Bumblebees socially learn behaviour too complex to innovate alone.

Culture refers to behaviours that are socially learned and persist within a population over time. Increasing evidence suggests that animal culture can, like human culture, be cumulative: characterized by sequential innovations that build on previous ones1. However, human cumulative culture involves behaviours so complex that they lie beyond the capacity of any individual to independently discover during their lifetime1-3. To our knowledge, no study has so far demonstrated this phenomenon in an invertebrate. Here we show that bumblebees can learn from trained demonstrator bees to open a novel two-step puzzle box to obtain food rewards, even though they fail to do so independently. Experimenters were unable to train demonstrator bees to perform the unrewarded first step without providing a temporary reward linked to this action, which was removed during later stages of training. However, a third of naive observer bees learned to open the two-step box from these demonstrators, without ever being rewarded after the first step. This suggests that social learning might permit the acquisition of behaviours too complex to 're-innovate' through individual learning. Furthermore, naive bees failed to open the box despite extended exposure for up to 24 days. This finding challenges a common opinion in the field: that the capacity to socially learn behaviours that cannot be innovated through individual trial and error is unique to humans.

Binocular mirror-symmetric microsaccadic sampling enables Drosophila hyperacute 3D vision.

SignificanceTo move efficiently, animals must continuously work out their x,y,z positions with respect to real-world objects, and many animals have a pair of eyes to achieve this. How photoreceptors actively sample the eyes' optical image disparity is not understood because this fundamental information-limiting step has not been investigated in vivo over the eyes' whole sampling matrix. This integrative multiscale study will advance our current understanding of stereopsis from static image disparity comparison to a morphodynamic active sampling theory. It shows how photomechanical photoreceptor microsaccades enable Drosophila superresolution three-dimensional vision and proposes neural computations for accurately predicting these flies' depth-perception dynamics, limits, and visual behaviors.

Ca2+-Activated K+ Channels Reduce Network Excitability, Improving Adaptability and Energetics for Transmitting and Perceiving Sensory Information.

Ca2+-activated K+ channels (BK and SK) are ubiquitous in synaptic circuits, but their role in network adaptation and sensory perception remains largely unknown. Using electrophysiological and behavioral assays and biophysical modeling, we discover how visual information transfer in mutants lacking the BK channel (dSlo- ), SK channel (dSK- ), or both (dSK- ;; dSlo- ) is shaped in the female fruit fly (Drosophila melanogaster) R1-R6 photoreceptor-LMC circuits (R-LMC-R system) through synaptic feedforward-feedback interactions and reduced R1-R6 Shaker and Shab K+ conductances. This homeostatic compensation is specific for each mutant, leading to distinctive adaptive dynamics. We show how these dynamics inescapably increase the energy cost of information and promote the mutants' distorted motion perception, determining the true price and limits of chronic homeostatic compensation in an in vivo genetic animal model. These results reveal why Ca2+-activated K+ channels reduce network excitability (energetics), improving neural adaptability for transmitting and perceiving sensory information.SIGNIFICANCE STATEMENT In this study, we directly link in vivo and ex vivo experiments with detailed stochastically operating biophysical models to extract new mechanistic knowledge of how Drosophila photoreceptor-interneuron-photoreceptor (R-LMC-R) circuitry homeostatically retains its information sampling and transmission capacity against chronic perturbations in its ion-channel composition, and what is the cost of this compensation and its impact on optomotor behavior. We anticipate that this novel approach will provide a useful template to other model organisms and computational neuroscience, in general, in dissecting fundamental mechanisms of homeostatic compensation and deepening our understanding of how biological neural networks work.

A biomimetic fly photoreceptor model elucidates how stochastic adaptive quantal sampling provides a large dynamic range.

Light intensities (photons s-1  µm-2 ) in a natural scene vary over several orders of magnitude from shady woods to direct sunlight. A major challenge facing the visual system is how to map such a large dynamic input range into its limited output range, so that a signal is neither buried in noise in darkness nor saturated in brightness. A fly photoreceptor has achieved such a large dynamic range; it can encode intensity changes from single to billions of photons, outperforming man-made light sensors. This performance requires powerful light adaptation, the neural implementation of which has only become clear recently. A computational fly photoreceptor model, which mimics the real phototransduction processes, has elucidated how light adaptation happens dynamically through stochastic adaptive quantal information sampling. A Drosophila R1-R6 photoreceptor's light sensor, the rhabdomere, has 30,000 microvilli, each of which stochastically samples incoming photons. Each microvillus employs a full G-protein-coupled receptor signalling pathway to adaptively transduce photons into quantum bumps (QBs, or samples). QBs then sum the macroscopic photoreceptor responses, governed by four quantal sampling factors (limitations): (i) the number of photon sampling units in the cell structure (microvilli), (ii) sample size (QB waveform), (iii) latency distribution (time delay between photon arrival and emergence of a QB), and (iv) refractory period distribution (time for a microvillus to recover after a QB). Here, we review how these factors jointly orchestrate light adaptation over a large dynamic range.

