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San Fedele Superiore, Italy

Bamford S.A.,University of Edinburgh | Bamford S.A.,Complex Systems Modelling Group | Murray A.F.,University of Edinburgh | Willshaw D.J.,University of Edinburgh
Electronics Letters | Year: 2012

A neuromorphic chip with an array of neurons has connections ('synapses') which implement a biological learning mechanism known as spike-timing-dependent plasticity. STDP is a homeostatic mechanism which regulates the firing rate of neurons. In this reported work, this mechanism is shown to reduce variation in performance between neurons, due to both mismatch in fabrication and inhomogeneities in the electronic design. © 2012 The Institution of Engineering and Technology.

Bamford S.A.,University of Edinburgh | Bamford S.A.,Complex Systems Modelling Group | Murray A.F.,University of Edinburgh | Willshaw D.J.,University of Edinburgh
IEEE Transactions on Biomedical Circuits and Systems | Year: 2012

Analogue and mixed-signal VLSI implementations of Spike-Timing-Dependent Plasticity (STDP) are reviewed. A circuit is presented with a compact implementation of STDP suitable for parallel integration in large synaptic arrays. In contrast to previously published circuits, it uses the limitations of the silicon substrate to achieve various forms and degrees of weight dependence of STDP. It also uses reverse-biased transistors to reduce leakage from a capacitance representing weight. Chip results are presented showing: various ways in which the learning rule may be shaped; how synaptic weights may retain some indication of their learned values over periods of minutes; and how distributions of weights for synapses convergent on single neurons may shift between more or less extreme bimodality according to the strength of correlational cues in their inputs. © 2007-2012 IEEE.

Bamford S.A.,University Pompeu Fabra | Bamford S.A.,Complex Systems Modelling Group | Giulioni M.,Complex Systems Modelling Group
2010 IEEE Biomedical Circuits and Systems Conference, BioCAS 2010 | Year: 2010

A field-programmable device has been developed, specialised for neural signal processing and neural modelling applications. The device combines analogue and digital functions, yet unlike other designs for Field-Programmable Mixed-signal Arrays (FPMA), there is no separation between the analogue and digital domains. To allow analogue values to act directly as inputs to digital blocks, all digital circuitry has limited crowbar current. The method of limiting yields lopsided logic thresholds. Two uses of this are demonstrated: a gate which detects digital saturation, and a D-type flip flop which is insensitive to clock slew rate. ©2010 IEEE.

Bamford S.A.,Complex Systems Modelling Group | Bamford S.A.,University Pompeu Fabra | Hogri R.,Tel Aviv University | Giovannucci A.,University Pompeu Fabra | And 7 more authors.
IEEE Transactions on Neural Systems and Rehabilitation Engineering | Year: 2012

A very-large-scale integration field-programmable mixed-signal array specialized for neural signal processing and neural modeling has been designed. This has been fabricated as a core on a chip prototype intended for use in an implantable closed-loop prosthetic system aimed at rehabilitation of the learning of a discrete motor response. The chosen experimental context is cerebellar classical conditioning of the eye-blink response. The programmable system is based on the intimate mixing of switched capacitor analog techniques with low speed digital computation; power saving innovations within this framework are presented. The utility of the system is demonstrated by the implementation of a motor classical conditioning model applied to eye-blink conditioning in real time with associated neural signal processing. Paired conditioned and unconditioned stimuli were repeatedly presented to an anesthetized rat and recordings were taken simultaneously from two precerebellar nuclei. These paired stimuli were detected in real time from this multichannel data. This resulted in the acquisition of a trigger for a well-timed conditioned eye-blink response, and repetition of unpaired trials constructed from the same data led to the extinction of the conditioned response trigger, compatible with natural cerebellar learning in awake animals. © 2012 IEEE.

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