Biology subjects

Silies, M.

Publications and source records attributed to Silies, M..

12 recordsLinked to original sources

bioRxiv2026

Functional temporal diversity in the fly reflects natural motion statistics

As animals move through the world, their visual input can change gradually or shift rapidly, spanning a broad range of temporal frequencies. Visual circuits therefore face the challenge of encoding inputs with an inherently multiscale temporal structure. From insects to vertebrates, peripheral visual neurons exhibit striking temporal diversity, yet the principles underlying this organization remain unclear. Here, we show that temporal diversity in the fly visual system supports efficient coding of natural motion by distributing encoding across complementary timescales. Using well-characterized fly motion-detection pathways as a model, we show that temporal filters within and across visual hierarchies occupy a low-dimensional feature space defined by filter polarity and characteristic timescale. Within an efficient-coding framework constrained by natural motion statistics, circuits that combine temporally distinct filters encode naturalistic inputs more efficiently than circuits composed of more similar filters, an advantage that largely disappears when changing the stimulus statistics. Measured filters of fly visual cell types closely match the optimal solutions predicted for natural motion, and these optima map onto both circuit architecture and function. Finally, extending beyond the motion pathway, we identify distinct correlation structures in circuits within and outside the motion pathway. Together, we identify temporal diversity in response filters as a circuit-level strategy for encoding natural motion, shaped by the multiscale statistics of the environment. Significance statementNeuronal diversity is ubiquitous across sensory systems, yet its functional role remains poorly understood. We investigate a prominent form of diversity: the wide temporal response profile of visual neurons, from transient detectors to slow integrators. Using the fly visual system, we uncover a coding function of temporal diversity. Neurons with complementary temporal properties span the multiscale structure of natural motion, achieving coding efficiency that no single neuron type can implement alone. Predictions from an efficient coding framework grounded in natural motion statistics closely match fly visual circuit organization, from cell-type response properties to anatomical wiring. Because similar temporal diversity exists in the vertebrate retina, we suggest this distributed temporal coding is a conserved design principle shaped by natural scene statistics.

neuroscience↗

bioRxiv2025

Inhibitory columnar feedback neurons are required for motion processing in Drosophila

Visual motion information is essential to guiding the movements of many animals. The establishment of direction-selective signals, a hallmark of motion detection, is considered a core neural computation and has been characterized extensively in primates, mice and fruit flies. In flies, the circuits that produce direction-selective signals rely on feedforward visual pathways that connect peripheral visual inputs to the dendrites of the ON and OFF-direction selective cells. Here we describe a novel role for feedback inhibition in motion computation. Two GABAergic neurons, C2 and C3, connect to neurons upstream of the direction-selective T4 and T5 cells and blocking C2 and C3 affects direction selectivity in T4/T5. In the ON pathway, this is likely achieved by C2-mediated suppression of responses in the major T4 input neuron Mi1. Together, C2 and C3 suppress responses to non-preferred stimuli in both T4 and T5. At the behavioral level, feedback inhibition temporally sharpens responses to ON-moving stimuli, enhancing the flys ability to discriminate visual stimuli that occur in quick succession. GABAergic inhibitory feedback neurons thus constitute an essential component within the circuitry that computes visual motion.

neuroscience↗

bioRxiv2024

Undoing of firing rate adaptation enables invariant population codes

Neural adaptation supports coding efficiency by tuning responses to prevailing stimulus statistics. However, when information is represented by neural populations, adaptation of individual units could degrade behaviorally relevant signals. Here we investigate how the fly olfactory system implements adaptation in Olfactory Receptor Neurons (ORNs) and the consequences for combinatorial coding in downstream circuits. We show that adaptation of ORN firing rate is compensated at the axon terminal, where calcium transients remain background-invariant through inhibitory presynaptic feedback. Background invariance requires an adaptation strategy that shifts ORN response amplitude rather than sensitivity, diverging from efficient coding principles in single neurons. This property supports contrast encoding in ORN populations necessary for background compensation across the glomeruli. Downstream, the modulation of presynaptic Unc13 proteins maintains postsynaptic projection neurons responses to ON stimuli background invariant. We identify a new coding strategy where olfactory neuronal populations encode asymmetrically contrast information by implementing circuit computations that compensate peripheral firing rate adaptation.

neuroscience↗

bioRxiv2024

Neural pathways and computations that achieve stable contrast processing tuned to natural scenes

