Sensory Integration: Neuronal Adaptations for Robust Visual Self-Motion Estimation

SummaryRecent studies on the fly visual system have revealed how the morphology of visual interneurons and their lateral electrical connectivity helps overcome a notorious problem in visuomotor control — the ambiguity of local sensor signals

Visuomotor Transformation in the Fly Gaze Stabilization System

For sensory signals to control an animal's 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 animal's 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

Octopaminergic Modulation of Temporal Frequency Coding in an Identified Optic Flow-Processing Interneuron

Flying generates predictably different patterns of optic flow compared with other locomotor states. A sensorimotor system tuned to rapid responses and a high bandwidth of optic flow would help the animal to avoid wasting energy through imprecise motor action. However, neural processing that covers a higher input bandwidth itself comes at higher energetic costs which would be a poor investment when the animal was not flying. How does the blowfly adjust the dynamic range of its optic flow-processing neurons to the locomotor state? Octopamine (OA) is a biogenic amine central to the initiation and maintenance of flight in insects. We used an OA agonist chlordimeform (CDM) to simulate the widespread OA release during flight and recorded the effects on the temporal frequency coding of the H2 cell. This cell is a visual interneuron known to be involved in flight stabilization reflexes. The application of CDM resulted in (i) an increase in the cell's spontaneous activity, expanding the inhibitory signaling range (ii) an initial response gain to moving gratings (20–60 ms post-stimulus) that depended on the temporal frequency of the grating and (iii) a reduction in the rate and magnitude of motion adaptation that was also temporal frequency-dependent. To our knowledge, this is the first demonstration that the application of a neuromodulator can induce velocity-dependent alterations in the gain of a wide-field optic flow-processing neuron. The observed changes in the cell's response properties resulted in a 33% increase of the cell's information rate when encoding random changes in temporal frequency of the stimulus. The increased signaling range and more rapid, longer lasting responses employed more spikes to encode each bit, and so consumed a greater amount of energy. It appears that for the fly investing more energy in sensory processing during flight is more efficient than wasting energy on under-performing motor control

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

The non-stationary nature and variability of neuronal signals is a fundamental problem in brain-machine interfacing. We developed a brain-machine interface to assess the robustness of different control-laws applied to a closed-loop image stabilization task. Taking advantage of the well-characterized fly visuomotor pathway we record the electrical activity from an identified, motion-sensitive neuron, H1, to control the yaw rotation of a two-wheeled robot. The robot is equipped with 2 high-speed video cameras providing visual motion input to a fly placed in front of 2 CRT computer monitors. The activity of the H1 neuron indicates the direction and relative speed of the robot's rotation. The neural activity is filtered and fed back into the steering system of the robot by means of proportional and proportional/adaptive control. Our goal is to test and optimize the performance of various control laws under closed-loop conditions for a broader application also in other brain machine interfaces

Early visual experience and the receptive-field organization of optic flow processing interneurons in the fly motion pathway

Karmeier K, Tabor R, Egelhaaf M, Krapp HG. Early visual experience and the receptive-field organization of optic flow processing interneurons in the fly motion pathway. Visual neuroscience. 2001;18(1):1-8.The distribution of local preferred directions and motion sensitivities within the receptive fields of so-called tangential neurons in the fly visual system was previously found to match optic flow fields as induced by certain self-motions. The complex receptive-field organization of the tangential neurons and the recent evidence showing that the orderly development of the fly's peripheral visual system depends on visual experience led us to investigate whether or not early visual input is required to establish the functional receptive field properties of such tangential neurons. In electrophysiological investigations of two identified tangential neurons, it turned out that dark-hatched flies which were kept in complete darkness for 2 days develop basically the same receptive-field organization as flies which were raised under seasonal light/dark conditions and were free to move in their cages. We did not find any evidence that the development of the sophisticated receptive-field organization of tangential neurons depends on sensory experience. Instead, the input to the tangential neurons seems to be "hardwired" and the specificity of these cells to optic flow induced during self-motions of the animal may have evolved on a phylogenetical time scale

Computation of Object Approach by a Wide-Field, Motion-Sensitive Neuron

The lobula giant motion detector (LGMD) in the locust visual system is a wide-field, motion-sensitive neuron that responds vigorously to objects approaching the animal on a collision course. We investigated the computation performed by LGMD when it responds to approaching objects by recording the activity of its postsynaptic target, the descending contralateral motion detector (DCMD). In each animal, peak DCMD activity occurred a fixed delay δ (15 ≤ δ ≤ 35 msec) after the approaching object had reached a specific angular threshold θthres on the retina (15° ≤ θthres ≤ 40°). θthres was independent of the size or velocity of the approaching object. This angular threshold computation was quite accurate: the error of LGMD and DCMD in estimating θthres(3.1–11.9°) corresponds to the angular separation between two and six ommatidia at each edge of the expanding object on the locust retina. It was also resistant to large amplitude changes in background luminosity, contrast, and body temperature. Using several experimentally derived assumptions, the firing rate of LGMD and DCMD could be shown to depend on the product ψ(t − δ) · e^(−αθ(t−δ0)), where θ(t) is the angular size subtended by the object during approach, ψ(t) is the angular edge velocity of the object and the constant, and α is related to the angular threshold size [α = 1/tan(θthres^(/2))]. Because LGMD appears to receive distinct input projections, respectively motion- and size-sensitive, this result suggests that a multiplication operation is implemented by LGMD. Thus, LGMD might be an ideal model to investigate the biophysical implementation of a multiplication operation by single neurons

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

Egelhaaf M, Kern R, Krapp HG, Kretzberg J, Kurtz R, Warzecha A-K. Neural encoding of behaviourally relevant visual-motion information in the fly. Trends in Neurosciences. 2002;25(2):96-102.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

Nutritional State Modulates the Neural Processing of Visual Motion

SummaryFood deprivation alters the processing of sensory information, increasing neural activity in the olfactory and gustatory systems in animals across phyla [1–4]. Neural signaling is metabolically costly [5–9], and a hungry animal has limited energy reserves, so we hypothesized that neural activity in other systems may be downregulated by food deprivation. We investigated this hypothesis in the motion vision pathway of the blowfly. Like other animals [10–17], flies augment their motion vision when moving: they increase the resting activity and gain of visual interneurons supporting the control of locomotion and gaze [18–21]. In the present study, walking-induced changes in visual processing depended on the nutritional state—they decreased with food deprivation and recovered after subsequent feeding. We found that changes in the motion vision pathway depended on walking speed in a manner dependent on the nutritional state. Walking also reduced response latencies in visual interneurons, an effect not altered by food deprivation. Finally, the optomotor reflex that compensates for visual wide-field motion was reduced in food-deprived flies. Thus, walking augmented motion vision, but the effect was decreased when energy reserves were low. Our results suggest that energy limitations may drive the rebalancing of neural activity with changes in the nutritional state