scholarly journals Maximally efficient prediction in the early fly visual system may support evasive flight maneuvers

2021 ◽  
Vol 17 (5) ◽  
pp. e1008965
Author(s):  
Siwei Wang ◽  
Idan Segev ◽  
Alexander Borst ◽  
Stephanie Palmer
Keyword(s):  
Visual System ◽  
Flight Control ◽  
Vertical Motion ◽  
Compartmental Modeling ◽  
Optimal Prediction ◽  
Motor Center ◽  
Motor Pathway ◽  
Efficient Prediction ◽  
Sensory Prediction ◽  
Fine Tune

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 fly’s future ego-rotation, potentially crucial for ongoing flight control. These results suggest a novel sensory-motor pathway that links sensory prediction to behavior.

scholarly journals Maximally efficient prediction in the early fly visual system may support evasive flight maneuvers

2019 ◽  
Author(s):  
Siwei Wang ◽  
Idan Segev ◽  
Alexander Borst ◽  
Stephanie Palmer
Keyword(s):  
Visual System ◽  
Flight Control ◽  
Sensory Information ◽  
Vertical Motion ◽  
Motor Center ◽  
Motor Pathway ◽  
Predictive Information ◽  
Sensory Motor ◽  
Efficient Prediction ◽  
Processing Delay

AbstractThe 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 fly’s 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 system’s 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.

Plasticity in the Visual System Is Correlated With a Change in Lifestyle of Solitarious and Gregarious Locusts

2004 ◽  
Vol 91 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Thomas Matheson ◽  
Stephen M. Rogers ◽  
Holger G. Krapp
Keyword(s):  
Visual System ◽  
Flight Control ◽  
Schistocerca Gregaria ◽  
Movement Detector ◽  
Time To Collision ◽  
Angular Extent ◽  
Behavioral Phase ◽  
Contralateral Movement ◽  
Gregarious Locusts ◽  
And Behavior

We demonstrate pronounced differences in the visual system of a polyphenic locust species that can change reversibly between two forms (phases), which vary in morphology and behavior. At low population densities, individuals of Schistocerca gregaria develop into the solitarious phase, are cryptic, and tend to avoid other locusts. At high densities, individuals develop instead into the swarm-forming gregarious phase. We analyzed in both phases the responses of an identified visual interneuron, the descending contralateral movement detector (DCMD), which responds to approaching objects. We demonstrate that habituation of DCMD is fivefold stronger in solitarious locusts. In both phases, the mean time of peak firing relative to the time to collision nevertheless occurs with a similar characteristic delay after an approaching object reaches a particular angular extent on the retina. Variation in the time of peak firing is greater in solitarious locusts, which have lower firing rates. Threshold angle and delay are therefore conserved despite changes in habituation or behavioral phase state. The different rates of habituation should contribute to different predator escape strategies or flight control for locusts living either in a swarm or as isolated individuals. For example, increased variability in the habituated responses of solitarious locusts should render their escape behaviors less predictable. Relative resistance to habituation in gregarious locusts should permit the continued responsiveness required to avoid colliding with other locusts in a swarm. These results will permit us to analyze neuronal plasticity in a model system with a well-defined and controllable behavioral context.

scholarly journals Differentiation signals from glia are fine-tuned to set neuronal numbers during development

2021 ◽  
Author(s):  
Anadika R Prasad ◽  
Matthew P Bostock ◽  
Ines Lago-Baldaia ◽  
Zaynab Housseini ◽  
Vilaiwan M Fernandes
Keyword(s):  
Cell Proliferation ◽  
Visual System ◽  
The Other ◽  
Tissue Architecture ◽  
Hedgehog Signalling ◽  
Target Field ◽  
Eye Disc ◽  
And Function ◽  
Circuit Formation ◽  
Fine Tune

Precise neuronal numbers are required for circuit formation and function. Known strategies to control neuronal numbers involve regulating either cell proliferation or survival. In the developing Drosophila visual system photoreceptors from the eye-disc induce their target field, the lamina, one column at a time. Although each column initially contains ~6 precursors, only 5 differentiate into neurons of unique identities (L1-L5); the extra precursor undergoes apoptosis. We uncovered that Hedgehog signalling patterns columns, such that the 2 precursors experiencing the lowest signalling activity are specified as L5s; only one differentiates while the other extra precursor dies. We showed that a glial population called the outer chiasm giant glia (xgO), which reside below the lamina, relays differentiation signals from photoreceptors to induce L5 differentiation. The precursors nearest to xgO differentiate into L5s and antagonise inductive signalling to prevent the extra precursors from differentiating, resulting in their death. Thus, tissue architecture and feedback from young neurons fine-tune differentiation signals from glia to limit the number of neurons induced.

scholarly journals Head movements quadruple the range of speeds encoded by the insect motion vision system in hawkmoths

2017 ◽  
Vol 284 (1864) ◽  
pp. 20171622 ◽  
Author(s):  
Shane P. Windsor ◽  
Graham K. Taylor
Keyword(s):  
Visual System ◽  
Flight Control ◽  
Vision System ◽  
Head Movements ◽  
Motion Vision ◽  
Full Field ◽  
Closed Loop Systems ◽  
Spatial Frequencies ◽  
Optokinetic Responses ◽  
Self Motion

