Some Economic Principles Deduced from Microeconomics
in Glial-Neuronal Synaptic Units
by Dr. Bernhard J. Mitterauer
Head, Volitronics-Institute for Basic Research and Brain Philosophy
Gotthard Günther Archives
Professor Emeritus of Neuropsychiatry
Editor’s note: As is detailed within this paper, ‘neuroeconomics’ attempts to employ recent neuroscientific methods in order to analyze economically-relevant brain processes. The explanation of this fascinating concept requires a certain degree of technical vocabulary, thus a glossary for review purposes is provided at the end of this paper. - JLP
For the solution of global economic problems the term ‘economic geography’ has been coined (Clark et al, 2000). In the past, studies of economy tended to take place on economics’ terms, using economic procedures and concepts. When economy has been studied by other disciplines, it has often been through recourse to the same practices and concepts, even if at times to criticize them. However, considering the various approaches to economic research, the search for basic economic principles seems most important to me. Note that as early as 1871 the economist Carl Menger had already published his book “Principles of Economics”. According to Menger, the individual mind is the source of economic value, and therefore he insisted that the function of economics is to investigate the essence rather than the specific quantities of economic phenomena. Supposing that individuality is basically generated in our brain, neuroscience might be most appropriate for the search of elementary economic principles.
Evidence that neuroscience improves our understanding of economic phenomena comes from a broad array of novel experimental findings. Despite this fact, the foundations of neuroeceonomics have evoked a controversial discussion. So have critics charged that neuroscience and economics are fundamentally incompatible (Gul and Pesendorfer, 2008). However, neuroeconomics attempts to employ recent neuroscientific methods in order to analyze economically-relevant brain processes. Experiments should be based on a theoretical background of a specific economic behavior so that neural correlates can be detected with pertinent techniques (for review see Kenning and Plassmann, 2005). Therefore, we deal mainly with a behavior-to-brain-to-behavior approach (Clithero et al, 2008).
My approach is contrary to this trend by deducing some economic principles from an experimentally-based theoretical model of the structure and function of the synapses (all terms in italics are explained in the Appendix) of the brain. Supposing that the brain operates per se according to economic principles, then synapses can be interpreted as microeconomic units. Importantly, microeconomic theory invoked the concept of a general equilibrium (Mas-Collel et al, 1995) to explain aggregate market outcomes based on individual behavior and preferences, representing a foundational concept to explain higher level outcomes from lower level data. In accordance with this approach to microeconomics, my model is this:
It is meanwhile experimentally verified that most synapses of the brain are composed not only of neuronal components (presynapse and postsynapse), but also of the glial component (astrocyte), the second main cell type of the brain. The interaction between these three components occurs via various substances and receptors building a balanced system in the sense of a glial-neuronal synaptic unit of information processing. Moreover, the presynapse, the postsynapse and the astrocyte are spatially separated and each component exerts a qualitatively distinct function. From this biological model and its economic organization an economic system and some elementary principles on the behavioral level can be deduced. The latter consists of an entrepreneur (astrocyte), a production unit (presynapse) and a customer (postsynapse), and the interactions between them are economically controlled.
Model of a glial-neuronal synaptic unit
As indicated above, there are two major classes of cells in the brain: neurons and glia. Neurons are able to respond to external stimulation by generation of an ‘all-or-none’ action potential, capable of propagating through the neuronal network, whereas glia represent nonexcitable cells. There are several glial cell types. Here I will focus on astrocytes, since these cells contact neuronal synapses and also build a network, called glial syncytium. The fundamental question in understanding economic brain function is: ‘How does the neuronal system communicate with the glial system?’
Recent results of brain research suggest that synaptic information proessing not only occurs from the presynapse to the postsynapse (neuronal components), but the astrocyte (glial component) as a third element is also at work, exerting an active and modulatory function on synaptic information transmission. Hence, one speaks of tripartite synapses (Auld and Robitaille, 2000) or of glial-neuronal synaptic units.
