN pairs receive input primarily from an overlapping population of descending neurons, many of which drive wing motor output. The two AHN pairs target almost exclusively non-overlapping downstream neural networks including those that process visual, auditory and mechanosensory information as well as networks coordinating wing, haltere, and leg motor output. These results support the conclusion that the AHN pairs multi-task, integrating a large amount of common input, then tile their output in the brain, providing predictive motor signals to non-overlapping sensory networks affecting motor control both directly and indirectly.

The Blimp-1 transcription factor acts in non-neuronal cells to regulate terminal differentiation of the Drosophila eye

The formation of a functional organ such as the eye requires specification of the correct cell types and their terminal differentiation into cells with the appropriate morphologies and functions. Here, we show that the zinc-finger transcription factor Blimp-1 acts in secondary and tertiary pigment cells in the Drosophila retina to promote the formation of a bi-convex corneal lens with normal refractive power, and in cone cells to enable complete extension of the photoreceptor rhabdomeres. Blimp-1 expression depends on the hormone ecdysone, and loss of ecdysone signaling causes similar differentiation defects. Timely termination of Blimp-1 expression is also important, as its overexpression in the eye has deleterious effects. Our transcriptomic analysis revealed that Blimp-1 regulates the expression of many structural and secreted proteins in the retina. Blimp-1 may function in part by repressing another transcription factor; Slow border cells is highly upregulated in the absence of Blimp-1, and its overexpression reproduces many of the effects of removing Blimp-1. This work provides insight into the transcriptional networks and cellular interactions that produce the structures necessary for visual function.

Multimodal Information Processing and Associative Learning in the Insect Brain

Simple Summary

Insect behaviors are a great indicator of evolution and provide useful information about the complexity of organisms. The realistic sensory scene of an environment is complex and replete with multisensory inputs, making the study of sensory integration that leads to behavior highly relevant. We summarize the recent findings on multimodal sensory integration and the behaviors that originate from them in our review.

Abstract

The study of sensory systems in insects has a long-spanning history of almost an entire century. Olfaction, vision, and gustation are thoroughly researched in several robust insect models and new discoveries are made every day on the more elusive thermo- and mechano-sensory systems. Few specialized senses such as hygro- and magneto-reception are also identified in some insects. In light of recent advancements in the scientific investigation of insect behavior, it is not only important to study sensory modalities individually, but also as a combination of multimodal inputs. This is of particular significance, as a combinatorial approach to study sensory behaviors mimics the real-time environment of an insect with a wide spectrum of information available to it. As a fascinating field that is recently gaining new insight, multimodal integration in insects serves as a fundamental basis to understand complex insect behaviors including, but not limited to navigation, foraging, learning, and memory. In this review, we have summarized various studies that investigated sensory integration across modalities, with emphasis on three insect models (honeybees, ants and flies), their behaviors, and the corresponding neuronal underpinnings.

Using Flies to Understand Social Networks

Many animals live in groups and interact with each other, creating an organized collective structure. Social network analysis (SNA) is a statistical tool that aids in revealing and understanding the organized patterns of shared social connections between individuals in groups. Surprisingly, the application of SNA revealed that Drosophila melanogaster, previously considered a solitary organism, displays group dynamics and that the structure of group life is inherited. Although the number of studies investigating Drosophila social networks is currently limited, they address a wide array of questions that have only begun to capture the details of group level behavior in this insect. Here, we aim to review these studies, comparing their respective scopes and the methods used, to draw parallels between them and the broader body of knowledge available. For example, we highlight how despite methodological differences, there are similarities across studies investigating the effects of social isolation on social network dynamics. Finally, this review aims to generate hypotheses and predictions that inspire future research in the emerging field of Drosophila social networks.

Multi-regional circuits underlying visually guided decision-making in Drosophila

Visually guided decision-making requires integration of information from distributed brain areas, necessitating a brain-wide approach to examine its neural mechanisms. New tools in Drosophila melanogaster enable circuits spanning the brain to be charted with single cell-type resolution. Here, we highlight recent advances uncovering the computations and circuits that transform and integrate visual information across the brain to make behavioral choices. Visual information flows from the optic lobes to three primary central brain regions: a sensorimotor mapping area and two 'higher' centers for memory or spatial orientation. Rapid decision-making during predator evasion emerges from the spike timing dynamics in parallel sensorimotor cascades. Goal-directed decisions may occur through memory, navigation and valence processing in the central complex and mushroom bodies.

