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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Biological cybernetics 55 (1986), S. 1-4 
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract Eye movements were produced in an elasmobranch preparation by electrical stimulation of the horizontal canal ampullary nerves. A pseudorandom binary sequence of stimulus pulse trains was delivered bilaterally. Eye position during this stimulus was cross-correlated with the stimulus pattern to obtain a linear model of the response. Sums of exponential functions were fitted to the crosscorrelogram data to estimate time-constants and transfer functions. The data was examined in the frequency domain by using Fourier transformation. The response is accurately described by a second order linear filter, which is essentially a low pass filter with a cutoff at 0.22 Hz. This nearly two octaves below the cutoff frequency of the eye motor plant, which has been estimated by the same method. Our data shows that there is no central phase compensation or prediction which might offset the substantial delay in eye motor plant response. We hypothesise that the necessary phase compensation may be achieved by driving the vestibulo-ocular reflex with sensory neurons having a phase advance at high frequency.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Journal of comparative physiology 158 (1986), S. 723-728 
    ISSN: 1432-1351
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Medicine
    Notes: Summary 1. A pseudorandom binary sequence electrical pulse rate stimulus was delivered to the abducens nerve of an elasmobranch preparation. Ipsilateral eye movements were recorded using a position-sensitive photodiode to measure the position of a reflective patch attached to the fish's eye. 2. Eye position data was cross-correlated with the stimulus pattern, and exponential decay curves were fitted to the cross-correlograms to estimate the time constant of a linear first order low-pass filter model. The cross-correlograms were transformed into the frequency domain using a Digital Fourier Transform, and Bode plots of eye dynamics were plotted. 3. Eye motor plant dynamics in the elasmobranchCephaloscyllium isabella can be accurately characterised by a linear first order low-pass filter model with a corner frequency of 0.73±0.10 Hz. Non-minimum phase lag reaches 90
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Journal of comparative physiology 177 (1995), S. 723-736 
    ISSN: 1432-1351
    Keywords: Adaptive filter ; Anti-Hebbian synaptic ; plasticity ; Computer simulation ; Dorsal octavolateral nucleus ; Neural model
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Medicine
    Notes: Abstract The electrosensory system of elasmobranchs is extremely sensitive to weak electric fields, with behavioral thresholds having been reported at voltage gradients as low as 5 nV/cm. To achieve this amazing sensitivity, the electrosensory system must extract weak extrinsic signals from a relatively large reafferent background signal associated with the animal's own movements. Ventilatory movements, in particular, strongly modulate the firing rates of primary electrosensory afferent nerve fibers, but this modulation is greatly suppressed in the medullary electrosensory processing nucleus, the dorsal octavolateral nucleus. Experimental evidence suggests that the neural basis of reafference suppression involves a common-mode rejection mechanism supplemented by an adaptive filter that fine tunes the cancellation. We present a neural model and computer simulation results that support the hypothesis that the adaptive component may involve an anti-Hebbian form of synaptic plasticity at molecular layer synapses onto ascending efferent neurons, the principal output neurons of the nucleus. Parallel fibers in the molecular layer carry a wealth of proprioceptive, efference copy, and sensory signals related to the animal's own movements. The proposed adaptive mechanism acts by canceling out components of the electrosensory input signal that are consistently correlated with these internal reference signals.
    Type of Medium: Electronic Resource
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  • 4
    Publication Date: 2009-11-23
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
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  • 5
    Publication Date: 1986-10-01
    Print ISSN: 0340-1200
    Electronic ISSN: 1432-0770
    Topics: Biology , Computer Science , Physics
    Published by Springer
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  • 6
    Publication Date: 2011-08-24
    Description: We have developed a neural system identification method for fitting models to stimulus-response data, where the response is a spike train. The method involves using a general nonlinear optimisation procedure to fit models in the time domain. We have applied the method to model bullfrog semicircular canal afferent neuron responses during naturalistic, broad-band head rotations. These neurons respond in diverse ways, but a simple four parameter class of models elegantly accounts for the various types of responses observed. c1999 Elsevier Science B.V. All rights reserved.
    Keywords: Life Sciences (General)
    Type: Neurocomputing (ISSN 0925-2312); Volume 26-27; 1-3; 223-8
    Format: text
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  • 7
    Publication Date: 2011-08-24
    Description: Receptive fields are commonly used to describe spatial characteristics of sensory neuron responses. They can be extended to characterize temporal or dynamical aspects by mapping neural responses in dynamical state spaces. The state-space receptive field of a neuron is the probability distribution of the dynamical state of the stimulus-generating system conditioned upon the occurrence of a spike. We have computed state-space receptive fields for semicircular canal afferent neurons in the bullfrog (Rana catesbeiana). We recorded spike times during broad-band Gaussian noise rotational velocity stimuli, computed the frequency distribution of head states at spike times, and normalized these to obtain conditional pdfs for the state. These state-space receptive fields quantify what the brain can deduce about the dynamical state of the head when a single spike arrives from the periphery. c2001 Elsevier Science B.V. All rights reserved.
    Keywords: Life Sciences (General)
    Type: Neurocomputing (ISSN 0925-2312); Volume 38-40; 1-4; 293-8
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  • 8
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    In:  Other Sources
    Publication Date: 2011-08-24
    Description: We define a measure for evaluating the quality of a predictive model of the behavior of a spiking neuron. This measure, information gain per spike (Is), indicates how much more information is provided by the model than if the prediction were made by specifying the neuron's average firing rate over the same time period. We apply a maximum Is criterion to optimize the performance of Gaussian smoothing filters for estimating neural firing rates. With data from bullfrog vestibular semicircular canal neurons and data from simulated integrate-and-fire neurons, the optimal bandwidth for firing rate estimation is typically similar to the average firing rate. Precise timing and average rate models are limiting cases that perform poorly. We estimate that bullfrog semicircular canal sensory neurons transmit in the order of 1 bit of stimulus-related information per spike.
    Keywords: Life Sciences (General)
    Type: Neural networks : the official journal of the International Neural Network Society (ISSN 0893-6080); Volume 14; 6-7; 877-81
    Format: text
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  • 9
    Publication Date: 2018-06-08
    Description: We present a model of cerebellar cortex that combines two types of learning: feedforward predicitve association based on local Hebbian-type learning between granule cell ascending branch and parallel fiber inputs, and reinforcement learning with feedback error correction based on climbing fiber activity.
    Type: Tenth Annual Computational Neuroscience Meeting; San Francisco, CA; United States
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  • 10
    Publication Date: 2019-07-13
    Description: The cerebellum is a neural structure that is essential for agility in vertebrate movements. Its contribution to motor control appears to be due to a fundamental role in dynamical state estimation, which also underlies its role in various non-motor tasks. Single spikes in vestibular sensory neurons carry information about head state. We show how computations for optimal dynamical state estimation may be accomplished when signals are encoded in spikes. This provides a novel way to design dynamical state estimators, and a novel way to interpret the structure and function of the cerebellum.
    Keywords: Life Sciences (General)
    Type: Autonomous robots (ISSN 0929-5593); 11; 3; 279-84
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