According to Thagard and Stewart :1–33, 2011), creativity results from the combination of neural representations, and combination results from convolution, an operation on vectors defined in the holographic reduced representation framework. They use these ideas to understand creativity as it occurs in many domains, and in particular in science. We argue that, because of its algebraic properties, convolution alone is ill-suited to the role proposed by Thagard and Stewart. The semantic pointer concept allows us to see how we can apply (...) the full range of HRR operations while keeping the modal representations so central to Thagard and Stewart’s theory. By adding another combination operation and using semantic pointers as the combinatorial basis, this modified version overcomes the limitations of the original theory and perhaps helps us explain aspects of creativity not covered by the original theory. While a priori reasons cast doubts on the use of HRR operations with modal representations :5039–5054, 1987) such as semantic pointers, recent models point in the other direction, allowing us to be optimistic about the success of the revised version. (shrink)

The proponents of machine consciousness predicate the mental life of a machine, if any, exclusively on its formal, organizational structure, rather than on its physical composition. Given that matter is organized on a range of levels in time and space, this generic stance must be further constrained by a principled choice of levels on which the posited structure is supposed to reside. Indeed, not only must the formal structure fit well the physical system that realizes it, but it must do (...) so in a manner that is determined by the system itself, simply because the mental life of a machine cannot be up to an external observer. To illustrate just how tall this order is, we carefully analyze the scenario in which a digital computer simulates a network of neurons. We show that the formal correspondence between the two systems thereby established is at best partial, and, furthermore, that it is fundamentally incapable of realizing both some of the essential properties of actual neuronal systems and some of the fundamental properties of experience. Our analysis suggests that, if machine consciousness is at all possible, conscious experience can only be instantiated in a class of machines that are entirely different from digital computers, namely, time-continuous, open, analog dynamical systems. (shrink)

It is worthwhile to search for forms of coding, processing, and learning common to various cortical regions and cognitive functions. Local cortical processors may coordinate their activity by maximizing the transmission of information coherently related to the context in which it occurs, thus forming synchronized population codes. This coordination involves contextual field (CF) connections that link processors within and between cortical regions. The effects of CF connections are distinguished from those mediating receptive field (RF) input; it is shown how CFs (...) can guide both learning and processing without becoming confused with the transmission of RF information. Simulations explore the capabilities of networks built from local processors with both RF and CF connections. Physiological evidence for synchronization, CFs, and plasticity of the RF and CF connections is described. Coordination via CFs is related to perceptual grouping, the effects of context on contrast sensitivity, amblyopia, implicit influences of color in achromotopsia, object and word perception, and the discovery of distal environmental variables and their interactions through self-organization. Cortical computation could thus involve the flexible evaluation of relations between input signals by locally specialized but adaptive processors whose activity is dynamically associated and coordinated within and between regions through specialized contextual connections. Key Words: cell assemblies; cerebral cortex; context; coordination; dynamic binding; epistemology; functional specialization; learning; neural coding; neural computation; neuropsychology; object recognition; perception; reading; self-organization; synaptic plasticity; synchronization. (shrink)

The additional data, perspectives, questions, and criticisms contributed by the commentaries strengthen our view that local cortical processors coordinate their activity with the context in which it occurs using contextual fields and synchronized population codes. We therefore predict that whereas the specialization of function has been the keynote of this century the coordination of function will be the keynote of the next.

In attempts to formulate a computational understanding of brain function, one of the fundamental concerns is the data structure by which the brain represents information. For many decades, a conceptual framework has dominated the thinking of both brain modelers and neurobiologists. That framework is referred to here as "classical neural networks." It is well supported by experimental data, although it may be incomplete. A characterization of this framework will be offered in the next section. Difficulties in modeling important functional aspects (...) of the brain on the basis of classical neural networks alone have led to the recognition that another, general mechanism must be invoked to explain brain function. That mechanism I call " binding." Binding by neural signal synchrony had been mentioned several times in the liter ature before it was fully formulated as a general phenomenon. Although experimental evidence for neural syn chrony was soon found, the idea was largely ignored for many years. Only recently has it become a topic of animated discussion. In what follows, I will summarize the nature and the roots of the idea of binding, especially of temporal binding, and will discuss some of the objec tions raised against it. (shrink)

