concept

homeostatic paradigm

Also known as: homeostatic paradigm, homeostasis paradigm

Facts (16)

Sources
A Copernican Approach to Brain Advancement: The Paradigm of ... frontiersin.org Frontiers in Human Neuroscience Apr 25, 2019 16 facts
claimThe homeostasis paradigm utilizes linear models, whereas the Paradigm of Allostatic Orchestration utilizes models based on complexity, criticality, and non-linear dynamics.
claimThe homeostasis paradigm defines stability as 'stability through constancy,' whereas the Paradigm of Allostatic Orchestration (PAO) defines stability as 'stability through change,' which resembles constancy when neural and environmental complexities are minimized.
claimHomeostasis approaches therapeutics by modifying specific mechanisms deemed dysfunctional, while the Paradigm of Allostatic Orchestration approaches therapeutics by facilitating the brain's endogenous orchestrative capacities and modifying influences from the natural environment.
claimThe homeostasis paradigm aims to elucidate the factors that maintain system stability, and therapeutics within this framework aim to correct abnormal factor functions.
claimIn the homeostasis paradigm, the brain is viewed as one organ among others, whereas in the Paradigm of Allostatic Orchestration, the brain is viewed as the central and integrative site of information processing for all organs and behaviors.
claimThe homeostasis paradigm, defined as 'stability through constancy' by Walter Cannon, originates from laboratory-based experimental physiology pioneered by Claude Bernard and posits that living systems tend to maintain system functionality in the direction of constancy or similitude.
claimHomeostasis explains pathology as the production of categorically dysfunctional molecular interactions, whereas the Paradigm of Allostatic Orchestration explains pathology as the persistence of molecular interactions that are not beneficial for a given context, often associated with neurally-directed rigidification of oscillatory patterns.
claimThe homeostasis paradigm views free will as a 'user illusion' resulting from determined molecular processes, whereas the Paradigm of Allostatic Orchestration views free will and consciousness as real phenomena with causal top-down efficacy.
claimThe homeostasis paradigm does not emphasize disease comorbidity due to its focus on system-specific mechanisms, while the Paradigm of Allostatic Orchestration predicts comorbidity due to cross-system effects orchestrated at the level of the brain.
claimBlood pressure regulation is a physiological phenomenon studied under the homeostatic paradigm, involving the heart (as a pump), blood vessels (which constrict and relax), and kidneys (which manage blood volume by filtering fluid and conserving sodium).
claimThe homeostatic paradigm interprets consistent mean values in biological parameters, such as blood pressure readings remaining at 120/80 over 10 days, as empirical evidence for homeostasis.
claimConciliation of the homeostasis and allostatic paradigms is possible, with 'reactive homeostasis' interpreted as an illusion stemming from the anticipation of environmental monotony.
claimHomeostasis utilizes a 'bottom-up' causal inference model where molecular interactions determine higher-level phenomena, whereas the Paradigm of Allostatic Orchestration utilizes a 'top-down' or bidirectional model where neocortical activity and environmental factors influence lower-level biological phenomena.
perspectiveWhen biological data varies between subjects, the homeostatic paradigm guides researchers to search for differences in local factors such as genes or gene expression, whereas the Predictive Adaptive Organization (PAO) paradigm searches for differences in environmental and top-down neural regulatory influences.
accountClaude Bernard established the foundation for the homeostatic paradigm in the late nineteenth century by demonstrating that biological systems tend to maintain constancy.
claimThe homeostasis paradigm does not formally recognize influences outside its controlled experimental frames and is variable in its modeling of neural contributions.