Fabrizio Gabbiani

Multiplexing of motor information in the discharge of a collision detecting neuron during escape behaviors.

Locusts possess an identified neuron, the descending contralateral movement detector (DCMD), conveying visual information about impending collision from the brain to thoracic motor centers. We built a telemetry system to simultaneously record, in freely behaving animals, the activity of the DCMD and of motoneurons involved in jump execution. Cocontraction of antagonistic leg muscles, a required preparatory phase, was triggered after the DCMD firing rate crossed a threshold. Thereafter, the number of DCMD spikes predicted precisely motoneuron activity and jump occurrence. Additionally, the time of DCMD peak firing rate predicted that of jump. Ablation experiments suggest that the DCMD, together with a nearly identical ipsilateral descending neuron, is responsible for the timely execution of the escape. Thus, three distinct features that are multiplexed in a single neurons sensory response to impending collision-firing rate threshold, peak firing time, and spike count-probably control three distinct motor aspects of escape behaviors.

Precise Subcellular Input Retinotopy and Its Computational Consequences in an Identified Visual Interneuron

The Lobula Giant Movement Detector (LGMD) is a higher-order visual interneuron of Orthopteran insects that responds preferentially to objects approaching on a collision course. It receives excitatory input from an entire visual hemifield that anatomical evidence suggests is retinotopic. We show that this excitatory projection activates calcium-permeable nicotinic acetylcholine receptors. In vivo calcium imaging reveals that the excitatory projection preserves retinotopy down to the level of a single ommatidium. Examining the impact of retinotopy on the LGMDs computational properties, we show that sublinear synaptic summation can explain orientation preference in this cell. Exploring retinotopys impact on directional selectivity leads us to infer that the excitatory input to the LGMD is intrinsically directionally selective. Our results show that precise retinotopy has implications for the dendritic integration of visual information in a single neuron.

Collision-avoidance behaviors of minimally restrained flying locusts to looming stimuli

SUMMARY Visually guided collision avoidance is of paramount importance in flight, for instance to allow escape from potential predators. Yet, little is known about the types of collision-avoidance behaviors that may be generated by flying animals in response to an impending visual threat. We studied the behavior of minimally restrained locusts flying in a wind tunnel as they were subjected to looming stimuli presented to the side of the animal, simulating the approach of an object on a collision course. Using high-speed movie recordings, we observed a wide variety of collision-avoidance behaviors including climbs and dives away from – but also towards – the stimulus. In a more restrained setting, we were able to relate kinematic parameters of the flapping wings with yaw changes in the trajectory of the animal. Asymmetric wing flapping was most strongly correlated with changes in yaw, but we also observed a substantial effect of wing deformations. Additionally, the effect of wing deformations on yaw was relatively independent of that of wing asymmetries. Thus, flying locusts exhibit a rich range of collision-avoidance behaviors that depend on several distinct aerodynamic characteristics of wing flapping flight.

Logarithmic Compression of Sensory Signals within the Dendritic Tree of a Collision-Sensitive Neuron

Neurons in a variety of species, both vertebrate and invertebrate, encode the kinematics of objects approaching on a collision course through a time-varying firing rate profile that initially increases, then peaks, and eventually decays as collision becomes imminent. In this temporal profile, the peak firing rate signals when the approaching objects subtended size reaches an angular threshold, an event which has been related to the timing of escape behaviors. In a locust neuron called the lobula giant motion detector (LGMD), the biophysical basis of this angular threshold computation relies on a multiplicative combination of the objects angular size and speed, achieved through a logarithmic-exponential transform. To understand how this transform is implemented, we modeled the encoding of angular velocity along the pathway leading to the LGMD based on the experimentally determined activation pattern of its presynaptic neurons. These simulations show that the logarithmic transform of angular speed occurs between the synaptic conductances activated by the approaching object onto the LGMDs dendritic tree and its membrane potential at the spike initiation zone. Thus, we demonstrate an example of how a single neurons dendritic tree implements a mathematical step in a neural computation important for natural behavior.

Impact of neural noise on a sensory-motor pathway signaling impending collision

Noise is a major concern in circuits processing electrical signals, including neural circuits. There are many factors that influence how noise propagates through neural circuits, and there are few systems in which noise levels have been studied throughout a processing pathway. We recorded intracellularly from multiple stages of a sensory-motor pathway in the locust that detects approaching objects. We found that responses are more variable and that signal-to-noise ratios (SNRs) are lower further from the sensory periphery. SNRs remain low even with the use of stimuli for which the pathway is most selective and for which the neuron representing its final sensory level must integrate many synaptic inputs. Modeling of this neuron shows that variability in the strength of individual synaptic inputs within a large population has little effect on the variability of the spiking output. In contrast, jitter in the timing of individual inputs and spontaneous variability is important for shaping the responses to preferred stimuli. These results suggest that neural noise is inherent to the processing of visual stimuli signaling impending collision and contributes to shaping neural responses along this sensory-motor pathway.

