Publications
78 results found
Gremillion G, Galfond M, Krapp HG, et al., 2012, Biomimetic Sensing and Modeling of the Ocelli Visual System of Flying Insects, 25th IEEE\RSJ International Conference on Intelligent Robots and Systems (IROS), Publisher: IEEE, Pages: 1454-1459, ISSN: 2153-0858
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- Citations: 2
Saleem AB, Longden KD, Schwyn DA, et al., 2012, Bimodal optomotor response to plaids in blowflies: mechanisms of component-selectivity and evidence for pattern-selectivity, Journal of Neuroscience
Krapp HG, Taylor GK, Humbert JS, 2012, The mode-sensing hypothesis: matching sensors, actuators and flight dynamics, FRONTIERS IN SENSING: FROM BIOLOGY TO ENGINEERING, Editors: Barth, Humphrey, Srinivasan, Publisher: SPRINGER-VERLAG WIEN, Pages: 101-114, ISBN: 978-3-211-99748-2
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- Citations: 6
Ejaz N, Tanaka RJ, Krapp HG, 2011, Closed-loop performance of a proportional controller for visual stabilization using a fly-robot interface, Pages: 1509-1515
The blowfly Calliphora is the model of choice for studying sensori-motor control principles common in biological systems. We present a fly-robot interface where the neural activity of an identified visual interneuron is used to control the angular velocity of a rotating robot. By placing the robot on a rotating turn-table in a visual arena, we use the fly-robot interface to quantify the dynamics and performance of a proportional controller in a closed-loop visual stabilization system. The properties of the system were characterized for both step and frequency responses. We analysed the data using a performance index based on the input-output energy dissipated by the controller. Our results suggest that the optimal strategy for the fly to minimize the visual slip speed would be to tune the closed-loop gain to the angular velocity and angular acceleration of the input stimuli. The design principles discovered by reverse-engineering sensori-motor control in to develop the next generation of autonomous robots and smart sensors. © 2011 IEEE.
Longden KD, Krapp HG, 2011, Sensory Neurophysiology: Motion Vision during Motor Action (vol 21, pg R650, 2011), CURRENT BIOLOGY, Vol: 21, Pages: 1684-1684, ISSN: 0960-9822
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- Citations: 4
Longden KD, Krapp HG, 2011, Sensory Neurophysiology: Motion Vision during Motor Action, CURRENT BIOLOGY, Vol: 21, Pages: R650-R652, ISSN: 0960-9822
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- Citations: 5
Ejaz N, Peterson KD, Krapp HG, 2011, An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces, JOVE-JOURNAL OF VISUALIZED EXPERIMENTS, ISSN: 1940-087X
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- Citations: 4
Schwyn DA, Heras FJH, Bolliger G, et al., 2011, Interplay between Feedback and Feedforward Control in Fly Gaze Stabilization, 18th IFAC World Congress
Hyslop A, Krapp HG, Humbert JS, 2010, Control theoretic interpretation of directional motion preferences in optic flow processing interneurons, BIOLOGICAL CYBERNETICS, Vol: 103, Pages: 353-364, ISSN: 0340-1200
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- Citations: 24
Parsons MM, Krapp HG, Laughlin SB, 2010, Sensor Fusion in Identified Visual Interneurons, CURRENT BIOLOGY, Vol: 20, Pages: 624-628, ISSN: 0960-9822
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- Citations: 40
Krapp HG, 2010, Sensorimotor Transformation: From Visual Responses to Motor Commands, CURRENT BIOLOGY, Vol: 20, Pages: R236-R239, ISSN: 0960-9822
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- Citations: 4
Rogers SM, Harston GWJ, Kilburn-Toppin F, et al., 2010, Spatiotemporal Receptive Field Properties of a Looming-Sensitive Neuron in Solitarious and Gregarious Phases of the Desert Locust, J NEUROPHYSIOL, Vol: 103, Pages: 779-792, ISSN: 0022-3077
Rogers SM, Harston GWJ, Kilburn-Toppin F, Matheson T, Burrows M, Gabbiani F, Krapp HG. Spatiotemporal receptive field properties of a looming-sensitive neuron in solitarious and gregarious phases of the Desert Locust. J Neurophysiol 103: 779-792, 2010. First published December 2, 2009; doi: 10.1152/jn.00855.2009. Desert locusts (Schistocerca gregaria) can transform reversibly between the swarming gregarious phase and a solitarious phase, which avoids other locusts. This transformation entails dramatic changes in morphology, physiology, and behavior. We have used the lobula giant movement detector (LGMD) and its postsynaptic target, the descending contralateral movement detector (DCMD), which are visual inter-neurons that detect looming objects, to analyze how differences in the visual ecology of the two phases are served by altered neuronal function. Solitarious locusts had larger eyes and a greater degree of binocular overlap than those of gregarious locusts. The receptive field to looming stimuli had a large central region of nearly equal response spanning 120 degrees x 60 degrees in both phases. The DCMDs of gregarious locusts responded more strongly than solitarious locusts and had a small caudolateral focus of even further sensitivity. More peripherally, the response was reduced in both phases, particularly ventrally, with gregarious locusts showing greater proportional decrease. Gregarious locusts showed less habituation to repeated looming stimuli along the eye equator than did solitarious locusts. By contrast, in other parts of the receptive field the degree of habituation was similar in both phases. The receptive field organization to looming stimuli contrasts strongly with the receptive field organization of the same neurons to nonlooming local-motion stimuli, which show much more pronounced regional variation. The DCMDs of both gregarious and solitarious locusts are able to detect approaching objects from across a wide expanse of visual space, but phase-s
Rogers SM, Harston GWJ, Kilburn-Toppin F, et al., 2010, Spatiotemporal Receptive Field Properties of a Looming-Sensitive Neuron in Solitarious and Gregarious Phases of the Desert Locust, JOURNAL OF NEUROPHYSIOLOGY, Vol: 103, Pages: 779-792, ISSN: 0022-3077
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- Citations: 27
Longden KD, Krapp HG, 2010, Octopaminergic modulation of temporal frequency coding in an identified optic flow-processing interneuron., Front Syst Neurosci, Vol: 4
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.
