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Biomedical subjects

A C Sanderson

Publications and source records attributed to A C Sanderson.

14 recordsLinked to original sources
PubMed1997

Multimodal function optimization using minimal representation size clustering and its application to planning multipaths.

A novel genetic algorithm (GA) using minimal representation size cluster (MRSC) analysis is designed and implemented for solving multimodal function optimization problems. The problem of multimodal function optimization is framed within a hypothesize-and-test paradigm using minimal representation size (minimal complexity) for species formation and a GA. A multiple-population GA is developed to identify different species. The number of populations, thus the number of different species, is determined by the minimal representation size criterion. Therefore, the proposed algorithm reveals the unknown structure of the multimodal function when a priori knowledge about the function is unknown. The effectiveness of the algorithm is demonstrated on a number of multimodal test functions. The proposed scheme results in a highly parallel algorithm for finding multiple local minima. In this paper, a path-planning algorithm is also developed based on the MRSC_GA algorithm. The algorithm utilizes MRSC_GA for planning paths for mobile robots, piano-mover problems, and N-link manipulators. The MRSC_GA is used for generating multipaths to provide alternative solutions to the path-planning problem. The generation of alternative solutions is especially important for planning paths in dynamic environments. A novel iterative multiresolution path representation is used as a basis for the GA coding. The effectiveness of the algorithm is demonstrated on a number of two-dimensional path-planning problems.

Algorithms↗
PubMed1985

Neural modeling and model identification.

The complexity of the nervous system poses challenging experimental and theoretical problems to the investigator. While experimental studies have provided a broad understanding of the physiological and anatomical role of neural elements, a comprehensive description of how the nervous system acquires and processes information is still lacking. Neural modeling addresses itself to the quantitative interpretation of neurophysiological experiments, to the assimilation of diverse experimental results into unified theories, and to the investigation of mechanisms of information-processing units, codes, and networks and their relation to capabilities of living systems. This review will emphasize neural models which can be tested by physiological or psychophysical experiments and will include the identification of model parameters based on experimental measurements. An overview of neural firing models, neural interaction models, neural variability and coding, design of input-output experiments for model identification, and description of small network interactions through multiunit and gross potential recording will be included.

Action Potentials↗
PubMed1979

Transient persistence of neural activity after periodic stimulation in the cat LGN.

Oscillatory neural activity recorded from gross concentric electrodes implanted in the lateral geniculate nucleus (LGN) of cat was investigated after trains of periodic electrical shock stimulation were applied to the contralateral optic nerve. Spectral analysis using repeated trials and spectral averaging revealed statistically significant spectral peaks (p less than 0.05) at the stimulus frequency when there was a 0.5 to 1.5 s delay between the last pulse of the stimulus train and the beginning of the data analysis window. This suggests that a loosely coupled neuronal net may allow for the continuation of activity far longer than the time accounted for by neuronal time constants and delays.

Animals↗
PubMed1979

Entrainment of oscillatory neural activity in the cat's lateral geniculate nucleus.

Oscillatory neural activity in the frequency range 7-12 Hz is observed in the lateral geniculate nucleus (LGN) of the lightly anesthetized cat. This paper describes a series of experiments in which the interactions between ongoing oscillatory potentials and periodic photic and electrical stimuli are analyzed using frequency domain techniques. The principal results of these experiments are consistent with a model of the neural system as an entrainable oscillator in which ongoing oscillations are suppressed by stimulation at nearby frequencies, but coexist with stimulus frequencies farther away. The physiological interpretation of these results may be closely tied to the role of the LGN as a "gating" mechanism between retina and cortex.

Alpha Rhythm↗
PubMed1973

Distribution coding in the visual pathway.

Although a variety of types of spike interval histograms have been reported, little attention has been given to the spike interval distribution as a neural code and to how different distributions are transmitted through neural networks. In this paper we present experimental results showing spike interval histograms recorded from retinal ganglion cells of the cat. These results exhibit a clear correlation between spike interval distribution and stimulus condition at the retinal ganglion cell level. The averaged mean rates of the cells studied were nearly the same in light as in darkness whereas the spike interval histograms were much more regular in light than in darkness. We present theoretical models which illustrate how such a distribution coding at the retinal level could be "interpreted" or recorded at some higher level of the nervous system such as the lateral geniculate nucleus. Interpretation is an essential requirement of a neural code which has often been overlooked in modeling studies. Analytical expressions are derived describing the role of distribution coding in determining the transfer characteristics of a simple interaction model and of a lateral inhibition network. Our work suggests that distribution coding might be interpreted by simply interconnected neural networks such as relay cell networks, in general, and the primary thalamic sensory nuclei in particular.

Animals↗