The confluence of creativity in music performance finds itself in performance practices and cultural motifs, the communication of the human body along with the instrument it interacts with, and individual performers’ perceptual, motor, and cognitive abilities that contribute to varied musical interpretations of the same piece or melodic line. The musical and artistic execution of a player, as well as the product of this phenomena can become determinant causes in a creative mental state. With advances in neurocognitive measures, the state (...) of one’s artistic intuition and execution has been a growing interest in understanding the creative thought process of human behavior, particularly in improvising artists. This article discusses the implementation on the concurrence of spontaneous (Type-1) and controlled (Type-2) processing modes that may be apparent in the perception of non-improvising artists on how melodic lines are perceived in music performance. Elucidating the cortical-subcortical activity in the dual-process model may extend to non-improvising musicians explored in the paradigm of neural correlates. These interactions may open new possibilities for expanding the repertoire of executive functions, creativity, and the coordinated activity of cortical-subcortical regions that regulate the free flow of artistic ideas and expressive spontaneity in future neuromusical research. (shrink)

The ontology of social objects and facts remains a field of continued controversy. This situation complicates the life of social scientists who seek to make predictive models of social phenomena. For the purposes of modelling a social phenomenon, we would like to avoid having to make any controversial ontological commitments. The overwhelming majority of models in the social sciences, including statistical models, are built upon ontological assumptions that can be questioned. Recently, however, artificial neural networks have made their (...) way into the social sciences, raising the question whether they can avoid controversial ontological assumptions. ANNs are largely distinguished from other statistical and machine learning techniques by being a representation-learning technique. That is, researchers can let the neural networks select which features of the data to use for internal representation instead of imposing their preconceptions. On this basis, I argue that neural networks can avoid ontological assumptions to a greater degree than common statistical models in the social sciences. I then go on, however, to establish that ANNs are not ontologically innocent either. The use of ANNs in the social sciences introduces ontological assumptions typically in at least two ways, via the input and via the architecture. (shrink)

Can findings from psychology and cognitive neuroscience about the neural mechanisms involved in decision-making can tell us anything useful about the commonly-understood mental phenomenon of making voluntary choices? Two philosophical objections are considered. First, that the neural data is subpersonal, and so cannot enter into illuminating explanations of personal level phenomena like voluntary action. Secondly, that mental properties are multiply realized in the brain in such a way as to make them insusceptible to neuroscientific study. The paper (...) argues that both objections would be weakened by the discovery of empirical generalisations connecting subpersonal properties with the personal level. It gives three case studies that furnish evidence to that effect. It argues that the existence of such interrelations are consistent with a plausible construal of the personal-subpersonal distinction. Furthermore, there is no reason to suppose that the notion subpersonal representation relied on in cognitive neuroscience illicitly imports personal-level phenomena like consciousness or normativity, or is otherwise explanatorily problematic. (shrink)

In the field theories in physics, any particular region of the presumed space-time continuum and all interactions between elementary objects therein can be objectively measured and/or accounted for mathematically. Since this does not apply to any of thefield theories, or any other neural theory, of consciousness, their explanatory power is limited. As discussed in detail herein, the matter is complicated further by the facts than any scientifically operational definition of consciousness is inevitably partial, and that the phenomenon has (...) no spatial dimensionality. Under the light of insights from research on meditation and expanded consciousness, chronic pain syndrome, healthy aging, and eudaimonic well being, we may conceive consciousness as a source of potential energy that has no clearly defined spatial dimensionality, but can produce significant changes in others and in the world, observable in terms of changes in time. It is argued that consciousness may have evolved to enable the human species to generate such changes in order to cope with unprecedented and/or unpredictable adversity. Such coping could, ultimately, include the conscious planning of our own extinction when survival on the planet is no longer an acceptable option. (shrink)

Can information theory be used to understand neural signaling? Yes, but assumptions have to be made about the nature of that signaling. The traditional view is that the individual neural spike is an all-or-none phenomenon, which allows neural spikes to be viewed as discrete, binary pulses, similar in kind to the signals in digital computers. Under this assumption, the tools of information theory can be used to derive results about the properties of neural signals. However, (...) new results from neuroscience demonstrate that the precise shape of the individual spike can be functionally significant, thus violating the assumption that spikes can always be treated as a binary pulse. Instead, spikes must sometimes be viewed as a continuous signal. Fortunately, information-theoretic tools exist for the study of continuous signals; unfortunately, their use in the continuous domain is very different from their use in the discrete domain, and not always well understood. Researchers interested in making precise claims about the nature of the information used, stored, and processed in neural systems must pay careful attention to these differences. (shrink)

