875 research outputs found

    Object approach computation by a giant neuron and its relation with the speed of escape in the crab Neohelice

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    Upon detection of an approaching object, the crab Neohelice granulata continuously regulates the direction and speed of escape according to ongoing visual information. These visuomotor transformations are thought to be largely accounted for by a small number of motion-sensitive giant neurons projecting from the lobula (third optic neuropil) towards the supraesophageal ganglion. One of these elements, the monostratified lobula giant neuron of type 2 (MLG2), proved to be highly sensitive to looming stimuli (a 2D representation of an object approach). By performing in vivo intracellular recordings, we assessed the response of the MLG2 neuron to a variety of looming stimuli representing objects of different sizes and velocities of approach. This allowed us to: (1) identify some of the physiological mechanisms involved in the regulation of the MLG2 activity and test a simplified biophysical model of its response to looming stimuli; (2) identify the stimulus optical parameters encoded by the MLG2 and formulate a phenomenological model able to predict the temporal course of the neural firing responses to all looming stimuli; and (3) incorporate the MLG2-encoded information of the stimulus (in terms of firing rate) into a mathematical model able to fit the speed of the escape run of the animal. The agreement between the model predictions and the actual escape speed measured on a treadmill for all tested stimuli strengthens our interpretation of the computations performed by the MLG2 and of the involvement of this neuron in the regulation of the animal's speed of run while escaping from objects approaching with constant speed.Fil: Oliva, Damian Ernesto. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Tomsic, Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; Argentin

    Spatial organization of visuomotor reflexes in Drosophila

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    In most animals, the visual system plays a central role in locomotor guidance. Here, we examined the functional organization of visuomotor reflexes in the fruit fly, Drosophila, using an electronic flight simulator. Flies exhibit powerful avoidance responses to visual expansion centered laterally. The amplitude of these expansion responses is three times larger than those generated by image rotation. Avoidance of a laterally positioned focus of expansion emerges from an inversion of the optomotor response when motion is restricted to the rear visual hemisphere. Furthermore, motion restricted to rear quarter-fields elicits turning responses that are independent of the direction of image motion about the animal's yaw axis. The spatial heterogeneity of visuomotor responses explains a seemingly peculiar behavior in which flies robustly fixate the contracting pole of a translating flow field

    The role of the femoral chordotonal organ in motor control, interleg coordination, and leg kinematics in Drosophila melanogaster

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    Legged locomotion in terrestrial animals is often essential for mating and survival, and locomotor behavior must be robust and adaptable in order to be successful. The behavioral plasticity demonstrated by animals’ ability to locomote across diverse types of terrains and to change their locomotion in a task-dependent manner highlights the flexible and modular nature of locomotor networks. The six legs of insects are under the multi-level control of local networks for each limb and limb joint in addition to over-arching central control of the local networks. These networks, consisting of pattern-generating groups of interneurons, motor neurons, and muscles, receive modifying and reinforcing feedback from sensory structures that encode motor output. Proprioceptors in the limbs monitoring their position and movement provide information to these networks that is essential for the adaptability and robustness of locomotor behavior. In insects, proprioceptors are highly diverse, and the exact role of each type in motor control has yet to be determined. Chordotonal organs, analogous to vertebrate muscle spindles, are proprioceptive stretch receptors that span joints and encode specific parameters of relative movement between body segments. In insects, when leg chordotonal organs are disabled or manipulated, interleg coordination and walking are affected, but the simple behavior of straight walking on a flat surface can still be performed. The femoral chordotonal organ (fCO) is the largest leg proprioceptor and monitors the position and movements of the tibia relative to the femur. It has long been studied for its importance in locomotor and postural control. In Drosophila melanogaster, an ideal model organism due its genetic tractability, investigations into the composition, connectivity, and function of the fCO are still in their infancy. The fCO in Drosophila contains anatomical subgroups, and the neurons within a subgroup demonstrate similar responses to movements about the femur-tibia joint. Collectively, the experiments laid out in this dissertation provide a multi-faceted analysis of the anatomy, connectivity, and functional importance of subgroups of fCO neurons in D. melanogaster. The dissertation is divided into four chapters, representing different aspects of this complex and intriguing system. First, I present a detailed analysis of the composition of the fCO and its connectivity within the peripheral and central nervous systems. I demonstrate that the fCO is made up of anatomically distinct groups of neurons, each with their own unique features in the legs and ventral nerve cord. Second, I investigated the neuropeptide profile of the fCO and demonstrate that some fCO neurons express a susbtance that is known to act as a neuromodulator. Third, I demonstrate the sufficiency of subsets of fCO neurons to elicit reflex responses, highlighting the role of the Drosophila fCO in postural control. Lastly, I take this a step further and look into the functional necessity of these neuronal subsets for intra- and interleg coordination during walking. The importance of the fCO in motor control in D. melanogaster has been considered rather minor, though research into the topic is very limited. In the work laid out herein, I highlight the complexity of the Drosophila fCO and its role in the determination of locomotor behavior

