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Floating-gate circuits for adaptation of saccadic eye movement accuracy

ANALOG INTEGRATED CIRCUITS AND SIGNAL PROCESSING 1997年第1-2期13卷 69-78页

作者： Horiuchi, TK Koch, C Computation and Neural Systems Program California Institute of Technology Pasadena

In this paper we describe an analog VLSI circuit, fabricated using a standard 2 mu m, n-well, BiCMOS process, which utilizes floating-gate structures for non-volatile, on-chip, analog parameter storage. This circuit is designed to operate in the context of a hardware model of the primate oculomotor system and performs visually-guided, saccadic adaptation. The chip contains a one-dimensional array of photoreceptors and floating-gate circuits which are used to map retinal positions to motor output commands. The system's functionality is demonstrated by training the chip with several different mapping functions using a supervised-learning technique.

关键词： neuromorphic analog VLSI saccadic eye movements learning floating-gate short-term adaptation

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Shunting inhibition does not have a divisive effect on firing rates

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neural computation 1997年第5期9卷 1001-1013页

作者： Holt, GR Koch, C Computation and Neural Systems Program California Institute of Technology Pasadena CA 91125 U.S.A.

Shunting inhibition, a conductance increase with a reversal potential close to the resting potential of the cell, has been shown to have a divisive effect on subthreshold excitatory postsynaptic potential amplitudes. It has therefore been assumed to have the same divisive effect on firing rates. We show that shunting inhibition actually has a subtractive effect on the firing rate in most circumstances. Averaged over several interspike intervals, the spiking mechanism effectively clamps the somatic membrane potential to a value significantly above the resting potential, so that the current through the shunting conductance is approximately independent of the firing rate. This leads to a subtractive rather than a divisive effect. In addition, at distal synapses, shunting inhibition will also have an approximately subtractive effect if the excitatory conductance is not small compared to the inhibitory conductance. Therefore regulating a cell's passive membrane conductance-for instance, via massive feedback-is not an adequate mechanism for normalizing or scaling its output.

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Monotonicity hints

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10th Annual Conference on neural Information Processing systems, NIPS 1996

作者： Sill, Joseph Abu-Mostafa, Yaser S. Computation and Neural Systems Program California Institute of Technology United States EE Department California Institute of Technology United States

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.

关键词： Diagnosis

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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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An analog VLSI model of the fly elementary motion detector 97

An analog VLSI model of the fly elementary motion detector

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Proceedings of the 11th International Conference on neural Information Processing systems

作者： Reid R. Harrison Christof Koch Computation and Neural Systems Program California Institute of Technology Pasadena CA

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-µm analog CMOS VLSI process. The result 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.

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Synaptic transmission: an information-theoretic perspective 97

Synaptic transmission: an information-theoretic perspective

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Proceedings of the 10th International Conference on neural Information Processing systems

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

Here we analyze synaptic transmission from an information-theoretic perspective. We derive closed-form expressions for the lower-bounds on the capacity of a simple model of a cortical synapse under two explicit coding paradigms. Under the "signal estimation" paradigm, we assume the signal to be encoded in the mean firing rate of a Poisson neuron. The performance of an optimal linear estimator of the signal then provides a lower bound on the capacity for signal estimation. Under the "signal detection" paradigm, the presence or absence of the signal has to be detected. Performance of the optimal spike detector allows us to compute a lower bound on the capacity for signal detection. We find that single synapses (for empirically measured parameter values) transmit information poorly but significant improvement can be achieved with a small amount of redundancy.

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Monotonic networks 97

Monotonic networks

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Proceedings of the 11th International Conference on neural Information Processing systems

作者： Joseph Sill Computation and Neural Systems program California Institute of Technology Pasadena CA

Monotonicity is a constraint which arises in many application domains. We present a machine learning model, the monotonic network, for which monotonicity can be enforced exactly, i.e., by virtue of functional form. A straightforward method for implementing and training a monotonic network is described. Monotonic networks are proven to be universal approximators of continuous, differentiable monotonic functions. We apply monotonic networks to a real-world task in corporate bond rating prediction and compare them to other approaches.

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computation and the single neuron

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NATURE 1997年第6613期385卷 207-210页

作者： Koch, C Computation and Neural Systems Program California Institute of Technology Pasadena California 91125 USA (e-mail: koch @klab. caltech. edu).

Neurons and their networks underlie our perceptions, actions and memories. The latest work on information processing and storage at the single-cell level reveals previously unimagined complexity and dynamism.

关键词： Adaptation, Physiological Animals Dendrites/physiology Nerve Net/physiology Neuronal Plasticity Neurons/physiology Synapses/physiology Time Factors

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Incorporating contextual information in white blood cell identification 97

Incorporating contextual information in white blood cell ide...

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Proceedings of the 11th International Conference on neural Information Processing systems

作者： Xubo Song Yaser Abu-Mostafa Joseph Sill Department of Electrical Engineering California Institute of Technology Pasadena CA Dept. of Electrical Engineering and Dept. of Computer Science California Institute of Technology Pasadena CA Computation and Neural Systems Program California Institute of Technology Pasadena CA

In this paper we propose a technique to incorporate contextual information into object classification. In the real world there are cases where the identity of an object is ambiguous due to the noise in the measurements based on which the classification should be made. It is helpful to reduce the ambiguity by utilizing extra information referred to as context, which in our case is the identities of the accompanying objects. This technique is applied to white blood cell classification. Comparisons are made against "no context" approach, which demonstrates the superior classification performance achieved by using context. In our particular application, it significantly reduces false alarm rate and thus greatly reduces the cost due to expensive clinical tests.

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Contribution of somatosensory cortex to responses in the rat cerebellar granule cell layer following peripheral tactile stimulation

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EXPERIMENTAL BRAIN RESEARCH 1996年第2期109卷 240-250页

作者： Morissette, J Bower, JM Computation and Neural Systems Program Caltech 216-76 California Institute of Technology Pasadena USA

The spatial coincidence of somatosensory cerebral cortex (SI) and trigeminal projections to the cerebellar hemisphere has been previously demonstrated. In this paper we describe the temporal relationship between tactilely-evoked responses in SI and in the granule cell layer of the cerebellar hemisphere, in anesthetized rats. We simultaneously recorded field potentials in areas of common receptive fields of SI and of the cerebellar folium crus IIa after peripheral tactile stimulation of the corresponding facial area. Response of the cerebellar granule cell layer to a brief tactile stimulation consisted of two components at different latencies. We found a strong correlation between the latency of the SI response and that of the second (long-latency) cerebellar component following facial stimulation. No such relationship was found between the latency of the SI response and that of the first (short-latency) cerebellar component, originating from a direct trigeminocerebellar pathway. In addition, lidocaine pressure injection in SI, cortical ablation, and decerebration all significantly affected the second cerebellar peak but not the first. Further, when tactile stimuli were presented 75 ms apart, the response in SI failed, as did the second cerebellar peak, while the short-latency cerebellar response still occurred. We found a wide spatial distribution of the upper lip response beyond the upper lip area in crus IIa for the long-latency component of the cerebellar response. Our results demonstrate that SI is the primary contributor to the cerebellar long-latency response to peripheral tactile stimulation. These results are discussed in the context of Purkinje cell responses to tactile input.

关键词： field potential timing lidocaine somatosensory cerebral cortex crus Ila mossy fiber cerebellum rat

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