Recent experiments have shown that the amplitudes of cortical gamma band oscillatory activities that occur during anesthesia are often greater than amplitudes of similar activities that occur without anesthesia. This result is apparently at odds with the hypothesis that synchronized oscillatory activities constitute the neural correlate of consciousness. We argue that while synchronization and oscillatory patterning are necessary conditions for consciousness, they are not sufficient. Based on the results of a binocular rivalry study of Fries et al. (1997), we propose (...) that the degrees of oscillatory strength and synchronization of neuronal activities determine the degree of awareness those activities produce. On the other hand, the overal firing rates of neurons in cortical sensory areas are not correlated with the degree of awareness the activities of those neurons produce. The results of the experiment of Fries et al. (1997) appear to conflict with the results of another binocular rivalry experiment, in which monkeys were trained to pull a lever in order to report which stimulus object was being perceived (Leopold & Logothetis, 1996). In the latter experiment, it was demonstrated that the firing rates of neurons in striate cortex did not change during perceptual alterations, while 90% of neurons in inferior and superior temporal cortices changed their firing rate when the perceived image changed. This result led to the conclusion that activities in temporal cortex are correlated with visual awareness, but those in striate cortex are not. We argue that activities in temporal cortex contribute little, if anything, to perceptual awareness, and that their primary function is computational. Thus the correlation between the firing rates of neurons in these areas and the responses of the monkeys is due to the recognition of a particular stimulus object, which in turn is due to the computations made there. (shrink)

Many current neurophysiological, psychophysical, and psychological approaches to vision rest on the idea that when we see, the brain produces an internal representation of the world. The activation of this internal representation is assumed to give rise to the experience of seeing. The problem with this kind of approach is that it leaves unexplained how the existence of such a detailed internal representation might produce visual consciousness. An alternative proposal is made here. We propose that seeing is a way of (...) acting. It is a particular way of exploring the environment. Activity in internal representations does not generate the experience of seeing. The out- side world serves as its own, external, representation. The experience of seeing occurs when the organism masters what we call the gov- erning laws of sensorimotor contingency. The advantage of this approach is that it provides a natural and principled way of accounting for visual consciousness, and for the differences in the perceived quality of sensory experience in the different sensory modalities. Sev- eral lines of empirical evidence are brought forward in support of the theory, in particular: evidence from experiments in sensorimotor adaptation, visual “filling in,” visual stability despite eye movements, change blindness, sensory substitution, and color perception. (shrink)

A central issue in philosophy and neuroscience is the problem of unified visual consciousness. This problem has arisen because we now know that an object's stimulus features (e.g., its color, texture, shape, etc.) generate activity in separate areas of the visual cortex (Felleman & Van Essen, 1991). For example, recent evidence indicates that there are very few, if any, neural connections between specific visual areas, such as those that correlate with color and motion (Bartels & Zeki, 2006; Zeki, 2003). So (...) how do unified objects arise in visual consciousness? Some neuroscientists propose that neural synchrony is the mechanism that binds an object's features into a unity (e.g., see Crick, 1994; Crick & Koch, 1990; Engel, 2003; Roelfsema, 1998; Singer, 1996; von der Malsburg, 1996, 1999). I argue, on both empirical and philosophical grounds, that neural synchrony fails to explain the unity of visual consciousness. (shrink)

Data production in experimental sciences depends on localised experimental systems, but the epistemic properties of data transcend the contingencies of the processes that produce them. Philosophers often believe that experimental systems instantiate but do not produce the epistemic properties of data. In this paper, we argue that experimental systems' local functioning entails intrinsic capacities to produce the epistemic properties of data. We develop this idea by applying Derrida's model of arche-writing to study a case of theory-oriented experimental practice. Derrida's model (...) relativises or dissolves the conceptual distinction between the moment of data production and a subsequent moment of data dissemination. It thus has consequences for understanding both data production (despite being intrinsically local, data production a priori generates transferrable and modellable information) and data dissemination (when modelling information, researchers needs to refer this information to the context of its production). We study a case of data production in a non-exploratory experimental system designed to test a pre-existing hypothesis in visual neuroscience. A case of theory-oriented experimental practice should allow us to identify the autonomous functioning of experimental systems in data production more clearly, insofar as it allows us to study the limits of pre-existing theory in the activities of these systems. We suggest that pre-existing concepts, hypotheses and theories condition the relevance but not the production of experimental data. (shrink)