Outline of a tripartite synapse
According to the prevailing view, chemical synaptic transmission exclusively involves bipartite synapses consisting of presynaptic and postsynaptic components and a synaptic cleft, in which a presynaptically-released neurotransmitter binds to cognate receptors in the postsynaptic cell. However, there is a new wave of information suggesting that glia, especially astrocytes, are intimately involved in the active control of neuronal activity and synaptic information transmission. As early as 1999, Haydon and co-workers showed that glia respond to neuronal activity with an elevation of their internal Ca 2+ concentration which triggers the release of chemical transmitters from glia themselves and, in turn, causes feedback regulation of neuronal activity and synaptic strength (Araque et al, 1999).
Although a true understanding of how the astrocyte, the dominant glial cell type, interacts with neurons is still missing, several models have been published. Here, I focus on a modified model proposed by Newman (2005). Figure 1 depicts a schematic diagram of possible glial-neuronal interactions at a glutamatergic tripartite synapse. Release of glutamate (GLU) from the presynaptic terminal activates glial receptors (glR) and postsynaptic receptors (poR) (1) (for the sake of clarity only one receptor is shown). The occupancy of glial receptors evokes a Ca2+ increase (2) and the release of glutamate from the astrocyte. Glutamate excitation of presynaptic receptors (prR) (3) modulates glutamate-release while activation of postsynaptic receptors (4) directly depolarizes the postsynapse. Activation of the astrocyte also elicits the release of adenosine-triphosphat (ATP), which inhibits the postsynaptic neuron (5) and the presynaptic terminal (6) via occupancy of the cognate receptors. In parallel, neurotransmission is also inactivated by re-uptake of the transmitter (GLU) in the membrane of the presynapse mediated by transporter molecules (t) (7).
In this model, glutamate determines the amount of Ca2+ in the astrocyte via occupancy of the astrocytic receptors that elicits the production of glutamate within the astrocyte called a gliotransmitter (Volterra et al, 2002). Glutamate as a gliotransmitter now activates presynaptic receptors. So this intracellular Ca2+–dependent glutamate release from astrocytes triggers opening of Ca2+ stores in the presynaptic terminal. Whereas glutamate released from astrocytes has an excitatory function on the presynaptic terminal, inhibition of it is provided by the release of ATP and the resulting accumulation of adenosine. Importantly, we apparently deal with different time scales of presynaptic and astrocytic glutamate release. Hence, the astrocytic modulatory function of synaptic neurotransmission may occur within seconds, minutes or even hours. Here, I hypothesize that the duration from presynaptic activation to the inhibition of synaptic neurotransmission may also be dependent on the number of astrocytic receptors that must be occupied by glutamate. This mechanism may be based on the occupancy probability of astrocytic receptors by glutamate releases from the presynaptic terminal. In addition, the release of ATP from astrocytes may also be dependent on a comparable mechanism. Accordingly, in tripartite synapses glia may have a temporal boundary-setting function in temporarily turning off synaptic information transmission (Mitterauer, 1998).
Basic mechanisms of synaptic glial-neuronal interactions
Generally speaking, both the neuronal system and the glial system exert comparable functions, but they are differently organized. This situation may allow an interpretation of glial-neuronal synaptic units (tripartite synapses) as a microeconomic system as I attempt to show below. Before doing so, the basic mechanisms of synaptic information processing must be described as follows:
From a structural point of view I have hypothesized that in the glial networks (syncytia) intentional programs are generated that must be tested in the neuronal networks whether they are feasible in the outer environment or not (Mitterauer, 2007). Therefore, glia (astrocytes) can be interpreted as the active, intentional part of a glial-neuronal synapse.
