14 research outputs found
Correlations, Risk and Crisis: From Physiology to Finance
We study the dynamics of correlation and variance in systems under the load
of environmental factors. A universal effect in ensembles of similar systems
under the load of similar factors is described: in crisis, typically, even
before obvious symptoms of crisis appear, correlation increases, and, at the
same time, variance (and volatility) increases too. This effect is supported by
many experiments and observations of groups of humans, mice, trees, grassy
plants, and on financial time series.
A general approach to the explanation of the effect through dynamics of
individual adaptation of similar non-interactive individuals to a similar
system of external factors is developed. Qualitatively, this approach follows
Selye's idea about adaptation energy.Comment: 42 pages, 15 figures, misprints corrections, a proof is added,
improved journal versio
Evolution of adaptation mechanisms: adaptation energy, stress, and oscillating death
In 1938, H. Selye proposed the notion of adaptation energy and published
"Experimental evidence supporting the conception of adaptation energy".
Adaptation of an animal to different factors appears as the spending of one
resource. Adaptation energy is a hypothetical extensive quantity spent for
adaptation. This term causes much debate when one takes it literally, as a
physical quantity, i.e. a sort of energy. The controversial points of view
impede the systematic use of the notion of adaptation energy despite
experimental evidence. Nevertheless, the response to many harmful factors often
has general non-specific form and we suggest that the mechanisms of
physiological adaptation admit a very general and nonspecific description.
We aim to demonstrate that Selye's adaptation energy is the cornerstone of
the top-down approach to modelling of non-specific adaptation processes. We
analyse Selye's axioms of adaptation energy together with Goldstone's
modifications and propose a series of models for interpretation of these
axioms. {\em Adaptation energy is considered as an internal coordinate on the
`dominant path' in the model of adaptation}. The phenomena of `oscillating
death' and `oscillating remission' are predicted on the base of the dynamical
models of adaptation. Natural selection plays a key role in the evolution of
mechanisms of physiological adaptation. We use the fitness optimization
approach to study of the distribution of resources for neutralization of
harmful factors, during adaptation to a multifactor environment, and analyse
the optimal strategies for different systems of factors
Dynamic and Thermodynamic Models of Adaptation
The concept of biological adaptation was closely connected to some
mathematical, engineering and physical ideas from the very beginning. Cannon in
his "The wisdom of the body" (1932) used the engineering vision of regulation.
In 1938, Selye enriched this approach by the notion of adaptation energy. This
term causes much debate when one takes it literally, i.e. as a sort of energy.
Selye did not use the language of mathematics, but the formalization of his
phenomenological theory in the spirit of thermodynamics was simple and led to
verifiable predictions. In 1980s, the dynamics of correlation and variance in
systems under adaptation to a load of environmental factors were studied and
the universal effect in ensembles of systems under a load of similar factors
was discovered: in a crisis, as a rule, even before the onset of obvious
symptoms of stress, the correlation increases together with variance (and
volatility). During 30 years, this effect has been supported by many
observations of groups of humans, mice, trees, grassy plants, and on financial
time series. In the last ten years, these results were supplemented by many new
experiments, from gene networks in cardiology and oncology to dynamics of
depression and clinical psychotherapy. Several systems of models were
developed: the thermodynamic-like theory of adaptation of ensembles and several
families of models of individual adaptation. Historically, the first group of
models was based on Selye's concept of adaptation energy and used fitness
estimates. Two other groups of models are based on the idea of hidden attractor
bifurcation and on the advection--diffusion model for distribution of
population in the space of physiological attributes. We explore this world of
models and experiments, starting with classic works, with particular attention
to the results of the last ten years and open questions.Comment: Review paper, 48 pages, 29 figures, 183 bibliography, the final
version accepted in Phys Life Re
Simple model of complex dynamics of activity patterns in developing networks of neuronal cultures
Living neuronal networks in dissociated neuronal cultures are widely known
for their ability to generate highly robust spatiotemporal activity patterns in
various experimental conditions. These include neuronal avalanches satisfying
the power scaling law and thereby exemplifying self-organized criticality in
living systems. A crucial question is how these patterns can be explained and
modeled in a way that is biologically meaningful, mathematically tractable and
yet broad enough to account for neuronal heterogeneity and complexity. Here we
propose a simple model which may offer an answer to this question. Our
