This glossary contains a vocabulary used by CPER concerning the overall site, regarding: meaning of scientific words, useful definitions, short explanations of some concepts, and references to reliable external sources of information on the Internet or on paper.
Ontogenesis is also called: Ontogeny.
The process during which personality and sexual behavior of an individual person mature through a series of stages (Psychosexual development).
Compare with: Phylogenesis , Palingenesis .
Phylogeny relates to genetic development of a species during evolution, while Ontogeny relates to physiological (and psychological) development of an individual during his / her lifetime. Phylogenesis: long-term time scale. Ontogenesis: short-term time scale.
The term Ontogenesis is derived from the ancient Greek
words ontos (ὄντος), meaning "being", plus the term
genesis (γένεσις) meaning "origin", "source", or
In biology, Palingenesis (or palingenesia) is also called Recapitulation.
CPER uses this biological meaning.
Compare with: Ontogenesis , Phylogenesis .
Phylogeny relates to genetic development of a species during evolution, while Ontogeny relates to physiological (and psychological) development of an individual during his / her lifetime. Phylogenesis: long-term time scale. Ontogenesis: short-term time scale.
Palingenesis assumes that a fetus undergoes a condensed reflection of genetic evolutional traits (cf. phylogeny), during the embryonic development of this organism (cf. ontogeny).
The term Palingenesis is derived from the ancient Greek word palingenesia (παλιγγενεσία) that exists of the terms palin (πάλιν), meaning "again", plus the term genesis (γένεσις) meaning "origin", "source", or "birth".
Phenology is the study of periodic plant and animal life cycle events and how these are influenced by seasonal and interannual variations in climate, as well as habitat factors (such as elevation). Phenology has been principally concerned with the dates of first occurrence of biological events in their annual cycle. Examples include the date of emergence of leaves and flowers, the first flight of butterflies and the first appearance of migratory birds, the date of leaf colouring and fall in deciduous trees, the dates of egg-laying of birds and amphibia, or the timing of the developmental cycles of temperate-zone honey bee colonies. In the scientific literature on ecology, the term is used more generally to indicate the time frame for any seasonal biological phenomena, including the dates of last appearance (e.g.: the seasonal phenology of a species may be from April through September).
Because many such phenomena are very sensitive to small variations in climate, especially to temperature, phenological records can be a useful proxy for temperature in historical climatology, especially in the study of climate change and global warming. For example, viticultural records of grape harvests in Europe have been used to reconstruct a record of summer growing season temperatures going back more than 500 years. In addition to providing a longer historical baseline than instrumental measurements, phenological observations provide high temporal resolution of on-going changes related to global warming.
The term Phenology is derived from the Greek phainō (φαίνω), meaning "to show, to bring to light, make to appear" + logos (λόγος), which has many meanings, such as "word, study, discourse, reasoning".
Phylogenesis is also called: Phylogeny.
Compare with: Ontogenesis , Palingenesis .
Phylogeny relates to genetic development of a species during
evolution, while Ontogeny relates to physiological (and
psychological) development of an individual during his / her
The term Phylogenesis is derived from the
words phylé (φυλή) and phulon (φῦλον), meaning
"tribe", "clan", or "race", plus the term genesis
(γένεσις) meaning "origin", "source", or
Positive Feedback Loop
Positive Feedback Loop
Positive feedback is a process that occurs in a feedback loop in which the effects of a small disturbance on a system include an increase in the magnitude of the perturbation. That is, mechanism A produces more of B which in turn produces more of A. In contrast, a system in which the results of a change act to reduce or counteract it, has negative feedback (see: Negative Feedback Loop).
Figure: Positive feedback loop.
Mathematically, positive feedback is defined as a positive loop gain around a closed loop of cause and effect. That is, positive feedback is in phase with the input, in the sense that it adds to make the input larger. Positive feedback tends to cause system instability. When the loop gain is positive and above 1, there will typically be exponential growth, increasing oscillations or divergences from equilibrium. System parameters will typically accelerate towards extreme values, which may damage or destroy the system, or may end with the system latched into a new stable state. Positive feedback may be controlled by signals in the system being filtered, damped, or limited, or it can be cancelled or reduced by adding negative feedback.
