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Borst, A.

Publications and source records attributed to Borst, A..

15 recordsLinked to original sources

Connectome-based biophysical modeling of a figure-ground discrimination circuit

Figure-ground discrimination (FGD) via relative motion represents a highly conserved visual computation essential for breaking camouflage. Over forty years ago, the Reichardt-Poggio-Hausen (RPH) model proposed a circuit architecture to explain this phenomenon, relying on an inhibitory wide-field pool cell to aggregate global motion and subsequently inhibit elementary motion detectors. However, a biological implementation of the RPH model has remained elusive. Using Drosophila connectomics data and biophysically accurate modeling, we reveal a biological circuit implementing this canonical architecture. Strikingly, we find that while the dendrites of the elemental motion detectors, T4a, are tuned to motion, their axon terminals compute relative motion. This secondary computation is achieved via presynaptic shunting inhibition from the ventral Centrifugal Horizontal (vCH) cell, which acts as a global motion integrator that normalizes the signal carried by the T4 axon terminals during whole-field optic flow. We extend our model to include the motion-opponency and the binocular communication pathways and show that FGD depends on the T4a-vCH interactions. We further show that specific circuit adjustments are sufficient for our model to make predictions consistent with several physiological and behavioral experiments across different fly species. Ultimately, by uniting connectomic connectivity with morphologically accurate biophysics, our approach demonstrates how detailed, synapse-resolution models of the brain can yield fine-grained biological predictions.

neuroscience↗

Motion-based depth estimation in Drosophila

Inferring three-dimensional structure from two-dimensional visual input requires a second perspective, either in time or in space. In flying animals, the first of these options lends itself as an ideal source for constructing internal representations of the environment, since their continuous self-motion automatically produces an optic flow. How neural circuits transform this signal into estimates of object distance, and what form such representations take, remains unknown. We address this problem in the visual system of the fruit fly. By immersing flies in a virtual environment while recording population-level calcium activity of motion-sensitive neurons, we extract an optic flow-based map of space. This map contains accurate estimates of object distance computed through spatial integration of elementary motion detector signals. Using electrophysiological recordings, we identify postsynaptic wide-field neurons as a cellular substrate for this operation. In behavioural experiments, we show that motion vision is essential for depth perception; without access to visual motion information, the free flight trajectories of motion-blind flies inevitably end in collisions. Our experiments link population-level neural activity to behaviourally relevant representations of environmental structure and demonstrate that motion vision is essential for navigation in three-dimensional space. One Sentence SummaryPopulation activity of motion-sensitive neurons accurately captures object distance and is required for navigation in three dimensions.

neuroscience↗

A multi-input optic glomerulus mediates opposing behavioral responses to visual objects

Prey, predators or conspecifics are first detected as visual objects in many seeing animals. Vision guides behavioral actions towards or away from these objects. An error in this visual perception could prove fatal. How object information is untangled to avoid errors remains unclear. Here we show that LC10d visual projection neurons in Drosophila melanogaster mediate avoidance of visual objects in the absence of a chemosensory profile. LC10d neurons are broadly tuned to objects and project to the same retinorecipient brain region that receives inputs from LC10a neurons, which are required for tracking. The descending neurons DNa10 are directly downstream of the anterior-facing LC10d sub-population and mediate LC10d-dependent avoidance. Our work demonstrates the use of two similar neuron types and chunking of the visual field into zones as strategies to disentangle similar sets of visual cues requiring nearly opposite behavioral responses.

neuroscience↗

Population Morphology Implies a Common Developmental Blueprint for Drosophila Motion Detectors

