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H A Mastebroek

Publications and source records attributed to H A Mastebroek.

9 recordsLinked to original sources
PubMed1998

Neural coding in antennal olfactory cells of tsetse flies (Glossina spp.).

Spike trains from individual antennal olfactory cells of tsetse flies (Glossina spp.) obtained during steady-state conditions (spontaneous as well as during stimulation with 1-octen-3-ol) and dynamic stimulation with repetitive pulses of 1-octen-3-ol were investigated by studying the spike frequency and the temporal structure of the trains. In general, stimulation changes the intensity of the spike activity but leaves the underlying stochastic structure unaffected. This structure turns out to be a renewal process. The only independently varying parameter in this process is the mean interspike interval length, suggesting that olfactory cells of tsetse flies may transmit information via a frequency coding. In spike records with high firing rates, however, the stationary records had significant negative first-order serial correlation coefficients and were non-renewal. Some cells in this study were capable of precisely encoding the onset of the odour pulses at frequencies up to at least 3 Hz. Cells with a rapid return to pre-stimulus activity at the end of stimulation responded more adequately to pulsed stimuli than cells with a long increased spike frequency. While short-firing cells process information via a frequency code, long-firing cells responded with two distinctive phases: a phasic, non-renewal response and a tonic, renewal response which may function as a memory of previous stimulations.

Action Potentials↗
PubMed1993

Circadian control of visual information processing in the optic lobe of the giant cockroach Blaberus giganteus.

Extracellular spike activity from three different types of visual interneurons found in the optic lobe of the giant cockroach Blaberus giganteus was recorded. The spike rate of all three types of neurons fluctuated in a circadian manner in constant darkness (DD). Two types, so-called "on" neurons (ON1 and ON2), responded exclusively to stationary light stimuli. A static light pulse elicited a sustained component in ON1, whereas in ON2 only a brief transient response was observed. In ON1 neurons, responsiveness was high during the subjective night and low during the subjective day. The responsiveness of ON2 neurons had a peak during a few hours around subjective dusk and a smaller peak in the later subjective night. The third neuron type recorded consisted of a directionally selective motion-detecting (DSMD) neuron. The pure intensity response and the motion response of the DSMD neuron were high during the subjective day and low during the subjective night. The results show that visual interneurons in the optic lobes are influenced differently by the circadian oscillator system. It is suggested that the mode of circadian control depends on the role a neuron plays in the process of visual information processing.

Animals↗
PubMed1991

Circadian inputs influence the performance of a spiking, movement-sensitive neuron in the visual system of the blowfly.

Long-term extracellular recordings from a spiking, movement-sensitive giant neuron (H1) in the third optic ganglion of the blowfly Calliphora vicina (L.) revealed periodic endogenous sensitivity fluctuations. The sensitivity changes showed properties typical of an endogenous circadian rhythm. This was true for the responses in reaction to intensity changes of visual patterns as well as for the responses elicited by pattern movement. For these two types of stimuli, the circadian fluctuations were comparable, but the envelope in the case of responses to movement was more robust. A circadian fluctuation in responses to movement is, therefore, present at the level of single elementary movement detectors. The tonic activity of the neuron was also shown to be under circadian control. In constant darkness (DD) the fluctuation was circadian, whereas in constant light it was not. The subjective light-dark (LD) transitions in the tonic activity in DD closely followed the LD transitions in the holding cages initially; that is, there was low activity at night and high activity during the daytime. The sensitivity fluctuations in response to visual stimuli led the tonic spike activity fluctuations by several hours.

Animals↗
PubMed1990

The computational measurement of apparent motion: a recurrent pattern recognition strategy as an approach to solve the correspondence problem.