How a fly photoreceptor samples light information in time.

A photoreceptor's information capture is constrained by the structure and function of its light-sensitive parts. Specifically, in a fly photoreceptor, this limit is set by the number of its photon sampling units (microvilli), constituting its light sensor (the rhabdomere), and the speed and recoverability of their phototransduction reactions. In this review, using an insightful constructionist viewpoint of a fly photoreceptor being an 'imperfect' photon counting machine, we explain how these constraints give rise to adaptive quantal information sampling in time, which maximises information in responses to salient light changes while antialiasing visual signals. Interestingly, such sampling innately determines also why photoreceptors extract more information, and more economically, from naturalistic light contrast changes than Gaussian white-noise stimuli, and we explicate why this is so. Our main message is that stochasticity in quantal information sampling is less noise and more processing, representing an 'evolutionary adaptation' to generate a reliable neural estimate of the variable world.

Speed and sensitivity of phototransduction in Drosophila depend on degree of saturation of membrane phospholipids.

Drosophila phototransduction is mediated via a G-protein-coupled PLC cascade. Recent evidence, including the demonstration that light evokes rapid contractions of the photoreceptors, suggested that the light-sensitive channels (TRP and TRPL) may be mechanically gated, together with protons released by PLC-mediated PIP2 hydrolysis. If mechanical gating is involved we predicted that the response to light should be influenced by altering the physical properties of the membrane. To achieve this, we used diet to manipulate the degree of saturation of membrane phospholipids. In flies reared on a yeast diet, lacking polyunsaturated fatty acids (PUFAs), mass spectrometry showed that the proportion of polyunsaturated phospholipids was sevenfold reduced (from 38 to ∼5%) but rescued by adding a single species of PUFA (linolenic or linoleic acid) to the diet. Photoreceptors from yeast-reared flies showed a 2- to 3-fold increase in latency and time to peak of the light response, without affecting quantum bump waveform. In the absence of Ca(2+) influx or in trp mutants expressing only TRPL channels, sensitivity to light was reduced up to ∼10-fold by the yeast diet, and essentially abolished in hypomorphic G-protein mutants (Gαq). PLC activity appeared little affected by the yeast diet; however, light-induced contractions measured by atomic force microscopy or the activation of ectopic mechanosensitive gramicidin channels were also slowed ∼2-fold. The results are consistent with mechanosensitive gating and provide a striking example of how dietary fatty acids can profoundly influence sensory performance in a classical G-protein-coupled signaling cascade.

Refractory sampling links efficiency and costs of sensory encoding to stimulus statistics.

Sensory neurons integrate information about the world, adapting their sampling to its changes. However, little is understood mechanistically how this primary encoding process, which ultimately limits perception, depends upon stimulus statistics. Here, we analyze this open question systematically by using intracellular recordings from fly (Drosophila melanogaster and Coenosia attenuata) photoreceptors and corresponding stochastic simulations from biophysically realistic photoreceptor models. Recordings show that photoreceptors can sample more information from naturalistic light intensity time series (NS) than from Gaussian white-noise (GWN), shuffled-NS or Gaussian-1/f stimuli; integrating larger responses with higher signal-to-noise ratio and encoding efficiency to large bursty contrast changes. Simulations reveal how a photoreceptor's information capture depends critically upon the stochastic refractoriness of its 30,000 sampling units (microvilli). In daylight, refractoriness sacrifices sensitivity to enhance intensity changes in neural image representations, with more and faster microvilli improving encoding. But for GWN and other stimuli, which lack longer dark contrasts of real-world intensity changes that reduce microvilli refractoriness, these performance gains are submaximal and energetically costly. These results provide mechanistic reasons why information sampling is more efficient for natural/naturalistic stimulation and novel insight into the operation, design, and evolution of signaling and code in sensory neurons.