Cystathionine β-synthase Deficiency Impairs Vision in the Fruit Fly, Drosophila melanogaster

PURPOSE

Deficiency in Cystathionine β-synthase (CBS) leads to an abnormal accumulation of homocysteine and results in classical homocystinuria, a multi-systemic disorder that affects connective tissue, muscles, the central nervous system, and the eyes. However, the genetic players and mechanisms underlying vision alterations in patients with homocystinuria are little understood.

MATERIALS AND METHODS

The fruit fly, Drosophila melanogaster, is a useful system to investigate the genetic basis of several human diseases, but no study to date has used Drosophila as model of homocystinuria. Here, we use Drosophila genetic tools to down-regulate CBS expression and evaluate its behavioral response to light.

RESULTS

We show that CBS-deficient flies do not display the normal stereotypical behavior of attraction towards a luminous source, known as phototaxis. This behavior cannot be attributed to a motor or olfactory deficiency, but it is most likely related to a lower visual acuity. CBS-deficient flies are overall smaller, but smaller eyes do not explain their lack of phototactic response.

CONCLUSIONS

The vision phenotype of CBS knock-down flies is consistent with severe myopia in homocystinuria patients. We propose to use Drosophila as a model to investigate ocular manifestations underlying homocystinuria.

Third-Order Neurons in the Lateral Horn Enhance Bilateral Contrast of Odor Inputs Through Contralateral Inhibition in Drosophila

The survival and reproduction of Drosophila melanogaster depends heavily on its ability to determine the location of an odor source and either to move toward or away from it. Despite the very small spatial separation between the two antennae and the redundancy in sensory neuron projection to both sides of the brain, Drosophila can resolve the concentration gradient by comparing the signal strength between the two antennae. When an odor stimulates the antennae asymmetrically, ipsilateral projection neurons from the first olfactory center are more strongly excited compared to the contralateral ones. However, it remains elusive how higher-order neurons process such asymmetric or lateralized odor inputs. Here, we monitored and analyzed for the first time the activity patterns of a small cluster of third-order neurons (so-called ventrolateral protocerebrum neurons) to asymmetric olfactory stimulation using two-photon calcium imaging. Our data demonstrate that lateralized odors evoke distinct activation of these neurons in the left and right brain hemisphere as a result of contralateral inhibition. Moreover, using laser transection experiments we show that this contralateral inhibition is mediated by presynaptic neurons most likely located in the lateral horn. Finally, we propose that this inhibitory interaction between higher-order neurons facilitates odor lateralization and plays a crucial role in olfactory navigation behavior of Drosophila, a theory that needs to be experimentally addressed in future studies.

Challenges for theories of consciousness: seeing or knowing, the missing ingredient and how to deal with panpsychism

Significant progress has been made in the study of consciousness. Promising theories have been developed and a wealth of experimental data has been generated, both guiding us towards a better understanding of this complex phenomenon. However, new challenges have surfaced. Is visual consciousness about the seeing or the knowing that you see? Controversy about whether the conscious experience is better explained by theories that focus on phenomenal (P-consciousness) or cognitive aspects (A-consciousness) remains, and the debate seems to reach a stalemate. Can we ever resolve this? A further challenge is that many theories of consciousness seem to endorse high degrees of panpsychism-the notion that all beings or even lifeless objects have conscious experience. Should we accept this, or does it imply that these theories require further ingredients that would put a lower bound on beings or devices that have conscious experience? If so, what could these 'missing ingredients' be? These challenges are discussed, and potential solutions are offered.This article is part of the theme issue 'Perceptual consciousness and cognitive access'.

N-Cadherin Orchestrates Self-Organization of Neurons within a Columnar Unit in the Drosophila Medulla