T4 and T5 neurons are the first direction-selective neurons in the visual pathway. They are the most numerous cell types in the fly brain ([~] 6000 within each optic lobe) and, as a population, their compact dendritic arbours span the entire visual field. They are classified into four subtypes (a, b, c, and d). Each subtype encodes one of four orthogonal motion directions (up, down, forwards, backwards). Crucially, the dendrites of these neurons are oriented inversely to the functional direction of motion which they encode. This dendritic orientation is what ultimately determines their functional directional encoding. The development of these neurons is well characterised up to the point of neuropil innervation. However, the full population of these neurons innervate their target neuropil prior to the emergence of directionality within their dendrites. As it stands, development prior to the emergence of dendritic orientations, and the adult oriented dendrite are both well understood, but the key components relating to the emergence of orientation itself are missing. Recent whole-brain electron microscopy (EM) connectomes of Drosophila melanogaster provide an unprecedented level of resolution and completeness when considering the morphology of neurons. Utilising this, we isolate the dendritic arbour of every T4 and T5 neuron within a female adult Drosophila brain, made available through FAFB-FlyWire. In doing so we are able to rigorously quantify the morphology of these dendrites in order to understand their similarities and differences. In doing so we aim to shed light on the origins of dendritic directionality. We reason that either this emerges through a tightly controlled, subtype specific mechanism, or is the result of a subtype agnostic mechanism and external factors. In the former case, we would expect evidence of this in differences between the morphological structure of individual dendrites between T4 and T5, and their subtypes. Our analysis however reveals a high degree of structural similarity between T4 and T5, and within their subtypes. Particularly, the geometry of branching, section orientation, and tree-graph structure of these dendrites show only minor variability, with no consistent separation between T4 and T5, or their subtypes. These results indicate that, despite forming in different neuropils, and serving distinct motion directions, T4 and T5 dendrites follow closely aligned morphological patterns. This suggests a shared mechanism of directed outgrowth, as opposed to symmetry breaking emerging through neuron type or subtype specific mechanisms. Author summaryThe Dendrites of T4 and T5 neurons orient spatially in a direction inverse to the direction of motion which they encode. The development of these neurons is understood up to the point of neuropil innervation, however they remain unicolumnar. The window between the directed adult dendrite, and their unicolumnar neuropil innervation is not yet understood. In order to shed light on how directionality within these dendrites may emerge, we perform a rigorous quantification of the morphology of all T4 and T5 dendrites within a single female adult Drosophila brain using nm-resolution reconstructions available from recent electron microscopy. This allows for the characterisation of neuropil and directionally specific morphological similarities and differences within this population. Although insightful variability is observed at the level of spatial properties of these dendrites, their geometry and topology is highly conserved across T4 and T5 populations, and directions of outgrowth. From these analyses, we conclude that although these dendrites originate in differing brain regions, with differing input partners, and perform differing, subtype-specific, detection of motion directions, the underlying process of dendritic outgrowth and emergence of orientation is most likely shared across both T4 and T5 and their subtypes.

neuroscience↗

Polyadic synapses introduce unique wiring architectures in T5 cells of Drosophila

Connectomes provide neuronal wiring diagrams and allow for investigating the detailed synaptic morphology of each connection. In the visual system of Drosophila, T5 cells are the primary motion-sensing neurons in the OFF-pathway. On their dendrites, they receive input from the excitatory Tm1, Tm2, Tm4, Tm9 and the inhibitory CT1 neurons in a spatial arrangement which depends on their preferred direction. This connectivity, however, has not yet been investigated with respect to specific types of polyadic synapses which are known to be abundant in the fly nervous system. In this study, we use the FlyWire database and identify that Tm and CT1 cells wire on T5a dendrites via eight polyadic synapse types. We then explore the distribution of the different synapse types on T5a dendrites and find differences in their spatial patterns. Finally, we show that the polyadic morphology is setting a directional wiring architecture at the T5 network level. Our work showcases the complexity that polyadic synapses introduce in T5 connectivity.

neuroscience↗

Differential temporal filtering in the fly optic lobe

Visual interneurons come in many different flavors, representing luminance changes at one location as ON or OFF signals with different dynamics, ranging from purely sustained to sharply transient responses. While the functional relevance of this representation for subsequent computations like direction-selective motion detection is well understood, the mechanisms by which these differences in dynamics arise are unclear. Here, I study this question in the fly optic lobe. Taking advantage of the known connectome I simulate a network of five adjacent optical columns each comprising 65 different cell types. Each neuron is modeled as an electrically compact single compartment, conductance-based element that receives input from other neurons within its column and from its neighboring columns according to the intra- and inter-columnar connectivity matrix. The sign of the input is determined according to the known transmitter type of the presynaptic neuron and the receptor on the postsynaptic side. In addition, some of the neurons are given voltage-dependent conductances known from the fly transcriptome. As free parameters, each neuron has an input and an output gain, applied to all its input and output synapses, respectively. The parameters are adjusted such that the spatio-temporal receptive field properties of 13 out of the 65 simulated neurons match the experimentally determined ones as closely as possible. Despite the fact that all neurons have identical leak conductance and membrane capacitance, this procedure leads to a surprisingly good fit to the data, where specific neurons respond transiently while others respond in a sustained way to luminance changes. This fit critically depends on the presence of an H-current in some of the first-order interneurons, i.e., lamina cells L1 and L2: turning off the H-current eliminates the transient response nature of many neurons leaving only sustained responses in all of the examined interneurons. I conclude that the diverse dynamic response behavior of the columnar neurons in the fly optic lobe starts in the lamina and is created by their different intrinsic membrane properties. I predict that eliminating the hyperpolarization-activated current by RNAi should strongly affect the dynamics of many medulla neurons and, consequently, also higher-order functions depending on them like direction-selectivity in T4 and T5 neurons. Author summaryVisual interneurons come in many different flavors, representing luminance changes at one location as ON or OFF signals and with different dynamics, ranging from purely sustained to sharply transient. While the functional relevance of this representation for subsequent computations, like direction-selective motion detection, is well understood, the mechanism by which these differences in dynamics arise is unclear. Here, I study this question by using the connectome of the fly optic lobe and simulating the network of interneurons in a biophysically plausible way. Adjusting the input and the output gain of each neuron such that a subset of neurons (those where experimental data exist) matches the response kinetics of their real counterparts, I identify a particular voltage-gated ion channel present in some of the first-order interneurons as being critical for the transient response behavior of postsynaptic neurons. This study, therefore, predicts that eliminating this current from the circuit should strongly affect the response kinetics in downstream circuit elements and destruct the computation of direction selectivity.