A glial-neuronal synaptic unit is equipped with two types of receptor channels for occupancy by the various substances (neurotransmitter, etc.) responsible for information processing. Ionotropic receptors are represented by ligand-gated ion channels. Neurotransmitter binding to the receptor site opens directly the channel pore resulting in ion fluxes. The function of metabotropic receptors differs considerably from ionotropic receptors. They are coupled to numerous G-proteins. Activation of metabotropic receptors results in indirect opening of ion channels or in activation/inhibition of enzymes responsible for synthesis of different intra-cellular second messengers (Ca2+, inositol-triphosphate, etc.).
Most important for an economic interpretation of synapses is the fact that action of a transmitter in the postsynapse does not depend on the chemical properties of the transmitter, but rather on the properties of the receptors that recognize and bind the transmitter. For example, acetylcholine can excite some postsynaptic cells and inhibit others, yet at other cells it can produce both excitation and inhibition. Therefore, it is the receptor that determines whether a cholinergic synapse is excitatory or inhibitory and whether an ion channel will be activated directly by the transmitter or indirectly through a second messenger (Kandel et al, 2000).
In metabotropic (indirect) information processing second messengers play a significant role. Many second messenger actions depend on activation of protein kinases, leading to phosphorilation of a variety of cellular proteins, including ion channels, which changes their functional state. Second messenger actions not only open ion channels, as do the transmitter-gated receptors, but they can also close channels that normally open in the absence of transmitter, producing decreases in membrane conductance. In addition, second messengers modify pre-existing proteins, but may also induce the synthesis of new proteins (receptors) by altering gene expression (Kandel et al, 2000).
What the termination of neurotransmission concerns, the basic mechanisms between the neuronal components work as follows: re-uptake of transmitter substance is the most common mechanism for inactivation. This mechanism serves the dual purposes of terminating the synaptic action of the transmitter and recapturing the transmitter molecule for possible reuse. Importantly, this mechanism is mediated by transporter molecules in the membranes of nerve terminals and glia (astrocyte). As depicted in Figure 1, the glial component (astrocyte) of the synapse influences or modulates synaptic information processing on the presynapse and on the postsynapse via gliotransmitters (glutamate, adenosine triphosphate). These transmitters exert an inverse function on the presynaptic terminal. Glutamate positively feeds back on the presynapse and adenosine-triphosphate negatively feeds back temporarily turning off synaptic information transmission (Mitterauer, 2009). In addition, these gliotransmitters also influence the postsynapse in the same manner. Glutamate can activate and adenosine triphosphate inactivate the postsynaptic neurotransmission to the neuronal network.
Whereas ‘pure’ neurotransmission between the presynapse and the postsynapse occurs within milliseconds, the interaction between the astrocyte and the neuronal components of the synapse is slower (seconds, minutes, hours to weeks). Supposing that glial networks (syncytia) are generating intentional programs, then their testing by neuronal information processing is a cognitive procedure in the sense of a thinking process that might often last for hours, days or weeks. Hence, astrocytes may structure synaptic information processing and decide if an intentional program is feasible or not.
Macroeconomic model deduced from synaptic microeconomics
Figure 2 shows the diagram of the interpretation of synaptic microeconomics (Figure 1) as a macroeconomic system in the sense of a small firm. Supposing that the firm is already successfully present on the market, the basic economic structures and functions can be described as follows:
Dependent on the resources of the environment (physiological state of the brain) (1), a production unit is selling products (neurotransmitter) to a customer (2). The customer (neurotransmission) pays money for the product to the production unit (re-uptake of neurotransmitter) (3). The business is mediated by one or more persons (transporters, t). Now, the customer is able to sell the product (neurotransmission) to the market (neuronal networks) (4) earning money (5). The whole economic procedure is commanded and controlled by the entrepreneur.