The present empirical study investigates limitations of human visual working memory. The experiments of the present work involve the experimental paradigm of change detection using simple geometrical objects in the form of rectangles of different colour, length, and orientation. It can be shown, that a limited performance in the temporary storage of visual information has multiple sources. Limitations of VWM can be attributed to a limited capacity or a limited duration, but also to limitations in retrieval, which so far has (...) found only little attention. Key findings of the present study show, that a capacity limitation cannot be described by a simple and generally valid size of the store. It is in fact generally acknowledged that the capacity limitation of VWM is object-based, which means that the capacity can roughly be determined by the number of visual objects. However, it could be shown that the complexity of the objects has an influence on memory performance: Experimental evidence shows, e.g., that memory performance decreases, when an object is characterized not only by one feature, but by a number of features. The results are explained by increased storage demands for the binding of the features. Other key findings of the present study relate to the process of retrieval of information from VWM. For example, an asymmetric performance pattern could be observed: In a change detection task a memory performance was observed that corresponds to a capacity of 3 - 4 objects. In contrast a drastic decrease of performance corresponding to a capacity of only 1 object was observed, when the task was to find a matching item among changed distractors. These results lead to the idea of a change signal, by which the empirical data can be explained. The change signal is elicited by a local mismatch between the information stored in VSTM and perceptual online information. The retrieval process is efficient, when the change signal can be used in the memory task. However, retrieval is extremely limited, when in the presence of multiple changes a less efficient strategy has to be applied. In the course of the present study, moreover, it became evident that there are various links between VWM processes and visual attention. Visual attention is probably crucial for feature binding in VWM. In retrieval the change signal probably involves mechanisms of visual attention. The present study could, therefore, contribute to a clarification of the relation between VWM and visual attention. (shrink)

By characterizing the function of the ventral and dorsal visual streams as, respectively, vision-for-perception and vision-for-action, Milner and Goodale have brought some action onto the perceptual scene. However, with the distinction of the ventral "what" system and the dorsal "how" system, comes a dilemma: How is the operation of the two systems united toward common goals? This is an example of a binding problem. We propose that for binding these two systems, no mechanism needs to exist in the brain to (...) bring ventral and dorsal representations together. Coherent behavior may be accomplished by focusing the two streams upon the same external object through a strategy of spatial selection, using either the fovea or selective attention. This strategy exploits the simple fact that two objects cannot occupy the same place at the same time. Other kinds of binding, like that involving the perceptual binding of the elements of a scene into coherent perceptual units, may be accomplished by exploiting other regularities of the environment, such as the likelihood that two simultaneous sounds were caused by a common event. From an evolutionary perspective, the most effective way to cope with the distant environment is to use different but complementary sensors, both contributing to aspects of identification and action guidance. For example, audition plays a role both in perceptual analysis and in action guidance, suggesting the possibility of segregated processing of auditory information. Thus, the functional distinction between a "what" system and a "how" system may not be limited to the visual modality, but may be a fundamental distinction for behavioral control in general. (shrink)

The binding problem is fundamental to visual perception. It is the problem of associating an object's visual properties with itself and not with some other object. The problem is made particular difficult because different properties of an object, such as its color, shape, size, and motion, are often processed independently, sometimes in different cortical areas. The results of these separate analyses have to be combined before the object can be seen as a single coherent entity as opposed to a collection (...) of unconnected features. Visual bindings are typically initiated and updated in a serial fashion, one object at a time. Here, we show that one type of binding, location-identity bindings, can be updated in parallel. We do this by using two complementary techniques, the simultaneous-sequential paradigm and systems factorial technology. These techniques make different assumptions and rely on different behavioral measures, yet both came to the same conclusion. (shrink)

Auditory scene analysis is critical for complex auditory processing. We study auditory segregation from the neural network perspective, and develop a framework for primitive auditory scene analysis. The architecture is a laterally coupled two‐dimensional network of relaxation oscillators with a global inhibitor. One dimension represents time and another one represents frequency. We show that this architecture, plus systematic delay lines, can in real time group auditory features into a stream by phase synchrony and segregate different streams by desynchronization. The network (...) demonstrates a set of psychological phenomena regarding primitive auditory scene analysis, including dependency on frequency proximity and the rate of presentation, sequential capturing, and competition among different perceptual organizations. We offer a neurocomputational theory—shifting synchronization theory—for explaining how auditory segregation might be achieved in the brain, and the psychological phenomenon of stream segregation. Possible extensions of the model are discussed. (shrink)

