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A Borst

Publications and source records attributed to A Borst.

At least 55 records · Page 3Linked to original sources
PubMed1993

Neural circuit tuning fly visual neurons to motion of small objects. II. Input organization of inhibitory circuit elements revealed by electrophysiological and optical recording techniques.

1. The FD1-cell in the visual system of the fly is an identified visual interneuron that is specifically tuned to motion of small objects. In the companion paper it was shown that this response property is mediated by one of the two CH-cells, the VCH-cell, that inhibits the FD1-cell by GABAergic synapses. Here the input organization of the two CH-cells is analyzed by both electrophysiological and optical recording techniques. 2. Both CH-cells are excited by front-to-back motion in the ipsilateral and by back-to-front motion in the contralateral visual field. They respond maximally to binocular rotatory motion about the vertical axis of the animal. The latter response is only slightly less than the sum of the corresponding monocular response components. The relative contribution of the ipsi-and contralateral eye to the binocular response varies considerably between flies. In extreme cases it is dominated by either the ipsi- or the contralateral eye. The two CH-cells are not equally sensitive along the vertical axis of the eye. The DCH-cell has its sensitivity maximum in the dorsal part, the VCH-cell in the ventral part of the visual field. 3. The CH-cells have two arborizations, a large one in the posterior part of the third visual neuropil, the lobula plate, and a smaller one in the ipsilateral ventrolateral brain. With the calcium-sensitive dye fura-2 as an activity marker, it is analyzed which of these branches of the CH-cells receive the ipsi- and contralateral motion input, respectively. During motion in the preferred direction within the ipsilateral visual field, calcium accumulates only in the CH-cells' main arborization in the lobula plate but not in their branches in the ventrolateral brain, indicating that the arborization in the lobula plate is postsynaptic to the ipsilateral input. In contrast, contralateral motion in the preferred direction leads to calcium accumulation in both arborizations, suggesting that both are postsynaptic to contralateral input elements. During preferred direction motion in the upper or lower part of the ipsilateral visual field, calcium accumulates in only dorsal or ventral branches of the CH-cells' arborization in the lobula plate, respectively, revealing that their ipsilateral motion input is organized retinotopically. Because this arborization, most likely, is also the main output terminal of the CH-cells, it is both pre- and postsynaptic. This specific neuronal design is discussed with respect to its consequences for the mechanism of tuning the FD1-cell to motion of small objects.

Animals↗
PubMed1992

Photo-ablation of single neurons in the fly visual system reveals neural circuit for the detection of small moving objects.

Many animals use relative motion to segregate objects from their background. Nerve cells tuned to this visual cue have been found in various animal groups, such as insects, amphibians, birds and mammals. Well examined examples are the figure detection (FD) cells in the visual system of the blowfly. The mechanism that tunes a particular FD-cell, the FD1-cell, to small-field motion is analyzed by injecting individual visual interneurons with a fluorescent dye and ablating them by illumination with a laser beam. In this way, it is shown that the FD1-cell acquires its specific spatial tuning by inhibitory input from an identified GABAergic cell, the ventral centrifugal horizontal (VCH)-cell which is most sensitive to coherent large-field motion in front of both eyes. For the first time, the detection of small objects by evaluation of their motion parallax, thus, can be attributed to synaptic interactions between identified neurons.

Animals↗
PubMed1992

Dendritic integration of motion information in visual interneurons of the blowfly.

Dendritic integration plays a key role in the way information is processed by nerve cells. The large motion-sensitive interneurons of the fly appear to be most appropriate for an investigation of this process. These cells are known to receive input from numerous local motion-sensitive elements and to control visually-guided optomotor responses (e.g., Trends Neurosci., 11 (1988) 351-358; Stavenga and Hardie, Facets of Vision, Springer, 1989). The retinotopic input organization of these cells allows for in vivo stimulation of selected parts of their dendritic tree with their natural excitatory and inhibitory synaptic input signals. By displaying motion in either the cells' preferred or null direction in different regions of the receptive field we found: (i) Responses to combinations of excitatory and inhibitory motion stimuli can be described as the sum of the two response components. (ii) Responses to combination of excitatory stimuli show saturation effects. The deviation from linear superposition depends on the distance and relative position of the activated synaptic sites on the dendrite and makes the responses almost insensitive to the number of activated input channels. (iii) The saturation level depends on different stimulus parameters, e.g. the velocity of the moving pattern. The cell still encodes velocity under conditions of spatial saturation. The results can be understood on the basis of passive dendritic integration of the signals of retinotopically organized local motion-detecting elements with opposite polarity.

Animals↗
PubMed1992

In vivo imaging of calcium accumulation in fly interneurons as elicited by visual motion stimulation.