Tactile distance perception is believed to require that immediate afferent signals be referenced to a stored representation of body size and shape (the body model). For this ability, recent studies have reported that the stored body representations involved are highly distorted, at least in the case of the hand, with the hand dorsum represented as wider and squatter than it actually is. Here, we aim to define the neural basis of this phenomenon. In a behavioural experiment participants estimated (...) the distance between touches on two points by adjusting the length of a visually-presented line on the screen. The technique of multidensional scaling (MDS) was used to reconstruct a perceptual map of tactile space. Analysis of spatial distortion using Procrustes alignment showed that maps were stretched in the mediolateral hand axis. In order to determine the neural correlates of these body distortions, we performed an fMRI study. For each participant, we used a searchlight pattern classifier with Euclidean distance on pre-defined regions of interests (ROIs). In order to relate the representations between the different points and to computational models, we compare response-pattern dissimilarity matrices in these ROIs. Similar to the behavioural experiment, we used MDS to reconstruct maps of the neural representation of tactile space using the values from the dissimilarities matrices. We were able to reconstruct the perceptual map of tactile space in the contralateral primary somatosensory and motor cortices. This suggests that these areas are critical to generate the tactile representations of the dorsum of the hand. (shrink)

Byrne & Russon suggest that there are two kinds of imitation learning – action level and program level – and that the latter is critical for great apes' learning. I have interpreted this phenomenon from the standpoint of clinical neuropsychology and conjecture that action-level imitation might be related to parietal lobe function and program-level imitation might be related to frontal lobe function.

Although complex hallucinations are extremely vivid, painful symptoms in schizophrenia, little is known about the underlying mechanisms of multisensory integration in such a phenomenon. We investigated the neural basis of these altered states of consciousness in a patient with schizophrenia, by combining state of the art neuroscientific exploratory methods like functional MRI, diffusion tensor imaging, cortical thickness analysis, electrical source reconstruction and trans-cranial magnetic stimulation. The results shed light on the functional architecture of the hallucinatory processes, in which (...) unimodal information from different modalities is strongly functionally connected to higher-order integrative areas. (shrink)

Mood in humans is a complex phenomenon that integrates emotion , cognition, perception, ideation, and action in a coherent manner. In bipolar disorder extremes of mood occur outside the normal range, in which all the above functions are coherently affected. Mood is controlled by a series of separate but interactive brain circuits that involve much of the brain, but particularly the limbic system. The question addressed in this paper is whether the coordination of all these separate systems into one (...) coherent functional mood is mediated by non-linear dynamics acting between these systems as equal participants; or whether it is affected by a single master regulator controlling the others. The possible roles, as master regulators, of non-linear dynamically linked populations of neurons, and of the C1–C3 adrenergic nuclei in the medulla is discussed. (shrink)

Recent developments in psychology and neuroscience suggest away to link the mental phenomenon of visual awareness with specific neural processes. Here, it is argued that the feed-forward activation of cells in any area of the brain is not sufficient to generate awareness, but that recurrent processing, mediated by horizontal and feedback connections is necessary. In linking awareness with its neural mechanisms it is furthermore important to dissociate phenomenal awareness from visual attention or decision processes.

We find the theory of neural reuse to be highly plausible, and suggest that human individual differences provide an additional line of argument in its favor, focusing on the well-replicated finding of in which individual differences are highly correlated across domains. We also suggest that the theory of neural reuse may be an important contributor to the phenomenon of positive manifold itself.

Inattentional blindness is the failure to perceive salient stimuli presented at unattended locations. Whereas the behavioral manifestation of inattentional blindness has been investigated, the neural basis of this phenomenon has remained elusive. In the current study, event-related fMRI was used to identify the neural substrates associated with inattentional blindness. During central fixation, participants named colored digits presented at a peripheral location. On a subset of trials, an unexpected checkerboard circle was presented at the same eccentricity along with (...) the colored digits . Neural activity during inattentional blindness was observed in the prefrontal cortex. Together with previous findings, these results call into question the widespread view that activity in the prefrontal cortex reflects conscious processing. (shrink)

Inhibition of return refers to the phenomenon that a person is slower to respond to targets at a previously cued location. The present study aimed to explore whether target-reward association is subject to IOR, using event-related potentials to explore the underlying neural mechanism. Each participant performed a localization task and a color discrimination task in an exogenous cueing paradigm, with the targets presented in colors previously associated with high- or low-reward probability. The results of both tasks revealed that (...) the N1, Nd, and P3 components exhibited differential amplitudes between cued and uncued trials under low reward, with the N1 and Nd amplitudes being enhanced for uncued trials compared to cued trials, and the P3 amplitude being enhanced for cued trials vs. uncued trials. Under high reward, however, no difference was found between the amplitudes on cued and uncued trials for any of the components. These findings demonstrate that targets that were previously associated with high reward can be resistant to IOR and the current results enrich the evidence for interactions between reward-association and attentional orientation in the cueing paradigm. (shrink)

Delay discounting is a common phenomenon in daily life, which refers to the subjective value of a future reward decreasing as a function of time. Previous studies have identified several cortical regions involved in delay discounting, but the neural network constructed by the cortical regions of delay discounting is less clear. In this study, we employed resting-state functional magnetic resonance imaging (RS-fMRI) to measure the spontaneous neural activity in a large sample of healthy young adults and used (...) the Monetary Choice Questionnaire to directly measure participants’ level of delay discounting. To identify the neural network of delay discounting at rest, we used an individual difference approach to explore brain regions whose spontaneous activities were related to delay discounting across the whole brain. Then, these brain regions served as seeds to identify the neural network of delay discounting. We found that the fractional amplitude of low-frequency fluctuations (fALFF) of the left insula were positively correlated to delay discounting. More importantly, its connectivity to the anterior cingulate cortex was read out for participants’ behavioral performance in the task of delay discounting. In short, our study provides empirical evidence that insula-anterior cingulate cortex connectivity may serve as a part of the neural network for delay discounting. (shrink)