neuroscience↗

Columnar cholinergic neurotransmission onto T5 cells of Drosophila

Several nicotinic and muscarinic acetylcholine receptors (AChRs) are expressed in the brain of Drosophila melanogaster. However, the contribution of different AChRs to visual information processing remains poorly understood. T5 cells are the primary motion-sensing neurons in the OFF pathway and receive input from four different columnar cholinergic neurons, Tm1, Tm2, Tm4 and Tm9. We reasoned that different AChRs in T5 postsynaptic sites might contribute to direction selectivity, a central feature of motion detection. We show that the nicotinic nAChR1, nAChR4, nAChR5 and nAChR7 subunits localize on T5 dendrites. By targeting synaptic markers specifically to each cholinergic input neuron, we find a prevalence of the nAChR5 in Tm1-, Tm2- and Tm4-to-T5 synapses and of nAChR7 in Tm9-to-T5 synapses. Knock-down of nAChR4, nAChR5, nAChR7, or mAChR-B individually in T5 cells alters the optomotor response and reduces T5 directional selectivity. Our findings indicate a differential contribution of postsynaptic receptors to input visual processing and, thus, to the computation of motion direction in T5 cells.

neuroscience↗

Efficient Search for Circuit Structure by 'Smooth-Index' Matrix-Reordering

Volume electron microscopy together with computer-based image analysis are yielding neural circuit diagrams of ever larger regions of the brain [1-10]. These datasets are usually represented in a cell-to-cell connectivity matrix and contain important information about prevalent circuit motifs allowing to directly test various theories on the computation in that brain structure [11,12]. Of particular interest are the detection of cell assemblies and the quantification of feedback, which can profoundly change circuit properties. While the ordering of cells along the rows and columns doesnt change the connectivity, it can make special connectivity patterns recognizable. For example, ordering the cells along the flow of information, feedback and feedforward connections are segregated above and below the main matrix diagonal, respectively. Different algorithms are used to renumber matrices such as to minimize a given cost function, but either their performance becomes unsatisfying at a given size of the circuit or the CPU time needed to compute them scales in an unfavorable way with increasing number of neurons [13-15]. Based on previous ideas [16-18], we describe an algorithm which is effective in matrix reordering with respect to both its performance as well as to its scaling in computing time. Rather than trying to reorder the matrix in discrete steps, the algorithm transiently assigns a real-valued parameter to each cell describing its location on a continuous axis ( smooth-index) and finds the parameter set that minimizes the cost. We find that the smooth-index algorithm outperforms all algorithms we compared it to, including those based on topological sorting. Author SummaryConnectomic data provide researchers with neural circuit diagrams of ever larger regions of the brain. These datasets are usually represented in a cell-to-cell connectivity matrix and contain important information about prevalent circuit motifs. Such motifs, however, only become visible if the connectivity matrix is reordered appropriately. For example, ordering the cells along the flow of information, feedback and feedforward connections are segregated above and below the main matrix diagonal, respectively. While most previous approaches rely on topological sorting, our method treats the discrete vertex indices as real numbers ( smooth-index) along independent parameter axes and defines a differentiable cost function, thus, allowing gradient-based algorithms to find a minimum. The parameter set at this minimum is then re-discretized to reorder the connectivity matrix accordingly. We find our method to scale favorably with the circuit size and to outperform all algorithms we compared it to.

