A theoretical framework for CNS arousal

Pfaff, Donald W.; Banavar, Jayanth R.

doi:10.1002/bies.20611

Cited by 45 publications

(34 citation statements)

References 62 publications

(42 reference statements)

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“…Instead we seek a dynamic, nonlinear system capable of providing the rapid lability and great power of amplification that would allow a disturbing sensory stimulus to cause the entire CNS to swing into action. The logistic equation, one of several forms of mathematics that yield deterministic chaos (33), appealed to us, as a first step, consonant with our previously stated hypothesis (34).…”

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confidence: 53%

“…For an initial set of experiments we were attracted to the use of the logistic equation because of its capacity for producing large and rapid changes in output and its sensitivity to small changes in the input, and because of its link to our previous theory about phase transitions in the regulation of CNS arousal (34). Of course, other nonlinear dynamic systems have similar characteristics, but the long history of intense work on the logistic equation recommended it to us (35-37).…”

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confidence: 99%

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

Quinkert

Vimal

Weil

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

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

Quinkert

Vimal

Weil

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

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“…This observation raises the question whether there is some evolutionary advantage to a particular value of the exponent (e.g., ref. 28). This notion is consistent with our observations that the scaling exponent is approximately the same for different individual mice.…”

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confidence: 99%

Scale invariance in the dynamics of spontaneous behavior

Proekt

Banavar

Maritan

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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110

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Typically one expects that the intervals between consecutive occurrences of a particular behavior will have a characteristic time scale around which most observations are centered. Surprisingly, the timing of many diverse behaviors from human communication to animal foraging form complex self-similar temporal patterns reproduced on multiple time scales. We present a general framework for understanding how such scale invariance may arise in nonequilibrium systems, including those that regulate mammalian behaviors. We then demonstrate that the predictions of this framework are in agreement with detailed analysis of spontaneous mouse behavior observed in a simple unchanging environment. Neural systems operate on a broad range of time scales, from milliseconds to hours. We analytically show that such a separation between time scales could lead to scale-invariant dynamics without any fine tuning of parameters or other model-specific constraints. Our analyses reveal that the specifics of the distribution of resources or competition among several tasks are not essential for the expression of scale-free dynamics. Rather, we show that scale invariance observed in the dynamics of behavior can arise from the dynamics intrinsic to the brain.power law | criticality

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“…One operational definition of arousal in mammals is increased motor activation, sensory responsiveness and emotional reactivity [1]. Applied to invertebrates, these categories might be more realistically combined under the common theme of behavioural responsiveness.…”

Section: The Problem Of Arousalmentioning

confidence: 99%

Dopamine in Drosophila : setting arousal thresholds in a miniature brain

2011

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In mammals, the neurotransmitter dopamine (DA) modulates a variety of behaviours, although DA function is mostly associated with motor control and reward. In insects such as the fruitfly, Drosophila melanogaster, DA also modulates a wide array of behaviours, ranging from sleep and locomotion to courtship and learning. How can a single molecule play so many different roles? Adaptive changes within the DA system, anatomical specificity of action and effects on a variety of behaviours highlight the remarkable versatility of this neurotransmitter. Recent genetic and pharmacological manipulations of DA signalling in Drosophila have launched a surfeit of stories-each arguing for modulation of some aspect of the fly's waking (and sleeping) life. Although these stories often seem distinct and unrelated, there are some unifying themes underlying DA function and arousal states in this insect model. One of the central roles played by DA may involve perceptual suppression, a necessary component of both sleep and selective attention.

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A theoretical framework for CNS arousal

Cited by 45 publications

References 62 publications

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

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

Scale invariance in the dynamics of spontaneous behavior

Dopamine in Drosophila : setting arousal thresholds in a miniature brain

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