The computation of motion plays a central role in visual orientation. The fly has been successfully used as a model system for analyzing the mechanisms underlying motion detection. Thereby, much attention has been paid to a neuronal circuit of individually identifiable neurons in the third visual ganglion that extracts different types of retinal motion patterns and converts these patterns into specific components of visual orientation behavior. The extended dendritic trees of these large cells are the sites of convergence of numerous spatially distributed local motion-sensitive elements. As is revealed by in vivo microfluorometric imaging, these cells accumulate calcium during activation by visual motion stimulation. The spatiotemporal pattern of calcium distribution shows the following characteristics: (i) calcium accumulation is first spatially restricted to those dendritic branches that are depolarized by the retinotopic input, (ii) during ongoing motion stimulation calcium may also accumulate throughout the cell and, in particular, in regions that do not receive direct synaptic input. These experiments successfully monitor the intracellular distribution of activity-dependent ions in visual interneurons of living animals stimulated by their natural synaptic input.

Animals↗
PubMed1992

Are there separate ON and OFF channels in fly motion vision?

Visual information is processed in a series of subsequent steps. The performance of each of these steps depends not only on the computations it performs itself but also on the representation of the visual surround on which it operates. Here we investigate the consequences of signal preprocessing for the performance of the motion-detection system of the fly. In particular, we analyze whether the retinal input signals are rectified and segregate into separate ON and OFF channels, which then feed independent parallel motion-detection pathways. We recorded the activity of an identified directionally selective interneuron (H1-cell) in response to apparent motion stimuli, i.e. sequential brightness changes at two neighboring locations in the visual field, as well as to brightness changes at only a single location. For apparent motion stimuli, the motion-dependent response component was determined by subtracting from the overall response to the individual stimulus components when presented alone. The following conclusions could be derived: (1) Apparent motion consisting of a sequence of increased or decreased brightness at two locations in the visual field have the same optimum interstimulus time interval (Fig. 3). (2) Sequences of brightness steps of like polarity (either increments or decrements) elicit positive and negative motion-dependent response components when mimicking motion in the cell's preferred and null direction, respectively. The motion-dependent response components are inverted in sign when the brightness steps of a stimulus sequence have a different polarity (Fig. 7). (3) The responses to the beginning and the end of a brightness pulse depend on the pulse duration. For pulse durations of less than 2 s, both events interact with each other (Fig. 9). All of these results do not provide any indication that the fly processes motion information in independent ON and OFF motion detectors. Brightness changes of both signs are rather represented at the input of the same movement detectors, and interactions between signals resulting from both brightness increments and decrements take their sign into account. This type of preprocessing of the retinal input is argued to render a motion-detection system particularly robust against noise.

Animals↗
PubMed1990

The role of GABA in detecting visual motion.

The basic computations underlying the extraction of motion from the visual environment have been characterized in great detail. A non-linear interaction, such as a multiplication, between neighbouring visual elements was shown to be the core of biological motion detectors in different species ranging from insects to man. GABA (gamma-aminobutyric acid)-ergic inhibitory synapses suppressing the responses to motion in one direction but not in the other are widely accepted to be the cellular basis for this non-linear interaction. Based on model predictions we can show in combined pharmacological and electrophysiological experiments that in the fly motion detection system GABAergic synapses do not play this role but rather are involved in another important step of motion computation. This makes a reconsideration of the role of inhibition in other motion detection systems necessary.

Animals↗
PubMed1990

Neuronal architecture of the antennal lobe in Drosophila melanogaster.

Computer reconstruction of the antennal lobe of Drosophila melanogaster has revealed a total of 35 glomeruli, of which 30 are located in the periphery of the lobe and 5 in its center. Several prominent glomeruli are recognizable by their location, size, and shape; others are identifiable only by their positions relative to prominent glomeruli. No obvious sexual dimorphism of the glomerular architecture was observed. Golgi impregnations revealed: (1) Five of the glomeruli are exclusive targets for ipsilateral antennal input, whereas all others receive afferents from both antennae. Unilateral amputation of the third antennal segment led to a loss of about 1000 fibers in the antennal commissure. Hence, about 5/6 of the approximately 1200 antennal afferents per side have a process that extends into the contralateral lobe. (2) Afferents from maxillary palps (most likely from basiconic sensilla) project into both ipsi- and contralateral antennal lobes, yet their target glomeruli are apparently not the same as those of antennal basiconic sensilla. (3) Afferents in the antennal lobe may also stem from pharyngeal sensilla. (4) The most prominent types of interneurons with arborizations in the antennal lobe are: (i) local interneurons ramifying in the entire lobe, (ii) unilateral relay interneurons that extend from single glomeruli into the calyx and the lateral protocerebrum (LPR), (iii) unilateral interneurons that connect several glomeruli with the LPR only, (iv) bilateral interneurons that link a small number of glomeruli in both antennal lobes with the calyx and LPR, (v) giant bilateral interneurons characterized by extensive ramifications in both antennal lobes and the posterior brain and a cell body situated in the midline of the suboesophageal ganglion, and (vi) a unilateral interneuron with extensive arborization in one antennal lobe and the posterior brain and a process that extends into the thorax. These structural results are discussed in the context of the available functional and behavioral data.

Animals↗
PubMed1990

Direction selectivity of blowfly motion-sensitive neurons is computed in a two-stage process.

