A general model for the simulation of balance, imbalance and control by agonistic antagonistic biological couples

Bernard-Weil, E

doi:10.1016/0270-0255(86)90091-6

Cited by 18 publications

(9 citation statements)

References 22 publications

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“…Likewise, from Pierce and Freud to Heidegger, Winnicott, and Bateson, some more recent researches have undertaken looking for the role played by oppositional couples in mind, knowledge, and strategy processes and helping to surpass the limits imposed by the reductionistic point of view on the modeling activity, and even going beyond the obstacles sometimes encountered by Systems Science. [See also References 26,32, and 33 to find some elements concerning this inventory (particularly as far as modern authors are concerned-some also being quoted in the present article)]. We note, nevertheless, that all the characteristics of the AASS (cf.…”

Section: Brief History Of the Agonistic Antagonistic Phylummentioning

confidence: 68%

Transcendance, an essential concept for system and complexity sciences to spread out

Bernard-Weil

2000

Complexity

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Section: Brief History Of the Agonistic Antagonistic Phylummentioning

confidence: 68%

Transcendance, an essential concept for system and complexity sciences to spread out

Bernard-Weil

2000

Complexity

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“…Healthy regulation is often characterized as sympathetic and parasympathetic activity converging in a limit cycle around a critical value, such as is the case of cortisol-vasopressin or acetylcholine-epinephrine reactions, where each process induces a compensatory reaction in the other (Bernard-Weil, 1986). Thus, sympathetic activity may simultaneously suppress parasympathetic activity, but increase parasympathetic reactivity , thereby producing an oscillation .…”

Section: Autonomic Regulationmentioning

confidence: 99%

Dynamic Processes in Regulation and Some Implications for Biofeedback and Biobehavioral Interventions

Lehrer

Eddie

2013

Appl Psychophysiol Biofeedback

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Systems theory has long been applied in psychology, biology, and sociology. This paper applies newer methods of control systems modeling to the assessment of system stability in health and disease. Control systems can be characterized as open or closed systems with feedback loops. Feedback produces oscillatory activity, and the complexity of naturally occurring oscillatory patterns reflects the multiplicity of feedback mechanisms, such that many mechanisms operate simultaneously to control the system. Unstable systems, often associated with poor health, are characterized by absence of oscillation, random noise, or a very simple pattern of oscillation. This modeling approach can be applied to a diverse range of phenomena, including cardiovascular and brain activity, mood and thermal regulation, and social system stability. External system stressors such as disease, psychological stress, injury, or interpersonal conflict may perturb a system, yet simultaneously stimulate oscillatory processes and exercise control mechanisms. Resonance can occur in systems with negative feedback loops, causing high-amplitude oscillations at a single frequency. Resonance effects can be used to strengthen modulatory oscillations, but may obscure other information and control mechanisms, and weaken system stability. Positive as well as negative feedback loops are important for system function and stability. Examples are presented of oscillatory processes in heart rate variability, and regulation of autonomic, thermal, pancreatic and central nervous system processes, as well as in social/organizational systems such as marriages and business organizations. Resonance in negative feedback loops can help stimulate oscillations and exercise control reflexes, but also can deprive the system of important information. Empirical hypotheses derived from this approach are presented, including that moderate stress may enhance health and functioning.

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“…In fact, this way of reasoning becomes difficult to follow if the number of couples would be high, noticeably as far as the linearization matrix is concerned (how to get the matrix positive definite and with a sum of the principal diagonal elements negative (if we want an asymptotical stability) or positive (if we want limit-cycles)?) It is possible to find hints with this approximative rule: if we report to the conditions of stability of the elementary AA models, such as they were indicated in Bernard-Weil (1987), we may try to apply these conditions to the parameters of the interconnecting structure.…”

Section: + E Ko'(u+r )I + E Cu(v+sy + -K#e E (U+ry + C#e E (V+rymentioning

confidence: 99%

Is it possible to equilibrate the different “levels” of an imbalanced biological system by acting upon one of them only? Example of the agonistic antagonistic networks

Bernard-Weil¹

1991

Acta Biotheor

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To answer the question in the title, we take as an example the model for the regulation of agonistic antagonistic couples (MRAAC). It is a model that associates 4 non-linear differential equations and allows to simulate balance, imbalance between two state variables, and control, if necessary, by two control variables of the same nature as the state variables: this control is defined as a bilateral strategy (bipolar therapy in the medical field). The super model for the regulation of agonism antagonistic couples (SMRAAC), that may be also considered as an agonistic antagonistic network (AAN), associates several elementary MRAAC's, but the interconnection structure falls equally under the category of the agonistic antagonism (AA). First we indicate what may be the results of the interconnection, favourable or not. In the last case, a control can be performed, by acting upon a sole couple of the SMRAAC, even if other couples were imbalanced (with two AA control variables only). Simulation examples are given. We bring also a new result with the SMRAAC, i.e. the appearance of "strange attractors" with this model. The general models belonging to the AA phylum should put on a growing importance in the future, because they could be the sole models enable to control some complex systems by avoiding the perverse effects of the unilateral strategies.

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A general model for the simulation of balance, imbalance and control by agonistic antagonistic biological couples

Cited by 18 publications

References 22 publications

Transcendance, an essential concept for system and complexity sciences to spread out

Transcendance, an essential concept for system and complexity sciences to spread out

Dynamic Processes in Regulation and Some Implications for Biofeedback and Biobehavioral Interventions

Is it possible to equilibrate the different “levels” of an imbalanced biological system by acting upon one of them only? Example of the agonistic antagonistic networks

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