Concepts in vertebrate neuroethology

Neuroethology is concerned with the analysis of the neural substrates and mechanisms that underlie behaviour. In 1951, Tinbergen implied the following goals of Ethophysiology, today known as Neuroethology: (1) recognition and localization of behaviourally meaningful stimuli, e.g. key stimuli; (2) sensorimotor interfacing and feedback interactions; (3) modulations according to internal states and acquired information; (4) motor pattern generation; and (5) ontogenetic and phylogenetic aspects. Using the toad's (Bufo bufo) visually-guided prey-catching behaviour as an example, experimental strategies and concepts of vertebrate Neuroethology can be demonstrated: (i) visual space is mapped in the brain in a multiple manner; (ii) specification of neurons results from inhibitory and/or excitatory interactions among and within space-mapped neuronal networks; (iii) specialized neurons, e.g. those with stimulus recognition and localization properties, show information processing that takes place in functional units of cell assemblies (so-called ‘neuronal machines’ or ‘brain chips’); (iv) activation of motor pattern generators for different behavioural actions may require coincidence of inputs from different combinations of specialized neurons that serve as command elements and together form a command system; (v) a command system can be regarded as a sensorimotor interface fulfilling tasks with respect to (a) visual pattern recognition and localization, (b) command functions, by initiating the activation of the motor pattern generation system, (c) motor pattern generation through participation in the temporal sequence of the positive feedback from the motor system, and (d) integration of modulatory inputs according to internal states; (vi) the motor pattern generation circuitry consists of a neuronal network capable of producing a consistent distribution of excitation and inhibition and whose output has privileged access to the required motoneuronal pools; (vii) the basic principles of prey selection and motor pattern generation of prey capture emerge in the post-metamorphic juvenile toad with the transition to land and without previous prey experience. During early ontogeny the acuity of sensory discrimination and the performance of motor patterns are subject to maturation paralleled by neural differentiations in the bbrain. performance of motor patterns are subject to maturation paralleled by neural differentiations in the brain. those are programmed and, in amphibians, presumably less dependent on the interaction with the environment than in mammals. This of course does not exclude the possibility of modulating, modifying, specifying and/or extending the visual pattern recognition system of toads due to internal states and individual experience.     

A recurrent network for landmark-based navigation

A new type of network is proposed that can be applied to landmark navigation. It solves the guidance task, that is, it finds a nonvisually marked location using knowledge concerning its spatial relation to other, visible landmarks. The path to the searched location is not disturbed if a landmark is not visible for some time. The network can also describe findings obtained by experiments with insects and rodents, where the position of the landmarks has been changed after training. In this net, recognition does not occur by searching for a match between a pattern seen and the same pattern being stored but by searching for a match between a pattern seen with a prediction calculated from different data. A simple extension allows a unique match of the landmarks seen with the items stored in memory. With this extension a recognition of the individual landmark is not necessary. A specific output unit of the network can be interpreted in such a way as to show properties of place cells found in vertebrates and the function of the network proposed here as to determine the input to a place cell. The model can explain the observation that a given place cell can also be active when the animal moves in a different environment. An extension is discussed of how the network could be exploited for recognition-triggered response that allows animals to follow fixed routes.     

Combining structural connectivity and response latencies to model the structure of the visual system

Several approaches exist to ascertain the connectivity of the brain, and these approaches lead to markedly different topologies, often incompatible with each other. Specifically, recent single-cell recording results seem incompatible with current structural connectivity models. We present a novel method that combines anatomical and temporal constraints to generate biologically plausible connectivity patterns of the visual system of the macaque monkey. Our method takes structural connectivity data from the CoCoMac database and recent single-cell recording data as input and employs an optimization technique to arrive at a new connectivity pattern of the visual system that is in agreement with both types of experimental data. The new connectivity pattern yields a revised model that has fewer levels than current models. In addition, it introduces subcortical-cortical connections. We show that these connections are essential for explaining latency data, are consistent with our current knowledge of the structural connectivity of the visual system, and might explain recent functional imaging results in humans. Furthermore we show that the revised model is not underconstrained like previous models and can be extended to include newer data and other kinds of data. We conclude that the revised model of the connectivity of the visual system reflects current knowledge on the structure and function of the visual system and addresses some of the limitations of previous models.     

