Scaling up the nervous system of Caenorhabditis elegans: is one ape equal to 33 million worms?

Although vastly different, both the mammalian brain and the nematode Caenorhabditis elegans' nervous system must contribute critically to assure survival. Two quantitative conditions which place bounds on networks for connectedness and stability are tested on the published neural network of C. elegans and fit. Consideration of networks scaled up to mammalian size and confined between these bounds suggests that perhaps, the entire spectrum of brain size may be built between these bounds. Further consequences of increasing brain size relate to the trade-off between complexity, providing internal resistance to individual damage, and redundancy of population, as survival mechanisms.

The role of a clinically based computer department of instruction in a school of medicine.

The evolution of activities and educational directions of a department of instruction in medical computer technology in a school of medicine are reviewed. During the 18 years covered, the society at large has undergone marked change in availability and use of computation in every aspect of medical care. It is argued that a department of instruction should be clinical and develop revenue sources based on patient care, perform technical services for the institution with a decentralized structure, and perform both health services and scientific research. Distinction should be drawn between utilization of computing in medical specialties, library function, and instruction in computer science. The last is the proper arena for the academic content of instruction and is best labelled as the philosophical basis of medical knowledge, in particular, its epistemology. Contemporary pressures for teaching introductory computer skills are probably temporary.

The orthogonal electrocardiogram as risk indicator for the prediction of myocardial infarction and/or cardiac death.

In a prospective study on Coronary Heart Disease (CHD) orthogonal electrocardiograms (Frank) were recorded annually for ten years from 1,444 asymptomatic, middle-aged males with a mean age of 57.4 +/- 10.6 years. Cases with overt or suspected CHD were excluded. The purpose of the study was to identify risk indicators in electrocardiograms and to compare them with other known risk factors used for prediction of acute CHD events such as myocardial infarction (MI) and/or cardiac death (CD). Such acute events occurred in 88 cases. Pre-event ECGs of these acute events were compared with all others without events, using logistic regression analysis. Identified ECG risk indicators were then compared with other known risk factors such as smoking, blood pressure, cholesterol, age, weight, etc. The predictive power of the ECG, derived mainly from the ST-T complex, exceeded all others by a wide margin. The amplitude of the first 1/8 of the ST-T complex in lead x (similar to V5-V6) together with relative body weight proved best when one pre-event record was available. Prediction improved when ECG changes between two pre-event recordings were included. Precision of measurements by computer appeared essential for improvements in CHD prediction.

Model analysis of steady-state ventilatory response to CO2 into component factors.

A method is described to partition measured values of steady-state ventilatory response into an estimation of the blood flow in the respiratory controller and the sensitivity of the controller to CO2 assuming proportional control. The analysis is derived from the describing equations of a computer model and leads to the definition of a grid of lines emanating from a hypothetical reference point at negative ventilation and zero central nervous system metabolism. Data from the literature reporting differences in CO2 response among normal subjects and changes in resting ventilation and cerebral blood flow with age are reinterpreted from this perspective. Use of a structural model to interpret physiological data is shown to give a different meaning to data reduction in contrast to interpretation using statistical models like regression.

On the identification of verbs in computer programs of physiological models.

The rationale for identifying verbs (actions modeled) in the source code of a mathematical model is presented, with algorithms leading to computational techniques for devising explanations of such models. Using flow graph methodology the source code of a program can be described as disjoint intervals of its directed acyclic graph. Intervals of this set containing complete loops represent the code structure conceptually equivalent to verbs modeled. In turn, such structures can be mapped uniquely as functional dependencies of the intensional form of a relational data base which is the model output. Simulation, then, can be viewed as retrieval, and the logical inferences of a model appear to be derivable via relational algebra of the data base. In these terms, a verb is a relation consisting of at least one variable defined in an interval. The relation's key attributes must include at least one variable, also defined in the interval. Verb definitions are essential if programs are to explain themselves.

Information systems approach to integrated responses in the respiratory control system.

The appropriateness of integrated information systems to the description of integrated biological systems is discussed. An integrated information system in the physiology of the regulation of respiration is argued to be a structural mathematical model of the system and the relational data base, which it can compute. In contrast to the customary method of applying nonspecific statistical or control system formulations to data, the model-data base combination attempts to produce insight by reproducing from a single formulation many sets of experimentally validated data. The model then may predict results for experiments not yet done. An information system (thus defined) has both explanatory power and heuristic value.

