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...
A hint is any piece of side information about the target function to be learned. We consider the monotonicity hint, which states that the function to be learned is monotonic in some or all of the input variables. The ...
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ISBN:
(纸本)0262100657
A hint is any piece of side information about the target function to be learned. We consider the monotonicity hint, which states that the function to be learned is monotonic in some or all of the input variables. The application of monotonicity hints is demonstrated on two real-world problems- a credit card application task, and a problem in medical diagnosis. A measure of the monotonicity error of a candidate function is defined and an objective function for the enforcement of monotonicity is derived from Bayesian principles. We report experimental results which show that using monotonicity hints leads to a statistically significant improvement in performance on both problems.
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 neuralsystems....
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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 neuralsystems. 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.
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 tim...
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.
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 spect...
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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.
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 ...
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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)].
We have designed and tested a one-dimensional 64 pixel, analog CMOS VLSI chip which localizes intensity edges in real-time. This device exploits on-chip photoreceptors and the natural filtering properties of resistive...
ISBN:
(纸本)9781558601840
We have designed and tested a one-dimensional 64 pixel, analog CMOS VLSI chip which localizes intensity edges in real-time. This device exploits on-chip photoreceptors and the natural filtering properties of resistive networks to implement a scheme similar to and motivated by the Difference of Gaussians (DOG) operator proposed by Marr and Hildreth (1980). Our chip computes the zero-crossings associated with the difference of two exponential weighting functions. If the derivative across this zero-crossing is above a threshold, an edge is reported. Simulations indicate that this technique will extend well to two dimensions.
Information from the senses must be compressed into the limited range of firing rates generated by spiking nerve cells. Optimal compression uses all firing rates equally often, implying that the nerve cell's respo...
Information from the senses must be compressed into the limited range of firing rates generated by spiking nerve cells. Optimal compression uses all firing rates equally often, implying that the nerve cell's response matches the statistics of naturally occurring stimuli. Since changing the voltage-dependent ionic conductances in the cell membrane alters the flow of information, an unsupervised, non-Hebbian, developmental learning rule is derived to adapt the conductances in Hodgkin-Huxley model neurons. By maximizing the rate of information transmission, each firing rate within the model neuron's limited dynamic range is used equally often.
We describe a parallel analog VLSI architecture that integrates optical flow data obtained from arrays of elementary velocity sensors to estimate the direction of heading for pure translational motion sequences. We pe...
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We describe a parallel analog VLSI architecture that integrates optical flow data obtained from arrays of elementary velocity sensors to estimate the direction of heading for pure translational motion sequences. We performed software simulations at different levels of abstraction to evaluate the most important qualitative properties of the optical flow field, determine the best functional operators for the implementation of the architecture and define the numerical values of some of the free parameters present in the hardware implementation. Furthermore we describe the properties of the circuits used in the hardware implementation and the functionality of the elementary motion sensors used to extract the optical flow field. Measurements from the chips developed and software simulation results are provided to show the validity of the followed approach.
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