derivations are based on just few phenomenological observations concerning
input-output behavior of an isolated neuron. A distinctive feature of the model
is that at the simplest level of description it comprises of only two
variables, a network activity variable and an exogenous variable corresponding
to energy needed to sustain the activity and modulate the efficacy of signal
transmission. Strikingly, this simple model is already capable of explaining
emergence of network spikes and bursts in developing neuronal cultures. The
model behavior and predictions are supported by empirical observations and
published experimental evidence on cultured neurons behavior exposed to oxygen
and energy deprivation. At the larger, network scale, introduction of the
energy-dependent regulatory mechanism enables the network to balance on the
edge of the network percolation transition. Network activity in this state
shows population bursts satisfying the scaling avalanche conditions. This
network state is self-sustainable and represents a balance between global
network-wide processes and spontaneous activity of individual elements
Correlations, Risk and Crisis: From Physiology to Finance
We study the dynamics of correlation and variance in systems under the load of environmental factors. A universal effect in ensembles of similar systems under the load of similar factors is described: in crisis, typically, even before obvious symptoms of crisis appear, correlation increases, and, at the same time, variance (and volatility) increases too. This effect is supported by many experiments and observations of groups of humans, mice, trees, grassy plants, and on financial time series. A general approach to the explanation of the effect through dynamics of individual adaptation of similar non-interactive individuals to a similar system of external factors is developed. Qualitatively, this approach follows Selye's idea about adaptation energy.
General Laws of Adaptation to Environmental Factors: from Ecological Stress to Financial Crisis
We study ensembles of similar systems
under load of environmental factors. The phenomenon of adaptation
has similar properties for systems of different nature. Typically,
when the load increases above some threshold, then the adapting
systems become more different (variance increases), but the
correlation increases too. If the stress continues to increase
then the second threshold appears: the correlation achieves
maximal value, and start to decrease, but the variance continue to
increase. In many applications this second threshold is a signal
of approaching of fatal outcome.
This effect is supported by many experiments and observation of
groups of humans, mice, trees, grassy plants, and on financial
time series. A general approach to explanation of the effect
through dynamics of adaptation is developed. H. Selye introduced
“adaptation energy" for explanation of adaptation phenomena. We
formalize this approach in factors – resource models and
develop hierarchy of models of adaptation. Different organization
of interaction between factors (Liebig's versus synergistic
systems) lead to different adaptation dynamics. This gives an
explanation to qualitatively different dynamics of correlation
under different types of load and to some deviation from the
typical reaction to stress.
In addition to the “quasistatic" optimization factor – resource
models, dynamical models of adaptation are developed, and a
simple model (three variables) for adaptation to one factor load
is formulated explicitly
Evolution of adaptation mechanisms: adaptation energy, stress, and oscillating death
Текст статьи не публикуется в открытом доступе в соответствии с политикой журнала.In 1938, Selye proposed the notion of adaptation energy and published ‘Experimental evidence supporting the conception of adaptation energy.’ Adaptation of an animal to different factors appears as the spending of one resource. Adaptation energy is a hypothetical extensive quantity spent for adaptation. This term causes much debate when one takes it literally, as a physical quantity, i.e. a sort of energy. The controversial points of view impede the systematic use of the notion of adaptation energy despite experimental evidence. Nevertheless, the response to many harmful factors often has general non-specific form and we suggest that the mechanisms of physiological adaptation admit a very general and nonspecific description.
We aim to demonstrate that Selye׳s adaptation energy is the cornerstone of the top-down approach to modelling of non-specific adaptation processes. We analyze Selye׳s axioms of adaptation energy together with Goldstone׳s modifications and propose a series of models for interpretation of these axioms. Adaptation energy is considered as an internal coordinate on the ‘dominant path’ in the model of adaptation. The phenomena of ‘oscillating death’ and ‘oscillating remission’ are predicted on the base of the dynamical models of adaptation. Natural selection plays a key role in the evolution of mechanisms of physiological adaptation. We use the fitness optimization approach to study of the distribution of resources for neutralization of harmful factors, during adaptation to a multifactor environment, and analyze the optimal strategies for different systems of factors