Perceptual color map in macaque visual area V4.

Colors distinguishable with trichromatic vision can be defined by a 3D color space, such as red-green-blue or hue-saturation-lightness (HSL) space, but it remains unclear how the cortex represents colors along these dimensions. Using intrinsic optical imaging and electrophysiology, and systematically choosing color stimuli from HSL coordinates, we examined how perceptual colors are mapped in visual area V4 in behaving macaques. We show that any color activates 1-4 separate cortical patches within "globs," millimeter-sized color-preferring modules. Most patches belong to different hue or lightness clusters, in which sequential representations follow the color order in HSL space. Some patches overlap greatly with those of related colors, forming stacks, possibly representing invariable features, whereas few seem positioned irregularly. However, for any color, saturation increases the activity of all its patches. These results reveal how the color map in V4 is organized along the framework of the perceptual HSL space, whereupon different multipatch activity patterns represent different colors. We propose that such distributed and combinatorial representations may expand the encodable color space of small cortical maps and facilitate binding color information to other image features.

Compound eyes and retinal information processing in miniature dipteran species match their specific ecological demands.

The compound eye of insects imposes a tradeoff between resolution and sensitivity, which should exacerbate with diminishing eye size. Tiny lenses are thought to deliver poor acuity because of diffraction; nevertheless, miniature insects have visual systems that allow a myriad of lifestyles. Here, we investigate whether size constraints result in an archetypal eye design shared between miniature dipterans by comparing the visual performance of the fruit fly Drosophila and the killer fly Coenosia. These closely related species have neural superposition eyes and similar body lengths (3 to 4 mm), but Coenosia is a diurnal aerial predator, whereas slow-flying Drosophila is most active at dawn and dusk. Using in vivo intracellular recordings and EM, we report unique adaptations in the form and function of their photoreceptors that are reflective of their distinct lifestyles. We find that although these species have similar lenses and optical properties, Coenosia photoreceptors have three- to fourfold higher spatial resolution and rate of information transfer than Drosophila. The higher performance in Coenosia mostly results from dramatically diminished light sensors, or rhabdomeres, which reduce pixel size and optical cross-talk between photoreceptors and incorporate accelerated phototransduction reactions. Furthermore, we identify local specializations in the Coenosia eye, consistent with an acute zone and its predatory lifestyle. These results demonstrate how the flexible architecture of miniature compound eyes can evolve to match information processing with ecological demands.

The Drosophila SK channel (dSK) contributes to photoreceptor performance by mediating sensitivity control at the first visual network.

The contribution of the SK (small-conductance calcium-activated potassium) channel to neuronal functions in complex circuits underlying sensory processing and behavior is largely unknown in the absence of suitable animal models. Here, we generated a Drosophila line that lacks the single highly conserved SK gene in its genome (dSK). In R1-R6 photoreceptors, dSK encodes a slow Ca²âº-activated K(+) current similar to its mammalian counterparts. Compared with wild-type, dSK(-) photoreceptors and interneurons showed accelerated oscillatory responses and adaptation. These enhanced kinetics were accompanied with more depolarized dSK(-) photoreceptors axons, assigning a role for dSK in network gain control during light-to-dark transitions. However, compensatory network adaptation, through increasing activity between synaptic neighbors, overcame many detriments of missing dSK current enabling dSK(-) photoreceptors to maintain normal information transfer rates to naturalistic stimuli. While demonstrating important functional roles for dSK channel in the visual circuitry, these results also clarify how homeostatically balanced network functions can compensate missing or faulty ion channels.

High-speed imaging of light-induced photoreceptor microsaccades in compound eyes.

Inside compound eyes, photoreceptors contract to light changes, sharpening retinal images of the moving world in time. Current methods to measure these so-called photoreceptor microsaccades in living insects are spatially limited and technically challenging. Here, we present goniometric high-speed deep pseudopupil (GHS-DPP) microscopy to assess how the rhabdomeric insect photoreceptors and their microsaccades are organised across the compound eyes. This method enables non-invasive rhabdomere orientation mapping, whilst their microsaccades can be locally light-activated, revealing the eyes' underlying active sampling motifs. By comparing the microsaccades in wild-type Drosophila's open rhabdom eyes to spam-mutant eyes, reverted to an ancestral fused rhabdom state, and honeybee's fused rhabdom eyes, we show how different eye types sample light information. These results show different ways compound eyes initiate the conversion of spatial light patterns in the environment into temporal neural signals and highlight how this active sampling can evolve with insects' visual needs.

