Mathematical modeling of brain function is an important tool needed for a better understanding of experimental results and clinical situations. In the present study, we are constructing and testing a mathematical model capable of simulating changes in brain energy metabolism that develop in real time under various pathophysiological conditions. The model incorporates the following parameters: cerebral blood flow, partial oxygen pressure, mitochondrial NADH redox state, and extracellular potassium. Accordingly, all the model variables are only time dependent (;point-model' approach). Numerical runs demonstrate the ability of the model to mimic pathological conditions, such as complete and partial ischemia, cortical spreading depression under normoxic and partial ischemic conditions. They also show that, when properly tuned, a model of this type permits the monitoring of only one or two crucial variables and the computation of the remaining variables in real time during clinical or experimental procedures.

The approach suggested is in the class of cohort methods; it is a new technique for processing catch-at-age data on species having short (within a year) periods of fishery. The method can also be regarded as an approximation to more general conditions when fishery varies continuously during the year. In many cases it enables a more complete extraction of information on exploited populations and fishery from the catch-at-age matrices, including the natural mortality coefficient and terminal fishing parameters, without using any auxiliary data (survey data, fishing effort series etc.). A number of numerical experiments using simulated data illustrate the methodology and demonstrate the merits of the suggested method.1997 International Council for the Exploration of the Sea