Quantitative descriptions of generalized arousal, an elementary function of the vertebrate brain

Abstract

We review a concept of the most primitive, fundamental function of the vertebrate CNS, generalized arousal (GA). Three independent lines of evidence indicate the existence of GA: statistical, genetic, and mechanistic. Here we ask, is this concept amenable to quantitative analysis? Answering in the affirmative, four quantitative approaches have proven useful: (i) factor analysis, (ii) information theory, (iii) deterministic chaos, and (iv) application of a Gaussian equation. It strikes us that, to date, not just one but at least four different quantitative approaches seem necessary for describing different aspects of scientific work on GA. In this brief review, we present a global concept of brain function, generalized arousal (GA), and illustrate the application of four mathematical methods to its description and analysis. Here, in order of the sections below, we (i) use factor analysis to help prove that GA actually exists; (ii) use information theory to characterize stimuli that elicit GA; (iii) resort to the logistic equation to speculate on how GA might make use of nonlinear dynamics; and (iv) having studied GA in the context of the hunger-induced activation of behavior, characterize the behavioral data with a simple Gaussian.We have proposed that the most powerful and essential activity in any vertebrate nervous system is GA (1). As conceived, GA is universal and fundamental, initiating the activation of all behavioral responses in all vertebrate animals. The operational definition of GA is that a more-aroused animal or human is (i) more responsive to sensory stimuli in all modalities; (ii) more active motorically; and (iii) more reactive emotionally (1). GA's performance requirements are listed in Table 1.Evidence for the Existence of GA of the CNS Three independent lines of evidence indicate that generalized CNS arousal actually exists: statistical, genetic, and mechanistic.The first line of evidence derives from recently reported behavioral results that show, statistically, the influence of GA (2). We did several experiments with mice, which tapped all three components of the operational definition of GA: S (sensory alertness) measured as motor activity in response to sensory stimuli of various modalities; M (motor activity) measured as spontaneous home cage motor activity; and E (emotional reactivity) measured as motor activity and freezing behavior in a conditioned fear paradigm. These three parameters did not covary either genetically or phenotypically. We analyzed the data using factor analysis, which probes the covariance structure of a large data set-in our case it tabulates the statistical relations among various arousal-related response measures. Factor analysis as applied here "lets the subject (in our case, a mouse) tell us" the structure of its arousal functions. Application of this analysis to our five sets of experimental data allowed us to estimate the contribution of GA, measured as the most generalized, least specific factor, as revealed by an unrotated covariance matrix and a forced one...

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