neuroscience↗

Super Bowl, an open platform for visual stimulation of insects

To study how the nervous system processes visual information, experimenters must record neural activity while delivering visual stimuli in a controlled fashion. In animals with a nearly panoramic field of view, such as flies, precise stimulation of the entire visual field is challenging. We describe a projector-based device for stimulation of the insect visual system under a microscope. The device is based on a bowl-shaped screen that provides a wide and nearly distortion-free field of view. It is compact, cheap, easy to assemble, and easy to operate using the included open-source software for stimulus generation. We validate the virtual reality system technically and demonstrate its capabilities in a series of experiments at two levels: the cellular, by measuring the membrane potential responses of visual interneurons; and the organismal, by recording optomotor and fixation behavior of Drosophila melanogaster in tethered flight. Our experiments reveal the importance of stimulating the visual system of an insect with a wide field of view, and we provide a simple solution to do so.

neuroscience↗

Identification of NAD-RNAs and ADPR-RNA decapping in the archaeal model organisms Sulfolobus acidocaldarius and Haloferax volcanii

NAD is a coenzyme central to metabolism that was also found to serve as a 5-terminal cap of bacterial and eukaryotic RNA species. The presence and functionality of NAD-capped RNAs (NAD-RNAs) in the archaeal domain remain to be characterized in detail. Here, by combining LC-MS and NAD captureSeq methodology, we quantified the total levels of NAD-RNAs and determined the identity of NAD-RNAs in the two model archaea, Sulfolobus acidocaldarius and Haloferax volcanii. A complementary differential RNA-Seq (dRNA-Seq) analysis revealed that NAD transcription start sites (NAD-TSS) correlate with well-defined promoter regions and often overlap with primary transcription start sites (pTSS). The population of NAD-RNAs in the two archaeal organisms shows clear differences, with S. acidocaldarius possessing more capped small non-coding RNAs (sncRNAs) and leader sequences. The NAD-cap did not prevent 5[->]3 exonucleolytic activity by the RNase Saci-aCPSF2. To investigate enzymes that facilitate the removal of the NAD-cap, four Nudix proteins of S. acidocaldarius were screened. None of the recombinant proteins showed NAD decapping activity. Instead, the Nudix protein Saci_NudT5 showed activity after incubating NAD-RNAs at elevated temperatures. Hyperthermophilic environments promote the thermal degradation of NAD into the toxic product ADPR. Incorporating NAD into RNAs and the regulation of ADPR-RNA decapping by Saci_NudT5 is proposed to provide additional layers of maintaining stable NAD levels in archaeal cells. ImportanceThis study reports the first characterization of 5-terminally modified RNA molecules in Archaea and establishes that NAD-RNA modifications, previously only identified in the other two domains of life, are also prevalent in the archaeal model organisms Sulfolobus acidocaldarius and Haloferax volcanii. We screened for NUDIX hydrolases that could remove the NAD-RNA cap and showed that none of these enzymes removed NAD modifications, but we discovered an enzyme that hydrolyzes ADPR-RNA. We propose that these activities influence the stabilization of NAD and its thermal degradation to potentially toxic ADPR products at elevated growth temperatures.

molecular biology↗

Voltage to Calcium Transformation Enhances Direction Selectivity in Drosophila T4 neurons

A critical step in neural information processing is the transformation of membrane voltage into calcium signals leading to transmitter release. However, the effect of voltage to calcium transformation on neural responses to different sensory stimuli is not well understood. Here, we use in vivo two-photon imaging of genetically encoded voltage and calcium indicators, Arclight and GCaMP6f respectively, to measure responses in Drosophila direction-selective T4 neurons. Comparison between Arclight and GCaMP6f signals revealed calcium signals to have a significantly higher direction selectivity compared to voltage signals. Using these recordings we build a model which transforms T4 voltage responses to calcium responses. The model reproduces experimentally measured calcium responses across different visual stimuli using different temporal filtering steps and a stationary non-linearity. These findings provide a mechanistic underpinning of the voltage-to-calcium transformation and show how this processing step, in addition to synaptic mechanisms on the dendrites of T4 cells, enhances direction selectivity in the output signal of T4 neurons.