Positive feedback is used in digital electronics to force voltages away from intermediate voltages into '0' and '1' states. On the other hand, thermal runaway is a positive feedback that can destroy semiconductor junctions. Positive feedback in chemical reactions can increase the rate of reactions, and in some cases can lead to explosions. Positive feedback in mechanical design causes tipping-point, or 'over-centre', mechanisms to snap into position, for example in switches and locking pliers. Out of control, it can cause bridges to collapse. Positive feedback in economic systems can cause boom-then-bust cycles. A familiar example of positive feedback is the loud squealing or howling sound produced by audio feedback in public address systems: the microphone picks up sound from its own loudspeakers, amplifies it, and sends it through the speakers again.
In place of the adjective "Positive", alternative terms are used, such as: regenerative, self-stimulating, self-reinforcing, self-amplifying, discrepancy-increasing, or centrifugal.
Figure: Possible results of a Positive feedback loop.
Positive feedback enhances or amplifies an effect by it having an influence on the process which gave rise to it. For example, when part of an electronic output signal returns to the input, and is in phase with it, the system gain is increased. The feedback from the outcome to the originating process can be direct, or it can be via other state variables. Such systems can give rich qualitative behaviours, but whether the feedback is instantaneously positive or negative in sign has an extremely important influence on the results. Positive feedback reinforces and negative feedback moderates the original process. Positive and negative in this sense refer to loop gains greater than or less than zero, and do not imply any value judgements as to the desirability of the outcomes or effects. A key feature of positive feedback is thus that small disturbances get bigger. When a change occurs in a system, positive feedback causes further change, in the same direction.
If the loop gain AB is positive, then a condition of positive or regenerative feedback exists. Thus depending on the feedback, state changes can be convergent, or divergent. The result of positive feedback is to augment changes, so that small perturbations may result in big changes.
In the real world, positive feedback loops typically do not cause ever-increasing growth, but are modified by limiting effects of some sort. According to Donella Meadows: "Positive feedback loops are sources of growth, explosion, erosion, and collapse in systems. A system with an unchecked positive loop ultimately will destroy itself. That’s why there are so few of them. Usually a negative loop will kick in sooner or later."
Fields of application
Positive feedback is a mechanism by which an output is enhanced, such as protein levels. However, in order to avoid any fluctuation in the protein level, the mechanism is inhibited stochastically (I). Therefore, when the concentration of the activated protein (A) is past the threshold ([I]), the loop mechanism is activated and the concentration of A increases exponentially if d[A]=k [A] .
A number of examples of positive feedback systems may be found in physiology. One example is the onset of contractions in childbirth, known as the Ferguson reflex. When a contraction occurs, the hormone oxytocin causes a nerve stimulus, which stimulates the hypothalamus to produce more oxytocin, which increases uterine contractions. This results in contractions increasing in amplitude and frequency.
Another example is the process of blood clotting. The loop is initiated when injured tissue releases signal chemicals that activate platelets in the blood. An activated platelet releases chemicals to activate more platelets, causing a rapid cascade and the formation of a blood clot.
Lactation also involves positive feedback in that as the baby suckles on the nipple there is a nerve response into the spinal cord and up into the hypothalamus of the brain. The hypothalamus then stimulates the pituitary gland to produce more prolactin to produce more milk.
A spike in estrogen during the follicular phase of the menstrual cycle causes ovulation.
The generation of nerve signals is another example, in which the membrane of a nerve fibre causes slight leakage of sodium ions through sodium channels. This results in a change in the membrane potential, which in turn causes more opening of channels, and so on. So a slight initial leakage results in an explosion of sodium leakage which creates the nerve action potential.
In excitation–contraction coupling of the heart, an increase in intracellular calcium ions to the cardiac myocyte is detected by ryanodine receptors in the membrane of the sarcoplasmic reticulum. These ryanodine receptors transport calcium out into the cytosol in a positive feedback physiological response.
In most cases, such feedback loops culminate in counter-signals being released that suppress or breaks the loop. Childbirth contractions stop when the baby is out of the mother's body. Chemicals break down the blood clot. Lactation stops when the baby no longer nurses.
Positive feedback is a well studied phenomenon in gene regulation, where it is most often associated with bistability. Positive feedback occurs when a gene activates itself directly or indirectly via a double negative feedback loop. Genetic engineers have constructed and tested simple positive feedback networks in bacteria to demonstrate the concept of bistability. A classic example of positive feedback is the lac operon in Escherichia coli. Positive feedback plays an integral role in cellular differentiation, development, and cancer progression, and therefore, positive feedback in gene regulation can have significant physiological consequences. Random motions in molecular dynamics coupled with positive feedback can trigger interesting effects, such as create population of phenotypically different cells from the same parent cell. This happens because noise can become amplified by positive feedback. Positive feedback can also occur in other forms of cell signaling, such as enzyme kinetics or metabolic pathways.
