Review article: gastric electrical stimulation for gastroparesis--physiological foundations, technical aspects and clinical implications.

BACKGROUND: Application of electrical stimulation to the gut, primarily the stomach, has rapidly advanced in the last two decades, from mostly animal studies to the clinical arena. Most studies focused on the use of electrical stimulation for gastroparesis, the only approved indication for such intervention. AIM: To review the physiological basis of gastric electrical activity and the technical aspects and clinical outcome of gastric electrical stimulation (GES) for gastroparesis. METHODS: PubMed search from 1966 to 2009, using gastroparesis and GES as search terms. Areas in focus were systematically reviewed. RESULTS: The literature consists of open-label studies, mostly from single centres, published in the last decade. Improvement in symptoms, quality of life and nutritional status was reported by most studies. Physiologically, stimulation parameters approved in clinical practice do not regulate gastric slow wave activity and have inconsistent effect on gastric emptying. The mechanism of action of GES is not fully known, but data support modulation of gastric biomechanical activity and afferent neural mechanisms. CONCLUSIONS: Gastric electrical stimulation is a helpful intervention in recalcitrant gastroparesis. Controlled studies and better understanding of mechanisms of action of electrical stimulation are needed to evaluate further the clinical utility of this intervention and to exploit its therapeutic potential better.

The use of gastric electrical signals for algorithm for automatic eating detection in dogs.

Food ingestion increases fundic impedance (FI) and reduces antral slow wave rate (SWR). Our aim was to determine if such changes can be integrated into an algorithm for automatic eating detection (AED). When incorporated in implantable medical devices, AED can time treatment to food intake without need for patient input. Four dogs were implanted with fundic and antral electrodes, connected to an implantable recording device. Changes in FI and SWR induced by fixed meals of different weights were determined, and were used to build an AED algorithm. Its performance was then tested on the same animals given an ad libitum access to food. The effects of gastric balloon distension and nitroglycerin on SWR and FI were also tested. Fixed meals reduced SWR in a weight-dependent manner, R(2) = 0.936, P < 0.05 baseline compared to 50, 100, 200 and 400 g. Meals increased FI above baseline in a weight-dependent manner; R(2) = 0.994, P < 0.05 baseline compared to 200 and 400 g. During ad libitum intake, the AED algorithm detected 86% of all meals > or =15 g. Gastric distension reduced SWR and increased FI. Nitroglycerin reduced SWR. AED, using changes in FI and gastric SWR is feasible. Changes in FI and SWR are induced primarily by the presence of food in the stomach.

Circadian patterns of gastric electrical and mechanical activity in dogs.

Gastric motor function assessment, in humans and animals, is typically performed for short recording periods. The aim of this article was to monitor gastric electrical and motor activity in the antrum and fundus simultaneously, for long periods, using a new implantable system. Ten dogs were implanted with fundic and antral electrodes for assessment of impedance and electrical activity. Dogs were studied while in cages, for periods of 22-26 h. From late evening and until feeding on the next day, slow wave (SW) rhythm demonstrated a distinct pattern of intermittent pauses (mean duration = 22.8 +/-4.1 s) that delineated groups of SW's. Phasic increases in fundic tone were seen mostly in association with SW pauses, and were highly correlated with antral contractions, R(2) = 0.652, P < 0.05. The SW rate (events per minute) in the postprandial period, fasting and night time was 4.2 +/- 0.2, 5 +/- 0.2 and 4.7 +/- 0.3, respectively, P < 0.05 postprandial vs other periods. Antral and fundic mechanical activities were highly correlated during fasting, particularly at night. This novel method of prolonged gastric recording provides valuable data on the mechanical and electrical activity of the stomach, not feasible by current methods of recording. During fasting, fundic and antral motor activities are highly correlated and are associated with periodic pauses in electrical activity.

Errors in a nonlinear graphic-semantic mapping task resulting from lesions in Boltzmann machine: is it relevant to dyslexia?

One of the most fascinating aspects of brain research is the subject of language. As in many other cases, the malfunctions that occur in different persons for various reasons give us insight on the mechanisms that support our ability to talk, read and listen. Following the work of Plaut and associates, we deal with the dyslexia disorder, which is the overall name for a large number of reading disorders. A Boltzmann machine neural network scheme was trained to implement the nonlinear mapping task of graphic representation into semantic representation, which may model the brain sections responsible for the translation of a written word into meanings and syllables. After training, various types of lesions were applied and the performance of the network was tested in order to measure the effect of each lesion on the error rate and type distribution that were detected. The system's errors were classified into several categories and the distribution of errors between the categories was studied. Using the simulations, it is demonstrated that a finite scheduling process in the Boltzmann machine causes the distribution of the network's errors to be unique and different from its expected error distribution. The phenomenon is given a mathematical explanation rooted in the statistical mechanics basics of the Boltzmann machine. Test results suggest the localization of certain reading functions within the network. Comparison is made to relevant types of dyslexia and shows resemblance in major symptoms as well as in certain known side effects.

Nonstationary time series analysis by temporal clustering.

The object of this paper is to present a model and a set of algorithms for estimating the parameters of a nonstationary time series generated by a continuous change in regime. We apply fuzzy clustering methods to the task of estimating the continuous drift in the time series distribution and interpret the resulting temporal membership matrix as weights in a time varying, mixture probability distribution function (PDF). We analyze the stopping conditions of the algorithm to infer a novel cluster validity criterion for fuzzy clustering algorithms of temporal patterns. The algorithm performance is demonstrated with three different types of signals.