PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Models, Neurological”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13Linked to original sources
PubMed1980

Photoreceptor optics I: introduction to formalism and excitation in a lens-photoreceptor system.

An analysis is presented of the optical factors influencing photoreceptor excitation. Small receptors are considered and the incident light is focussed onto them by a lens. The theoretical principles involved are outlined and explained in simple terms and by using analogies, so that they are also accessible to the nontheoretician. System parameters relevant to the fly are used as a basis for study. The theory is used to discuss the choice of lens parameters, the effects of defocussing and chromatic aberration. The emphasis is on results and in all cases graphs are presented so that magnitudes and trends are readily appreciated.

Absorption↗
PubMed1984

A hierarchical neural network model for associative memory.

A hierarchical neural network model with feedback interconnections, which has the function of associative memory and the ability to recognize patterns, is proposed. The model consists of a hierarchical multi-layered network to which efferent connections are added, so as to make positive feedback loops in pairs with afferent connections. The cell-layer at the initial stage of the network is the input layer which receives the stimulus input and at the same time works as an output layer for associative recall. The deepest layer is the output layer for pattern-recognition. Pattern-recognition is performed hierarchically by integrating information by converging afferent paths in the network. For the purpose of associative recall, the integrated information is again distributed to lower-order cells by diverging efferent paths. These two operations progress simultaneously in the network. If a fragment of a training pattern is presented to the network which has completed its self-organization, the entire pattern will gradually be recalled in the initial layer. If a stimulus consisting of a number of training patterns superposed is presented, one pattern gradually becomes predominant in the recalled output after competition between the patterns, and the others disappear. At about the same time when the recalled pattern reaches a steady state in the initial layer, in the deepest layer of the network, a response is elicited from the cell corresponding to the category of the finally-recalled pattern. Once a steady state has been reached, the response of the network is automatically extinguished by inhibitory signals from a steadiness-detecting cell.(ABSTRACT TRUNCATED AT 250 WORDS)

Association Learning↗
PubMed1979

A model for processing of movement in the visual system.

Processing of spatio-temporal information in the human visual system has been investigated thoroughly during the past decade, but is still far from being properly understood. Moreover, the theory of separation of information by means of sustained and transient channels already at the retinal level is not satisfactory, as experimental results indicate that these two types of channels span a continuum of temporal characteristics. It is however obvious, that the process of pattern recognition and velocity perception calls for their separation at some level of the hierarchy. In this communication, we extend our model of three-dimensional spatio-temporal frequency expansion in the visual system (Gafni and Zeevi, 1977) to show how velocity-information extraction channels, sensitive to direction and velocity exclusively, can be formed by simple summation of signals from well-defined sets of channels representing points in the frequency space. Correspondence of these channels to characteristics of the cortical neurons is discussed.

Depth Perception↗
PubMed1979

Studies on human finger tapping neural networks by phase transition curves.

The human finger tapping was studied psychologically by the phase transition curves. We assumed that some oscillatory neural network controls the tapping. One of our future works on the human finger tapping is to devise a method to change the magnitude of perturbation continuously in phase resetting experiments of a constant tapping interval with a same kind of task. If this is achieved, we can obtain a phase transition surface (i.e. the new phase as a function of the old phase and the magnitude of perturbation). From the shape of a phase transition surface, the intrinsic properties of the oscillatory network which controls the tapping can be studied (Kawato et al., 1978).

Conditioning, Psychological↗
PubMed1979

Sensitivity variations in the visual system, contrast resolution and eye movements.

Attention is drawn to the fact that under normal visual conditions the sensitivity of the receptor units of the visual system are subject to spatial and temporal variations, and that consequently in performing pattern recognition the visual cortex has to discriminate between external luminance structure and internal sensitivity structure. It is suggested that eye movements are the method by which this discrimination is performed. In a simplified model analysis it is shown that eye movements are a suitable mechanism for this discrimination. Implications of this model for detection threshold and stabilized retinal images are discussed. A new interpretation of the adaptation to sine wave grids is given.

Eye Movements↗
PubMed1979

Analysis of recall and recognition in a certain class of adaptive networks.

A general model of adaptive networks which perform recall is analyzed in view of qualitative psychological findings. The assumptions underlying the basic model are few and general in the sense that no specifications of structure or mechanisms of adaptation are imposed. The analysis of the model is towards the addition of various features drawn from the global input-output relations expected from the networks. The memorizing process of recognition is found to be intrinsic to the model, and four of the most prominent relations between the performance of recall and recognition are shown to either exist in model or to be realizable by means of few additional plausible features.

Association Learning↗
PubMed1979

Initial processing of visual information within the retina and the LGN.