The entrepreneur (astrocyte) had the idea of a new product (glial syncytium, intentional programming) and founded a firm that is functioning successfully. Moreover, the entrepreneur must optimize his (her) products via a permanent interaction with the development unit (comparable to the interaction of the astrocyte with its syncytium) (6). A rule is established according to which a new product is to be developed in a certain time and its production in the production unit ordered by the entrepreneur (7). In addition, the entrepreneur decides if the product is appropriate to a customer or if it has to be altered or even rejected (8). This economic behavior of the entrepreneur is comparable to the functions of neurotransmitters (gliotransmitters) that either activate or inhibit synaptic neurotransmission (Figure 1). In parallel, the communication between the entrepreneur and the production unit is also based on feedback information from the production unit (9).
Moreover, the entrepreneur must also influence the market behavior of the customer. This occurs both by supporting the business (10) and by controlling it (11) with regard to possible misconduct. Negotiations between the entrepreneur and the customer are mostly mediated by one or more persons (m) (12). Importantly, the communication between the firm and the customer can be realized in a twofold manner what the customer concerns. The entrepreneur and his (her) team can either directly (d) or indirectly (id) negotiate with the customer. A direct negotiation is possible if the customer is represented by one person who is able to decide alone. In the case of an indirect negotiation, the customer is a kind of team speaker who co-decides.
Here, we deal with two elementary mechanisms of information processing that already work on receptors in glial-neuronal synaptic units. As described above, ionotropic receptors on the postsynapse transfer information directly to the neuronal network, whereas metabotropic receptors must cooperate with second messengers in information processing. Note that the operations of second messengers are not only very complex comparable to a hidden layer, but they also influence the structure of the receptors. This means on the behavioral level that the firm might be faced with customer behavior which may at times be unpredictable.
Finally, the whole economic system described is constrained by the resources of the environment in general and the market situation in specific. As depicted in Figure 2, the available resources of the environment set limits to the entrepreneur (13) and to the market (14). In parallel, the market sets limits to the entrepreneur and his (her) firm (15). From the perspective of synaptic microeconomics, the structure and function of the whole brain embodies the environment. In other words: only if the whole brain is functioning in an equilibrium based on appropriate ‘nutrition’, synaptic units can do their jobs well.
Considering the fact that the brain consists not only of the neuronal system but of the glial system as well, the concept of neuroeconomics is not comprehensive. This argument holds for all other scientific disciplines with the prefix “neuro”. Therefore, we should speak of braineconomics. As introductorily mentioned, my novel approach to braineconomics is to investigate possible economic interactions or even principles in the brain itself. Of course, using neural measures (functional magnetic resonance imaging, etc.) for exploring typical reaction patterns to a specific behavior contribute to our understanding about in which systems the brain reacts, but scarcely concerning which principles these reactions are based on and how the brain is integrating all the relevant components within the behavior observed.
As I mention again and again, robotics may represent an alternative approach. Because if we are able to implement principles of economics working in the brain per se in a robot brain based on biomimetic structures and functions, we can learn from its behavior where we are right and where we are wrong, and where we are confronted with limits of brain research per se.
However, already at the present preliminary stage of investigation, the synaptic microeconomics described may teach us some principles on which our economic behavior in business affairs might be based.
First, the experimentally-verified mechanism according to which the postsynaptic receptors (customer) determine neurotransmission (business) and not the neurotransmitters (products) by their occupancy of the receptors, teaches us that an entrepreneur should be aware of the fact that not the quality of his (her) product is primarily decisive for a successful business, but rather the situation of the customer. Therefore, the success of a product on the market depends essentially on the readiness of consumers to buy it. Hence, the quality of a product as such may not be decisive. This is at first glance a rather trivial statement. However, it may represent a basic economic principle already operating in glial-neuronal synaptic units of the brain, as proposed by Menger (1871). According to him, marginal utility as the source of value means that the perceived need for an object is dictating the value, on an individual rather than general level. The implication is that the individual mind is the source of economic value.
Second, on the one hand the entrepreneur can directly negotiate with the customer, if the customer is able to decide alone, comparable to ionotropic receptors. On the other hand, an indirect negotiation (metabotropic receptors) occurs if the customer is dependent on a team that co-decides (second messengers). In the latter case, a hidden decision procedure may be at work similar to phase transitions in non-linear dynamics of the brain.