After people learn to sort objects into categories they see them differently. Members of the same category look more alike and members of different categories look more different. This phenomenon of within-category compression and between-category separation in similarity space is called categorical perception (CP). It is exhibited by human subjects, animals and neural net models. In backpropagation nets trained first to auto-associate 12 stimuli varying along a onedimensional continuum and then to sort them into 3 categories, CP arises (...) as a natural side-effect because of four factors: (1) Maximal interstimulus separation in hidden-unit space during autoassociation learning, (2) movement toward linear separability during categorization learning, (3) inverse-distance repulsive force exerted by the between-category boundary, and (4) the modulating effects of input iconicity, especially in interpolating CP to untrained regions of the continuum. Once similarity space has been "warped" in this way, the compressed and separated "chunks" have symbolic labels which could then be combined into symbol strings that constitute propositions about objects. The meanings of such symbolic representations would be "grounded" in the system's capacity to pick out from their sensory projections the object categories that the propositions were about. (shrink)

An adaptive fractional-order nonsingular terminal sliding mode controller for a microgyroscope is presented with uncertainties and external disturbances using a fuzzy neural network compensator based on a backstepping technique. First, the dynamic of the microgyroscope is transformed into an analogical cascade system to guarantee the application of a backstepping design. Then, a fractional-order nonsingular terminal sliding mode surface is designed which provides an additional degree of freedom, higher precision, and finite convergence without a singularity problem. The proposed control scheme (...) requires no prior knowledge of the unknown dynamics of the microgyroscope system since the fuzzy neural network is utilized to approximate the upper bound of the lumped uncertainties and adaptive algorithms are derived to allow online adjustment of the unknown system parameters. The chattering phenomenon can be reduced simultaneously by the fuzzy neural network compensator. The stability and finite time convergence of the system can be established by the Lyapunov stability theorem. Finally, simulation results verify the effectiveness of the proposed controller and the comparison of root mean square error between different fractional orders and integer order is given to signify the high precision tracking performance of the proposed control scheme. (shrink)

In this paper we aim to show that phenomenal consciousness is realized by a particular level of brain operational organization and that understanding human consciousness requires a description of the laws of the immediately underlying neural collective phenomena, the nested hierarchy of electromagnetic fields of brain activity – operational architectonics. We argue that the subjective mental reality and the objective neurobiological reality, although seemingly worlds apart, are intimately connected along a unified metastable continuum and are both guided by the (...) universal laws of the physical world such as criticality, self-organization and emergence. (shrink)

It is generally accepted that, in the cognitive and neural sciences, there are both computational and mechanistic explanations. We ask how computational explanations can integrate into the mechanistic hierarchy. The problem stems from the fact that implementation and mechanistic relations have different forms. The implementation relation, from the states of an abstract computational system to the physical, implementing states is a homomorphism mapping relation. The mechanistic relation, however, is that of part/whole; the explaining features in a mechanistic explanation are (...) the components of the explanandum phenomenon and their causal organization. Moreover, each component in one level of mechanism is constituted and explained by components of an underlying level of mechanism. Hence, it seems, computational variables and functions cannot be mechanistically explained by the medium-dependent states and properties that implement them. How then, do the computational and the implementational integrate to create the mechanistic hierarchy? After explicating the general problem, we further demonstrate it through a concrete example, of reinforcement learning, in the cognitive and neural sciences. We then examine two possible solutions. On one solution, the mechanistic hierarchy embeds at the same levels computational and implementational properties. This picture fits with the view that computational explanations are mechanistic sketches. On the other solution, there are two separate hierarchies, one computational and another implementational, which are related by the implementation relation. This picture fits with the view that computational explanations are functional and autonomous explanations. It is less clear how these solutions fit with the view that computational explanations are full-fledged mechanistic explanations. Finally, we argue that both pictures are consistent with the reinforcement learning example, but that scientific practice does not align with the view that computational models are merely mechanistic sketches. (shrink)

Spatial neglect is a disorder of space-related behaviour. It is characterized by failure to explore the side of space contralateral to a brain lesion, or to react or respond to stimuli or subjects located on this side. Research on spatial neglect and related disorders has developed rapidly inrecent years. These advances have been made as a result of neuropsychological studies of patients with brain damage, behavioural studies of animal models, as well as through functional neurophysiological experiments and functional neuroimaging.The Cognitive (...) and Neural Bases of Spatial Neglect provides an overview of this wide-ranging field of scientific endeavour, providing a cohesive synthesis of the most recent observations and results. As well as being a fascinating clinical phenomenon, the study of spatial neglect helps us tounderstand normal mechanisms of directing and maintaining spatial attention and is relevant to the contemporary search for the cerebral correlates of conscious experience, voluntary action and the nature of personal identity itself.The book is divided into seven sections covering the anatomical and neurophysiological bases of the disorder, frameworks of neglect, perceptual and motor factors, the relation to attention, the cognitive processes involved, and strategies for rehabilitation.Chapters have been written by a team of the leading international experts in this field.This will be essential reading for neuropsychologists, neurologists, neurophysiologists, cognitive neuroscientists and psychologists. (shrink)

