Holger G. Krapp

Multiplicative computation in a visual neuron sensitive to looming.

Multiplicative operations are important in sensory processing, but their biophysical implementation remains largely unknown. We investigated an identified neuron (the lobula giant movement detector, LGMD, of locusts) whose output firing rate in response to looming visual stimuli has been described by two models, one of which involves a multiplication. In this model, the LGMD multiplies postsynaptically two inputs (one excitatory, one inhibitory) that converge onto its dendritic tree; in the other model, inhibition is presynaptic to the LGMD. By using selective activation and inactivation of pre- and postsynaptic inhibition, we show that postsynaptic inhibition has a predominant role, suggesting that multiplication is implemented within the neuron itself. Our pharmacological experiments and measurements of firing rate versus membrane potential also reveal that sodium channels act both to advance the response of the LGMD in time and to map membrane potential to firing rate in a nearly exponential manner. These results are consistent with an implementation of multiplication based on dendritic subtraction of two converging inputs encoded logarithmically, followed by exponentiation through active membrane conductances.

Sensory Systems and Flight Stability: What do Insects Measure and Why?

Abstract In the absence of much passive stability, flying insects rely upon active stabilisation, necessitating the provision of rich sensory feedback across a range of modalities. Here we consider from a sensory perspective what quantities flying insects measure, in order to ask from a mechanical perspective why they should want to do so. We consider each of the sensory modalities separately and uncover three general principles. Firstly, we find that insects have evolved to measure changes in kinematic state, rather than absolute state. For example, although the antennae may be loosely thought of as airspeed sensors, we show that they are configured as a sophisticated adaptive sensing system which is much more appropriate for measuring changes in airspeed than absolute airspeed. Secondly, we find that insect sensory systems are tuned to sense self-motion components in specific directions. For example, certain visual interneurons of flies operate as matched filters that are tuned to detect the optic flow fields induced specifically by rotation about one particular axis. Thirdly, we find that insects commonly combine sensory input from across modalities to form composite, multi-modal quantities which they use as feedback to the control system. For example, certain individually identified descending interneurons combine input from the compound eyes, ocelli, antennae, and cephalic wind-sensitive hairs into one composite signal which is then used in flight control. We infer from these three general organisational principles that insects are configured to sense excitation of their natural modes of motion. This natural-mode sensing hypothesis: (1) explains why insects should want to sense changes in state rather than absolute state; (2) predicts what specific directions of motion they should sense, and (3) specifies how sensory input from different modalities should be combined.

Neural encoding of behaviourally relevant visual-motion information in the fly

Information processing in visual systems is constrained by the spatial and temporal characteristics of the sensory input and by the biophysical properties of the neuronal circuits. Hence, to understand how visual systems encode behaviourally relevant information, we need to know about both the computational capabilities of the nervous system and the natural conditions under which animals normally operate. By combining behavioural, neurophysiological and computational approaches, it is now possible in the fly to assess adaptations that process visual-motion information under the constraints of its natural input. It is concluded that neuronal operating ranges and coding strategies appear to be closely matched to the inputs the animal encounters under behaviourally relevant conditions.

Wide-field, motion-sensitive neurons and matched filters for optic flow fields

Abstract. The receptive field organization of a class of visual interneurons in the fly brain (vertical system, or VS neurons) shows a striking similarity to certain self-motion-induced optic flow fields. The present study compares the measured motion sensitivities of the VS neurons (Krapp et al. 1998) to a matched filter model for optic flow fields generated by rotation or translation. The model minimizes the variance of the filter output caused by noise and distance variability between different scenes. To that end, prior knowledge about distance and self-motion statistics is incorporated in the form of a “world model”. We show that a special case of the matched filter model is able to predict the local motion sensitivities observed in some VS neurons. This suggests that their receptive field organization enables the VS neurons to maintain a consistent output when the same type of self-motion occurs in different situations.

