0000000000276766

AUTHOR

Hanspeter A. Mallot

showing 6 related works from this author

Characteristics of neuronal systems in the visual cortex

1987

The coupling complexity of cortical areas makes it very difficult to analyse them experimentally. Studies of model systems provide the possibility of adapting the analysis to the available data base and elaborating the fundamental properties that depend on the structure of the system. We propose a model system of variable complexity that is spatially two-dimensional and time-dependent, uses feedback for iteration and smoothing, includes the mapping of the cortical networks and can be nonlinear as the case requires. Combining such elementary systems on the basis of neuroanatomical findings enables us to simulate cortical mappings and to interpret neurophysiological data. The decisive factor …

General Computer ScienceComputer scienceModels NeurologicalComplex systemRetinamedicineAnimalsVision OcularVisual CortexNeuronsQuantitative Biology::Neurons and CognitionBasis (linear algebra)business.industryPattern recognitionNeurophysiologyNonlinear systemVisual cortexmedicine.anatomical_structureCoupling (computer programming)RetinotopyVisual PerceptionArtificial intelligencebusinessMathematicsSmoothingBiotechnologyBiological Cybernetics
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Cycle-triggered averaging of respiration-related neuronal activity

1985

Abstract A computer system is presented which provides off-line computation of cycle-triggered histograms (CTH) of respiration-related neuronal activity. Binwidths of the histograms are freely selectable by software from 10 ms to 100 ms. For special evaluation purposes. CTHs can be standardized in different ways concerning cycle duration as well as amplitude. Time incidence of maximum frequency, center of gravity and expiration-to-inspiration phase transition within the respiratory cycle are computed. The system employs special hardware interfaces to an 8-bit microcomputer which are briefly described. Data acquisition, data manipulation and output handling of the results are performed by ch…

NeuronsSignal processingComputersComputer sciencebusiness.industryRespirationData manipulation languageRespiratory SystemReal-time computingMedicine (miscellaneous)computer.software_genreElectrophysiologyPhrenic NerveSoftwareData acquisitionMicrocomputerHistogramChainingRespiratory Physiological PhenomenaAnimalsCompilerbusinessAlgorithmcomputerSoftwareComputer Programs in Biomedicine
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An overall description of retinotopic mapping in the cat's visual cortex areas 17, 18, and 19.

1985

Mathematical functions are derived which model the retinotopic mapping in the cat's visual cortical areas 17, 18, and 19. All three mappings are simple modifications of a complex power function with an exponent of 0.43. This function is decomposed so as to give an intermediate stage which is common to all three mappings and can be regarded as a model of the lateral geniculate nucleus mapping. The influence of retinotopic mapping on visual receptive fields was studied. The results show that a dependence of the receptive field properties on the position in the visual field is to be expected.

General Computer ScienceModels NeurologicalVisual systemLateral geniculate nucleusRetinaPosition (vector)medicineAnimalsVisual CortexOrientation columnbusiness.industryPattern recognitionFunction (mathematics)Visual fieldVisual cortexmedicine.anatomical_structureReceptive fieldCatsVisual PerceptionArtificial intelligenceVisual FieldsbusinessPsychologyNeuroscienceMathematicsSoftwareBiotechnologyBiological cybernetics
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On Information Processing in the Cat’s Visual Cortex

1986

We assume that the visual system serves for orientation in space, recognition of objects and the interpretation of scenes and scene sequences. This task breaks up into a series of partially interdependent subproblems which are solved by some 13–15 usually retinotopically organized areas. So far it has not been possible to correlate functions and areas unequivocally. One reason for this could be the inadequacy of the questions posed as a basis for experiments. However, we think it more likely that correlating a function with an area is, as a rule, inadmissible since the degree of the coupling in the whole system does not permit a simple divsion. Rather the type and degree of coupling determi…

Basis (linear algebra)business.industryOrientation (computer vision)Computer sciencemedia_common.quotation_subjectInformation processingPattern recognitionTask (project management)ControllabilityObservabilityArtificial intelligencebusinessFunction (engineering)Complement (set theory)media_common
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Why Cortices? Neural Networks for Visual Information Processing

1989

Neural networks for the processing of sensory information show remarkable similarities between different species and across different sensory modalities. As an example, cortical organization found in the mamalian neopallium and in the optic tecta of most vertebrates appears to be equally appropriate as a substrate for visual, auditory, and somatosensory information processing. In this paper, we formulate three structural principles of the vertebrate visual cortex that allow to analyze structure and function of these neural networks on an intermediate level of complexity. Computational applications are taken from the field of early vision. The proposed principles are: (a) Average anatomy, i …

Artificial neural networkbusiness.industryComputer scienceOptical flowPattern recognitionSensory systemImage processingModels of neural computationVisual cortexmedicine.anatomical_structureReceptive fieldmedicineArtificial intelligenceMotion perceptionbusinessNeuroscience
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Spatiotemporal receptive fields: A dynamical model derived from cortical architectonics

1986

We assume that the mammalian neocortex is built up out of some six layers which differ in their morphology and their external connections. Intrinsic connectivity is largely excitatory, leading to a considerable amount of positive feedback. The majority of cortical neurons can be divided into two main classes: the pyramidal cells, which are said to be excitatory, and local cells (most notably the non-spiny stellate cells), which are said to be inhibitory. The form of the dendritic and axonal arborizations of both groups is discussed in detail. This results in a simplified model of the cortex as a stack of six layers with mutual connections determined by the principles of fibre anatomy. This …

Models AnatomicModels NeurologicalPyramidal TractsInhibitory postsynaptic potentialLateral inhibitionCortex (anatomy)medicineAnimalsHumansNeurons AfferentGeneral Environmental ScienceVisual CortexCerebral CortexNeuronsAfferent PathwaysNeocortexLinear systemGeneral Engineeringmedicine.anatomical_structureCerebral cortexReceptive fieldExcitatory postsynaptic potentialGeneral Earth and Planetary SciencesPsychologyNeuroscienceMathematics
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