Columnar structure is a basic unit of the brain, but the mechanism underlying its development remains largely unknown. The medulla, the largest ganglion of the Drosophila melanogaster visual center, provides a unique opportunity to reveal the mechanisms of 3D organization of the columns. In this study, using N-cadherin (Ncad) as a marker, we reveal the donut-like columnar structures along the 2D layer in the larval medulla that evolves to form three distinct layers in pupal development. Column formation is initiated by three core neurons, R8, R7, and Mi1, which establish distinct concentric domains within a column. We demonstrate that Ncad-dependent relative adhesiveness of the core columnar neurons regulates their relative location within a column along a 2D layer in the larval medulla according to the differential adhesion hypothesis. We also propose the presence of mutual interactions among the three layers during formation of the 3D structures of the medulla columns.SIGNIFICANCE STATEMENT The columnar structure is a basic unit of the brain, but its developmental mechanism remains unknown. The medulla, the largest ganglion of the fly visual center, provides a unique opportunity to reveal the mechanisms of 3D organization of the columns. We reveal that column formation is initiated by three core neurons that establish distinct concentric domains within a column. We demonstrate the in vivo evidence of N-cadherin-dependent differential adhesion among the core columnar neurons within a column along a 2D layer in the larval medulla. The 2D larval columns evolve to form three distinct layers in the pupal medulla. We propose the presence of mutual interactions among the three layers during formation of the 3D structures of the medulla columns.

Neurogenetic dissection of the Drosophila lateral horn reveals major outputs, diverse behavioural functions, and interactions with the mushroom body

Animals exhibit innate behaviours to a variety of sensory stimuli including olfactory cues. In Drosophila, one higher olfactory centre, the lateral horn (LH), is implicated in innate behaviour. However, our structural and functional understanding of the LH is scant, in large part due to a lack of sparse neurogenetic tools for this region. We generate a collection of split-GAL4 driver lines providing genetic access to 82 LH cell types. We use these to create an anatomical and neurotransmitter map of the LH and link this to EM connectomics data. We find ~30% of LH projections converge with outputs from the mushroom body, site of olfactory learning and memory. Using optogenetic activation, we identify LH cell types that drive changes in valence behavior or specific locomotor programs. In summary, we have generated a resource for manipulating and mapping LH neurons, providing new insights into the circuit basis of innate and learned olfactory behavior.

Implementing artificial neural networks through bionic construction

It is evident through biology research that, biological neural network could be implemented through two means: by congenital heredity, or by posteriority learning. However, traditionally, artificial neural network, especially the Deep learning Neural Networks (DNNs) are implemented only through exhaustive training and learning. Fixed structure is built, and then parameters are trained through huge amount of data. In this way, there are a lot of redundancies in the implemented artificial neural network. This redundancy not only requires more effort to train the network, but also costs more computing resources when used. In this paper, we proposed a bionic way to implement artificial neural network through construction rather than training and learning. The hierarchy of the neural network is designed according to analysis of the required functionality, and then module design is carried out to form each hierarchy. We choose the Drosophila’s visual neural network as a test case to verify our method’s validation. The results show that the bionic artificial neural network built through our method could work as a bionic compound eye, which can achieve the detection of the object and their movement, and the results are better on some properties, compared with the Drosophila’s biological compound eyes.

A Single-Cell Level and Connectome-Derived Computational Model of the Drosophila Brain

Computer simulations play an important role in testing hypotheses, integrating knowledge, and providing predictions of neural circuit functions. While considerable effort has been dedicated into simulating primate or rodent brains, the fruit fly (Drosophila melanogaster) is becoming a promising model animal in computational neuroscience for its small brain size, complex cognitive behavior, and abundancy of data available from genes to circuits. Moreover, several Drosophila connectome projects have generated a large number of neuronal images that account for a significant portion of the brain, making a systematic investigation of the whole brain circuit possible. Supported by FlyCircuit (http://www.flycircuit.tw), one of the largest Drosophila neuron image databases, we began a long-term project with the goal to construct a whole-brain spiking network model of the Drosophila brain. In this paper, we report the outcome of the first phase of the project. We developed the Flysim platform, which (1) identifies the polarity of each neuron arbor, (2) predicts connections between neurons, (3) translates morphology data from the database into physiology parameters for computational modeling, (4) reconstructs a brain-wide network model, which consists of 20,089 neurons and 1,044,020 synapses, and (5) performs computer simulations of the resting state. We compared the reconstructed brain network with a randomized brain network by shuffling the connections of each neuron. We found that the reconstructed brain can be easily stabilized by implementing synaptic short-term depression, while the randomized one exhibited seizure-like firing activity under the same treatment. Furthermore, the reconstructed Drosophila brain was structurally and dynamically more diverse than the randomized one and exhibited both Poisson-like and patterned firing activities. Despite being at its early stage of development, this single-cell level brain model allows us to study some of the fundamental properties of neural networks including network balance, critical behavior, long-term stability, and plasticity.

