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11th Annual Conference on neural Information Processing systems, NIPS 1997

作者： Harrison, Reid R. Koch, Christof Computation and Neural Systems Program 139-74 California Institute of Technology Pasadena CA 91125 United States

ISBN: (纸本)0262100762

Flies are capable of rapidly detecting and integrating visual motion information in behaviorly-relevant ways. The first stage of visual motion processing in flies is a retinotopic array of functional units known as elementary motion detectors (EMDs). Several decades ago, Reichardt and colleagues developed a correlation-based model of motion detection that described the behavior of these neural circuits. We have implemented a variant of this model in a 2.0-/im analog CMOS VLSI process. The re-sult is a low-power, continuous-time analog circuit with integrated photoreceptors that responds to motion in real time. The responses of the circuit to drifting sinusoidal gratings qualitatively resemble the temporal frequency response, spatial frequency response, and direction selectivity of motion-sensitive neurons observed in insects. In addition to its possible engineering applications, the circuit could potentially be used as a building block for constructing hardware models of higher-level insect motion integration.

关键词： Frequency response

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Distinct rhythmic locomotor patterns can be generated by a simple adaptive neural circuit: Biology, simulation, and VLSI implementation

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Journal of computational Neuroscience 1994年第4期1卷 339-358页

作者： Ryckebusch, Sylvie Wehr, Mike Laurent, Gilles California Institute ofTechnology Biology Division Computation and Neural Systems Program Pasadena 91125 CA Mail Code 139-74 United States

Rhythmic motor patterns can be induced in leg motor neurons of isolated locust thoracic ganglia by bath application of pilocarpine. We observed that the relative phases of levators and depressors differed in the three thoracic ganglia. Assuming that the central pattern generating circuits underlying these three segmental rhythms are probably very similar, we developed a simple model circuit that can produce any one of the three activity patterns and characteristic phase relationships by modifying a single synaptic weight. We show results of a computer simulation of this circuit using the neuronal simulator neuralOG/Spike. We built and tested an analog VLSI circuit implementation of this model circuit that exhibits the same range of "behaviors" as the computer simulation. This multidisciplinary strategy will be useful to explore the dynamics of central pattern generating networks coupled to physical actuators, and ultimately should allow the design of biologically realistic walking robots. © 1994 Kluwer Academic Publishers.

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Collective frequencies and metastability in networks of limit-cycle oscillators with time delay

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Physical Review Letters 1991年第20期67卷 2753-2753页

作者： Ernst Niebur Heinz G. Schuster Daniel M. Kammen Computation and Neural Systems Program California Institute of Technology Pasadena California 91125

We analyze the dynamic behavior of large two-dimensional systems of limit-cycle oscillators with random intrinsic frequencies that interact via time-delayed nearest-neighbor coupling. We find that even small delay times lead to a novel form of frequency depression where the system decays to stable states which oscillate at a delay and interaction-dependent reduced collective frequency. For greater delay or tighter coupling between oscillators we find metastable synchronized states that we describe analytically and numerically.

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Modeling structural plasticity in the barn owl auditory localization system with a spike-time dependent hebbian learning rule

Modeling structural plasticity in the barn owl auditory loca...

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International Joint Conference on neural Networks, IJCNN 2005

作者： Mysore, Shreesh P. Quartz, Steven R. Control and Dynamical Systems Program California Institute of Technology Pasadena CA 91125 Division of the Humanities and Social Sciences Computation and Neural Systems Program California Institute of Technology Pasadena CA 91125

ISBN: (纸本)0780390482

Auditory localization behavior in barn owls is mediated by the integration of topographically encoded visual and auditory space maps. In juvenile owls, disruption of the audio-visual map alignment by exposure to spectacles that laterally shift the visual input results in behavioral adaptation over the course of several weeks. It has been reported in literature that this adaptation is produced by architectural plasticity in the neural circuits encoding the space maps. It is known that this plasticity is guided by visual input in a topographic manner, and that the error signal is embedded in the firing dynamics of neurons in the inferior colliculus. In this work, we use leaky integrateand-fire neurons to model the key elements in the auditory localization circuit of barn owls. We demonstrate that a Hebbian spike-time dependent learning rule, coupled with an activity-dependent mechanism that promotes growth, can account for the essentials of circuit-level plasticity associated with prism experience. We point out the importance of inhibition in both the normal functioning of this circuit, and prism-induced plasticity, and comment on potential mechanisms for activity-induced growth.

关键词： Learning systems

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Channel noise in excitable neuronal membranes

Channel noise in excitable neuronal membranes

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13th Annual neural Information Processing systems Conference, NIPS 1999

作者： Manwani, Amit Steinmetz, Peter N. Koch, Christof Computation and Neural Systems Program M-S 139-74 California Institute of Technology Pasadena CA 91125 United States

ISBN: (纸本)0262194503

Stochastic fluctuations of voltage-gated ion channels generate current and voltage noise in neuronal membranes. This noise may be a critical determinant of the efficacy of information processing within neural systems. Using Monte-Carlo simulations, we carry out a systematic investigation of the relationship between channel kinetics and the resulting membrane voltage noise using a stochastic Markov version of the Mainen-Sejnowski model of dendritic excitability in cortical neurons. Our simulations show that kinetic parameters which lead to an increase in membrane excitability (increasing channel densities, decreasing temperature) also lead to an increase in the magnitude of the sub-threshold voltage noise. Noise also increases as the membrane is depolarized from rest towards threshold. This suggests that channel fluctuations may interfere with a neuron's ability to function as an integrator of its synaptic inputs and may limit the reliability and precision of neural information processing.