The immune system as a neural network: a multi-epitope approach.

The term "neural network" has been applied to arrays of simple activation units linked by weighted connections. If the connections are modified according to a defined learning algorithm, such networks can be trained to store and retrieve patterned information. Memories are distributed throughout the network, allowing the network to recall complete patterns from incomplete input (pattern completion). The major biological application of neural network theory to date has been in the neurosciences, but the immune system may represent an alternative organ system in which to search for neural network architecture. Previous applications of parallel distributed processing to idiotype network theory have focused upon the recognition of individual epitopes. We argue here that this approach may be too restrictive, underestimating the power of neural network architecture. We propose that the network stores and retrieves large, complex patterns consisting of multiple epitopes separated in time and space. Such a network would be capable of perceiving an entire bacterium, and of storing the time course of a viral infection. While recognition of solitary epitopes occurs at the cellular level in this model, recognition of structures larger than the width of an antibody binding site takes place at the organ level, via network architecture integration of, i.e. individual epitope responses. The Oudin-Cazenave enigma, the sharing of idiotypic determinants by antibodies directed against distinct regions of the same antigen, suggests that some network level of integration of the individual clonal responses to large antigens does occur. The role of cytokines in prior neural network models of the immune system is unclear. We speculate that cytokines may influence the temperature of the network, such that changes in the cytokine milieu serve to "anneal" the network, allowing it to achieve the optimum steady-state in the shortest period of time.     

Visual recognition in infant pigtailed macaques after a 24-hour delay

Comparative studies of memory in monkey and human subjects suggest similarities in visual recognition memory across human and nonhuman primates. In order to investigate developmental aspects of visual recognition memory in monkey infants, the familiarization-novelty procedure, developed for use with human infants, was employed with pigtailed monkey infants to study long-delay recognition memory. Subjects were familiarized with a black-and-white abstract pattern. Twenty-four hours later they were tested with the familiar pattern paired with a novel one. Results indicated a significant visual preference for the novel stimulus, providing evidence for recognition memory. These results parallel those obtained with human infants, suggesting further similarities in the development of visual recognition memory.     

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.     

Neurobiological approach to computing devices

According to the old metaphor of classical cybernetics the brain can be considered as a computer. Newer theoretical endeavours reverse the question and ask: what could neurobiology offer to engineers of near-future generation computer systems? Three not completely disjoint abstract functions of the nervous system, namely pattern formation, pattern recognition and action, can be treated in a unified conceptual framework. Storage and retrieval mechanisms of information are connected to fault-tolerant, adaptive parallel structures. "Learning" and "plastic behaviour" are interpreted in terms of the theory of non-linear dynamic systems. As neural development and plasticity can be approached by deterministic models superimposed by random influence, noise might also have a positive role to play during the operation of technical computing devices. Molecular computation is discussed in relation to eventual hardware realization of "neurobiology-based" computers.     

Stiff polymer adsorption. Onset to pattern recognition

We present the results of extensive off-lattice Monte-Carlo simulations of a stiff polymer chain adsorbing onto a sticky periodic stripe-like pattern of variable width. We have analyzed, in terms of the chain length and rigidity, the adsorption and the pattern recognition process as a function of the stripe width. We have seen that this process is twofold: (i) the chain adsorbs rather isotropically onto the surface at a characteristic temperature T(c) and (ii) a further reduction in the temperature is needed for the chain to reorganize and adjust to the specific pattern. Such polymer reorganization has been studied through the evaluation of the chain degree of stretching and asphericity. We have found an optimal stripe width that maximizes the stretching. We have introduced a criteria to estimate the characteristic temperature at which the pattern recognition takes place T(r)相似文献   