Multiscale 'whole-cell' models to study neural information processing - New insights from fly photoreceptor studies.

Understanding a neuron's input-output relationship is a longstanding challenge. Arguably, these signalling dynamics can be better understood if studied at three levels of analysis: computational, algorithmic and implementational (Marr, 1982). But it is difficult to integrate such analyses into a single platform that can realistically simulate neural information processing. Multiscale dynamical "whole-cell" modelling, a recent systems biology approach, makes this possible. Dynamical "whole-cell" models are computational models that aim to account for the integrated function of numerous genes or molecules to behave like virtual cells in silico. However, because constructing such models is laborious, only a couple of examples have emerged since the first one, built for Mycoplasma genitalium bacterium, was reported in 2012. Here, we review dynamic "whole-cell" neuron models for fly photoreceptors and how these have been used to study neural information processing. Specifically, we review how the models have helped uncover the mechanisms and evolutionary rules of quantal light information sampling and integration, which underlie light adaptation and further improve our understanding of insect vision.

Overexpressing temperature-sensitive dynamin decelerates phototransduction and bundles microtubules in Drosophila photoreceptors.

shibire(ts1), a temperature-sensitive mutation of the Drosophila gene encoding a Dynamin orthologue, blocks vesicle endocytosis and thus synaptic transmission, at elevated, or restrictive temperatures. By targeted Gal4 expression, UAS-shibire(ts1) has been used to dissect neuronal circuits. We investigated the effects of UAS-shibire(ts1) overexpression in Drosophila photoreceptors at permissive (19 degrees C) and restrictive (31 degrees C) temperatures. At 19 degrees C, overexpression of UAS-shi(ts1) causes decelerated phototransduction and reduced neurotransmitter release. This phenotype is exacerbated with dark adaptation, age and in white mutants. Photoreceptors overexpressing UAS-shibire(ts1) contain terminals with widespread vacuolated mitochondria, reduced numbers of vesicles and bundled microtubules. Immuno-electron microscopy reveals that the latter are dynamin coated. Further, the microtubule phenotype is not restricted to photoreceptors, as UAS-shibire(ts1) overexpression in lamina cells also bundles microtubules. We conclude that dynamin has multiple functions that are interrupted by UAS-shibire(ts1) overexpression in Drosophila photoreceptors, destabilizing their neural communication irreversibly at previously reported permissive temperatures.

Distinct roles for two histamine receptors (hclA and hclB) at the Drosophila photoreceptor synapse.

Histamine (HA) is the photoreceptor neurotransmitter in arthropods, directly gating chloride channels on large monopolar cells (LMCs), postsynaptic to photoreceptors in the lamina. Two histamine-gated channel genes that could contribute to this channel in Drosophila are hclA (also known as ort) and hclB (also known as hisCl1), both encoding novel members of the Cys-loop receptor superfamily. Drosophila S2 cells transfected with these genes expressed both homomeric and heteromeric histamine-gated chloride channels. The electrophysiological properties of these channels were compared with those from isolated Drosophila LMCs. HCLA homomers had nearly identical HA sensitivity to the native receptors (EC(50) = 25 microM). Single-channel analysis revealed further close similarity in terms of single-channel kinetics and subconductance states ( approximately 25, 40, and 60 pS, the latter strongly voltage dependent). In contrast, HCLB homomers and heteromeric receptors were more sensitive to HA (EC(50) = 14 and 1.2 microM, respectively), with much smaller single-channel conductances ( approximately 4 pS). Null mutations of hclA (ort(US6096)) abolished the synaptic transients in the electroretinograms (ERGs). Surprisingly, the ERG "on" transients in hclB mutants transients were approximately twofold enhanced, whereas intracellular recordings from their LMCs revealed altered responses with slower kinetics. However, HCLB expression within the lamina, assessed by both a GFP (green fluorescent protein) reporter gene strategy and mRNA tagging, was exclusively localized to the glia cells, whereas HCLA expression was confirmed in the LMCs. Our results suggest that the native receptor at the LMC synapse is an HCLA homomer, whereas HCLB signaling via the lamina glia plays a previously unrecognized role in shaping the LMC postsynaptic response.

Normal mitochondrial dynamics requires rhomboid-7 and affects Drosophila lifespan and neuronal function.

