Online research in philosophy

The prevailing concept in modern cognitive neuroscience is that cognitive functions are performed predominantly at the network level, whereas the role of individual neurons is unlikely to extend beyond forming the simple basic elements of these networks. Within this conceptual framework, individuals of outstanding cognitive abilities appear as a result of a favorable configuration of the microarchitecture of the cognitive-implicated networks, whose final formation in ontogenesis may occur in a relatively random way. Here I suggest an alternative concept, which is (...) based on neurological data and on data from human behavioral genetics. I hypothesize that cognitive functions are performed mainly at the intracellular, probably at the molecular level. Central to this hypothesis is the idea that the neurons forming the networks involved in cognitive processes are complex elements whose functions are not limited to generating electrical potentials and releasing neurotransmitters. According to this hypothesis, individuals of outstanding abilities are so due to a lucky combination of specific genes that determine the intrinsic properties of neurons involved in cognitive functions of the brain. (shrink)

The canonical Buddhist account of the cognitive processes underlying our experience of the world prefigures recent developments in neuroscience. The developments in question are centered on two main trends in neuroscience research and thinking. The first of these involves the idea that our everyday experience of ourselves and of the world consists in a series of discrete microstates. The second closely related notion is that affective structures and systems play critical roles in governing the formation of such states. Both of (...) these ideas are contained within the Buddhist theory of dependent co-origination. This paper explicates the theory of dependent co-origination in light of the aforementioned developments. It examines the role of the theory of dependent co-origination within Buddhism and it draws attention to critical differences with the neuroscientific account of the same process. Finally, it discusses specific ways in which these differences may be usefully applied to neuroscience research and thinking. (shrink)

Two chronic problems have plagued functionalism in the philosophy of mind. The first is the chauvinism/liberalism dilemma, the second the absent qualia problem. The first problem is addressed by blocking excessively liberal counterexamples at a level of functional abstraction that is high enough to avoid chauvinism. This argument introduces the notion of emotional functional organization (EFO). The second problem is addressed by granting Block's skeptical conclusions with respect to mentality as such, while arguing that qualitative experience is a concomitant of (...) human mentality considered as a special case: a system with EFO implemented in an organic substrate. (shrink)

The NMDA receptor (NMDAR) channel has been proposed to function as a coincidence-detection mechanism for afferent and reentrant signals, supporting conscious perception, learning, and memory formation. In this paper we discuss the genesis of distorted perceptual states induced by subanesthetic doses of ketamine, a well-known NMDA antagonist. NMDAR blockage has been suggested to perturb perceptual processing in sensory cortex, and also to decrease GABAergic inhibition in limbic areas (leading to an increase in dopamine excitability). We propose that perceptual distortions and (...) hallucinations induced by ketamine blocking of NMDARs are generated by alternative signaling pathways, which include increase of excitability in frontal areas, and glutamate binding to AMPA in sensory cortex prompting Ca++ entry through voltage-dependent calcium channels (VDCCs). This mechanism supports the thesis that glutamate binding to AMPA and NMDARs at sensory cortex mediates most normal perception, while binding to AMPA and activating VDCCs mediates some types of altered perceptual states. We suggest that Ca++ metabolic activity in neurons at associative and sensory cortices is an important factor in the generation of both kinds of perceptual consciousness. (shrink)

The NMDA receptor (NMDAR) channel has been proposed to function as a coincidence-detection mechanism for afferent and reentrant signals, supporting conscious perception, learning, and memory formation. In this paper we discuss the genesis of distorted perceptual states induced by subanesthetic doses of ketamine, a well-known NMDA antagonist. NMDAR blockage has been suggested to perturb perceptual processing in sensory cortex, and also to decrease GABAergic inhibition in limbic areas (leading to an increase in dopamine excitability). We propose that perceptual distortions and (...) hallucinations induced by ketamine blocking of NMDARs are generated by alternative signaling pathways, which include increase of excitability in frontal areas, and glutamate binding to AMPA in sensory cortex prompting Ca ++ entry through voltage-dependent calcium channels (VDCCs). This mechanism supports the thesis that glutamate binding to AMPA and NMDARs at sensory cortex mediates most normal perception, while binding to AMPA and activating VDCCs mediates some types of altered perceptual states. We suggest that Ca ++ metabolic activity in neurons at associative and sensory cortices is an important factor in the generation of both kinds of perceptual consciousness. (shrink)