    Neutral coding - A report based on an NRP work session

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    Neural coding by impulses and trains on single and multiple channels, and representation of information in nonimpulse carrier

    Summation of visual and mechanosensory feedback in Drosophila flight control

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    The fruit fly Drosophila melanogaster relies on feedback from multiple sensory modalities to control flight maneuvers. Two sensory organs, the compound eyes and mechanosensory hindwings called halteres, are capable of encoding angular velocity of the body during flight. Although motor reflexes driven by the two modalities have been studied individually, little is known about how the two sensory feedback channels are integrated during flight. Using a specialized flight simulator we presented tethered flies with simultaneous visual and mechanosensory oscillations while measuring compensatory changes in stroke kinematics. By varying the relative amplitude, phase and axis of rotation of the visual and mechanical stimuli, we were able to determine the contribution of each sensory modality to the compensatory motor reflex. Our results show that over a wide range of experimental conditions sensory inputs from halteres and the visual system are combined in a weighted sum. Furthermore, the weighting structure places greater influence on feedback from the halteres than from the visual system

    Neuromechanical Analysis of Locust Jumping

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    The nervous systems of animals evolved to exert dynamic control of behavior in response to the needs of the animal and changing signals from the environment. To understand the mechanisms of dynamic control, we need a means of predicting how individual neural and body elements will interact to produce the performance of the entire system. We have developed a neuromechanical application named AnimatLab that addresses this problem through simulation. A computational model of a body and nervous system can be constructed from simple components and situated in a virtual world for testing. Simulations and live experiments were used to investigate questions about locust jumping. The neural circuitry and biomechanics of kicking in locusts have been extensively studied. It has been hypothesized that the same neural circuit and biomechanics governed both behaviors, but this hypothesis was not testable with current technology. We built a neuromechanical model to test this and to gain a better understanding of the role of the semi-lunar process (SLP) in jump dynamics. The SLP are bands of cuticle that store energy for use during jumping. The results of the model were compared to a variety of published data and were similar. The SLP significantly increased jump distance, power, total energy, and duration of the jump impulse. Locust can jump precisely to a target, but also exhibit tumbling. We proposed two mechanisms for controlling tumbling during the jump. The first was that locusts adjust the pitch of their body prior to the jump to move the center of mass closer to the thrust vector. The second was that contraction of the abdominal muscles during the jump produced torques that countered the torque due to thrust. There was a strong correlation relating increased pitch and takeoff angle. In simulations there was an optimal pitch-takeoff combination that minimized tumbling that was similar to the live data. The direction and magnitude of tumbling could be controlled by adjusting abdominal tension. Tumbling also influenced jump elevation. Neuromechanical simulation addressed problems that would be difficult to examine using traditional physiological approaches. It is a powerful tool for understanding the neural basis of behavior

    Linear and Nonlinear Encoding Properties of an Identified Mechanoreceptor on the Fly wing Measured with Mechanical Noise Stimuli

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    The wing blades of most flies contain a small set of distal campaniform sensilla, mechanoreceptors that respond to deformations of the cuticle. This paper describes a method of analysis based upon mechanical noise stimuli which is used to quantify the encoding properties of one of these sensilla (the d-HCV cell) on the wing of the blowfly Calliphora vomitoria (L.). The neurone is modelled as two components, a linear filter that accounts for the frequency response and phase characteristics of the cell, followed by a static nonlinearity that limits the spike discharge to a narrow portion of the stimulus cycle. The model is successful in predicting the response of campaniform neurones to arbitrary stimuli, and provides a convenient method for quantifying the encoding properties of the sensilla. The d-HCV neurone is only broadly frequency tuned, but its maximal response near 150 Hz corresponds to the wingbeat frequency of Calliphora. In the range of frequencies likely to be encountered during flight, the d-HCV neurone fires a single phase-locked action potential for each stimulus cycle. The phase lag of the cell decreases linearly with increasing frequency such that the absolute delay between stimulus and response remains nearly constant. Thus, during flight the neurone is capable of firing one precisely timed action potential during each wingbeat, and might be used to modulate motor activity that requires afferent input on a cycle-by-cycle basis

