COMPUTERS AND BIOMEDICAL RESEARCH 31, 465–475 (1998) ARTICLE NO. CO981494 Computer Assisted Neurophysiology by a Distributed Java Program Luc Jeandenans,* Michel Gautero,* Franc ¸ois Grize,* Igor V. Tetko,†‡ and Alessandro E. P. Villa† *Institut d’Informatique, Colle `ge prope ´deutique, and †Laboratoire de Neuro-heuristique, Institut de Physiologie, Universite ´ de Lausanne, Lausanne, Switzerland; and ‡Department of Biomedical Applications, IBPC-Academy of Sciences of Ukraine, Kiev 660, Ukraine Received February 26, 1998 We have developed a distributed software package which allows neurophysiologists to have at hand a set of network and graphic tools in order to perform the analysis of data collected from the electrical activity of neurons, studied in the experimental laboratory. This system is built around three major components. First, the experimental data are processed in order to select specific data files from the networked computer and display the spike trains as raster dots. The second part selects one type of analysis (e.g., cross-correlation, out of a set of possible choices) after configuration of some specific parameters. Finally, the third component deals with the results of data analyses, which are selected and displayed on a multi-parameter graphic ‘‘ring binder.’’ We have used the Java programming language to implement this application. This recent object-oriented language offers platform-independent software tools including graphic package and standard network protocols.  1998 Academic Press INTRODUCTION A better understanding of higher functions such as perception, motor planning, or retrieval of memories can only be achieved by testing new hypotheses of how the brain encodes and transmits information. The study of brain information processing can be based on theoretical models, on simulation results, or on experimental observations and the related analyses. The experimental approach is gaining a renewed interest since modern technological advances allow the recording of tens of neurons simultaneously in behaving animals (1, 2). Indeed, multiple dimensions of sensory and behaviorally relevant stimuli are processed by thousands of neurons distributed over many areas of the brain. That neurons convey a temporal code has been well known since early electro- physiological studies led to recognition that spike trains—the time series formed by the sequences of time intervals between spikes—were related to meaningful physiological variables (3, 4). Most methods of spike train analysis require a computational environment and programming know-how that limit their use 465 0010-4809/98 $25.00 Copyright  1998 by Academic Press All rights of reproduction in any form reserved.