Escape Behavior: Linking Neural Computation to Action

A new study uses a combination of physiological and optogenetic techniques to identify visual neurons in fruit flies that detect approaching objects, and whose activation is integral in escaping an oncoming threat.

Biophysics of object segmentation in a collision-detecting neuron

Collision avoidance is critical for survival, including in humans, and many species possess visual neurons exquisitely sensitive to objects approaching on a collision course. Here, we demonstrate that a collision-detecting neuron can detect the spatial coherence of a simulated impending object, thereby carrying out a computation akin to object segmentation critical for proper escape behavior. At the cellular level, object segmentation relies on a precise selection of the spatiotemporal pattern of synaptic inputs by dendritic membrane potential-activated channels. One channel type linked to dendritic computations in many neural systems, the hyperpolarization-activated cation channel, HCN, plays a central role in this computation. Pharmacological block of HCN channels abolishes the neurons spatial selectivity and impairs the generation of visually guided escape behaviors, making it directly relevant to survival. Additionally, our results suggest that the interaction of HCN and inactivating K+ channels within active dendrites produces neuronal and behavioral object specificity by discriminating between complex spatiotemporal synaptic activation patterns.

Pre-synaptic Muscarinic Excitation Enhances the Discrimination of Looming Stimuli in a Collision-Detection Neuron

SUMMARY Visual neurons that track objects on a collision course are often finely tuned to their target stimuli because this is critical for survival. The presynaptic neural networks converging on these neurons and their role in tuning them remain poorly understood. We took advantage of well-known characteristics of one such neuron in the grasshopper visual system to investigate the properties of its presynaptic input network. We find the structure more complex than hitherto realized. In addition to dynamic lateral inhibition used to filter out background motion, presynaptic circuits include normalizing inhibition and excitatory interactions mediated by muscarinic acetylcholine receptors. These interactions preferentially boost responses to coherently expanding visual stimuli generated by colliding objects, as opposed to spatially incoherent controls, helping to discriminate between them. Hence, in addition to active dendritic conductances within collision-detecting neurons, multiple layers of inhibitory and excitatory presynaptic connections are needed to finely tune neural circuits for collision detection.

Feedforward Inhibition Conveys Time-Varying Stimulus Information in a Collision Detection Circuit

Feedforward inhibition is ubiquitous as a motif in the organization of neuronal circuits. During sensory information processing, it is traditionally thought to sharpen the responses and temporal tuning of feedforward excitation onto principal neurons. As it often exhibits complex time-varying activation properties, feedforward inhibition could also convey information used by single neurons to implement dendritic computations on sensory stimulus variables. We investigated this possibility in a collision-detecting neuron of the locust optic lobe that receives both feedforward excitation and inhibition. We identified a small population of neurons mediating feedforward inhibition, with wide visual receptive fields and whose responses depend both on the size and speed of moving stimuli. By studying responses to simulated objects approaching on a collision course, we determined that they jointly encode the angular size of expansion of the stimulus. Feedforward excitation, on the other hand, encodes a function of the angular velocity of expansion and the targeted collision-detecting neuron combines these two variables non-linearly in its firing output. Thus, feedforward inhibition actively contributes to the detailed firing-rate time course of this collision-detecting neuron, a feature critical to the appropriate execution of escape behaviors. These results suggest that feedforward inhibition could similarly convey time-varying stimulus information in other neuronal circuits.

Optogenetic manipulation of medullary neurons in the locust optic lobe

The locust is a widely used animal model for studying sensory processing and its relation to behavior. Due to the lack of genomic information, genetic tools to manipulate neural circuits in locusts are not yet available. We examined whether Semliki Forest virus is suitable to mediate exogenous gene expression in neurons of the locust optic lobe. We subcloned a channelrhodopsin variant and the yellow fluorescent protein Venus into a Semliki Forest virus vector and injected the virus into the optic lobe of locusts ( Schistocerca americana). Fluorescence was observed in all injected optic lobes. Most neurons that expressed the recombinant proteins were located in the first two neuropils of the optic lobe, the lamina and medulla. Extracellular recordings demonstrated that laser illumination increased the firing rate of medullary neurons expressing channelrhodopsin. The optogenetic activation of the medullary neurons also triggered excitatory postsynaptic potentials and firing of a postsynaptic, looming-sensitive neuron, the lobula giant movement detector. These results indicate that Semliki Forest virus is efficient at mediating transient exogenous gene expression and provides a tool to manipulate neural circuits in the locust nervous system and likely other insects. NEW & NOTEWORTHY Using Semliki Forest virus, we efficiently delivered channelrhodopsin into neurons of the locust optic lobe. We demonstrate that laser illumination increases the firing of the medullary neurons expressing channelrhodopsin and elicits excitatory postsynaptic potentials and spiking in an identified postsynaptic target neuron, the lobula giant movement detector neuron. This technique allows the manipulation of neuronal activity in locust neural circuits using optogenetics.