Natural scenes are highly dynamic, challenging the reliability of visual processing. Yet, humans and many animals perform accurate visual behaviors, whereas computer vision devices struggle with changing environments. How does animal vision achieve this? Here, we reveal the algorithms and mechanisms of rapid luminance gain control in Drosophila, resulting in stable visual processing. We identify the dendrites of specific third order neurons, Tm1 and Tm9, as the site of luminance gain control. The circuitry further involves neurons with wide-field properties, matching computational predictions that local spatial pooling can drive optimal contrast processing in natural scenes where light conditions change rapidly. Experiments and theory argue that a spatially pooled luminance signal achieves luminance gain control via divisive normalization. This process relies on shunting inhibition using the glutamate-gated chloride channel GluCl. Our work describes computationally, algorithmically, and mechanistically, how visual circuits robustly process visual information in dynamically changing, natural scenes.

neuroscience↗

bioRxiv2023

Heterogeneity of synaptic connectivity in the fly visual system

Visual systems are homogeneous structures, where repeating columnar units are stereotypically arranged to retinotopically cover the visual field. Each of these columns contain many of the same neuron types that are distinguished by anatomic, genetic and - generally - by functional properties. However, there are exceptions to this rule. In the 800 visual columns of the Drosophila eye, there is an anatomically and genetically identifiable cell type with variable functional properties, Tm9. Since anatomical connectivity shapes functional neuronal properties, we identified the presynaptic inputs of several hundred Tm9s across both optic lobes using the FAFB connectome dataset and FlyWire analysis. Our work shows that Tm9 has three major, stereotypic, and many weaker, sparsely distributed inputs. This differs from the presynaptic connectivity of neurons with uniform properties, Tm1 and Tm2, which have only one major, and more stereotypic inputs than Tm9. Within the heterogeneous circuit architecture, we identified specific motifs, such as a set of wide-field neurons, which can be the source of the variable Tm9 physiology. Genetic synapse labeling combined with expansion microscopy showed that the heterogeneous wiring exists across individuals. Together, our data argue that the visual system uses heterogeneous, distributed circuit properties to achieve robust visual processing.

neuroscience↗

bioRxiv2023

Multifaceted luminance gain control beyond photoreceptors in Drosophila

Animals navigating in natural environments must handle vast changes in their sensory input. Visual systems, for example, handle changes in luminance at many timescales, from slow changes across the day to rapid changes during active behavior. To maintain luminance-invariant perception, visual systems must adapt their sensitivity to changing luminance at different timescales. We demonstrate that luminance gain control in photoreceptors alone is insufficient to explain luminance invariance at both fast and slow timescales and reveal the algorithms that adjust gain past photoreceptors in the fly eye. We combined imaging and behavioral experiments with computational modeling to show that, downstream of photoreceptors, circuitry taking input from the single luminance-sensitive neuron type L3 implements gain control at fast and slow timescales. This computation is bidirectional in that it prevents underestimation of contrasts in low luminance and overestimation in high luminance. An algorithmic model disentangles these multifaceted contributions and shows that the bidirectional gain control occurs at both timescales. The model implements a nonlinear interaction of luminance and contrast to achieve gain correction at fast timescales and a dark-sensitive channel to improve the detection of dim stimuli at slow timescales. Together, our work demonstrates how a single neuronal channel performs diverse computations to implement gain control at multiple timescales that are together important for navigation in natural environments. Significance StatementLuminance varies slowly throughout the day, or rapidly during movements. Yet, animals show luminance-invariant behaviors to visual cues across these scenarios. Combining in vivo imaging, behavioral analyses and computational modeling, we here show that diverse luminance gain control operations required for robust visual processing exist in the fly visual circuitry beyond photoreceptors. Despite relying on a single luminance-sensitive neuron type, this luminance gain control is multifaceted, in that it achieves both gain increments and decrements at two different timescales. Overall, the study sheds light on a circuit gain control strategy operating at multiple timescales, which together challenge luminance-invariant visual behaviors in natural environments.

neuroscience↗

bioRxiv2021

First-order visual interneurons distribute distinct contrast and luminance information across ON and OFF pathways to achieve stable behavior

The accurate processing of contrast is the basis for all visually guided behaviors. Visual scenes with rapidly changing illumination challenge contrast computation, because adaptation is not fast enough to compensate for such changes. Yet, human perception of contrast is stable even when the visual environment is quickly changing. The fruit fly Drosophila also shows nearly luminance invariant behavior for both ON and OFF stimuli. To achieve this, first-order interneurons L1, L2 and L3 all encode contrast and luminance differently, and distribute information across both ON and OFF contrast-selective pathways. Behavioral responses to both ON and OFF stimuli rely on a luminance-based correction provided by L1 and L3, wherein L1 supports contrast computation linearly, and L3 non-linearly amplifies dim stimuli. Therefore, L1, L2 and L3 are not distinct inputs to ON and OFF pathways but the lamina serves as a separate processing layer that distributes distinct luminance and contrast information across ON and OFF pathways to support behavioral performance in varying conditions.

