Online research in philosophy

The theory of the organism-environment system starts with the proposition that in any functional sense organism and environment are inseparable and form only one unitary system. The organism cannot exist without the environment and the environment has descriptive properties only if it is connected to the organism. Although for practical purposes we do separate organism and environment, this common-sense starting point leads in psychological theory to problems which cannot be solved. Therefore, separation of organism and environment cannot be the basis of any scientific explanation of human behavior. The theory leads to a reinterpretation of basic problems in many fields of inquiry and makes possible the definition of mental phenomena without their reduction either to neural or biological activity or to separate mental functions. According to the theory, mental activity is activity of the whole organism-environment system, and the traditional psychological concepts describe only different aspects of organisation of this system. Therefore, mental activity cannot be separated from the nervous system, but the nervous system is only one part of the organism­environment system. This problem will be dealt with in detail in the second part of the article.

A new theory of synaptic function in the nervous system (Dempsher, 1978) is applied to the simplest system for integration of function in the nervous system. This system includes a sensory and motor neuron and three synaptic regions associated with those two neurons; a receptor region, an interneuronal spinal synaptic region linking the two neurons, and an effector region.Information is first received and processed at the receptor region. The processing consists of five components:1. A highly selective mechanism which allows only that information to enter the receptor system which is appropriate. 2. The appropriateness of the information is determined by the alphabet (miniature potentials) already in that area. 3. The information entering the system is assembled in a pattern meaningful for the next processing operation. 4. The assembled information is then disassembled into its subunits and mapped into the alphabet (miniature potentials). 5. These miniature potentials are assembled into another pattern meaningful to fit the role of the receptor region. 6. This new pattern is repacked for transit to the central synaptic region.

Bionic technologies connecting biological nervous systems to computer or robotic devices for therapeutic purposes have been recently claimed to provide novel experimental tools for the investigation of biological mechanisms. This claim is examined here by means of a methodological analysis of bionics-supported experimental inquiries on adaptive sensory-motor behaviours. Two broad classes of bionic systems (regarded here as hybrid simulations of the target biological system) are identified, which differ from each other according to whether a component of the biological target system is replaced by an artificial component, or else a component of an artificial system is replaced by a biological component. The role of these hybrid systems in the modelling of adaptive sensory-motor biological behaviours is discussed with reference to bionics-supported experiments on the mechanisms of body stabilization in lampreys. Methodological problems emerging from these case studies often arise in computer-based and biorobotic simulations of biological behaviours too. Accordingly, the present analysis contributes to identifying a more general regulative methodological framework for the machine-based modelling of biological systems.

Some have suggested that there is no fact to the matter as to whether or not a particular physical system relaizes a particular computational description. This suggestion has been taken to imply that computational states are not real, and cannot, for example, provide a foundation for the cognitive sciences. In particular, Putnam has argued that every ordinary open physical system realizes every abstract finite automaton, implying that the fact that a particular computational characterization applies to a physical system does not tell oneanything about the nature of that system. Putnam''s argument is scrutinized, and found inadequate because, among other things, it employs a notion of causation that is too weak. I argue that if one''s view of computation involves embeddedness (inputs and outputs) and full causality, one can avoid the universal realizability results. Therefore, the fact that a particular system realizes a particular automaton is not a vacuous one, and is often explanatory. Furthermore, I claim that computation would not necessarily be an explanatorily vacuous notion even if it were universally realizable.

This article defends a modest version of the Physical Church-Turing thesis (CT). Following an established recent trend, I distinguish between what I call Mathematical CT—the thesis supported by the original arguments for CT— and Physical CT. I then distinguish between bold formulations of Physical CT, according to which any physical process—anything doable by a physical system—is computable by a Turing machine, and modest formulations, according to which any function that is computable by a physical system is computable by a Turing machine. I argue that Bold Physical CT is not relevant to the epistemological concerns that motivate CT and hence not suitable as a physical analog of Mathematical CT. The correct physical analog of Mathematical CT is Modest Physical CT. I propose to explicate the notion of physical computability in terms of a usability constraint, according to which for a process to count as relevant to Physical CT, it must be usable by a finite observer to obtain the desired values of a function. Finally, I suggest that proposed counterexamples to Physical CT are still far from falsifying it because they have not been shown to satisfy the usability constraint.