Video Sequence-Based Iris Recognition Inspired by Human Cognition Manner

In video sequence-based iris recognition system, the problem of making full use of relationship and correlation among frames still remains to be solved. A brand new template level multimodal fusion algorithm inspired by human cognition manner is proposed. In that a non-isolated geometrical manifold, named Hyper Sausage Chain due to its sausage shape, is trained using the frames from a pattern class for representing an iris class in feature space. We can classify any input iris by observing which manifold it locates in. This process is closer to the function of human being, which takes ＇matter cognition＇ instead of ＇matter classification＇ as its basic principle. The experiments on self-developed JLUBR-IRIS dataset with several video sequences per person demonstrate the effectiveness and usability of the proposed algorithm for video sequence-based iris recognition. Fur- thermore, the comparative experiments on public CASIA-I and CASIA-V4-Interval datasets show that our method can also achieve improved performance of image-based iris recognition system, provided enough samples are involved in training stage.     

Recognition of partly occluded patterns: a neural network model

 Human beings are often able to read a letter or word partly occluded by contaminating ink stains. However, if the stains are completely erased and the occluded areas of the letter are changed to white, we usually have difficulty in reading the letter. In this article I propose a hypothesis explaining why a pattern is easier to recognize when it is occluded by visible objects than by invisible opaque objects. A neural network model is constructed based on this hypothesis. The visual system extracts various visual features from the input pattern and then attempts to recognize it. If the occluding objects are not visible, the visual system will have difficulty in distinguishing which features are relevant to the original pattern and which are newly generated by the occlusion. If the occluding objects are visible, however, the visual system can easily discriminate between relevant and irrelevant features and recognize the occluded pattern correctly. The proposed model is an extended version of the neocognitron model. The activity of the feature-extracting cells whose receptive fields cover the occluding objects is suppressed in an early stage of the hierarchical network. Since the irrelevant features generated by the occlusion are thus eliminated, the model can recognize occluded patterns correctly, provided the occlusion is not so large as to prevent recognition even by human beings. Received: 21 February 2000 / Accepted in revised form: 11 September 2000     

Patterns of patchy spread in multi-species reaction–diffusion models

Spread of populations in space often takes place via formation, interaction and propagation of separated patches of high species density, without formation of continuous fronts. This type of spread is called a ‘patchy spread’. In earlier models, this phenomenon was considered to be a result of a pronounced environmental or/and demographic stochasticity. Recently, it was found that a patchy spread can arise in a fully deterministic predator–prey system and in models of infectious diseases; in each case the process takes place in a homogeneous environment. It is well recognized that the observed patterns of patchy spread in nature are a result of interplay between stochastic and deterministic factors. However, the models considering deterministic mechanism of patchy spread are developed and studied much less compared to those based on stochastic mechanisms. A further progress in the understanding of the role of deterministic factors in the patchy spread would be extremely helpful. Here we apply multi-species reaction–diffusion models of two spatial dimensions in a homogeneous environment. We demonstrate that patterns of patchy spread are rather common for the considered approach, in particular, they arise both in mutualism and competition models influenced by predation. We show that this phenomenon can occur in a system without a strong Allee effect, contrary to what was assumed to be crucial in earlier models. We show, as well, a pattern of patchy spread having significantly different speeds in different spatial directions. We analyze basic features of spatiotemporal dynamics of patchy spread common for the reaction–diffusion approach. We discuss in which ecosystems we would observe patterns of deterministic patchy spread due to the considered mechanism.     