neuroscience↗

bioRxiv2021

The physiological basis for the computation of direction selectivity in the Drosophila OFF pathway

In Drosophila, direction-selective neurons implement a mechanism of motion computation similar to cortical neurons, using contrast-opponent receptive fields with ON and OFF subunits. It is not clear how the presynaptic circuitry of direction-selective neurons in the OFF pathway supports this computation, because 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, also 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 is passed on to T5, and calcium decrements in Tm9 in response to ON stimuli are maintained 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.

neuroscience↗

bioRxiv2021

An optimal population code for global motion estimation in local direction-selective cells

Nervous systems allocate computational resources to match stimulus statistics. However, the physical information that needs to be processed depends on the animals own behavior. For example, visual motion patterns induced by self-motion provide essential information for navigation. How behavioral constraints affect neural processing is not known. Here we show that, at the population level, local direction-selective T4/T5 neurons in Drosophila represent optic flow fields generated by self-motion, reminiscent to a population code in retinal ganglion cells in vertebrates. Whereas in vertebrates four different cell types encode different optic flow fields, the four uniformly tuned T4/T5 subtypes described previously represent a local snapshot. As a population, six T4/T5 subtypes encode different axes of self-motion. This representation might serve to efficiently encode more complex flow fields generated during flight. Thus, a population code for optic flow appears to be a general coding principle of visual systems, but matching the animals individual ethological constraints.

neuroscience↗

bioRxiv2021

NECAB2 orchestrates an endosomal pathway of mitochondrial quality control at striatal synapses

Synaptic signaling depends on ATP generated by mitochondria. Due to extensive connectivity, the striatum is especially vulnerable to mitochondrial dysfunction and thus requires efficient mitochondrial quality control and repair. We found that global knockout of the neuronal calcium-binding protein 2 (NECAB2) in the mouse causes loss of striatal synapses and behavioral phenotypes related to striatal dysfunction such as reduced motivation and altered sensory gating. Striatal mitochondria from Necab2 knockout mice are more abundant and smaller. They are characterized by increased respiration and superoxide production resulting in oxidative stress. This accumulation of dysfunctional mitochondria is caused by a defective assembly of mitochondria with early endosomes in a pathway that involves the small GTPase Rab5 and its guanine nucleotide exchange factor Alsin/ALS2. NECAB2 therefore participates in an endosomal pathway of mitochondrial stress response and repair important for striatal function.

neuroscience↗

bioRxiv2020

m6A RNA methylation regulates promoter proximal pausing of RNA Polymerase II

RNA Polymerase II (RNAP II) pausing is essential to precisely control gene expression and is critical for development of metazoans. Here, we show that the m6A RNA modification regulates promoter-proximal RNAP II pausing. The m6A methyltransferase complex (MTC), with the nuclear reader Ythdc1, are recruited to gene promoters. Depleting the m6A MTC leads to a decrease in RNAP II pause release and in Ser2P occupancy on the gene body, and affects nascent RNA transcription. Tethering Mettl3 to a heterologous gene promoter is sufficient to increase RNAP II pause release, an effect that relies on its m6A catalytic domain. Collectively, our data reveal an important link between RNAP II pausing and the m6A RNA modification, thus adding another layer to m6A-mediated gene regulation.

molecular biology↗

bioRxiv2017

Drosophila Fezf coordinates laminar-specific connectivity through cell-intrinsic and cell-extrinsic mechanisms

Laminar arrangement of neural connections is a fundamental feature of neural circuit organization. Identifying mechanisms that coordinate neural connections within correct layers is thus vital for understanding how neural circuits are assembled. In the medulla of the Drosophila visual system neurons form connections within ten parallel layers. The M3 layer receives input from two neuron types that sequentially innervate M3 during development. Here we show that M3-specific innervation by both neurons is coordinated by Drosophila Fezf (dFezf), a conserved transcription factor that is selectively expressed by the earlier targeting input neuron. In this cell, dFezf instructs layer specificity and activates the expression of a secreted molecule (Netrin) that regulates the layer specificity of the other input neuron. We propose that employment of transcriptional modules that cell-intrinsically target neurons to specific layers, and cell-extrinsically recruit other neurons is a general mechanism for building layered networks of neural connections.

neuroscience↗