In short, the model consists of a two-dimensional set of edge detecting units, modelled according to the zero-crossing detectors introduced first by Marr and Ullman (1981). These detectors are located peripherally in our synthetic vision system and are the input elements for an intelligent recurrent network. The purpose of that network is to recognize and categorize the previously detected contrast changes in a multi-resolution representation of the original image in such a manner that the original information will be decomposed into a relatively small number N of well-defined edge primitives. The advantage of such a construction is that time-consuming pattern recognition has no longer to be done on the originally complex motion-blurred images of moving objects, but on a limited number of categorized forms. Based on a number M of elementary feature attributes for each individual edge primitive, the model is then able to decompose each edge pattern into certain features. In this way an M-dimensional vector can be constructed for each edge. For each sequence of two successive frames a tensor can be calculated containing the distances (measured in M-dimensional feature space) between all features in both images. This procedure yields a set of K-1 tensors for a sequence of K images. After cross-correlation of all N x M feature attributes from image (i) with those from image (i + 1), where i = 1,...,K-1, probability distributions can be computed. The final step is to search for maxima in these probability functions and then to construct from these extremes an optimal motion field. A number of simulation examples will be presented.

Algorithms↗
PubMed1988

Apparent movements induced by luminance modulations: a model study.

When the receptive-field profiles of the different units in the primary visual cortex are described by a series of different functions which are given by a Gaussian distribution and its first, second, and so on, spatial derivatives, a full analysis of the input-output processing of these units (under the assumption of linearity for small signals) can be achieved for a wide variety of optical stimuli consisting of closely adjacent fields modulated independently in intensity. Once the input-output relationship for one particular unit has been obtained, it is possible to calculate in a straightforward manner the spatial representation of the stimulus pattern in a two-dimensional distribution of such units. Investigations are reported into how a stimulus pattern (a dark or bright bar between two fields modulated in illuminance) is represented in a hierarchical structure of such layers of units, each layer containing just one type of receptive-field profile from the Gaussian family of derivatives. It is shown that if a visual percept is associated with the behaviour of the extrema or zero-crossings of the representations in the first few layers of such an architecture, a complete description can be given of the experimental results obtained by Gregory and Heard in their psychophysical experiments on illusory movement perception induced by luminance intensity modulations.

Attention↗
PubMed1984

Saturation in a wide-field, directionally selective movement detection system in fly vision.

In the third optic lobe of the fly large-field spiking neurons are found which detect movement in a directionally selective way. For a wide variety of stimuli the responses of one of these, the H1 neuron, can very well be described and predicted by Reichardt's correlation model which is based on behavioural optomoter responses. However, when the spike rate is driven to large values with intense stimuli, the correlation model needs to be extended in order to account for the saturation phenomena that occur. Saturation can take place in all the elements of the large and extensive movement detecting system which contains interneurons in the optic lobes which process and guide the signals from the peripheral receptors to the central H1 neuron. To separate saturation at the peripheral site from that at the central level of the H1 neuron, a special stimulation technique was chosen. In measuring the saturation at the central level the stimulus parameter was the size of the stimulus field, while the modulation depth of the moving grating in this field stayed constant. Saturation at the peripheral site of the system was studied with a stimulus in which the modulation depth of the moving grating was the parameter and the size of the stimulus field was small and constant. When a simple feedback loop is incorporated in the final stage of the correlation model the saturation phenomena at the central level for steady-state stimulus conditions can very well be described. Saturation phenomena at the peripheral site of the system can also be explained by the same kind of feedback mechanisms in the input channels.

Action Potentials↗
PubMed1978

On the correlation model: performance of a movement detecting neural element in the fly visual system.

The applicability of the basic principles of the correlation model to the description of the activity of a movement detecting neuron in the third optic ganglion of the fly's visual system has been investigated. This wide field neuron is supposed to sum the outputs of a large number of correlators (i.e. multiplying units followed by time averagers) that are distributed over almost the entire eye. The model describes and predicts the experimental results in a satisfactory way if a uniformly distributed system or correlators is assumed. The sampling base of the correlators in this system equals the interommatidial angles deltaphi. The half width of the spatial sensitivity distribution of the visual inputs of the correlators, deltarho, is equal to the half width of the retinula cells of the 1--6 system.

Action Potentials↗
PubMed1976

Huntington's chorea. A random process.

The purpose of the present study was to investigate statistically the irregular nature of the choreatic jerks in Huntington's Chorea. EMG-bursts of certain muscles in a patient with Huntington's Chorea were taken as a measure of the jerks. Statistical analysis of the measurements, i.e. durations of bursts and intervals between bursts, revealed that the irregular nature of the choreatic jerks originate from a random process. Each choreatic jerk appears to be an entirely independent and unpredictable event.

Buttocks↗