    Multimodal Proprioceptive Integration in Sensorimotor Networks of an Insect Leg

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    An animal’s nervous system monitors the actions of the body using its sense of proprioception. This information is used for precise motor control and to enable coordinated interaction with the animal’s surroundings. Proprioception is a multimodal sense that includes feedback about limb movement and loading from various peripheral sense organs. The sensory information from distinct sense organs must be integrated by the network to form a coherent representation of the current proprioceptive state and to elicit appropriate motor behavior. By combining intra- and extracellular electrophysiological recording techniques with precise mechanical sensory stimulation paradigms, I studied multimodal proprioceptive integration in the sensorimotor network of the stick insect leg. The findings demonstrate where, when, and how sensory feedback from load-sensing campaniform sensilla (CS) is integrated with movement information from the femoral chordotonal organ (fCO) in the sensorimotor network controlling movement of the femur-tibia (FTi) joint. Proprioceptive information about distinct sensory modalities (load / movement) and from distinct sense organs of the same sensory modality (trochanterofemoral CS (tr/fCS) / tibial CS (tiCS)) was distributed into one network of local premotor nonspiking interneurons (NSIs). The NSIs’ processing of fCO, tr/fCS, and tiCS was antagonistic with respect to a given NSI’s effect on the motor output of extensor tibiae motor neurons (ExtTi MNs). Spatial summation of load and movement feedback occurred in the network of premotor NSIs, whereas temporal summation was shifted between sensory modalities. Load feedback (tr/fCS / tiCS) was consistently delayed relative to movement signals (fCO) throughout the sensorimotor pathways of sensory afferents, premotor NSIs, and ExtTi MNs. The connectivity between these neuron types was inferred using transmission times and followed distinct patterns for individual sense organs. At the motor output level of the system, the temporal shift of simultaneously elicited load and movement feedback caused load responses to be superimposed onto ongoing movement responses. These results raised the hypothesis that load could alter movement signal processing. Load (tiCS) affected movement (fCO) signal gain by presynaptic afferent inhibition. In postsynaptic premotor NSIs, this led to altered movement parameter dependence and nonlinear summation of load and movement signals. Specifically, the amplitude dependence of NSIs opposing ExtTi MN output was increased, and, consistently, the movement response gain of the slow ExtTi MN was decreased. Movement signal processing in the premotor network was altered depending on the proprioceptive context, i.e. the presence or absence of load feedback. Lateral presynaptic interactions between load (tiCS) and movement (fCO) afferents were reciprocal, i.e. existed from fCO to tiCS afferents and vice versa, and also occurred between sensory afferents of the same sense organ. Additionally, a new type of presynaptic interaction was identified. Load signals increased the gain of directional movement information by releasing unidirectionally velocity- or acceleration-sensitive fCO afferents from tonic presynaptic inhibition. Paired double recordings showed lateral connectivity also at the level of the premotor NSI network. NSIs interacted via reciprocal excitatory connections. Additionally, the activity of individual NSIs was correlated in the absence of external stimuli, and specific types of NSIs showed rhythmic 30 Hz oscillations of the resting membrane potential, indicating an underlying mechanism of network synchronization. Taken together, the results of this dissertation provide an understanding of the integration of multimodal proprioceptive feedback in the sensorimotor network by identifying neuronal pathways and mechanism underlying spatial and temporal signal summation. The local network uses multimodal signal integration for context-dependent sensory processing, thereby providing insights into the mechanism by which a local network can adapt sensory processing to the behavioral context. Initial results clearly highlight the necessity to consider lateral connections along sensorimotor pathways to unravel the complex computations underlying proprioceptive processing and motor control. The findings on the integration of proprioceptive signals, obtained in the resting animal, broaden our understanding of sensorimotor processing and motor control not only in the stationary, but also in the walking animal
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