Current cognitive science models of perception and action assume that the objects that we move toward and perceive are represented as determinate in our experience of them. A proper phenomenology of perception and action, however, shows that we experience objects indeterminately when we are perceiving them or moving toward them. This indeterminacy, as it relates to simple movement and perception, is captured in the proposed phenomenologically based recurrent network models of brain function. These models provide a possible foundation from which (...) predicative structures may arise as an emergent phenomenon without the positing of a representing subject. These models go some way in addressing the dual constraints of phenomenological accuracy and neurophysiological plausibility that ought to guide all projects devoted to discovering the physical basis of human experience. (shrink)

The sense of agency is a central aspect of human self-consciousness and refers to the experience of oneself as the agent of one’s own actions. Several different cognitive theories on the sense of agency have been proposed implying divergent empirical approaches and results, especially with respect to neural correlates. A multifactorial and multilevel model of the sense of agency may provide the most constructive framework for integrating divergent theories and findings, meeting the complex nature of this intriguing phenomenon.

Due to the inevitable delay phenomenon in the process of signal conversion and transmission, time delay is bound to occur between neurons. Therefore, it is necessary to introduce the concept of time delay into the membrane computing models. Spiking neural P systems, as an attractive type of neural-like P systems in membrane computing, are widely followed. Inspired by the phenomenon of time delay, in our work, a new variant of spiking neural P systems called delayed (...) spiking neural P systems is proposed. Compared with normal spiking neural P systems, the proposed systems achieve time control by setting the schedule on spiking rules and forgetting rules, and the schedule is also used to realize the system delay. A schedule indicates the time difference between receiving and outputting spikes, and it also makes the system work in a certain time, which means that a rule can only be used within a specified time range. We specify that each rule is performed only in the continuous schedule, during which the neuron is locked and cannot send or receive spikes. If the neuron is not available at a given time, it will not receive or send spikes due to the lack of a schedule for this period of time. Moreover, the universality of DSN P systems in both generating and accepting modes is proved. And a universal DSN P system having 81 neurons for computing functions is also proved. (shrink)

With a focus in the financial market, stock market dynamics forecasting has received much attention. Predicting stock market fluctuations is usually challenging due to the nonlinear and nonstationary time series of stock prices. The Elman recurrent network is renowned for its capability of dealing with dynamic information, which has made it a successful application to predicting. We developed a hybrid approach which combined Elman recurrent network with factorization machine technique, i.e., the FM-Elman neural network, to predict stock market volatility. (...) In this paper, the Standard & Poor’s 500 Composite Stock Price index, the Dow Jones industrial average index, the Shanghai Stock Exchange Composite index, and the Shenzhen Securities Component Index were used to demonstrate the validity of our proposed FM-Elman model in time-series prediction. The results were compared with predictions obtained from the other two models which are basic BP neural network and the Elman neural network. Some experiments showed that the FM-Elman model outperforms others through different accuracy measures. Furthermore, the effects of volatility degree on prediction performance from different stock indexes were investigated. An interesting phenomenon had been found through some numerical experiments on the effects of different user-specified dimensions on the proposed FM-Elman neural network. (shrink)

Progress in neuroscience has left a central question of psychism unanswered: what is consciousness? Modeling the psyche from a computational perspective has helped to develop cognitive neurosciences, but it has also shown their limits, of which the definition, description and functioning of consciousness remain essential. From Rene Descartes, who tackled the issue of psychism as the brain-mind dualism, to Chambers, who defined qualia as the tough, difficult problem of research in neuroscience, many hypotheses and theories have been issued to encompass (...) the phenomenon of consciousness. Neuroscience specialists, such as Giulio Tononi or David Eagleman, consider consciousness as a phenomenon of emergence of all processes that take place in the brain. This hypothesis has the advantage of being supported by progress made in the study of complex systems in which the issue of emergence can be mathematically formalized and analyzed by physical-mathematical models. The current tendency to associate neural networks within the broad scope of network science also allows for a physical-mathematical formalization of phenomenology in neural networks and the construction of information-symbolic models. The extrapolation of emergence at the level of physical systems, biological systems and psychic systems can bring new models that can also be applied to the concept of consciousness. The meaning and significance that seem to structure the nature of consciousness is found as direction of evolution and teleological finality, of integration in the whole system and in any complex system at all scales. Starting from the wave-corpuscle duality in quantum physics, we can propose a model for structuring reality, based on the emergence of systems that contribute to the integration and coherence of the entire reality. Physical-mathematical models based mainly on topology can provide a mathematical formalization path, and the paradigm of information could allow the development of a pattern of emergence, that is common to all systems, including the psychic system, the difference being given only by the degree of information complexity. Thus, the mind-brain duality, which has been dominating the representation on psychism for a few centuries, could be solved by an informational approach, describing the connection between object and subject, reality and human consciousness, between mind and brain, thus unifying the perspective on natural sciences and humanities. (shrink)