视觉信息处理:阅读中文和英文时眼动模式的对比研究

文字阅读是一个复杂的视觉模式识别过程,虽然客观测量阅读过程中的脑的活动比较困难,但用记录分析阅读中由脑部控制的眼球活动来研究脑的信息处理特点却是可行的.本文采用两种不同结构的文字——以空间图象为基础的方块汉字和以发音序列为基础的横行英文——作为输入,用红外眼动仪测量阅读时的眼动曲线,再由计算机分析其异同.结果表明:1)阅读注视时程对中文及英文分别为0.260及0.265秒;2)阅读辨认跨度对中文及英文分别为1.7及1.8信息单位.由两者的相似性提示我们:整段理解阅读信息处理能力决定于神经系统高级阅读中枢的解码速率.     

Genetic analysis of Drosophila larval optic nerve development.

To identify genes necessary for establishing connections in the Drosophila sensory nervous system, we designed a screen for mutations affecting development of the larval visual system. The larval visual system has a simple and stereotypic morphology, can be recognized histologically by a variety of techniques, and is unnecessary for viability. Therefore, it provides an opportunity to identify genes involved in all stages of development of a simple, specific neuronal connection. By direct observation of the larval visual system in mutant embryos, we identified 24 mutations affecting its development; 13 of these are larval visual system-specific. These 13 mutations can be grouped phenotypically into five classes based on their effects on location, path or morphology of the larval visual system nerves and organs. These mutants and phenotypic classifications provide a context for further analysis of neuronal development, pathfinding and target recognition.     

Extraction of objects from structured backgrounds in the cat superior colliculus. Part II

Specific changes occur in the cells of the upper layers of the cat's superior colliculus when a two dimensional noise (background) is superimposed onto a deterministic signal (spot of light). Some of the measurements can be interpreted as meaning that some cells only react to certain relative movements of object (spot) and background (noise). The movement of the visual background is interpreted as environmental movement occurring due to the animal's own movement. The results of the measurements provide all the necessary presuppositions for a distinction between the animal's own velocity and that of the object (Part I). The experimental results can be interpreted with a model. The essential factor for the interpretation is the direction specific behavior of the cells which is bound up with an asymmetrical spatial coupling of the neurons with each other. The decisive advantage of asymmetrical systems for the pattern recognition of moving objects is that they can work without distortion and spatial displacement over large ranges of velocity (Part II).This research was supported by DFG Grant Se 251/7. Prof. Dr.-Ing. W. v. Seelen was in charge of the project     

Extraction of objects from structured backgrounds in the cat superior colliculus. Part I

Specific changes occur in the cells of the upper layers of the cat's supperior collicules when a two dimensional noise (background) is superimposed onto a deterministic signal (spot of light). Some of the measurements can be interpreted as meaning that some cells only react to certain relative movements of object (spot) and background (noise). The movement of the visual background is interpreted as environmental movement occurring due to the animal's own movement. The results of the measurements provide all the necessary presuppositions for a distinction between the animal's own velocity and that of the object (Part I). The experimental results can be interpreted with a model. The essential factor for the interpretation is the direction specific behavior of the cells which is bound up with an asymmetrical spatial coupling of the neurons with each other. The decisive advantage of asymmetrical systems for the pattern recognition of moving objects is that they can work without distortion and spatial displacement over large ranges of velocity (Part II).This research was supported by DFG Grant Se 251/7. Prof. Dr.-Ing. W.v. Seelen was in charge of the project     