Flying insects use compensatory head movements to stabilize gaze. Like other optokinetic responses, these movements can reduce image displacement, motion and misalignment, and simplify the optic flow field. Because gaze is imperfectly stabilized in insects, we hypothesized that compensatory head movements serve to extend the range of velocities of self-motion that the visual system encodes. We tested this by measuring head movements in hawkmoths Hyles lineata responding to full-field visual stimuli of differing oscillation amplitudes, oscillation frequencies and spatial frequencies. We used frequency-domain system identification techniques to characterize the head's roll response, and simulated how this would have affected the output of the motion vision system, modelled as a computational array of Reichardt detectors. The moths' head movements were modulated to allow encoding of both fast and slow self-motion, effectively quadrupling the working range of the visual system for flight control. By using its own output to drive compensatory head movements, the motion vision system thereby works as an adaptive sensor, which will be especially beneficial in nocturnal species with inherently slow vision. Studies of the ecology of motion vision must therefore consider the tuning of motion-sensitive interneurons in the context of the closed-loop systems in which they function.

scholarly journals The roles of vision and antennal mechanoreception in hawkmoth flight control

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Ajinkya Dahake ◽  
Anna L Stöckl ◽  
James J Foster ◽  
Sanjay P Sane ◽  
Almut Kelber
Keyword(s):  
Visual System ◽  
Visual Feedback ◽  
Flight Control ◽  
Sensory Feedback ◽  
Body Position ◽  
Temporal Frequency ◽  
Macroglossum Stellatarum ◽  
Position And Orientation ◽  
Open Question ◽  
Compensatory Interactions

Flying animals need continual sensory feedback about their body position and orientation for flight control. The visual system provides essential but slow feedback. In contrast, mechanosensory channels can provide feedback at much shorter timescales. How the contributions from these two senses are integrated remains an open question in most insect groups. In Diptera, fast mechanosensory feedback is provided by organs called halteres and is crucial for the control of rapid flight manoeuvres, while vision controls manoeuvres in lower temporal frequency bands. Here, we have investigated the visual-mechanosensory integration in the hawkmoth Macroglossum stellatarum. They represent a large group of insects that use Johnston’s organs in their antennae to provide mechanosensory feedback on perturbations in body position. Our experiments show that antennal mechanosensory feedback specifically mediates fast flight manoeuvres, but not slow ones. Moreover, we did not observe compensatory interactions between antennal and visual feedback.

Author response for "The brain of the African wild dog. IV . The visual system"

2020 ◽  
Author(s):  
Samson Chengetanai ◽  
Adhil Bhagwandin ◽  
Mads F. Bertelsen ◽  
Therese Hård ◽  
Patrick R. Hof ◽  
...  
Keyword(s):  
Visual System ◽  
Author Response ◽  
African Wild Dog ◽  
Wild Dog ◽  
The Brain

Digital differential hysteresis iimage processing displays what the microscope acquires but the eye can't see

1995 ◽  
Vol 53 ◽  
pp. 642-643
Author(s):  
Klaus-Ruediger Peters
Keyword(s):  
Image Processing ◽  
Visual System ◽  
High Precision ◽  
Image Data ◽  
Processing Technology ◽  
Output Data ◽  
Contrast Resolution ◽  
Pixel Intensity ◽  
Data Reading ◽  
Hysteresis Properties

Differential hysteresis processing is a new image processing technology that provides a tool for the display of image data information at any level of differential contrast resolution. This includes the maximum contrast resolution of the acquisition system which may be 1,000-times higher than that of the visual system (16 bit versus 6 bit). All microscopes acquire high precision contrasts at a level of <0.01-25% of the acquisition range in 16-bit - 8-bit data, but these contrasts are mostly invisible or only partially visible even in conventionally enhanced images. The processing principle of the differential hysteresis tool is based on hysteresis properties of intensity variations within an image.Differential hysteresis image processing moves a cursor of selected intensity range (hysteresis range) along lines through the image data reading each successive pixel intensity. The midpoint of the cursor provides the output data. If the intensity value of the following pixel falls outside of the actual cursor endpoint values, then the cursor follows the data either with its top or with its bottom, but if the pixels' intensity value falls within the cursor range, then the cursor maintains its intensity value.

Novel players fine-tune plant trade-offs

2015 ◽  
Vol 58 ◽  
pp. 83-100 ◽  
Author(s):  
Selena Gimenez-Ibanez ◽  
Marta Boter ◽  
Roberto Solano
Keyword(s):  
Ubiquitin Ligase ◽  
Feedback Loop ◽  
Molecular Level ◽  
26S Proteasome ◽  
Signalling Molecules ◽  
Transcriptional Reprogramming ◽  
Trade Offs ◽  
Jaz Proteins ◽  
Regulatory Feedback Loop ◽  
Fine Tune

Jasmonates (JAs) are essential signalling molecules that co-ordinate the plant response to biotic and abiotic challenges, as well as co-ordinating several developmental processes. Huge progress has been made over the last decade in understanding the components and mechanisms that govern JA perception and signalling. The bioactive form of the hormone, (+)-7-iso-jasmonyl-l-isoleucine (JA-Ile), is perceived by the COI1–JAZ co-receptor complex. JASMONATE ZIM DOMAIN (JAZ) proteins also act as direct repressors of transcriptional activators such as MYC2. In the emerging picture of JA-Ile perception and signalling, COI1 operates as an E3 ubiquitin ligase that upon binding of JA-Ile targets JAZ repressors for degradation by the 26S proteasome, thereby derepressing transcription factors such as MYC2, which in turn activate JA-Ile-dependent transcriptional reprogramming. It is noteworthy that MYCs and different spliced variants of the JAZ proteins are involved in a negative regulatory feedback loop, which suggests a model that rapidly turns the transcriptional JA-Ile responses on and off and thereby avoids a detrimental overactivation of the pathway. This chapter highlights the most recent advances in our understanding of JA-Ile signalling, focusing on the latest repertoire of new targets of JAZ proteins to control different sets of JA-Ile-mediated responses, novel mechanisms of negative regulation of JA-Ile signalling, and hormonal cross-talk at the molecular level that ultimately determines plant adaptability and survival.

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