关键词： Membranes

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Control of chaos by oscillating feedback

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Physical Review E 1997年第6期56卷 6410-6410页

作者： H. G. Schuster M. B. Stemmler Computation and Neural Systems Program California Institute of Technology 139-74 Pasadena California 91125

Parametric feedback control of chaos relies on detailed knowledge of the locations of unstable periodic orbits. We show that unstable periodic orbits of dynamical systems with unknown locations but known periodicity τ can be stabilized by an oscillating feedback term proportional to ɛt (x→t−x→t−τ), where x→t is the location of the trajectory at time t and ɛt is periodic in time. Periodic feedback overcomes the limitations of Giona’s theorem [Nonlinearity 4, 911 (1991)], which states that constant feedback (i.e., a time-independent ɛ) can stabilize an unstable periodic orbit only if the stability matrix has no positive eigenvalues greater than unity. As an application of oscillating feedback, we use it to stabilize the memory patterns in an associative memory (Hopfield [Proc. Natl. Acad. Sci. USA 79, 2554 (1982); 81, 3088 (1984)]) network, thereby enhancing the total capacity of the memory device. We extend our method to high-dimensional systems described by differential equations; in this framework, it is possible to stabilize the spatiotemporal chaos generated by the Kuramoto-Sivashinsky equation [G. J. Sivashinsky and D. M. Michelson, Prog. Theor. Phys. 63, 2122 (1980)].

关键词： Dynamics

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A two-dimensional analog VLSI circuit for detecting discontinuities in early vision

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Science 1990年第4960期248卷 1209-1211页

作者： Harris, John G. Koch, Christof Luo, Jin Computation and Neural Systems Program California Institute of Technology Pasadena CA 91125 United States Division of Biology 216-76 California Institute of Technology Pasadena CA 91125 United States

A large number of computer vision algorithms for finding intensity edges, computing motion, depth, and color, and recovering the three-dimensional shape of objects have been developed within the framework of minimizing an associated "energy" or "cost" functional. Particularly successful has been the introduction of binary variables coding for discontinuities in intensity, optical flow field, depth, and other variables, allowing image segmentation to occur in these modalities. The associated nonconvex variational functionals can be mapped onto analog, resistive networks, such that the stationary voltage distribution in the network corresponds to a minimum of the functional. The performance of an experimental analog very-large-scale integration (VLSI) circuit implementing the nonlinear resistive network for the problem of two-dimensional surface interpolation in the presence of discontinuities is demonstrated;this circuit is implemented in complementary metal oxide semiconductor technology.

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Oscillator-phase coupling for different two-dimensional network connectivities

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Physical Review A 1991年第10期44卷 6895-6895页

作者： Ernst Niebur Heinz G. Schuster Daniel M. Kammen Christof Koch Computation and Neural Systems Program California Institute of Technology 216-76 Pasadena California 91125

We investigate the dynamics of large arrays of coupled phase oscillators driven by random intrinsic frequencies under a variety of coupling schemes, by computing the time-dependent cross-correlation function numerically for a two-dimensional array consisting of 128×128 oscillators as well as analytically for a simpler model. Our analysis shows that for overall equal interaction strength, a sparse-coupling scheme in which each oscillator is coupled to a small, randomly selected subset of its neighbors leads to a more rapid and robust phase locking than nearest-neighbor coupling or locally dense connection schemes.

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A computer modeling approach to understanding the inferior olive and its relationship to the cerebellar cortex in rats 89

A computer modeling approach to understanding the inferior o...

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Proceedings of the 2nd International Conference on neural Information Processing systems

作者： Maurice Lee James M. Bower Computation and Neural Systems Program California Institute of Technology Pasadena CA

This paper presents the results of a simulation of the spatial relationship between the inferior olivary nucleus and folium crus IIA of the lateral hemisphere of the rat cerebellum. The principal objective of this modeling effort was to resolve an apparent conflict between a proposed zonal organization of olivary projections to cerebellar cortex suggested by anatomical tract-tracing experiments (Brodal & Kawamura 1980; Campbell & Armstrong 1983) and a more patchy organization apparent with physiological mapping (Robertson 1987). The results suggest that several unique features of the olivocerebellar circuit may contribute to the appearance of zonal organization using anatomical techniques, but that the detailed patterns of patchy tactile projections seen with physiological techniques are a more accurate representation of the afferent organization of this region of cortex.

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Channel noise in excitable neuronal membranes 99

Channel noise in excitable neuronal membranes

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Proceedings of the 12th International Conference on neural Information Processing systems

作者： Amit Manwani Peter N. Steinmetz Christof Koch Computation and Neural Systems Program California Institute of Technology Pasadena CA

Stochastic fluctuations of voltage-gated ion channels generate current and voltage noise in neuronal membranes. This noise may be a critical determinant of the efficacy of information processing within neural systems. Using Monte-Carlo simulations, we carry out a systematic investigation of the relationship between channel kinetics and the resulting membrane voltage noise using a stochastic Markov version of the Mainen-Sejnowski model of dendritic excitability in cortical neurons. Our simulations show that kinetic parameters which lead to an increase in membrane excitability (increasing channel densities, decreasing temperature) also lead to an increase in the magnitude of the subthreshold voltage noise. Noise also increases as the membrane is depolarized from rest towards threshold. This suggests that channel fluctuations may interfere with a neuron's ability to function as an integrator of its synaptic inputs and may limit the reliability and precision of neural information processing.

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