Visuomotor Transformation in the Fly Gaze Stabilization System

For sensory signals to control an animals behavior, they must first be transformed into a format appropriate for use by its motor systems. This fundamental problem is faced by all animals, including humans. Beyond simple reflexes, little is known about how such sensorimotor transformations take place. Here we describe how the outputs of a well-characterized population of fly visual interneurons, lobula plate tangential cells (LPTCs), are used by the animals gaze-stabilizing neck motor system. The LPTCs respond to visual input arising from both self-rotations and translations of the fly. The neck motor system however is involved in gaze stabilization and thus mainly controls compensatory head rotations. We investigated how the neck motor system is able to selectively extract rotation information from the mixed responses of the LPTCs. We recorded extracellularly from fly neck motor neurons (NMNs) and mapped the directional preferences across their extended visual receptive fields. Our results suggest that—like the tangential cells—NMNs are tuned to panoramic retinal image shifts, or optic flow fields, which occur when the fly rotates about particular body axes. In many cases, tangential cells and motor neurons appear to be tuned to similar axes of rotation, resulting in a correlation between the coordinate systems the two neural populations employ. However, in contrast to the primarily monocular receptive fields of the tangential cells, most NMNs are sensitive to visual motion presented to either eye. This results in the NMNs being more selective for rotation than the LPTCs. Thus, the neck motor system increases its rotation selectivity by a comparatively simple mechanism: the integration of binocular visual motion information.

Nonlinear Integration of Visual and Haltere Inputs in Fly Neck Motor Neurons

Animals use information from multiple sensory organs to generate appropriate behavior. Exactly how these different sensory inputs are fused at the motor system is not well understood. Here we study how fly neck motor neurons integrate information from two well characterized sensory systems: visual information from the compound eye and gyroscopic information from the mechanosensory halteres. Extracellular recordings reveal that a subpopulation of neck motor neurons display “gating-like” behavior: they do not fire action potentials in response to visual stimuli alone but will do so if the halteres are coactivated. Intracellular recordings show that these motor neurons receive small, sustained subthreshold visual inputs in addition to larger inputs that are phase locked to haltere movements. Our results suggest that the nonlinear gating-like effect results from summation of these two inputs with the action potential threshold providing the nonlinearity. As a result of this summation, the sustained visual depolarization is transformed into a temporally structured train of action potentials synchronized to the haltere beating movements. This simple mechanism efficiently fuses two different sensory signals and may also explain the context-dependent effects of visual inputs on fly behavior.

Multiplication and stimulus invariance in a looming-sensitive neuron

Multiplicative operations and invariance of neuronal responses are thought to play important roles in the processing of neural information in many sensory systems. Yet the biophysical mechanisms that underlie both multiplication and invariance of neuronal responses in vivo, either at the single cell or at the network level, remain to a large extent unknown. Recent work on an identified neuron in the locust visual system (the LGMD neuron) that responds well to objects looming on a collision course towards the animal suggests that this cell represents a good model to investigate the biophysical basis of multiplication and invariance at the single neuron level. Experimental and theoretical results are consistent with multiplication being implemented by subtraction of two logarithmic terms followed by exponentiation via active membrane conductances, according to a x 1/b = exp(log(a) - log(b)). Invariance appears to be in part due to non-linear integration of synaptic inputs within the dendritic tree of this neuron.

A motion-sensitive neurone responds to signals from the two visual systems of the blowfly, the compound eyes and ocelli.

SUMMARY In the blowfly Calliphora vicina, lobula plate tangential cells (LPTCs) estimate self-motion by integrating local motion information from the compound eyes. Each LPTC is sensitive to a particular (preferred) rotation of the flys head. The fly can also sense rotation using its three ocelli (simple eyes), by comparing the light intensities measured at each ocellus. We report that an individually identified tangential cell, V1, responds in an apparently rotation-specific manner to stimulation of the ocelli. This effect was seen with or without additional stimulation of the compound eye. We delivered stimuli to the ocelli which mimicked rotation of the flys head close to that of the preferred axis of rotation of V1. Alternating between preferred and anti-preferred rotation elicited a strongly phasic response, the amplitude of which increased with the rate of change of light intensity at the ocelli. With combined stimulation of one compound eye and the ocelli, V1 displayed a robust response to ocellar stimuli over its entire response range. These findings provide the opportunity to study quantitatively the interactions of two different visual mechanisms which both encode the same variable - the animals rotation in space.

Insect-inspired estimation of egomotion

Tangential neurons in the fly brain are sensitive to the typical optic flow patterns generated during egomotion. In this study, we examine whether a simplified linear model based on the organization principles in tangential neurons can be used to estimate egomotion from the optic flow. We present a theory for the construction of an estimator consisting of a linear combination of optic flow vectors that incorporates prior knowledge about the distance distribution of the environment and about the noise and egomotion statistics of the sensor. The estimator is tested on a gantry carrying an omnidirectional vision sensor. The experiments show that the proposed approach leads to accurate and robust estimates of rotation rates, whereas translation estimates are of reasonable quality, albeit less reliable.

In Vivo Time- Resolved Microtomography Reveals the Mechanics of the Blowfly Flight Motor

Time-resolved X-ray microtomography permits a real-time view of the blowfly in flight at a previously unprecedented level of detail, revealing how the tiny steering muscles work.