Yue X, Peterson K, Krapp HG, et al., 2010, A Low-Power Low-Distortion Amplifier for Fly Neural Recordings, 4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE), Publisher: IEEE, ISSN: 2151-7614
Longden KD, Krapp HG, 2009, State-Dependent Performance of Optic-Flow Processing Interneurons, JOURNAL OF NEUROPHYSIOLOGY, Vol: 102, Pages: 3606-3618, ISSN: 0022-3077
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- Citations: 56
Huston SJ, Krapp HG, 2009, Nonlinear Integration of Visual and Haltere Inputs in Fly Neck Motor Neurons, JOURNAL OF NEUROSCIENCE, Vol: 29, Pages: 13097-13105, ISSN: 0270-6474
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- Citations: 72
Krapp HG, 2009, Ocelli, CURRENT BIOLOGY, Vol: 19, Pages: R435-R437, ISSN: 0960-9822
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- Citations: 39
Krapp HG, 2009, Sensory Integration: Neuronal Adaptations for Robust Visual Self-Motion Estimation, CURRENT BIOLOGY, Vol: 19, Pages: R413-R416, ISSN: 0960-9822
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- Citations: 5
Huston SJ, Krapp HG, 2008, Visuomotor transformation in the fly gaze stabilization system, PLOS BIOLOGY, Vol: 6, Pages: 1468-1478, ISSN: 1545-7885
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- Citations: 69
Saleem AB, Krapp HG, Schultz SR, 2008, Receptive field characterisation by spike-triggered independent component analysis, Journal of Vision, Pages: in press-16
Krapp HG, 2007, Polarization vision: How insects find their way by watching the sky, CURRENT BIOLOGY, Vol: 17, Pages: R557-R560, ISSN: 0960-9822
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- Citations: 8
Rogers SM, Krapp HG, Burrows M, et al., 2007, Compensatory plasticity at an identified synapse tunes a visuomotor pathway, JOURNAL OF NEUROSCIENCE, Vol: 27, Pages: 4621-4633, ISSN: 0270-6474
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- Citations: 25
Peron SP, Krapp HG, Gabbiani F, 2007, Influence of electrotonic structure and synaptic mapping on the receptive field properties of a collision-detecting neuron, JOURNAL OF NEUROPHYSIOLOGY, Vol: 97, Pages: 159-177, ISSN: 0022-3077
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- Citations: 24
Taylor GK, Krapp HG, 2007, Sensory systems and flight stability: What do insects measure and why?, ADVANCES IN INSECT PHYSIOLOGY: INSECT MECHANICS AND CONTROL, Vol: 34, Pages: 231-316, ISSN: 0065-2806
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- Citations: 200
Gabbiani F, Krapp HG, 2006, Spike-frequency adaptation and intrinsic properties of an identified, looming-sensitive neuron, JOURNAL OF NEUROPHYSIOLOGY, Vol: 96, Pages: 2951-2962, ISSN: 0022-3077
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- Citations: 42
Parsons MM, Krapp HG, Laughlin SB, 2006, A motion-sensitive neurone responds to signals from the two visual systems of the blowfly, the compound eyes and ocelli, JOURNAL OF EXPERIMENTAL BIOLOGY, Vol: 209, Pages: 4464-4474, ISSN: 0022-0949
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- Citations: 46
Karmeier K, Krapp HG, Egelhaaf M, 2005, Population coding of self-motion: Applying Bayesian analysis to a population of visual Interneurons in the fly, JOURNAL OF NEUROPHYSIOLOGY, Vol: 94, Pages: 2182-2194, ISSN: 0022-3077
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- Citations: 27
Krapp HG, Gabbiani F, 2005, Spatial distribution of inputs and local receptive field properties of a wide-field, looming sensitive neuron, JOURNAL OF NEUROPHYSIOLOGY, Vol: 93, Pages: 2240-2253, ISSN: 0022-3077
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- Citations: 52
Franz MO, Chahl JS, Krapp HG, 2004, Insect-inspired estimation of egomotion, NEURAL COMPUTATION, Vol: 16, Pages: 2245-2260, ISSN: 0899-7667
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- Citations: 46
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