This article discusses the properties of a controllable, flexible, hybrid parallel computing architecture that potentially merges pattern recognition and arithmetic. Humans perform integer arithmetic in a fundamentally different way than logic-based computers. Even though the human approach to arithmetic is both slow and inaccurate it can have substantial advantages when useful approximations ( intuition ) are more valuable than high precision. Such a computational strategy may be particularly useful when computers based on nanocomponents become feasible because it offers a way (...) to make use of the potential power of these massively parallel systems. Because the system architecture is inspired by neuroscience and is applied to cognitive problems, occasional mention is made of experimental data from both fields when appropriate. (shrink)

This paper is a revised and extended version of a keynote contribution to a recent conference on Cognitive Informatics. It offers a brief summary of some of the core concerns of other contributions to the conference, highlighting the range of issues under discussion; and argues that many of the central concepts and preoccupations of cognitive informatics as understood by participants--and others in the general field of computation--rely on ill-founded realist assumptions, and what has been termed the functionalist view of representation. (...) Even if such ideas--albeit in a revised form -- can be defended, there must be a more extensive engagement with the literature and issues outside the confines of the computing and computational orthodoxy. (shrink)

This paper describes the processes of cognitive modeling and representation of human expertise for developing an ontology and knowledge base of an expert system. An ontology is an organization and classification of knowledge. Ontological engineering in artificial intelligence (AI) has the practical goal of constructing frameworks for knowledge that allow computational systems to tackle knowledge-intensive problems and supports knowledge sharing and reuse. Ontological engineering is also a process that facilitates construction of the knowledge base of an intelligent system, which can (...) be defined as a computer program that can duplicate problem-solving capabilities of human experts in specific areas. This paper presents the processes of knowledge acquisition, analysis, and representation, which laid the basis for ontology construction. In this case, the processes are applied in ontological engineering for construction of an expert system in the domain of monitoring of a petroleum production and separation facility. The acquired knowledge was also formally represented in two knowledge acquisition tools. (shrink)

Given a set of objects characterized by a number of attributes, hidden patterns can be discovered in them for the grouping of similar objects into clusters. If each of these clusters can be considered as exemplifying a certain concept, then the problem concerned can be referred to as a concept discovery problem. This concept discovery problem can be solved to some extent by existing data clustering techniques. However, they may not be applicable when the concept involved is vague in nature (...) or when the attributes characterizing the objects can be qualitative, quantitative, and fuzzy at the same time. To discover such concepts from objects with such characteristics, we propose a Genetic-Algorithm-based technique. By encoding a specific object grouping in a chromosome and a fitness measure to evaluate the cluster quality, the proposed technique is able to discover meaningful fuzzy clusters and assign membership degrees to objects that do not fully exemplify a certain concept. For evaluation, we tested the proposed technique with simulated and real data and the results are found to be very promising. (shrink)

One new tradition that has emerged from early research on autonomous robots is embodied cognitive science. This paper describes the relationship between embodied cognitive science and a related tradition, synthetic psychology. It is argued that while both are synthetic, embodied cognitive science is antirepresentational while synthetic psychology still appeals to representations. It is further argued that modern connectionism offers a medium for conducting synthetic psychology, provided that researchers analyze the internal representations that their networks develop. The paper then provides a (...) detailed example of the synthetic approach by showing how the construction (and subsequent analysis) of a connectionist network can be used to contribute to a theory of how humans solve Piaget's classic balance scale task. (shrink)

Rational decision making depends on what one believes, what one desires, and what one knows. In conventional decision models, beliefs are represented by probabilities and desires are represented by utilities. Software agents are knowledgeable entities capable of managing their own set of beliefs and desires, and they can decide upon the next operation to execute autonomously. They are also interactive entities capable of filtering communications and managing dialogues. Knowledgeability includes representing knowledge about the external world, reasoning with it, and sharing (...) it. Interactions include negotiations to perform tasks in cooperative, coordinative, and competitive ways. In this paper we focus on decision-making mechanisms for agent-based systems on the basis of agent interaction. We identify possible interaction scenarios and define mechanisms for decision making in uncertain environments. It is believed that software agents will become the underlying technology that offers the capability of distribution of competence, control, and information for the next generation of ubiquitous, distributed, and heterogeneous information systems. (shrink)

In this paper we describe the nature and problems of business and define one aspect of the business environment. We then propose a framework based on augmented soft systems methodology and object technology that captures both the soft and hard aspects of a business environment within the context of organisational culture. We also briefly discuss cognitive informatics and its relevance to understanding problems and solutions. Pólya's work, which is based around solving mathematical problems, is considered within the context of information (...) systems development. We propose a generic reusable business object model based on general systems theory. We also show how these approaches can be integrated to provide a strategy for understanding business problems and developing integrated solutions. (shrink)