The process of dehumanization, or thinking of others as less than human, is a phenomenon with significant societal implications. According to Haslam's model, two concepts of humanness derive from comparing humans with either animals or machines: individuals may be dehumanized by likening them to either animals or machines, or humanized by emphasizing differences from animals or machines. Recent work in cognitive neuroscience emphasizes understanding cognitive processes in terms of interactions between distributed cortical networks. It has been found that reasoning (...) about internal mental states is associated with activation of the default mode network and deactivation of the task positive network ; whereas reasoning about mechanical processes produces the opposite pattern. We conducted two neuroimaging studies. The first examined the neural bases of dehumanization and its relation to these two brain networks, using images and voice-over social narratives which either implicitly contrasted or implicitly likened humans to either animals or machines. The second study addressed a discrepancy between findings from the first study and prior work on the neural correlates of dehumanization: using a design similar to prior work we examined neural responses to pictures of humans, animals and machines, presented without any social context. In both studies, human and humanizing conditions were associated with relatively high activity in the DMN and relatively low activity in the TPN. However, the non-human and dehumanizing conditions deviated in different ways: they demonstrated more marked changes either in the DMN or in the TPN. Notably, differences between the animal dehumanizing and humanizing conditions were most evident in regions associated with mechanistic reasoning, not in the mentalizing network. Conjunction analysis of contrasts from both paradigms revealed that only one region was consistently more active when participants saw human, a medial parietal region regarded as the central hub of the DMN. These findings provide a neural basis for Haslam's distinction between two types of dehumanization, and suggest that the DMN and TPN play opposing roles in creating a sense of moral concern. (shrink)

The typical empirical approach to studying consciousness holds that we can only observe the neural correlates of experiences, not the experiences themselves. In this paper we argue, in contrast, that experiences are concrete physical phenomena that can causally interact with other phenomena, including observers. Hence, experiences can be observed and scientifically modelled. We propose that the epistemic gap between an experience and a scientific model of its neural mechanisms stems from the fact that the model is merely a (...) theoretical construct based on observations, and distinct from the concrete phenomenon it models, namely the experience itself. In this sense, there is a gap between any natural phenomenon and its scientific model. On this approach, a neuroscientific theory of the constitutive mechanisms of an experience is literally a model of the subjective experience itself. We argue that this metatheoretical framework provides a solid basis for the empirical study of consciousness. (shrink)

The phenomenon of knowledge withholding is a vital issue that undermines knowledge sharing and innovation, hinders the development of offline and online organizations. Clarifying the relationship between influencing factors and knowledge withholding is significant to improve the phenomenon of knowledge withholding in offline and online organizations. Few types of research focus on the online virtual academic community and integrate the three factors of knowledge, individual, and environment to research knowledge withholding. To solve the limitation, this research is based (...) on sociology and psychology-related theories. The two dimensions of enabling and inhibition are divided into factors affecting knowledge withholding. An attempt is made to explore the path between the three types of factors influencing knowledge, individual and environment, and knowledge withholding. This study collected data from 616 users in China’s virtual academic community. It used a structural equation model combined with a cross-layer connected neural network to conduct an empirical analysis on the proposed hypothesis. The results found that: in the virtual academic community, knowledge power in the enabling dimension is the main reason for users to form knowledge psychological ownership, which affects users’ knowledge withholding. However, the effect of professional commitment on users’ knowledge psychological ownership is not significant. After SEM-ANN model fitting, the combined inhibitory effect of community privacy protection and community reciprocity on user knowledge withholding in the inhibition dimension is significantly improved. This research has a specific guiding significance for enhancing the knowledge withholding phenomenon of the virtual academic community and creating an excellent academic exchange atmosphere. (shrink)

The distinction between true belief and knowledge is one of the most fundamental in philosophy, and a remarkable effort has been dedicated to formulating the conditions on which true belief constitutes knowledge. For decades, much of this epistemological undertaking has been dominated by a single strategy, referred to here as the modal approach. Shared by many of the most widely influential constraints on knowledge, including the sensitivity, safety, and anti-luck/risk conditions, this approach rests on a key underlying assumption — the (...) modal profiles available to known and unknown beliefs are in some way asymmetrical. The first aim of this paper is to deconstruct this assumption, identifying its plausibility with the way in which epistemologists frequently conceptualize human perceptual systems as excluding certain varieties of close error under conditions conducive to knowledge acquisition. The second aim of this paper is to then argue that a neural phase phenomenon indicates that this conceptualization is quite likely mistaken. This argument builds on the previous introduction of this neural phase to the context of epistemology, expanding the use of neural phase cases beyond relatively narrow questions about epistemic luck to a much more expansive critique of the modal approach as a whole. (shrink)

How can the fine-grained phenomenology of conscious experience arise from neural processes in the brain? How does a set of action potentials (nerve impulses) become like the feeling of pain in one's experience? Contemporary neuroscience is teaching us that our mental states correlate with neural processes in the brain. However, although we know that experience arises from a physical basis, we don't have a good explanation of why and how it so arises. The problem of how physical processes (...) give rise to experience is called the 'hard problem' of consciousness and it is the contemporary manifestation of the mind-body problem. This book explains the key concepts that surround the issue as well as the nature of the hard problem and the several approaches to it. It gives a comprehensive treatment of the phenomenon incorporating its main metaphysical and epistemic aspects, as well as recent empirical findings, such as the phenomenon of blindsight, change blindness, visual-form agnosia and optic ataraxia, mirror recognition in other primates, split-brain cases and synaesthesia. (shrink)