Positive feedback loops have been used to describe aspects of the dynamics of change in biological evolution. For example, beginning at the macro level, Alfred J. Lotka (1945) argued that the evolution of the species was most essentially a matter of selection that fed back energy flows to capture more and more energy for use by living systems. At the human level, Richard Alexander (1989) proposed that social competition between and within human groups fed back to the selection of intelligence thus constantly producing more and more refined human intelligence. Crespi (2004) discussed several other examples of positive feedback loops in evolution. The analogy of Evolutionary arms races provide further examples of positive feedback in biological systems.
During the Phanerozoic the biodiversity shows a steady but not monotonic increase from near zero to several thousands of genera. It has been shown that changes in biodiversity through the Phanerozoic correlate much better with hyperbolic model (widely used in demography and macrosociology) than with exponential and logistic models (traditionally used in population biology and extensively applied to fossil biodiversity as well). The latter models imply that changes in diversity are guided by a first-order positive feedback (more ancestors, more descendants) and/or a negative feedback arising from resource limitation. Hyperbolic model implies a second-order positive feedback. The hyperbolic pattern of the world population growth has been demonstrated (see below) to arise from a second-order positive feedback between the population size and the rate of technological growth. The hyperbolic character of biodiversity growth can be similarly accounted for by a positive feedback between the diversity and community structure complexity. It has been suggested that the similarity between the curves of biodiversity and human population probably comes from the fact that both are derived from the interference of the hyperbolic trend (produced by the positive feedback) with cyclical and stochastic dynamics.
A cytokine storm, or hypercytokinemia is a potentially fatal immune reaction consisting of a positive feedback loop between cytokines and immune cells, with highly elevated levels of various cytokines. In normal immune function, positive feedback loops can be utilized to enhance the action of B-lymphocytes. When a B-cell binds its antibodies to an antigen and becomes activated, it begins releasing antibodies and secreting a complement protein called C3. Both C3 and a B-cell's antibodies can bind to a pathogen, and when a B-cell has its antibodies bind to a pathogen with C3, it speeds up that B-cell's secretion of more antibodies and more C3, thus creating a positive feedback loop.
In psychology, the body receives a stimulus from the environment
or internally that causes the release of hormones. Release of
hormones then may cause more of those hormones to be released,
causing a positive feedback loop. This cycle is also found in
certain behaviour. For example, "shame loops" occur in people who
blush easily. When they realize that they are blushing, they
become even more embarrassed, which leads to further blushing,
and so on.
Winner (1996) described gifted children as driven by positive feedback loops involving setting their own learning course, this feeding back satisfaction, thus further setting their learning goals to higher levels and so on. Winner termed this positive feedback loop as a "rage to master."
Vandervert (2009) proposed that the child prodigy can be explained in terms of a positive feedback loop between the output of thinking/performing in working memory, which then is fed to the cerebellum where it is streamlined, and then fed back to working memory thus steadily increasing the quantitative and qualitative output of working memory. Vandervert also argued that this working memory/cerebellar positive feedback loop was responsible for language evolution in working memory.
In substance dependence a human seeks the effects of a drug, and the drug supplies an effect. The human thereafter continues to seek the effects from the drug. In time the body acclimates to the dosage of the drug, and finds a new homeostasis. The human then must consume a larger quantity of the drug to feel the effects the subject wants, a drug overdose may occur when seeking this new threshold of drug effect. If an accidental overdose doesn't kill the human, eventually the human body can no longer repair itself from the damage (ex. Kidney failure and Liver failure) and death is the final result to this positive feedback.
According to the theory of reflexivity advanced by George Soros, price changes are driven by a positive feedback process whereby investors' expectations are influenced by price movements so their behaviour acts to reinforce movement in that direction until it becomes unsustainable, whereupon the feedback drives prices in the opposite direction.