In addition to being energy generators, mitochondria control many cellular processes including apoptosis. They are dynamic organelles, and the machinery of membrane fusion and fission is emerging as a key regulator of mitochondrial biology. We have recently identified a novel and conserved mitochondrial rhomboid intramembrane protease that controls membrane fusion in Saccharomyces cerevisiae by processing the dynamin-like GTPase, Mgm1, thereby releasing it from the membrane. The genetics of mitochondrial membrane dynamics has until now focused primarily on yeast. Here we show that in Drosophila, the mitochondrial rhomboid (Rhomboid-7) is required for mitochondrial fusion during fly spermatogenesis and muscle maturation, both tissues with unusual mitochondrial dynamics. We also find that mutations in Drosophila optic atrophy 1-like (Opa1-like), the ortholog of yeast mgm1, display similar phenotypes, suggesting a shared role for Rhomboid-7 and Opa1-like, as with their yeast orthologs. Loss of human OPA1 leads to dominant optic atrophy, a mitochondrial disease leading to childhood onset blindness. rhomboid-7 mutant flies have severe neurological defects, evidenced by compromised signaling across the first visual synapse, as well as light-induced neurodegeneration of photoreceptors that resembles the human disease. rhomboid-7 mutant flies also have a greatly reduced lifespan.

Robustness of neural coding in Drosophila photoreceptors in the absence of slow delayed rectifier K+ channels.

Determining the contribution of a single type of ion channel to information processing within a neuron requires not only knowledge of the properties of the channel but also understanding of its function within a complex system. We studied the contribution of slow delayed rectifier K+ channels to neural coding in Drosophila photoreceptors by combining genetic and electrophysiological approaches with biophysical modeling. We show that the Shab gene encodes the slow delayed rectifier K+ channel and identify a novel voltage-gated K+ conductance. Analysis of the in vivo recorded voltage responses together with their computer-simulated counterparts demonstrates that Shab channels in Drosophila photoreceptors attenuate the light-induced depolarization and prevent response saturation in bright light. We also show that reduction of the Shab conductance in mutant photoreceptors is accompanied by a proportional drop in their input resistance. This reduction in input resistance partially restores the signaling range, sensitivity, and dynamic coding of light intensities of Shab photoreceptors to those of the wild-type counterparts. However, loss of the Shab channels may affect both the energy efficiency of coding and the processing of natural stimuli. Our results highlight the role of different types of voltage-gated K+ channels in the performance of the photoreceptors and provide insight into functional robustness against the perturbation of specific ion channel composition.

Feedback network controls photoreceptor output at the layer of first visual synapses in Drosophila.

At the layer of first visual synapses, information from photoreceptors is processed and transmitted towards the brain. In fly compound eye, output from photoreceptors (R1-R6) that share the same visual field is pooled and transmitted via histaminergic synapses to two classes of interneuron, large monopolar cells (LMCs) and amacrine cells (ACs). The interneurons also feed back to photoreceptor terminals via numerous ligand-gated synapses, yet the significance of these connections has remained a mystery. We investigated the role of feedback synapses by comparing intracellular responses of photoreceptors and LMCs in wild-type Drosophila and in synaptic mutants, to light and current pulses and to naturalistic light stimuli. The recordings were further subjected to rigorous statistical and information-theoretical analysis. We show that the feedback synapses form a negative feedback loop that controls the speed and amplitude of photoreceptor responses and hence the quality of the transmitted signals. These results highlight the benefits of feedback synapses for neural information processing, and suggest that similar coding strategies could be used in other nervous systems.

Modeling elucidates how refractory period can provide profound nonlinear gain control to graded potential neurons.

Refractory period (RP) plays a central role in neural signaling. Because it limits an excitable membrane's recovery time from a previous excitation, it can restrict information transmission. Classically, RP means the recovery time from an action potential (spike), and its impact to encoding has been mostly studied in spiking neurons. However, many sensory neurons do not communicate with spikes but convey information by graded potential changes. In these systems, RP can arise as an intrinsic property of their quantal micro/nanodomain sampling events, as recently revealed for quantum bumps (single photon responses) in microvillar photoreceptors. Whilst RP is directly unobservable and hard to measure, masked by the graded macroscopic response that integrates numerous quantal events, modeling can uncover its role in encoding. Here, we investigate computationally how RP can affect encoding of graded neural responses. Simulations in a simple stochastic process model for a fly photoreceptor elucidate how RP can profoundly contribute to nonlinear gain control to achieve a large dynamic range.