Miron Derchansky

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We present a neural recording and spectral analysis RECORDING ANALYSIS integrated microsystem. It is the instrumentational and computa-INTERACE PROCESSOR tional core of an envisioned miniature implantable brain implant for automated epileptic seizure therapy. The microsystem com-WAVELET bines two functional blocks: the neural recording interface and(More)
A 256-channel integrated interface for simultaneous recording of distributed neural activity from acute brain slices is presented. An array of 16 times 16 Au recording electrodes are fabricated directly on the die. Each channel implements differential voltage acquisition, amplification and band-pass filtering. In-channel analog memory stores an electronic(More)
In this paper, we investigate the dynamical scenarios of transitions between normal and paroxysmal state in epilepsy. We assume that some epileptic neural network are bistable i.e., they feature two operational states, ictal and interictal that co-exist. The transitions between these two states may occur according to a Poisson process, a random walk process(More)
— The architecture and VLSI implementation of an epileptic seizure prediction microsystem are presented. The microsystem comprises a neural recording interface and a seizure prediction processor. The two functional blocks have been proto-typed in a 0.35 µm CMOS technology and experimentally characterized. The integrated microsystem is validated in(More)
We present an architecture of an epileptic seizure prediction system suitable for an implantable implementation. The microsystem comprises a neural interface, a spectral analysis processor and an artificial neural network (ANN). The neural interface and the spectral analysis processor have been prototyped in a 0.35 microm CMOS technology with experimental(More)
BACKGROUND High-dose opioid therapy can precipitate seizures; however, the mechanism of such a dangerous adverse effect remains poorly understood. The aim of our study was to determine whether the neuroexcitatory activity of high-dose morphine is mediated by selective stimulation of opioid receptors. METHODS Mice hippocampi were resected intact and bathed(More)
It has been previously shown that wavelet artificial neural networks (WANNs) are able to classify the different states of epileptiform activity and predict the onsets of seizure-like events (SLEs) by offline processing (Ann. Biomed. Eng. 33(6):798-810, 2005) of the electrical data from the in-vitro hippocampal slice model of recurrent spontaneous SLEs. The(More)
BACKGROUND Epilepsy is a common neurological disorder characterized by recurrent electrophysiological activities, known as seizures. Without the appropriate detection strategies, these seizure episodes can dramatically affect the quality of life for those afflicted. The rationale of this study is to develop an unsupervised algorithm for the detection of(More)
We present an architecture and VLSI implemen-Various strategies in the analysis of spatio-temporal dynam-tation of a distributed neural interface and spatio-temporal ics of the neuronal activity have been developed. Examples of signal processor. The integrated neural interface records neural such analysis include cross-correlation, spectral analysis [9](More)