Since Descartes “separation” of the Soul from the Body, we observe a complete confusion in their causal, functional, and semiotic relationships. However, in modern knowledge (about the informational activity of the human brain, the functional and causal properties of its neural networks, the functions of psychic phenomena during the processing of information in it, about the causal “ability” of information) it is time to put an end to this problem. Here, in order to explain what I am talking about, (...) I will use the notion of “information” (which had been unknown by Descartes) regarding the “dispute” between Mind & Body (the Physicality and the Mentality) for “the right” to be a more fundamental ontology of Reality. I will do this by introducing an “arbitrator” — the Objective Reality. This goal is achieved through the study of information activity of the human brain. In the process of this study, it turns out that the information activity of the brain in principle cannot be carried out without mental phenomena. That is, it turns out that the classical physical causality, which operates in the neural networks of the brain, is not able, by itself, without mental phenomena, to implement the information operations that the human brain actually performs. It also turns out that the functional inclusion of mental phenomena (at least, the phenomena of subjective evaluation and mental images) in the neurophysiologic (by and large, physical) activity of the brain explains the possibility and necessity of functional inclusion in this information processing the phenomenon of freedom of choice. After all, the processing information in the brain through mental phenomena allows more than one degree of freedom than it is “allowed” by any physical process. (shrink)

This paper concentrates on the event-triggered H ∞ filter design for the discrete-time Markovian jump neural networks under random missing measurements and cyber attacks. Considering that the controlled system and the filtering can exchange information over a shared communication network which is vulnerable to the cyber attacks and has limited bandwidth, the event-triggered mechanism is proposed to relieve the communication burden of data transmission. A variable conforming to Bernoulli distribution is exploited to describe the stochastic phenomenon since the (...) missing measurements occur with random probability. Furthermore, seeing that the communication networks are vulnerable to external malicious attacks, the transferred information via the shared communication network may be changed by the injected false information from the attackers. Based on the above consideration, sufficient conditions for the filtering error system to maintain asymptotically stable are provided with predefined H ∞ performance. In the end, three numerical examples are given to verify the proposed theoretical results. (shrink)

Lifelines supports the theme that behavioral development is a fluid, life-long phenomenon. In contrast, many emotional and cognitive traits are subject to strong genetic influence, and are highly stable over many years. The manner in which neuroplasticity and trait stability cooccur needs to be modeled. An outline of such a model is provided to promote discussion of this complex issue.

This book explains the key concepts that surround the issue as well as the nature of the hard problem and the several approaches to it. It gives a comprehensive treatment of the phenomenon, incorporating its main metaphysical and epistemic aspects as well as recent empirical findings, such as the phenomena of blindsight, change blindness, visual-form agnosia and optic ataxia, mirror recognition in other primates, split-brain cases, and visual extinction.

Resumen En este trabajo se realiza un análisis exploratorio sobre lo que se ha venido concibiendo como un nuevo campo del saber científico desde hace algunas décadas, nos referimos a la neuroteología. También se pretende entender hasta qué punto la filosofía naturalista contemporánea puede estar vinculada con la neuroteología -sobre todo cuando el naturalismo implica, en la mayoría de los casos, un reduccionismo que conduce al materialismo-, teniendo en conside ración que en las distintas áreas neurocientíficas tiene lugar un fisicalismo, (...) esto es, una reducción de las propiedades o procesos cognitivos a meros procesos cerebrales e interacciones neuronales, que, gracias a la tecnología, hoy pueden ser visualizados por distintos instrumentos y técnicas.In this work an exploratory analysis is carried out on what has been conceived as a new field of scientific knowledge for some decades, we refer to neurotheology. It is also intended to under- stand to what extent contemporary naturalistic philosophy can be linked to neurotheology - especially when naturalism implies, in most cases, a reductionism that leads to materialism -, taking into account that in the different neuroscientific areas it has instead a physicalism, that is, a reduction of cognitive properties or processes to mere brain processes and neural interactions, which, thanks to technology, can now be visualized by different instruments and techniques. (shrink)

Consciousness is a natural phenomenon, the object of a flourishing area of research in the natural sciences – research whose primary goal is to identify the neural correlates of consciousness. This raises the question: why is there need for a philosophy of consciousness? As we see things, the need for a philosophy of consciousness arises for two reasons. First, as a young and energetic science operating as yet under no guiding paradigm, the science of consciousness has been subject (...) to considerable confusion regarding its methodological, conceptual, and philosophical foundations, and it is philosophy’s mandate to address such confusion in an attempt to regiment scientific practice. Secondly, the identification of a neural feature that correlated perfectly with consciousness would still leave open a certain metaphysical question: is the relation between consciousness and the relevant neural feature merely correlation, or is that correlation indicative of a deeper, more intimate relation between the two? In this paper, we offer an opinionated overview of the philosophy of consciousness as it addresses these two dimensions of consciousness research. (shrink)

