There is no controversy in psychology or brain sciences that brains create mind and consciousness. Doubts and opinions to the contrary are quite frequently expressed in non-scientific publications. In particular the idea that conscious mind is received, rather than created by the brain, is quite often used against “materialistic” understanding of consciousness. I summarize here arguments against such position, show that neuroscience gives coherent view of mind and consciousness, and that this view is intrinsically non-materialistic.

What type of artificial systems will claim to be conscious and will claim to experience qualia? The ability to comment upon physical states of a brain-like dynamical system coupled with its environment seems to be sufficient to make claims. The flow of internal states in such systems, guided and limited by associative memory, is similar to the stream of consciousness. A specific architecture of an artificial system, termed articon, is introduced that by its very design has to claim being conscious. (...) Non-verbal discrimination of the working memory states of the articon gives it the ability to experience different qualities of internal states. Analysis of the flow of inner states of such a system during typical behavioral process shows that qualia are inseparable from perception and action. The role of consciousness in learning of skills — when conscious information processing is replaced by subconscious — is elucidated. Arguments confirming that phenomenal experience is a result of cognitive processes are presented. Possible philosophical objections based on the Chinese room and other arguments are discussed, but they are insufficient to refute articon’s claims that it is conscious. Conditions for genuine understanding that go beyond the Turing test are presented. Articons may fulfill such conditions and in principle the structure of their experiences may be arbitrarily close to human. (shrink)

What type of artificial systems will claim to be conscious and will claim to experience qualia? The ability to comment upon physical states of a brain-like dynamical system coupled with its environment seems to be sufficient to make claims. The flow of internal states in such system, guided and limited by associative memory, is similar to the stream of consciousness. Minimal requirements for an artificial system that will claim to be conscious were given in form of specific architecture named articon. (...) Nonverbal discrimination of the working memory states of the articon gives it the ability to experience different qualities of internal states. Analysis of the inner state flows of such a system during typical behavioral process shows that qualia are inseparable from perception and action. The role of consciousness in learning of skills, when conscious information processing is replaced by subconscious, is elucidated. Arguments confirming that phenomenal experience is a result of cognitive processes are presented. Possible philosophical objections based on the Chinese room and other arguments are discussed, but they are insufficient to refute claims articon’s claims. Conditions for genuine understanding that go beyond the Turing test are presented. Articons may fulfill such conditions and in principle the structure of their experiences may be arbitrarily close to human. (shrink)

Experiments with remote perception and Random Event Generators (REG) performed over the last decades show small but significant anomalous effects. Since these effects seem to be independent of spatial and temporal distance, they appear to be in disagreement with the standard scientific worldview. A very simple explanation of quantum mechanics is pre- sented, rejecting all unjustified claims about the world. A view of mind in agreement with cognitive neuroscience is introduced. It is argued that mind and consciousness are emer- gent (...) properties of the brain and are understandable without any nonphysical assumptions. A plausible explanation of the results of anomalous experiments, based on the concept of synchronicity, introduced by C.G. Jung and advocated by W. Pauli, is offered. A proof is given that strong correlations should exist between any systems that once interacted. Synchronicity events between parts of the brain and physical objects may be sufficient to explain the results of anomalous experiments. Standard physics is sufficient to understand these phenomena. Motto. (shrink)

Current cognitive architectures are either working at the abstract, symbolic level, or the low, emergent level related to neural modeling. The best way to understand phenomena is to see, or imagine them, hence the need for a geometric model of mental processes. Geometric models should be based on an intermediate level of modeling that describe mental states in terms of features relevant from the first-person perspective but also linked to neural events. Concepts should be represented as geometrical objects that have (...) sufficiently rich structures to show their properties and their relations to other concepts. The best way to create such geometrical representations of concepts is through the approximate description of the physical states of neural networks. The evolution of brain states is then represented as a trajectory linking successful concepts, and topological constraints on the shape of such trajectory define grammar and logic. (shrink)

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The following questions are considered: Why is it difficult to create a theory of consciousness? What are the contents of consciousness? What kind of theory is acceptable as transparent? and, What is the value of conscious experience?

Lehar misrepresents the Neuron Doctrine and indirect realism. His conclusions on consciousness are unjustified. The Bubble Gestalt perceptual modeling disconnected from neuroscience has no explanatory power.

Rules and similarity are two sides of the same phenomenon, but the number of features has nothing to do with transition from similarity to rules; threshold logic helps to understand why.

Neuronauki dokonały znacznego postępu w rozumieniu wyższych czynności poznawczych, w tym procesów decyzyjnych. Brakuje jednak zarówno prostych modeli, które pozwolą wyobrazić sobie te procesy, jak i głębszej refleksji nad wpływem tych wyników na zrozumienie natury umysłu, rozproszenia obaw, że nie jesteśmy tylko automatami. Płodny punkt widzenia na kwestię reprezentacji mentalnych daje próba zrozumienia, w jaki sposób informacja reprezentowana jest przez mózgi, jak w przybliżony sposób opisać stany mózgu tak, by można je było zinterpretować jako reprezentacje mentalne odnoszące się do umysłu. (...) Czym jest w nas to, co podejmuje decyzje? Jest to kluczowa kwestia dla zrozumienia wielu zagadnień klasycznej filozofii, od wolnej woli i problemu ciała i umysłu poczynając. Chociaż iluzja homunkulusa jest silna można się od niej uwolnić. Analiza procesów podejmowania decyzji wymaga zrozumienia w jaki sposób zakodowane są w mózgu najprostsze pojęcia. Jedynie przez aproksymację fizycznych stanów mózgu, zawierających znacznie więcej informacji niż stany mentalne, możemy dokonać istotnego postępu w rozumieniu i opisie reprezentacji mentalnych, przydatnych nie tylko filozofom, ale też mających zastosowania w analizie języka naturalnego, kategoryzacji pojęć w psychologii i architekturach kognitywnych w sztucznej inteligencji. Ucieleśnienie jak i enaktywizm są dla rozwoju reprezentacji pojęć bardzo istotne ale nie wystarczające. Po analizie współczesnej wiedzy o reprezentacji pojęć w mózgu zaprezentowano podejście oparte o język układów dynamicznych, które oferuje dość prosty język, pozwalający zrozumieć zaskakujące, często nieracjonalne decyzje podejmowane przez ludzi. Dzięki symulacjom komputerowym można się spodziewać znacznego postępu w rozumieniu reprezentacji mentalnych i wyższych czynności poznawczych, w szczególności procesów podejmowania decyzji. (shrink)

Yarkoni's analysis clearly articulates a number of concerns limiting the generalizability and explanatory power of psychological findings, many of which are compounded in infancy research. ManyBabies addresses these concerns via a radically collaborative, large-scale and open approach to research that is grounded in theory-building, committed to diversification, and focused on understanding sources of variation.