Systemic risk is the risk that an amplification or leverage or positive feedback process is built into a system. This is usually unknown, and under certain conditions this process can amplify exponentially and rapidly lead to destructive or chaotic behavior. A Ponzi scheme is a good example of a positive-feedback system: funds from new investors are used to pay out unusually high returns, which in turn attract more new investors, causing rapid growth toward collapse. W. Brian Arthur has also studied and written on positive feedback in the economy (e.g. W. Brian Arthur, 1990). Hyman Minsky proposed a theory that certain credit expansion practices could make a market economy into "a deviation amplifying system" that could suddenly collapse, sometimes called a "Minsky moment". Simple systems that clearly separate the inputs from the outputs are not prone to systemic risk. This risk is more likely as the complexity of the system increases, because it becomes more difficult to see or analyze all the possible combinations of variables in the system even under careful stress testing conditions. The more efficient a complex system is, the more likely it is to be prone to systemic risks, because it takes only a small amount of deviation to disrupt the system. Therefore well-designed complex systems generally have built-in features to avoid this condition, such as a small amount of friction, or resistance, or inertia, or time delay to decouple the outputs from the inputs within the system. These factors amount to an inefficiency, but they are necessary to avoid instabilities. The 2010 Flash Crash incident was blamed on the practice of high-frequency trading (HFT), although whether HFT really increases systemic risk remains controversial.
Human population growth
Agriculture and human population can be considered to be in a positive feedback mode, which means that one drives the other with increasing intensity. It is suggested that this positive feedback system will end sometime with a catastrophe, as modern agriculture is using up all of the easily available phosphate and is resorting to highly efficient monocultures which are more susceptible to systemic risk. Technological innovation and human population can be similarly considered, and this has been offered as an explanation for the apparent hyperbolic growth of the human population in the past, instead of a simpler exponential growth. It is proposed that the growth rate is accelerating because of second-order positive feedback between population and technology. Technological growth increases the carrying capacity of land for people, which leads to more population, and so more potential inventors in further technological growth.
Prejudice, social institutions and poverty Gunnar Myrdal described a vicious circle of increasing inequalities, and poverty, which is known as "circular cumulative causation".
Drought intensifies through positive feedback. A lack of rain decreases soil moisture, which kills plants and/or causes them to release less water through transpiration. Both factors limit evapotranspiration, the process by which water vapor is added to the atmosphere from the surface, and add dry dust to the atmosphere, which absorbs water. Less water vapor means both low dew point temperatures and more efficient daytime heating, decreasing the chances of humidity in the atmosphere leading to cloud formation. Lastly, without clouds, there cannot be rain, and the loop is complete.
The climate system is characterized by strong positive and
negative feedback loops between processes that affect the state
of the atmosphere, ocean, and land.
The Intergovernmental Panel on Climate Change
IPCC's Fourth Assessment Report states that "Anthropogenic warming could lead to some effects that are abrupt or irreversible, depending upon the rate and magnitude of the climate change."
A self-fulfilling prophecy is a social positive feedback loop between beliefs and behaviour: if enough people believe that something is true, their behaviour can make it true, and observations of their behaviour may in turn increase belief. A classic example is a bank run.
Another sociological example of positive feedback is the network effect. When more people are encouraged to join a network this increases the reach of the network therefore the network expands ever more quickly. A viral video is an example of the network effect in which links to a popular video are shared and redistributed, ensuring that more people see the video and then re-publish the links. This is the basis for many social phenomena, including Ponzi schemes and chain letters. In many cases population size is the limiting factor to the feedback effect.
On the Internet
Internet recommendation systems are expected to increase the diversity of what we see and do online. They help us discover new content and websites among myriad choices. Some recommendation systems, however, unintentionally do the opposite. Because some recommendation systems (i.e. certain collaborative filters) recommend products based on past sales or ratings, they cannot usually recommend products with limited historical data. This can create positive feedback: a rich-get-richer effect for popular products. This bias toward popularity can prevent what are otherwise better recommendations for that user's preferences. A Wharton study details this phenomenon along with several ideas that may promote diversity.
If a chemical reaction causes the release of heat, and the reaction itself happens faster at higher temperatures, then there is a high likelihood of positive feedback. If the heat produced is not removed from the reactants fast enough, thermal runaway can occur and very quickly lead to a chemical explosion.
Practopoiesis is an overarching biological theory from Danko
Nikolic. The term reflects the fundamental presumption on what
the common property is, that can be found across all the
different levels of organization of biological systems: to
Due to this focus on biological action, practopoiesis has a strong cybernetic flavour as it has to deal with the need of acting systems to close feedback loops.
Thus, the theory of practopoiesis builds on the concepts of
cybernetics. Cybernetic laws assumes monitor-and-act
machinery (either physical or biological):
The key novelty of practopoiesis is that it introduces the mechanisms explaining how different levels of organization mutually interact. These mechanisms help explain how genes create anatomy of the nervous system, or how anatomy creates behaviour.