Computer simulation of experiments in responses to intravenous and inhaled CO2.

A simulation of ventilatory responses to infused and inhaled CO2 at controlled cardiac output and high and low levels of neural excitation mimics comparable experiments in animals. The model suggests that at low levels of endogenous and exogenous CO2 load the alert quiescent animal will show hyperpnea to both test states associated with hypercapnia. The nonalert quiescent animal simulated will show an isocapnic response to endogenous load and hypercapnic response to exogenous load. The explanation of this behavior lies in the model formulation, which allows the neural signal from metabolically active sources to drive the proportional component of the controller below an operating level established by its set point. By this reasoning the excited but metabolically inactive animal should be paradoxically less sensitive to small changes in CO2, whether exogenous or endogenous, than the quiescent animal. The model demonstrates further that a neural "exercise" signal in proportion to venous return better simulates observations in which CO2 load and venous return are dissociated than one in which the neural signal is computed from metabolism. The use of delta V/delta P slopes as estimates of sensitivity go awry in experiment and simulation when blood flow, CO2 level, and neural excitatory state are dissociated. This is particularly true when the organism is operating at and below the hypothesized set point.

Computer simulation of ventilatory control by both neural and humoral CO2 signals.

A mathematical model portraying a humoral signal derived from time-dependent variations in arterial carbon dioxide tension (PaCO2) and a neural signal proportional to the metabolic CO2 production was tested by computer simulation. The signals were assumed to enter the central mechanism through afferent pathways connected in reciprocal inhibition. The central mechanism, previously described, contained proportional, gradient, and positive feedback components. The model simulates steady-state isocapnic hyperpnea under endogenous CO2 load and hyperpnea proportional to PaCO2 under exogenous CO2 load. This behavior is consistent whether the neural signal is present alone, the humoral signal is present alone, or both are present and synergistic. When the neural and humoral signals are opposed hypocapnia and hyperventilation ensue; the values being consistent with the isometabolic hyperbola. The model also portrays steady-state behavior when CO2 is inhaled during exercise. During hypometabolic states of rest the mechanism appears to become insensitive to PaCO2 levels.

A mathematical simulation of the hyperneas of metabolic CO2 production and inhalation.

Mathematical models of the CO2 responsive controller for ventillatory responses to CO2 inhaled and to CO2 introduced in the perpheral tissues are formulated in the context of a controlled system that is a compartmented tissue system with a lung undergoing breathing movements. Equations representing the system are either ordinary difference-differential equations or algebraic equations. If the controller contains three components simulating, respectively, a proportional controller with a set point, a mechanism sensitive to trans-membrane CO2 gradients, and a mechanism responsive to the autocovariance difference in arterial carbon dioxide tension (PaCO2) about 1.2 s apart; and if the neural tissues produce CO2 as a result of their own activity (positive feedback), the entire system responds to metabolic production of CO2 by increasing ventilation in proportion to metabolism while maintaining a constant PaCO2. The same system responds to inhaled CO2 mixtures with ventilation increasing in proportion to increases in PaCO2. The behavior of the model is used to postulate a spatiotemporal hypothesis for the humoral component of respiratory regulation of CO2 exchanges.

On the evolution of the physiological model.

Most of us who have concerned ourselves with models can perceive outlines like those above to catalog the future evolution of the expository function of models. In the context of a single class of computerized mathematical models of respiratory physiology, we can observe at once the burgeoning interest among scientists, and the similarities between model activity and the general organization of scientific information for use. Although physiological models have become quite advanced in their subject control, there is relatively little coordinated activity in the mechanization of the purposes and philosophical potential of automata. The outlines, however, are visible. An assiduous pursuit of the notion of "explanation" by machine is a major evolutionary step next to occur. It appears to us that various diagrams similar to Figures 5 or 6 can be created and investigated in terms of their relation to the human mind and in terms of formalizing rules for traversing from one plane to the next. The evolution of models will require program-making programs which can decide when and how to aggregate for deductive inference, and how far to penetrate top-down for explanation. The rules for identifying "second order" effects must be established. The decision to ignore or use these rules will be crucial. These are the means whereby the systems are traversed from plane to plane. In a word, models need to synthesize the means to ignore, "forget," and gloss over; only then will we have useful tools for taking informed action in physiology, diagnosis in medicine, or the writing of "scholarly" reviews.