Direction selectivity of motion-sensitive neurons is generally thought to result from the nonlinear interaction between the signals derived from adjacent image points. Modeling of motion-sensitive networks, however, reveals that such elements may still respond to motion in a rather poor directionally selective way. Direction selectivity can be significantly enhanced if the nonlinear interaction is followed by another processing stage in which the signals of elements with opposite preferred directions are subtracted from each other. Our electrophysiological experiments in the fly visual system suggest that here direction selectivity is acquired in such a two-stage process.

Animals↗
PubMed1989

Principles of visual motion detection.

Motion information is required for the solution of many complex tasks of the visual system such as depth perception by motion parallax and figure/ground discrimination by relative motion. However, motion information is not explicitly encoded at the level of the retinal input. Instead, it has to be computed from the time-dependent brightness patterns of the retinal image as sensed by the two-dimensional array of photoreceptors. Different models have been proposed which describe the neural computations underlying motion detection in various ways. To what extent do biological motion detectors approximate any of these models? As will be argued here, there is increasing evidence from the different disciplines studying biological motion vision, that, throughout the animal kingdom ranging from invertebrates to vertebrates including man, the mechanisms underlying motion detection can be attributed to only a few, essentially equivalent computational principles. Motion detection may, therefore, be one of the first examples in computational neurosciences where common principles can be found not only at the cellular level (e.g., dendritic integration, spike propagation, synaptic transmission) but also at the level of computations performed by small neural networks.

Animals↗
PubMed1989

Transient and steady-state response properties of movement detectors.

The transient and steady-state responses of movement detectors are studied at various pattern contrasts (i) by intracellularly recording from an identified movement-sensitive interneuron in the fly's brain and (ii) by comparing these results with computer simulations of an array of movement detectors of the correlation type. At the onset of stimulus motion, the membrane potential oscillates with a frequency corresponding to the temporal frequency of the stimulus pattern before it settles at its steady-state level. Both the transient and the steady-state response amplitudes show a characteristic contrast dependence. As is shown by computer modeling, the transient behavior that we found in the experiments reflects an intrinsic property of the general scheme of movement detectors of the correlation type. To account for the contrast dependence, however, this general scheme has to be elaborated by (i) a subtraction stage, which eliminates the background light intensity from the detector input signal, and (ii) saturation characteristics in both branches of each movement-detector subunit.

Animals↗
PubMed1989

Computational structure of a biological motion-detection system as revealed by local detector analysis in the fly's nervous system.

The computations performed by individual movement detectors are analyzed by intracellularly recording from an identified direction-selective motion-sensitive interneuron in the fly's brain and by comparing these results with model predictions based on movement detectors of the correlation type. Three main conclusions were drawn with respect to the movement-detection system of the fly: (1) The essential nonlinear interaction between the two movement-detector input channels can be characterized formally by a mathematically almost perfect multiplication process. (2) Even at high contrasts no significant nonlinearities seem to distort the time course of the movement-detector input signals. (3) The movement detectors of the fly are not perfectly antisymmetrical; i.e., they respond with different time courses and amplitudes to motion in their preferred and null directions. As a consequence of this property, the motion detectors can respond to some degree to stationary patterns whose brightness is modulated in time. Moreover, the direction selectivity, i.e., the relative difference of the responses to motion in the preferred and null directions, depends on the contrast and on the spatial-frequency content of the stimulus pattern.

Animals↗
PubMed1985

Drosophila mushroom body mutants are deficient in olfactory learning.

Two Drosophila mutants are described in which the connections between the input to and the output from the mushroom bodies is largely interrupted. In all forms of the flies (larva, imago, male, female) showing the structural defect, olfactory conditioning is impaired. Learning is completely abolished when electroshock is used as reinforcement and partially suppressed in reward learning with sucrose. No influence of the mushroom body defect on the perception of the conditioning stimuli or on spontaneous olfactory behavior is observed. The defect seems not to impair learning of color discrimination tasks or operant learning involving visual cues.

Animals↗
PubMed1982

Determination of n-dimensional reference ellipsoids using patient data.

A method is described for the calculation of n-dimensional reference ellipsoids, using patient data. The advantages and drawbacks of the use of reference ellipsoids for a set of different parameters, in contrast with the use of a reference range for every single parameter, are discussed. The use of reference ellipsoids in practice is illustrated with an example.

Albumins↗
PubMed1980

The use of patient data for the calculation of reference values for some haematological parameters.

We have investigated the use of patient data for the calculation of reference values for the parameters which are determined by the Hemalog. For this purpose we used the Bhattacharya plot. All the parameters, with the exception of leukocytes, appear to meet the main underlying assumption of this plot, namely that the frequency distribution is Gaussian. In the case of leukocytes, however, the frequency distribution could be resolved into two overlapping Gaussian curves, thus making it possible to calculate reference values for this parameter also. The reference values as calculated from 14,500 unselected data (excluding children) are in general agreement with the literature. Significant differences were however detected between a group of patients and a group of blood donors. When a Bhattacharya plot has to be constructed with relatively few data, smoothing of the observed frequencies is very helpful in deciding which part of the plot is linear. Smoothing was carried out using the least squares method with a quadratic equation. Since the classes are equally spaced, this involves only a simple numerical transformation of the frequencies.

Blood Donors↗