The initial stage of information processing by the visual system reduces the information contained in the continuous image on the retina into a discrete set of responses which are carried from the lateral geniculate nucleus (LGN) to the visual cortex. -- 1. The optimal sampling of the light intensity distribution in the visual environment is achieved only if each channel in the visual pathways carries undistorted information corresponding to an image element. The visual system approaches as closely as possible the scheme of optimal spatial sampling, retaining the full information on the low spatial frequency content of the object light intensity. The ideal receptive field of a sustained LGN cell is then of the form J1(Kr)/Kr. -- 2. The experimentally determined receptive fields of sustained LGN cells (and to some extent retinal ganglion cells as well) in cat closely resemble the functional form J1(Kr)/Kr. The centre-surround organization of the receptive fields is therefore understood as a scheme which leads to a maximal information flow through the visual pathways. -- 3. The optimal sampling scheme cannot be realized by the retina alone, because of restrictions on the size of neural networks. It is therefore constructed in two stages, ending at the LGN level. A recombination of ganglion cell signals into optimal receptive fields is a major role of the LGN.

Animals↗
PubMed1975

[Three basic kinds of behaviour, a scheme of their neurobiological correlates (author's transl)].

The psychic sphere is to be regarded as the source of meaningful behaviour, which is carried out in the service of the cell community that makes up our body. Three fundamental types of behaviour can be distinguished: the purely practical, the theoretical-practical, and the purely theoretical. These three types of behaviour have three different reasons: the first a determining reason, the second a motivating reason, and the third a supporting reason. The threefold nature of the reasons is related to the threefold needs of the cell community (in this context man is considered as an example of an animal). Possible neurobiological bases of human behaviour are depicted in a schematic figure showing the relation of cerebral centres and sensorimotor functions of the human face including eye movements. The psychic centre may be located in the thalamus, the areas of the central sulcus are regarded as an objectivation zone. This indicates that the motor zones of the cortex, including the frontal adversive fields, are intention zones, and the sensory zones reproduction, expectation, and recollection zones. A system so composed would render possible what we see in every animal being: decision-making, foresight, and learning.

Behavior↗
PubMed1986

Texture discrimination by Gabor functions.

A 2D Gabor filter can be realized as a sinusoidal plane wave of some frequency and orientation within a two dimensional Gaussian envelope. Its spatial extent, frequency and orientation preferences as well as bandwidths are easily controlled by the parameters used in generating the filters. However, there is an "uncertainty relation" associated with linear filters which limits the resolution simultaneously attainable in space and frequency. Daugman (1985) has determined that 2D Gabor filters are members of a class of functions achieving optimal joint resolution in the 2D space and 2D frequency domains. They have also been found to be a good model for two dimensional receptive fields of simple cells in the striate cortex (Jones 1985; Jones et al. 1985). The characteristic of optimal joint resolution in both space and frequency suggests that these filters are appropriate operators for tasks requiring simultaneous measurement in these domains. Texture discrimination is such a task. Computer application of a set of Gabor filters to a variety of textures found to be preattentively discriminable produces results in which differently textured regions are distinguished by first-order differences in the values measured by the filters. This ability to reduce the statistical complexity distinguishing differently textured region as well as the sensitivity of these filters to certain types of local features suggest that Gabor functions can act as detectors of certain "texton" types. The performance of the computer models suggests that cortical neurons with Gabor like receptive fields may be involved in preattentive texture discrimination.

Discrimination, Psychological↗
PubMed1986

Simple neural models of classical conditioning.

A systematic study of the necessary and sufficient ingredients of a successful model of classical conditioning is presented. Models are constructed along the lines proposed by Gelperin, Hopfield, and Tank, who showed that many conditioning phenomena could be reproduced in a model using non-trivial distributed representations of the sensory stimuli. The additional phenomena of extinction and blocking are found to be obtainable by generalizing the Hebbian learning algorithm, rather than by additional complications in the hardware. The most successful algorithms have a minimal number of adjustable parameters, and require only local-time information about the level of postsynaptic activity. The proper behavior of these algorithms is verified by both simple analytic arguments and by direct numerical simulation. Certain detailed assumptions concerning the distributed sensory representations are also found to have a surprising degree of importance.

Algorithms↗
PubMed1986

[Efficiency of associative memory inherent in post-tetanic potentiation].

An associative memory is modeled in networks of cells that are assumed to have the short-term plasticity of the neuromuscular junction of the frog. The data relating synaptic transmission efficiency and stimulation frequency for post-tetanic potentiation of the neuromuscular junction are represented by polynomial expansions. Simulation of storage and retrieval demonstrates that functional associative memory is feasible based on this particular synaptic plasticity. Retrieval reaches a maximum efficiency at a delay of three minutes after storage and is lost after about 9 min. The signal to noise ratio of the retrieved pattern drops steadily as additional associations are stored in memory but retrieval appears to be possible with up to four stored associations. Although the data are derived from synapses not normally proposed as a basis for memory functions, the results here will generalize to other synaptic junctions located more centrally that have similar characteristics. This simulation technique allows the efficiency of associative memory based on various types of synaptic plasticity to be evaluated.