The thresholds of human observers detecting line targets improve significantly when the targets are presented in a spatial context of collinear inducing stimuli. This phenomenon is referred to as spatial facilitation, and may reflect the output of long-range interactions between cortical feature detectors. Spatial facilitation has thus far been observed with luminance-defined, achromatic stimuli on achromatic backgrounds. This study compares spatial facilitation with line targets and collinear, edge-like inducers defined by luminance contrast to spatial facilitation with targets and inducers (...) defined by color contrast. The results of a first experiment show that achromatic inducers facilitate the detection of achromatic targets on gray and colored backgrounds, but tend to suppress the detection of chromatic targets. Chromatic inducers facilitate the detection of chromatic targets on gray and colored backgrounds, but tend to suppress the detection of achromatic targets. Chromatic spatial facilitation appears to be strongest when inducers and background are isoluminant. The results of a second experiment show that spatial facilitation with chromatic targets and inducers requires a longer exposure duration of the inducers than spatial facilitation with achromatic targets and inducers, which is already fully effective at an inducer exposure of 30 ms only. The findings point towards two separate mechanisms for spatial facilitation with collinear form stimuli: one that operates in the domain of luminance, and one that operates in the domain of color contrast. These results are consistent with neural models of boundary and surface formation which suggest that achromatic and chromatic visual cues are represented on different cortical surface representations that are capable of selectively attracting attention. Multiple copies of these achromatic and chromatic surface representations exist corresponding to different ranges of perceived depth from an observer, and each can attract attention to itself. Color and contrast differences between inducing and test stimuli, and transient responses to inducing stimuli, can cause attention to shift across these surface representations in ways that sometimes enhance and sometimes interfere with target detection. (shrink)

In recent decades, investigation of brain injuries associated with amnesia allowed progress in the philosophy and science of memory, but it also paved the way for the hubris of assuming that memory is an exclusively neural phenomenon. Nonetheless, there are methodological and conceptual reasons preventing a reduction of the ecological and contextual phenomenon of memory to a neural phenomenon, since memory is the observed action of an individual before being the simple output of a brain (...) (or, at least, so we will argue), and there is no good reason to suppose that it is necessary to postulate a more basic reality to memory lying behind the mere individual actions. (shrink)

In a recent reply to our article, “What is Interpretability?,” Prasetya argues against our position that artificial neural networks are explainable. It is claimed that our indefeasibility thesis—that adding complexity to an explanation of a phenomenon does not make the phenomenon any less explainable—is false. More precisely, Prasetya argues that unificationist explanations are defeasible to increasing complexity, and thus, we may not be able to provide such explanations of highly complex AI models. The reply highlights an important (...) lacuna in our original paper, the omission of the unificationist account of explanation, and affords us the opportunity to respond. Here, we argue that artificial neural networks are explainable in a way that should satisfy unificationists and that interpretability methods present ways in which ML theories can achieve unification. (shrink)

Among psychologists and vision scientists,binocular rivalry has enjoyed sustainedinterest for decades dating back to the 19thcentury. In recent years, however, rivalry''saudience has expanded to includeneuroscientists who envision rivalry as a tool for exploring the neural concomitants ofconscious visual awareness and perceptualorganization. For rivalry''s potential to berealized, workers using this tool need toknow details of this fascinating phenomenon,and providing those details is the purpose ofthis article. After placing rivalry in ahistorical context, I summarize major findingsconcerning the spatial characteristics and (...) thetemporal dynamics of rivalry, discuss two majortheoretical accounts of rivalry ( eye vs stimulus rivalry) and speculate on possibleneural concomitants of binocular rivalry. (shrink)

The easy problems of consciousness are those that seem directly susceptible to the standard methods of cognitive science, whereby a phenomenon is explained in terms of computational or neural mechanisms. The hard problems are those that seem to resist those methods. The easy problems are easy precisely because they concern the explanation of cognitive abilities and functions. Once we have specified the neural or computational mechanism that performs the function of verbal report, for example, the bulk of (...) our work in explaining reportability is over. Baars theory of cognitive accessibility addresses many aspects of human cognition and shows promise as a theory of awareness, the functional correlate of conscious experience, but an explanation of experience itself is not on offer. The key is the conceptual point that the explanation of functions does not suffice for the explanation of experience. (shrink)

Artificial intelligence has historically been conceptualized in anthropomorphic terms. Some algorithms deploy biomimetic designs in a deliberate attempt to effect a sort of digital isomorphism of the human brain. Others leverage more general learning strategies that happen to coincide with popular theories of cognitive science and social epistemology. In this paper, I challenge the anthropomorphic credentials of the neural network algorithm, whose similarities to human cognition I argue are vastly overstated and narrowly construed. I submit that three alternative supervised (...) learning methods—namely lasso penalties, bagging, and boosting—offer subtler, more interesting analogies to human reasoning as both an individual and a social phenomenon. Despite the temptation to fall back on anthropomorphic tropes when discussing AI, however, I conclude that such rhetoric is at best misleading and at worst downright dangerous. The impulse to humanize algorithms is an obstacle to properly conceptualizing the ethical challenges posed by emerging technologies. (shrink)