Third, a successful organization of the firm and a successful business should be supported by mediation (transporters). These are persons experienced in successful information transfer.
Fourth, ideally the entrepreneur only invests money already earned by the firm and does not need to acquire bank loans. This is comparable to the synaptic self-organization in the sense of a permanent production of neurotransmitter and their re-uptake for reuse. Note that synaptic information processing uses mainly substances that are produced within the synaptic unit. In the case of external application of substances for receptor occupancy (medicine, drugs), the system is either disordered in the first place or it gets disordered. A similar role of bank loans in economics is at least imaginable.
Finally, let me mention that imbalances in glial-neuronal synaptic units cause psychobiological disorders such as depression, mania, and schizophrenia (Mitterauer, 2004; 2005). These disorders may also significantly impair the economic dynamics in the brain. How this might happen in detail must be further investigated.
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Appendix: definitions of special biological terms
Astrocytes: are the most abundant type of macroglial cells (astrocytes and oligodendrocytes) having numerous projections that anchor neurons to their blood supply. They regulate the external chemical environment of neurons by removing excess ions and recycling neurotransmitters released during synaptic transmission. Most importantly, astrocytes modulate synaptic information processing as shown in the present paper. They are physically connected forming a functional cellular network, called glial syncytium (see definition below).
Depolarization: if the inside of the cell membrane becomes more positive while the outside of the membrane becomes more negative, a progressive decrease in the normal separation of charge occurs, called depolarization. A sufficiently large depolarizing current triggers the opening of voltage-gated channels. The opening of these channels leads to the action potential.
Glial cells: commonly called neuroglia or glia (Greek for ‘glue’), are non-neuronal cells that maintain homeostasis, form myelin, and provide support and protection for the brain’s neurons. In the human brain, there is roughly one glia for every neuron with a ratio of about two neurons for every three glia in the cerebral grey matter. Glia should not be regarded as glue in the nervous system as the name implies. It is rather more of a partner to neurons and even capable of modulating neurotransmission (information processing) in synaptic glial-neuronal units (tripartite synapses).
Glial syncytium: macroglial cells (astrocytes and oligodendrocytes) are physically connected, forming a functional network, called syncytium. This represents a fundamental difference between neuronal and glial networking. For the majority of neurons, networking is provided by synaptic contacts. The latter preclude physical continuity of the neuronal network, while providing for functional inter-neuronal signal propagation. In contrast, glial networks are supported by direct intercellular contacts, generally known as gap junctions (electrical synapses).
Gliotransmitter: astrocytes may release transmitter substances themselves, such as glutamate, adenosine-triphosphate (ATP), D-serine etc., called gliotransmitters. These may serve as modulators of neuronal physiology.
Neurotransmitter: in contrast to the situation at electrical synapses, there is no structural continuity between pre- and postsynaptic neurons at chemical synapses. In fact, at chemical synapses the region separating the pre- and postsynaptic cells – the synaptic cleft – is usually wider than the adjacent nonsynaptic intercellular space. As a result, chemical synaptic transmission depends on the release of a neurotransmitter from the presynapse occupying both the postsynaptic receptors and cognate receptors on the astrocyte. The main neurotransmitters are acetylcholine, biogenic amines (dopamine, norepinephrine, epinephrine, serotonin, histamine), amino acids (gamma-aminobutyric acid, glycine, glutamate).
Regulation of gene expression: includes the processes that cells and viruses use to turn the information in genes into gene products. The majority of known mechanisms regulate protein coding genes. Note, the receptors of tripartite synapses as described in the present paper consist of proteins.
Second messengers: are small molecules that act as information transducers between the plasmalemma and cell interior. Typical second messengers are calcium and inositol-triphosphate. Second messengers interact with intracellular receptors (proteins, enzymes) and either up- or down-regulate their activity, therefore producing cellular physiological response.
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