Brain↗
PubMed1986

Non-linearities in cortical simple cells and the possible detection of zero crossings.

A theory of early visual information processing proposed by Marr and co-workers suggests that simple cortical cells may be involved in the detection of zero crossing in the retinal output. We have tested this theory by using pairs of adjacent edges (staircases stimuli) and recording from edge-specific simple cells in cat striate cortex. The zero crossing hypothesis gives rise for such stimuli to non-obvious predictions that were generally confirmed by the experiment.

Animals↗
PubMed1983

Parameter estimation of the threshold time function in the neural system.

An algorithm for parameter estimation is presented for the neural system model. Because of its firing mechanism analogous to that of the model based on the first time crossing problem, this problem is solved numerically for our model according to the results of Kostyukov et al. (1981). We propose the algorithm that estimates the parameters of the model considering the equivalence between the probability density function of the 1st crossing time and that of the interspike interval, which is derived from the interspike interval histogram by making use of the spline function technique. The ability of the algorithm is ensured by the application to the simulated interspike interval data. The parameter estimation is carried out also for the practical neural data recorded in the cat's optic tract fibers in both the spontaneous and the stimulated cases. These applications will show the effectiveness of the algorithm in practical cases.

Animals↗
PubMed1987

A model-based monitor of human sleep stages.

Stochastic models are proposed for sleep and for the sleep related electroencephalogram (EEG), electrooculogram (EOG), and electromyogram (EMG). The evolution of sleep through its various stages is described as a Markov chain. The EEG is modelled using Wiener processes. The EOG and EMG are modelled as combinations of Poisson point processes and Gaussian processes, respectively. The EEG models contain a feedback structure that is based on physiological data. The maximum likelihood sleep stage monitor, that uses the sleep-related observations, has been derived and implemented. The agreement between automatic and human stage classifications of six sleep recordings was 70.6%, which was 4.5% worse than the average agreement between six human classifiers. Monitoring of simulated sleep suggests that the difficulty in separating wakefulness from stage 1 is due to poor modelling. If one ignores this difference, which, from a diagnostic point of view is fairly unimportant, the above mentioned agreement reaches 81.8%, which is 0.5% better than the corresponding average human vs human agreement.

Brain↗
PubMed1986

The effect of saccades on threshold perception--a model study.

The effect of saccadic eye movements on threshold perception is investigated theoretically. The proposed model considers eye movements by taking into account the shifting of the stimulus pattern on the retina during the occurrence of an eye movement. Saccades are characterized by high velocity and short duration. These motions cause overshoots in the response of linear filters to certain stimulus patterns. Therefore, the model predicts facilitation effects of saccades in the perception of low spatial frequency patterns and patterns flickering with high temporal frequencies. These results agree with experimentally obtained data presented in a subsequent paper. A simple approach is formulated which approximates the complex shifting function of a saccade by a switching of the pattern.

Eye Movements↗
PubMed1986

A model for the perception of curves in dot figures: the role of local salience of "virtual lines".

In many models of visual information processing the notion of a virtual line or dipole is introduced in order to represent the configurational information, notably length and relative orientation, between identical figure elements in figures with discrete elements. Virtual lines have proven to be very useful in predicting perceptual phenomena (Julesz et al. 1973; Stevens 1978). In the present study, virtual lines are utilized in a model which aims to predict the perception of (dotted) curves in dot figures. Clearly many possible curves, formed by adjacent virtual lines, can be constructed within a set of dots. It is proposed that already at the local level of the virtual lines each line has a perceptual salience which results from the function induced by the global dot figure. It is this local line salience or "connectivity" that directs further processing and determines the curves to be seen in a dot figure. The model presented is an information processing model with a clear modular design. It entails three successive levels of representation. First image functions are derived through a convolution of the input with gaussian distribution functions. Next, a discrete internal representation is extracted from the image function consisting of two primitives; blobs, representing the dots, and virtual lines, representing pairwise relations between blobs. The attributes of the blobs are their positions in the image plane, while those of the virtual lines are length, relative orientation and connectivity. At the third level, the discrete internal representation is used to predict the perceived curves. It is shown that the model has advantages over other approaches, e.g. autocorrelation and network models.

Humans↗
PubMed1986

Neural computation of inner geometric pattern relations.

A method for the description of patterns is proposed that is based on the evaluation of their inner geometric relations. They serve as features and are determined through operations that are mathematically formulated by so-called "generalized auto comparison functions", i.e., by measures that express a pattern's "auto-match" under geometric transformations. A subset of these features, namely the similarity features, are treated in greater detail, especially with regard to their invariance properties. The dominant role of spatial relations in the formation process of early visual representations is exemplified and a mechanism for the extraction of relational features from such representations is proposed. The feasibility for self-organization of suitable computing structures is discussed.

Form Perception↗