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The human visual system demonstrates powerful image processing functionalities. Inspired by the visual system, a spiking neural network is proposed to segment visual images. The network is constructed in the two parts. The first part is a spiking neural network which is composed of photon receptors, cone and rod cells, and ON/OFF ganglion cells. Colour features can be extracted and passed through different ON/OFF pathways. The second part is a BP neural network which is trained to recognize the colour features and segment the visual image. The network has been successfully applied to segment leukocytes from blood smeared images. [ABSTRACT FROM AUTHOR]

To understand the details of brain function, a large scale system model that reflects anatomical and neurophysiological characteristics needs to be implemented. Though numerous computational models of different brain areas have been proposed, these integration for the development of a large scale model have not yet been accomplished because these models were described by different programming languages, and mostly because they used different data formats. This paper introduces a platform for a collaborative brain system modeling (PLATO) where one can construct computational models using several programming languages and connect them at the I/O level with a common data format. As an example, a whole visual system model including eye movement, eye optics, retinal network and visual cortex is being developed. Preliminary results demonstrate that the integrated model successfully simulates the signal processing flow at the different stages of visual system. [ABSTRACT FROM AUTHOR]

The human visual system demonstrates powerful image processing functionalities. Inspired by the principles from neuroscience, a spiking neural network is proposed to perform the discrete cosine transform for visual images. The structure and the properties of the network are detailed in this paper. Simulation results show that the network is able to perform the discrete cosine transform for visual images. Based on this mechanism, the key features can be extracted in ON/OFF neuron arrays. These key features can be used to reconstruct the visual images. The network can be used to explain how the spiking neuron-based system can perform key feature extraction. The differences between the discrete cosine transform and the spiking neural network transform are discussed. [ABSTRACT FROM AUTHOR]

This paper presents a novel binocular active visual platform for monitoring the workspace of a parallel mechanism. Its cameras are mounted on two independent controlled kinematic chains which moving along a circular orbit. The system is designed for precise kinematic calibration of the end-effector on the parallel mechanism and other deepening application. At first, the geometric model of the platform and the 3D reconstruct model based stereo vision are established. Then, in order to eliminate the influence of monitoring accuracy because of the own accuracy of visual system, A dynamic system calibration and error rectification method is proposed. Experiment results show that the approach is effective with respect to dynamic property and calibration accuracy. [ABSTRACT FROM AUTHOR]

Inspired by the behaviour of the human visual system, a spiking neural network is proposed to detect moving objects in a visual image sequence. The structure and the properties of the network are detailed in this paper. Simulation results show that the network is able to perform motion detection for dynamic visual image sequence. Boundaries of moving objects are extracted from an active neuron group. Using the boundary, a moving object filter is created to take the moving objects from the grey image. The moving object images can be used to recognise moving objects. The moving tracks can be recorded for further analysis of behaviours of moving objects. It is promising to apply this approach to video processing domain and robotic visual systems. [ABSTRACT FROM AUTHOR]

The ancient concept of animal spirits moving in hollow nerve fibers to account for sensation and motor control was replaced in the Renaissance with such surrogates as a gas, a thin vapor, a fiery fiuid, vibrating particles, and so on, until eventually the nerve impulse was recognized as being electrical in nature. However, this left still unaccounted for the slow onset of Wallerian degeneration appearing a day or so after nerve transection, along with the later slowly developing atrophy of muscles and sensory organs. Some other nerve principle was involved. With the establishment of the neuron doctrine, the question turned on the possibility of the loss of supply of some substance from the nerve cell to its fibers and the tissues innervated, a hormone, an enzyme, or whatever. And, another related question arose, the nature of the mechanism that transports that principle in the fibers. EARLY HYPOTHESES OF TRANSPORT BASED ON CELL BODY CHANGES The chromatolysis of cell bodies, loss of Nissl particles staining dark blue with aniline dyes that was seen to follow the transection of its nerve fibers (Chapter 9), drew the attention of Scott to this phenomenon. He found the particles to consist of a “nucleoproteid,” later identified as ribonucleic acid (RNA), having a remarkable resemblance to the granular material present in secretory gland cells, such as those in the fundus of the stomach and pancreas. [ABSTRACT FROM AUTHOR]