Program comprehension is an essential part of software engineering. The paper describes the constructivist theory of comprehension, a process based on assimilation and accommodation of knowledge. Assimilation means that the new facts are either added to the existing knowledge or rejected. Accommodation means that the existing knowledge is reorganized in order to absorb new facts. These processes are illustrated by case studies of knowledge-level reengineering of a legacy program and of incremental change. In both cases, we constructed preliminary knowledge from (...) the program documentation, and then adjusted it by comprehending the actual code. The case studies supported constructivism as a suitable theory of program comprehension. (shrink)

Supplementary to matter and energy, information is the third essence for modeling the natural world. An emerging discipline known as cognitive informatics (CI) is developed recently that forms a profound interdisciplinary study of cognitive and information sciences, and tackles the common root problems sharing by informatics, computing, software engineering, artificial intelligence, cognitive science, neuropsychology, philosophy, linguistics, and life science. CI focuses on internal information processing mechanisms and the natural intelligence of the brain. This paper describes the historical development of informatics (...) from the classical information theory and contemporary informatics, to CI. The domain of CI, and its interdisciplinary nature are explored. Foundations of CI, particularly the brain versus the mind, the acquired life functions versus the inherited ones, and generic relationships between information, matter, and energy are investigated. The potential engineering applications of CI and perspectives on future research are discussed. It is expected that the investigation into CI will result in fundamental findings towards the development of next generation IT and software technologies, and new architectures of computing systems. (shrink)

Although there are various ways to express actions and behaviors in natural languages, it is found in cognitive informatics that human and system behaviors may be classified into three basic categories: to be , to have , and to do . All mathematical means and forms, in general, are an abstract description of these three categories of system behaviors and their common rules. Taking this view, mathematical logic may be perceived as the abstract means for describing to be, set theory (...) for describing 'to have,' and algebras, particularly the process algebra, for describing to do. This is a fundamental view toward the formal description and modeling of human and system behaviors in general, and software behaviors in particular, because a software system can be perceived as a virtual agent of human beings, and it is created to do something repeatable, to extend human capability, reachability, and/or memory capacity. The author found that both human and software behaviors can be described by a three-dimensional representative model comprising action, time, and space. For software system behaviors, the three dimensions are known as mathematical operations, event/process timing, and memory manipulation. This paper introduces the real-time process algebra (RTPA) that serves as an expressive notation system for describing thoughts and notions of dynamic software behaviors. Experimental case studies on applications of RTPA in describing the equivalent software and human behaviors as a series of actions and cognitive processes are demonstrated with real-world examples. (shrink)

Despite the fact that the number of neurons in the human brain has been identified in cognitive and neural sciences, the magnitude of human memory capacity is still unknown. This paper reports the discovery of the memory capacity of the human brain, which is on the order of 10 8432 bits. A cognitive model of the brain is created, which shows that human memory and knowledge are represented by relations, i.e., connections of synapses between neurons, rather than by the neurons (...) themselves as the traditional container metaphor described. The determination of the magnitude of human memory capacity is not only theoretically significant in cognitive science, but also practically useful to unveil the human potential, as well as the gap between the natural and machine intelligence. (shrink)

This paper reports on the investigation of the effects of neuronal shape, at both individual cell and network level, on the behavior of neuronal systems. More specifically, two-dimensional biologically realistic neuronal networks are obtained that take explicity into account the position and morphology of neuronal cells, with the respective behavior for associative recall being simulated through a diluted version of Hopfield's model. While a specific probability density function is used for the placement of the cell bodies, images of real neuronal (...) cells (namely alpha and beta ganglion cells from the cat retina) are used to obtain biologically realistic models. Several morphological measures – including fractal dimension, the excluded volume, and integral geometry functionals–are estimated for the considered cells, and their values are correlated with the potential of the network for associative recall, which is quantified in terms of the overlap between distorted version of the trained patterns and their original version. Such an approach allows the quantitative and objective characterization of the relationship between neuronal shape and function, an important issue in neuroscience. The obtained results substantiate interesting relationships between the neural morphology and function as determined by the performance of the network. (shrink)

This paper reports on the investigation of the effects of neuronal shape, at both individual cell and network level, on the behavior of neuronal systems. More specifically, two-dimensional biologically realistic neuronal networks are obtained that take explicity into account the position and morphology of neuronal cells, with the respective behavior for associative recall being simulated through a diluted version of Hopfield's model. While a specific probability density function is used for the placement of the cell bodies, images of real neuronal (...) cells (namely alpha and beta ganglion cells from the cat retina) are used to obtain biologically realistic models. Several morphological measures – including fractal dimension, the excluded volume, and integral geometry functionals–are estimated for the considered cells, and their values are correlated with the potential of the network for associative recall, which is quantified in terms of the overlap between distorted version of the trained patterns and their original version. Such an approach allows the quantitative and objective characterization of the relationship between neuronal shape and function, an important issue in neuroscience. The obtained results substantiate interesting relationships between the neural morphology and function as determined by the performance of the network. (shrink)