Genetic architecture of natural variation in visual senescence in Drosophila

Senescence, i.e., functional decline with age, is a major determinant of health span in a rapidly aging population, but the genetic basis of interindividual variation in senescence remains largely unknown. Visual decline and age-related eye disorders are common manifestations of senescence, but disentangling age-dependent visual decline in human populations is challenging due to inability to control genetic background and variation in histories of environmental exposures. We assessed the genetic basis of natural variation in visual senescence by measuring age-dependent decline in phototaxis using Drosophila melanogaster as a genetic model system. We quantified phototaxis at 1, 2, and 4 wk of age in the sequenced, inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP) and found an average decline in phototaxis with age. We observed significant genetic variation for phototaxis at each age and significant genetic variation in senescence of phototaxis that is only partly correlated with phototaxis. Genome-wide association analyses in the DGRP and a DGRP-derived outbred, advanced intercross population identified candidate genes and genetic networks associated with eye and nervous system development and function, including seven genes with human orthologs previously associated with eye diseases. Ninety percent of candidate genes were functionally validated with targeted RNAi-mediated suppression of gene expression. Absence of candidate genes previously implicated with longevity indicates physiological systems may undergo senescence independent of organismal life span. Furthermore, we show that genes that shape early developmental processes also contribute to senescence, demonstrating that senescence is part of a genetic continuum that acts throughout the life span.

From the Eye to the Brain: Development of the Drosophila Visual System

How stem cells produce the huge diversity of neurons that form the visual system, and how these cells are assembled in neural circuits are a critical question in developmental neurobiology. Investigations in Drosophila have led to the discovery of several basic principles of neural patterning. In this chapter, we provide an overview of the field by describing the development of the Drosophila visual system, from the embryo to the adult and from the gross anatomy to the cellular level. We then explore the general molecular mechanisms identified that might apply to other neural structures in flies or in vertebrates. Finally, we discuss the major challenges that remain to be addressed in the field.

NMDA-R inhibition affects cellular process formation in Tilapia melanocytes; a model for pigmented adrenergic neurons in process formation and retraction

Parkinson's disease has long been described to be a product of dopamine and (or) melanin loss in the substanstia nigra (SN). Although most studies have focused on dopaminergic neurons, it is important to consider the role of pigment cells in the etiology of the disease and to create an in vitro live cell model for studies involving pigmented adrenergic cells of the SN in Parkinsonism. The Melanocytes share specific features with the pigmented adrenergic neurons as both cells are pigmented, contain adrenergic receptors and have cellular processes. Although the melanocyte cellular processes are relatively short and observable only when stimulated appropriately by epinephrine and other factors or molecules. This study employs the manipulation of N-Methyl-D-Aspartate Receptor (NMDA-R), a major receptor in neuronal development, in the process formation pattern of the melanocyte in order to create a suitable model to depict cellular process elongation and shortening in pigmented adrenergic cells. NMDA-R is an important glutamate receptor implicated in neurogenesis, neuronal migration, maturation and cell death, thus we investigated the role of NMDA-R potentiation by glutamate/KCN and its inhibition by ketamine in the behavior of fish scale melanocytes in vitro. This is aimed at establishing the regulatory role of NMDA-R in this cell type (melanocytes isolated form Tilapia) in a similar manner to what is observable in the mammalian neurons. In vitro live cell culture was prepared in modified Ringer's solution following which the cells were treated as follows; Control, Glutamate, Ketamine, Glutamate + Ketamine, KCN + Ketamine and KCN. The culture was maintained for 10 min and the changes were captured in 3D-Time frame at 0, 5 and 10 min for the control and 5, 7 and 10 min for each of the treatment category. Glutamate treatment caused formation of short cellular processes localized directly on the cell body while ketamine treatment (inhibition of NMDA-R) facilitated elongation of secondary cellular processes (highly branched) from primary major processes (Less branched); co-incubation of glutamate and ketamine induced short and highly branched process formation. Cyanide toxicity induced degeneration and reduction of cell size while co-treatment of cyanide and ketamine gave changes similar to that observed in glutamate-ketamine co-incubation. NMDA-R is present in the melanocytes. Activation of the receptor reduced elongation process, while inhibition of the receptor facilitated cell process elongation and branching. This confirms that like pigmented adrenergic cells of the nervous system, this cell contains NMDA-R and this receptor also regulates cell process elongation. The study also showed that inhibition of NMDA-R in melanocytes gave opposite outcomes to the role of the receptor in developing neurons; a function that is protective in adult neurons.