In a recent paper, Erasmus et al. (2021) defend the idea that the ambiguity of the term “explanation” in explainable AI (XAI) can be solved by adopting any of four different extant accounts of explanation in the philosophy of science: the Deductive Nomological, Inductive Statistical, Causal Mechanical, and New Mechanist models. In this chapter, I show that the authors’ claim that these accounts can be applied to deep neural networks as they would to any natural phenomenon is mistaken. (...) I also provide a more general argument as to why the notion of explainability as it is currently used in the XAI literature bears little resemblance to the traditional concept of scientific explanation. It would be more fruitful to use the label “understandable AI” to avoid the confusion that surrounds the goal and purposes of XAI. In the second half of the chapter, I argue for a pragmatic conception of understanding that is better suited to play the central role attributed to explanation in XAI. Following De Regt (2017) and Kuorikoski and Ylikoski (2015), the conditions of satisfaction for understanding an ML system are fleshed out in terms of an agent’s success in using the system. (shrink)

Explanation does not exist in a metaphysical vacuum. Conceptions of the structure of a phenomenon play an important role in guiding attempts to explain it, and erroneous conceptions of a phenomenon may direct investigation in misleading directions. I believe that there is a case to be made for thinking that much work on the neural underpinnings of consciousness—what is often called the neural correlates of consciousness—is driven by an erroneous conception of the structure of consciousness. The (...) aim of this paper is lay bare some connections between the explanation of consciousness and the structure of consciousness, and to argue for a conception of the structure of consciousness that is more adequate than that which currently drives much research into the neural correlates of consciousness. (shrink)

As a reply to the commentary (Humphreys in Found Sci, 2012), we explore the methodological implications of seeing artificial neural networks as generic classification tools, we show in which sense the use of descriptions and models in data analysis is not equivalent to the original empirical use of epicycles in describing planetary motion, and we argue that agnostic science is essentially related to the type of problems we ask about a phenomenon and to the processes used to find (...) answers. (shrink)

An argument recently proposed by Chirimuuta seems to motivate the rejection of the claims that every neurocognitive phenomenon can have a mechanistic explanation and that every neurocognitive explanation is mechanistic. In this paper, I focus on efficient coding models involving the so-called “canonical neural computations” and argue that although they imply some form of pluralism, they are compatible with two mechanistic generalizations: all neurocognitive explanations are mechanistic; and all neurocognitive phenomena that have an explanation have a purely mechanistic (...) explanation. (shrink)

The disambiguation of a syntactically ambiguous sentence in favor of a less preferred parse can lead to slower reading at the disambiguation point. This phenomenon, referred to as a garden‐path effect, has motivated models in which readers initially maintain only a subset of the possible parses of the sentence, and subsequently require time‐consuming reanalysis to reconstruct a discarded parse. A more recent proposal argues that the garden‐path effect can be reduced to surprisal arising in a fully parallel parser: words (...) consistent with the initially dispreferred but ultimately correct parse are simply less predictable than those consistent with the incorrect parse. Since predictability has pervasive effects in reading far beyond garden‐path sentences, this account, which dispenses with reanalysis mechanisms, is more parsimonious. Crucially, it predicts a linear effect of surprisal: the garden‐path effect is expected to be proportional to the difference in word surprisal between the ultimately correct and ultimately incorrect interpretations. To test this prediction, we used recurrent neural network language models to estimate word‐by‐word surprisal for three temporarily ambiguous constructions. We then estimated the slowdown attributed to each bit of surprisal from human self‐paced reading times, and used that quantity to predict syntactic disambiguation difficulty. Surprisal successfully predicted the existence of garden‐path effects, but drastically underpredicted their magnitude, and failed to predict their relative severity across constructions. We conclude that a full explanation of syntactic disambiguation difficulty may require recovery mechanisms beyond predictability. (shrink)

An English double-embedded relative clause from which the middle verb is omitted can often be processed more easily than its grammatical counterpart, a phenomenon known as the grammaticality illusion. This effect has been found to be reversed in German, suggesting that the illusion is language specific rather than a consequence of universal working memory constraints. We present results from three self-paced reading experiments which show that Dutch native speakers also do not show the grammaticality illusion in Dutch, whereas both (...) German and Dutch native speakers do show the illusion when reading English sentences. These findings provide evidence against working memory constraints as an explanation for the observed effect in English. We propose an alternative account based on the statistical patterns of the languages involved. In support of this alternative, a single recurrent neural network model that is trained on both Dutch and English sentences is shown to predict the cross-linguistic difference in the grammaticality effect. (shrink)

The phenomenon of synesthesia has undergone an invigoration of research interest and empirical progress over the past decade. Studies investigating the cognitive mechanisms underlying synesthesia have yielded insight into neural processes behind such cognitive operations as attention, memory, spatial phenomenology and inter-modal processes. However, the structural and functional mechanisms underlying synesthesia still remain contentious and hypothetical. The first section of the present paper reviews recent research on grapheme-color synesthesia, one of the most common forms of synesthesia, and addresses (...) the ongoing debate concerning the role of selective attention in eliciting synesthetic experience. Drawing on conclusions of the first half, the paper’s second half examines the various models proposed to explain the cognitive mechanisms behind grapheme-color synesthesia, and discusses the explanatory virtues of a new model suggesting that grapheme-color synesthesia is grounded in memory. The last section offers an examination of some of the broader philosophical implications of synesthesia. (shrink)