Cognition or higher brain activity is sometimes seen as a phenomenon greater than the sum of its parts. This viewpoint however is largely dependent on the state of the art of experimental techniques that endeavor to characterize morphology and its association to function. Retinal ganglion cells are readily accessible for this work and we discuss recent advances in computational techniques in identifying novel parameters that describe structural attributes possibly associated with specific function. These parameters are based on calculating wavelet gradients (...) from cell images followed by the extraction of meaningful measures including 2nd wavelet moment, entropy of orientation, and curvature. For the three cell types analyzed, the mean 2nd wavelet moment, which relates to the field of influence of the dendritic-tree segments was significantly different. cells had the highest mean 2nd wavelet moment, followed by the and cells (134 ± 22, 93 ± 19 and 63 ± 12, respectively). There was no significant difference between cells for entropy of orientation, indicating no class with a preferential orientation of their dendritic tree. Curvature provided similar results to the 2nd wavelet moment with cells having the highest curvature followed by and the cells (mean ± SD: 161 ± 15; 134 ± 22; 121 ± 15). Our feature space analysis also indicated a difference between these cell types. No difference was found between the and cell types and their physiological counterparts the Y and X cells based on wavelet analysis. Both the X and Y cells can be divided into two subtypes, the ON- and OFF-center cells based on the stratification level of the dendritic tree within the retina. Using 2nd wavelet moment, a difference in their morphological attributes, not reported previously, was noted for these subtypes. The 2nd wavelet moment and curvature are further discussed with respect to explaining regularity of spacing and coverage associated with retinal ganglion cell mosaics. (shrink)

The shapes of neurons and glial cells dictate many important aspects of their functions. In olfactory systems, certain architectural features are characteristics of these two cell types across a wide variety of species. The accumulated evidence suggests that these common features may play fundamental roles in olfactoryinformation processing. For instance, the primary olfactory neuropil in most vertebrate and invertebrate olfactory systems is organized into discrete modules called glomeruli. Inside each glomerulus, sensory axons and CNS neurons branch and synapse in patterns (...) that are repeated across species. In many species, moreover, the glomeruli are enveloped by a thin and ordered layer of glial processes. Theglomerular arrangement reflects the processing of odor information in modules that encode the discrete molecular attributes of odorant stimuli being processed. Recent studies of the mechanisms that guide the development of olfactory neurons and glial cells have revealed complex reciprocal interactions between these two cell types, which may be necessary for the establishment of modular compartments. Collectively, the findings reviewed here suggest that specialized cellular architecture plays key functional roles in the detection, analysis, and discrimination of odors at early steps in olfactory processing. (shrink)

The shapes of neurons and glial cells dictate many important aspects of their functions. In olfactory systems, certain architectural features are characteristics of these two cell types across a wide variety of species. The accumulated evidence suggests that these common features may play fundamental roles in olfactoryinformation processing. For instance, the primary olfactory neuropil in most vertebrate and invertebrate olfactory systems is organized into discrete modules called glomeruli. Inside each glomerulus, sensory axons and CNS neurons branch and synapse in patterns (...) that are repeated across species. In many species, moreover, the glomeruli are enveloped by a thin and ordered layer of glial processes. Theglomerular arrangement reflects the processing of odor information in modules that encode the discrete molecular attributes of odorant stimuli being processed. Recent studies of the mechanisms that guide the development of olfactory neurons and glial cells have revealed complex reciprocal interactions between these two cell types, which may be necessary for the establishment of modular compartments. Collectively, the findings reviewed here suggest that specialized cellular architecture plays key functional roles in the detection, analysis, and discrimination of odors at early steps in olfactory processing. (shrink)

The temporal profile of dendritic branching in developing neurons is an interplay between the proliferating number of branching sites and the branching rates at these individual sites. The eventual metrical structure of dendritic arborizations is the outcome of joint processes of branching and elongation of outgrowing neurites. Dendritic growth models have shown to be powerful tools for quantitatively studying the rules of outgrowth, aiming at reproducing the shape characteristics in observed dendritic arborizations. Recent model studies, focusing on the branching process, (...) have predicted strongly decreasing branching rates during dendritic outgrowth. The implications of these findings for the metrical development of outgrowing dendrites will be discussed. (shrink)