Practopoiesis is a theory on how life organizes into a mind. It proposes the principles by which adaptive systems organize. It is a general theory of what it takes to be biologically intelligent. Being general, the theory is applicable to the brain as much as it is applicable to artificial intelligence (AI) technologies. What makes the theory so general is that it is grounded in the principles of cybernetics (e.g. feedback loops), rather than describing the physiological implementations of those mechanisms (e.g. inhibition/excitation, plasticity, etc.).
In practopoiesis there is no longer a cycle: action → representation → action … . Instead, practopoietic theory works with actions only, which interact and form a hierarchy: One action is in a service of another action. This hierarchy starts with actions of gene expression mechanisms and ends with our overt behavior. Perception and cognition are then understood as emergent properties of those cybernetics-like actions.
The practopoietic theory of Prof. Dr. Danko Nikolic consists of two parts:
The term Practopoiesis is derived from Ancient Greek words praxis (πρᾶξις)) meaning "deed", "act" or "action" + poiesis (ποίησις, ποιέω) which means "to make". Practopoiesis means: creation of actions.
PseudoCode is a 'language syntax shorthand notation' that uses expressions in between human language and computer programming language. A programmer tries to write down cause-effect actions, using normal human words, so that a laymen (with no programming experience) can read and understand the serie of commands (= algorithms) that execute a specific computer process.
Bio-Mental Cybernetics describes the underlying mechanism of certain cause-effect phenomena that emerged during evolution to give rise to brain processes with regard to emotions (feelings) and cognitions (thought).
Mental-pseudocode (also called: neuro-pseudocode) denotes, on the concrete level, the actual thought process as a result of functional neuronal process.
Evo-pseudocode (also called: meta-pseudocode) describes, on a meta level, the way evolution gave birth to processes by which animals obtained the ability to generate brain processes resembling human thought.
Semi-Science is an attribute given by scientists to questionable knowledge-findings of certain people or non-objective truth-claims of certain groups. This attribute indicates that the underlying facts are not (yet) properly proven according to scientific rules, or that they are based on half-truths.
This means that certain theorems can not be refuted, and should not be ignored by the scientific community, as long as science does not contain 'all answers to everything'.
The prefix Semi is derived from the Latin word semi, meaning "half" and the term Science from Latin scientia, meaning "knowledge".
Taxonomy is the science of defining groups of biological organisms on the basis of shared characteristics and giving names to those groups. Organisms are grouped together into taxa (singular: taxon) and given a taxonomic rank. Groups of a given rank can be aggregated to form a super group of higher rank and thus create a taxonomic hierarchy. The Swedish botanist Carolus Linnaeus is regarded as the father of taxonomy, as he developed a system known as Linnaean classification for categorization of organisms and binomial nomenclature for naming organisms. With the advent of such fields of study as phylogenetics, cladistics, and systematics, the Linnaean system has progressed to a system of modern biological classification based on the evolutionary relationships between organisms, both living and extinct
The term taxonomy is derived from the Ancient Greek word taxis (τάξις) meaning "arrangement" and -nomia (νομία) meaning "method".
In biology, a taxon (plural taxa; back-formation from taxonomy) is a group of one or more populations of an organism or organisms seen by taxonomists to form a unit. A taxon is usually known by a particular name and given a particular ranking.
In biological classification, rank is the level (the relative
position) in a taxonomic hierarchy. Examples of taxonomic ranks
are species, genus, family, and class.
Cladistics is an approach to biological classification in which organisms are grouped together. This grouping is based on whether or not organisms have one or more shared unique characteristics that come from the group's last common ancestor and are not present in more distant ancestors. Therefore, members of the same group are thought to share a common history and are considered to be more closely related. When these lineage-branching (with regard to common ancestor) are drawn in a diagram, this is called a cladogram.
The term cladistic is derived from the Ancient Greek word klados (κλάδος) meaning "branch".
Phylogenetic nomenclature, often called cladistic nomenclature, is a method of nomenclature for taxa in biology that uses phylogenetic definitions for taxon names. This contrasts with the traditional approach, in which taxon names are defined by a type, which can be a specimen or a taxon of lower rank, and a diagnosis, a statement intended to supply characters that differentiate the taxon from others with which it is likely to be confused. Phylogenetic nomenclature is currently not regulated, but the International Code of Phylogenetic Nomenclature (PhyloCode) is intended to regulate it once it is ratified.