A computational theory of visual receptive fields

A receptive field constitutes a region in the visual field where a visual cell or a visual operator responds to visual stimuli. This paper presents a theory for what types of receptive field profiles can be regarded as natural for an idealized vision system, given a set of structural requirements on the first stages of visual processing that reflect symmetry properties of the surrounding world. These symmetry properties include (i) covariance properties under scale changes, affine image deformations, and Galilean transformations of space–time as occur for real-world image data as well as specific requirements of (ii) temporal causality implying that the future cannot be accessed and (iii) a time-recursive updating mechanism of a limited temporal buffer of the past as is necessary for a genuine real-time system. Fundamental structural requirements are also imposed to ensure (iv) mutual consistency and a proper handling of internal representations at different spatial and temporal scales. It is shown how a set of families of idealized receptive field profiles can be derived by necessity regarding spatial, spatio-chromatic, and spatio-temporal receptive fields in terms of Gaussian kernels, Gaussian derivatives, or closely related operators. Such image filters have been successfully used as a basis for expressing a large number of visual operations in computer vision, regarding feature detection, feature classification, motion estimation, object recognition, spatio-temporal recognition, and shape estimation. Hence, the associated so-called scale-space theory constitutes a both theoretically well-founded and general framework for expressing visual operations. There are very close similarities between receptive field profiles predicted from this scale-space theory and receptive field profiles found by cell recordings in biological vision. Among the family of receptive field profiles derived by necessity from the assumptions, idealized models with very good qualitative agreement are obtained for (i) spatial on-center/off-surround and off-center/on-surround receptive fields in the fovea and the LGN, (ii) simple cells with spatial directional preference in V1, (iii) spatio-chromatic double-opponent neurons in V1, (iv) space–time separable spatio-temporal receptive fields in the LGN and V1, and (v) non-separable space–time tilted receptive fields in V1, all within the same unified theory. In addition, the paper presents a more general framework for relating and interpreting these receptive fields conceptually and possibly predicting new receptive field profiles as well as for pre-wiring covariance under scaling, affine, and Galilean transformations into the representations of visual stimuli. This paper describes the basic structure of the necessity results concerning receptive field profiles regarding the mathematical foundation of the theory and outlines how the proposed theory could be used in further studies and modelling of biological vision. It is also shown how receptive field responses can be interpreted physically, as the superposition of relative variations of surface structure and illumination variations, given a logarithmic brightness scale, and how receptive field measurements will be invariant under multiplicative illumination variations and exposure control mechanisms.     

Methoden zum Vergleich des Leistungsvermögens biologischer und technischer Systeme

Summary In this work the methods of the communication theory for binary detection, multiple detection and extraction are applied to biological systems. It is the objective of this investigation to compare the performance of optimal and biological systems in receiving signals superimposed by noise. The required mathematical relations and methods of measurements are derived.In the second part of this work pattern recognition experiments (multiple detection) at the human visual system with stationary and time variant patterns are described. The comparison of the performance between optimal and biological system shows that the human visual system acts in a suboptimal way. From some other detection experiments it can be concluded that the recognition process is describable by spatial cross-correlation.

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Herr Dr. von Seelen ist seit dem 1. Januar 1971 Mitarbeiter des Battelle-Instituts, Frankfurt.

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Von Herrn Dr. Reinig wurden die optischen Versuche zum großen Teil aufgebaut und durchgeführt.

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Die Verfasser danken dem Bundesministerium für Bildung und Wissenschaft für die Förderung dieser Arbeit im Rahmen des Technologieprogrammes sowie Herrn Dr. H. Niemann und Herrn Dr. P. Barlai für ihre Unterstützung bei Rechnerbzw. Holographieproblemen.     

The influence of two-dimensional stimulus properties in a reconstruction task with minimal information stimuli

Effects of viewpoint that are typically found in shape recognition tasks have been interpreted in the past as strong evidence against approaches based on the use of geometric invariants by the human visual system. At first sight, the use of such invariants would indeed predict shape recognition to be viewpoint independent. It has been argued before, however, that the visual estimation of invariants need not itself be invariant. Changes of viewpoint introduce changes in 2D stimulus features. The latter may make the estimation of invariants by the visual system more or less difficult. The present study explores how such 2D features influence estimation distributions in a reconstruction paradigm. Subjects were shown four coplanar dots. They were asked to estimate the position of one of the dots relative to the three others on the basis of a slanted version of the configuration. An estimation distribution was obtained for every position of the dot to be estimated. Biases in these distributions indicated that subjects performed the task by using 2D reference axes that were unambiguously identifiable in both the images of the dot pattern.