A key question in studying consciousness is how neural operations in the brain can identify streams of sensory input as belonging to distinct modalities, which contributes to the representation of qualitatively different experiences. The basis for identification of modalities is proposed to be constituted by self-organized comparative operations across a network of unimodal and multimodal sensory areas. However, such network interactions alone cannot answer the question how sensory feature detectors collectively account for an integrated, yet phenomenally differentiated experiential content. This (...) problem turns out to be different from, although related to, the binding problem. It is proposed that the neural correlate of an enriched, multimodal experience is constituted by the attractor state of a dynamic associative network. Within this network, unimodal and multimodal sensory maps continuously interact to influence each other’s attractor state, so that a feature change in one modality results in a fast re-coding of feature information in another modality. In this scheme, feature detection is coded by firing-rate, whereas firing phase codes relational aspects. (shrink)

What is Computational Intelligence (CI) and what are its relations with Artificial Intelligence (AI)? A brief survey of the scope of CI journals and books with ``computational intelligence'' in their title shows that at present it is an umbrella for three core technologies (neural, fuzzy and evolutionary), their applications, and selected fashionable pattern recognition methods. At present CI has no comprehensive foundations and is more a bag of tricks than a solid branch of science. The change of focus from methods (...) to challenging problems is advocated, with CI defined as a part of computer and engineering sciences devoted to solution of non-algoritmizable problems. In this view AI is a part of CI focused on problems related to higher cognitive functions, while the rest of the CI community works on problems related to perception and control, or lower cognitive functions. Grand challenges on both sides of this spectrum are addressed. (shrink)

For scene analysis, it is important to ask the question of how synchronized population codes – the basic representation employed in the target article – are generated. Recent computational advances have resolved the critical challenges of rapid synchronization with local coupling and rapid desynchronization. The synchronized codes make real contributions to tackling the problem of scene analysis.

The discussion begins with a familiar and defensible characterization of the eureka moment, according to which it is the unexpected product of separate and often seemingly incompatible perspectives. The principal aim of the discussion is to explain how, so characterized, vision-related eureka moments can occur. To fulfill this aim, the discussion employs a notion of crosstalk, in which cognitive interference slightly increases as a result of the creative thinker's considerable, albeit only partly successful, pre-eureka cognitive effort. Such crosstalk, it is (...) suggested, is likely to occur when top-down visual imaging repeatedly stimulates pyramidal cells closely apposed to others that, although simultaneously active, are part of bottom-up visual perception that is initially cognitively unrelated to such imaging. It is further suggested that local circuitry, in the form of inhibitory interneurons, can synchronize cells associated with these initially separate processes, thus causing subsequent perceptual patterns to be subtly modified by pre-eureka problem-solving imagery. This modification, it is claimed, may help explain the unexpected shift in visual perception that accompanies the creative thinker's eureka moment, a shift that can improve the thinker's subsequent understanding of the relevance of information to a problem's solution. (shrink)

Libet discovered that a substantial duration (> 0.5-1.0 s) of direct electrical stimulation of the surface of the somatosensory cortex at threshold currents is required before human subjects can report that a conscious somatosensory experience had occurred. Using a reaction time method we confirm that a similarly long stimulation duration at threshold currents is required for activation of elementary visual experiences (phosphenes) in human subjects following stimulation of the surface of the striate cortex. However, the reaction times for the subject (...) to respond to the cessation of the visual experience after the end of electrical stimulation could be as brief as 225-242 ms. We also carried out extensive studies in cats under a variety of anesthetic conditions using the same electrodes and parameters of stimulation employed in the human studies to study the patterns of neuronal activity beneath the stimulating surface electrode. Whereas sufficiently strong currents can activate neurons within milliseconds, stimulating currents close to threshold activate sustained neural activity only after at least 350-500 ms. When currents are close to threshold, some neurons are inhibited for several hundreds of millisecond before the balance between inhibition and excitation shifts towards excitation. These results suggest that the prolonged latencies, i.e., latencies beyond 200-250 ms, for the emergence of conscious experience following direct cortical stimulation result from a delay in the sustained activation of underlying cortical neurons at threshold currents rather than being due to any unusually long duration in central processing time. Intracellular records from cortical neurological cells during repetitive electrical stimulation of the surface of the feline striate cortex demonstrate that such stimulation induces a profound depolarizing shift in membrane potential that may persist after each stimulus train. Such a depolarization is evidence that extracellular K+ concentrations have increased during electrical stimulation. Such an increase in extracellular K+ progressively increases cortical excitability until the threshold for sustained activation of cortical neurons is reached and then exceeded. Consequently, the long latency for threshold activation of cortical neurons depends upon a dynamically increasing cortical facilatory process that begins hundreds of milliseconds before there is sustained activation of such neurons. In some cases, this facilatory process must overcome an initial stimulus-induced inhibition before neuronal firing commences. (shrink)