The purpose of this paper is to present a bio-physical basis of mathematics. The essence of the theory is that function in the nervous system is mathematical. The mathematics arises as a result of the interaction of energy (a wave with a precise curvature in space and time) and matter (a molecular or ionic structure with a precise form in space and time). In this interaction, both energy and matter play an active role. That is, the interaction results in a change in form of both energy and matter. There are at least six mathematical operations in a simple synaptic region. It is believed the form of both energy and matter are specific, and their interaction is specific, that is, function in most of the nervous system is stereotyped. It is suggested that mathematics be taken out of the mind and placed where it belongs — in nature and the synaptic regions of the nervous system; it results in both places from a precise interaction between energy (in a precise form) and matter (in a precise structure).

Neuro-technical interfaces are technical devices that bridge the electronic world to neurons with the objective to establish a long term stable contact for bidirectional information exchange. What does that mean in detail and to what kind of machine and for what purpose should the central nervous system, i.e. the brain, be connected? Science fiction literature and movies offer a tremendous variety of usually uncomfortable scenarios including cyborg and robocop super-humans and mass control. Do these implants change the psyche in general and what is feasible in nowadays therapeutic and rehabilitative approaches? In this overview, the author will not answer these questions but tries to deliver an overview of the technological background, the opportunities and the limitations of neuro-technical interfaces to the central nervous system. The fundamental specifications for neuro-technical interfaces will be introduced. Different degrees of implant invasiveness will be discussed and lead to a summary of clinical systems with their application-specific complexity. Actual technological opportunities and limitations will be addressed as well as general physical limitations. Current and future scenarios of neuro-technical interfaces to the central nervous system will be presented from an engineering point of view arising some questions that might be of interest with respect to ethical and societal implications when those interfaces are transferred into clinical practice and public applications.

Goedel's theorem states that in any consistent system which is strong enough to produce simple arithmetic there are formulae which cannot be proved-in-the-system, but which we can see to be true. Essentially, we consider the formula which says, in effect, "This formula is unprovable-in-the-system". If this formula were provable-in-the-system, we should have a contradiction: for if it were provablein-the-system, then it would not be unprovable-in-the-system, so that "This formula is unprovable-in-the-system" would be false: equally, if it were provable-in-the-system, then it would not be false, but would be true, since in any consistent system nothing false can be provedin-the-system, but only truths. So the formula "This formula is unprovable-in-the-system" is not provable-in-the-system, but unprovablein-the-system. Further, if the formula "This formula is unprovablein- the-system" is unprovable-in-the-system, then it is true that that formula is unprovable-in-the-system, that is, "This formula is unprovable-in-the-system" is true. Goedel's theorem must apply to cybernetical machines, because it is of the essence of being a machine, that it should be a concrete instantiation of a formal system. It follows that given any machine which is consistent and capable of doing simple arithmetic, there is a formula which it is incapable of producing as being true---i.e., the formula is unprovable-in-the-system-but which we can see to be true. It follows that no machine can be a complete or adequate model of the mind, that minds are essentially different from machines.

The first brief description is given of a project aimed at searching for the neural correlates of consciousness through computer simulation. The underlying model is based on the known circuitry of the mammalian nervous system, the neuronal groups of which are approximated as binary composite units. The simulated nervous system includes just two senses - hearing and touch - and it History..

1. The Physical Church-Turing Thesis. Physicists often interpret the Church-Turing Thesis as saying something about the scope and limitations of physical computing machines. Although this was not the intention of Church or Turing, the Physical Church Turing thesis is interesting in its own right. Consider, for example, Wolfram’s formulation: One can expect in fact that universal computers are as powerful in their computational capabilities as any physically realizable system can be, that they can simulate any physical system . . . No physically implementable procedure could then shortcut a computationally irreducible process. (Wolfram 1985) Wolfram’s thesis consists of two parts: (a) Any physical system can be simulated (to any degree of approximation) by a universal Turing machine (b) Complexity bounds on Turing machine simulations have physical significance. For example, suppose that the computation of the minimum energy of some system of n particles takes at least exponentially (in n) many steps. Then the relaxation time of the actual physical system to its minimum energy state will also take exponential time.