neuroscience↗

Spatial and temporal control of expression with light-gated LOV-LexA

The ability to drive expression of exogenous genes in different tissues and cell types, under control of specific enhancers, has been crucial for discovery in biology. While many enhancers drive expression broadly, several genetic tricks were developed to obtain access to isolated cell types. Studies of spatially organized neuropiles in the central nervous system of insects have raised the need for a system that targets subsets of cells within a single neuron type, a feat currently dependent on stochastic flip-out methods. To access the same subsets of cells within a given expression pattern consistently across fruit flies, we developed the light-gated expression system LOV-LexA. We combined the bacterial LexA transcription factor with the plant-derived light oxygen voltage (LOV) photosensitive domain and a fluorescent protein. Exposure to blue light uncages a nuclear localizing signal in the C-terminal of the LOV domain, and leads to translocation of LOV-LexA to the nucleus, with subsequent initiation of transcription. LOV-LexA enables spatial and temporal control of expression of transgenes under LexAop sequences in larval fat body as well as pupal and adult neurons with blue light. The LOV-LexA tool is ready to use with GAL4 and Split-GAL4 drivers in its current form, and constitutes another layer of intersectional genetics, that provides light-controlled genetic access to specific subsets of cells across flies.

genetics↗

Aerial course stabilization is impaired in motion-blind flies

Visual motion detection is among the best understood neuronal computations. One assumed behavioural role is to detect self-motion and to counteract involuntary course deviations, extensively investigated in tethered walking or flying flies. In free flight, however, any deviation from a straight course is signalled by both the visual system as well as by proprioceptive mechanoreceptors called halteres, which are the equivalent of the vestibular system in vertebrates. Therefore, it is yet unclear to what extent motion vision contributes to course control, or whether straight flight is completely controlled by proprioceptive feedback from the halteres. To answer these questions, we genetically rendered flies motion-blind by blocking their primary motion-sensitive neurons and quantified their free-flight performance. We found that such flies have difficulties maintaining a straight flight trajectory, much like control flies in the dark. By unilateral wing clipping, we generated an asymmetry in propulsory force and tested the ability of flies to compensate for this perturbation. While wild-type flies showed a remarkable level of compensation, motion-blind animals exhibited pronounced circling behaviour. Our results therefore unequivocally demonstrate that motion vision is necessary to fly straight under realistic conditions.

animal behavior and cognition↗

Nanopore-based native RNA sequencing provides insights into prokaryotic transcription, operon structures, rRNA maturation and modifications

The prokaryotic transcriptome is shaped by transcriptional and posttranscriptional events that define the characteristics of an RNA, including transcript boundaries, the base modification status, and processing pathways to yield mature RNAs. Currently, a combination of several specialised short-read sequencing approaches and additional biochemical experiments are required to describe all transcriptomic features. In this study, we present native RNA sequencing of bacterial (E. coli) and archaeal (H. volcanii, P. furiosus) transcriptomes employing the Oxford Nanopore sequencing technology. Based on this approach, we could address multiple transcriptomic characteristics simultaneously with single-molecule resolution. Taking advantage of long RNA reads provided by the Nanopore platform, we could (re-)annotate large transcriptional units and boundaries. Our analysis of transcription termination sites suggests that diverse termination mechanisms are in place in archaea. Moreover, we shed additional light on the poorly understood rRNA processing pathway in Archaea. One of the key features of native RNA sequencing is that RNA modifications are retained. We could confirm this ability by analysing the well-known KsgA-dependent methylation sites and mapping of N4-acetylcytosines modifications in rRNAs. Notably, we were able to follow the relative timely order of the installation of these modifications in the rRNA processing pathway.

microbiology↗

Axonal gap junctions in the fly visual system enable fast prediction for evasive flight maneuvers

The visual system must make predictions to compensate for inherent delays in its processing. Yet little is known, mechanistically, about how prediction aids natural behaviors. Here, we show that despite a 20-30ms intrinsic processing delay, the vertical motion sensitive (VS) network of the blowfly achieves maximally efficient prediction. This prediction enables the fly to fine-tune its complex, yet brief, evasive flight maneuvers according to its initial ego-rotation at the time of detection of the visual threat. Combining a rich database of behavioral recordings with detailed compartmental modeling of the VS network, we further show that the VS network has axonal gap junctions that are critical for optimal prediction. During evasive maneuvers, a VS subpopulation that directly innervates the neck motor center can convey predictive information about the flys future ego-rotation, potentially crucial for ongoing flight control. These results suggest a novel sensory-motor pathway that links sensory prediction to behavior. Author summarySurvival-critical behaviors shape neural circuits to translate sensory information into strikingly fast predictions, e.g. in escaping from a predator faster than the systems processing delay. We show that the fly visual system implements fast and accurate prediction of its visual experience. This provides crucial information for directing fast evasive maneuvers that unfold over just 40ms. Our work shows how this fast prediction is implemented, mechanistically, and suggests the existence of a novel sensory-motor pathway from the fly visual system to a wing steering motor neuron. Echoing and amplifying previous work in the retina, our work hypothesizes that the efficient encoding of predictive information is a universal design principle supporting fast, natural behaviors.

neuroscience↗