Results for 'Neural'

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  1. The Neural Correlates of Consciousness.Jorge Morales & Hakwan Lau - 2020 - In Uriah Kriegel (ed.), The Oxford Handbook of the Philosophy of Consciousness. Oxford University Press. pp. 233-260.
    In this chapter, we discuss a selection of current views of the neural correlates of consciousness (NCC). We focus on the different predictions they make, in particular with respect to the role of prefrontal cortex (PFC) during visual experiences, which is an area of critical interest and some source of contention. Our discussion of these views focuses on the level of functional anatomy, rather than at the neuronal circuitry level. We take this approach because we currently understand more about (...)
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  2.  96
    Neural Representations Not Needed - No More Pleas, Please.Daniel D. Hutto & Erik Myin - 2014 - Phenomenology and the Cognitive Sciences 13 (2):241-256.
    Colombo (Phenomenology and the Cognitive Sciences, 2012) argues that we have compelling reasons to posit neural representations because doing so yields unique explanatory purchase in central cases of social norm compliance. We aim to show that there is no positive substance to Colombo’s plea—nothing that ought to move us to endorse representationalism in this domain, on any level. We point out that exposing the vices of the phenomenological arguments against representationalism does not, on its own, advance the case for (...)
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  3. Artificial Neural Network for Forecasting Car Mileage Per Gallon in the City.Mohsen Afana, Jomana Ahmed, Bayan Harb, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2018 - International Journal of Advanced Science and Technology 124:51-59.
    In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict MPG_City with (...)
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  4. Neural Correlates of Moral Sensitivity and Moral Judgment Associated with Brain Circuitries of Selfhood: A Meta-Analysis.Hyemin Han - 2017 - Journal of Moral Education 46 (2):97-113.
    The present study meta-analyzed 45 experiments with 959 subjects and 463 activation foci reported in 43 published articles that investigated the neural mechanism of moral functions by comparing neural activity between the moral-task and non-moral-task conditions with the Activation Likelihood Estimate method. The present study examined the common activation foci of morality-related task conditions. In addition, this study compared the neural correlates of moral sensibility with the neural correlates of moral judgment, which are the two functional (...)
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  5. Artificial Neural Network for Predicting Workplace Absenteeism.Raghad Adnan Abu Hassanein, Saja Ahmed Al-Qassas, Fatima Naji Abu Tir & Samy S. Abu-Naser - 2020 - International Journal of Academic Engineering Research (IJAER) 4 (9):62-67.
    Associations can grow, succeed, and sustain if their employees are committed. The main assets of an association are those employees who are giving it a required number of hours per month, in other words, those employees who are punctual towards their attendance. Absenteeism from work is a multibillion-dollar problem, and it costs money and decreases revenue. At the time of hiring an employee, Associations do not have an objective mechanism to predict whether an employee will be punctual towards attendance or (...)
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  6. Neural Computation and the Computational Theory of Cognition.Gualtiero Piccinini & Sonya Bahar - 2013 - Cognitive Science 37 (3):453-488.
    We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism—neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog (...)
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  7. Neural Correlates of Consciousness: Empirical and Conceptual Questions.Thomas Metzinger - 2000 - MIT Press.
  8. Neural Reuse: A Fundamental Organizational Principle of the Brain.Michael L. Anderson - 2010 - Behavioral and Brain Sciences 33 (4):245.
    An emerging class of theories concerning the functional structure of the brain takes the reuse of neural circuitry for various cognitive purposes to be a central organizational principle. According to these theories, it is quite common for neural circuits established for one purpose to be exapted (exploited, recycled, redeployed) during evolution or normal development, and be put to different uses, often without losing their original functions. Neural reuse theories thus differ from the usual understanding of the role (...)
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  9. Neural Plasticity and Consciousness.Susan Hurley & Alva Noë - 2003 - Biology and Philosophy 18 (1):131-168.
    and apply it to various examples of neural plasticity in which input is rerouted intermodally or intramodally to nonstandard cortical targets. In some cases but not others, cortical activity ‘defers’ to the nonstandard sources of input. We ask why, consider some possible explanations, and propose a dynamic sensorimotor hypothesis. We believe that this distinction is important and worthy of further study, both philosophical and empirical, whether or not our hypothesis turns out to be correct. In particular, the question of (...)
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  10.  44
    Neural Organoids and the Precautionary Principle.Jonathan Birch & Heather Browning - 2021 - American Journal of Bioethics 21 (1):56-58.
    Human neural organoid research is advancing rapidly. As Greely notes in the target article, this progress presents an “onrushing ethical dilemma.” We can’t rule out the possibility that suff...
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  11. Neural Correlates of Consciousness in Humans.Geraint Rees, G. Kreiman & Christof Koch - 2002 - Nature Reviews Neuroscience 3 (4):261-270.
  12. The Neural Basis of Cognitive Development: A Constructivist Manifesto.Steven R. Quartz & Terrence J. Sejnowski - 1997 - Behavioral and Brain Sciences 20 (4):537-556.
    How do minds emerge from developing brains? According to the representational features of cortex are built from the dynamic interaction between neural growth mechanisms and environmentally derived neural activity. Contrary to popular selectionist models that emphasize regressive mechanisms, the neurobiological evidence suggests that this growth is a progressive increase in the representational properties of cortex. The interaction between the environment and neural growth results in a flexible type of learning: minimizes the need for prespecification in accordance with (...)
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  13. Artificial Neural Network for Predicting Animals Category.Ibrahim M. Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic and Applied Research (IJAAR) 3 (2):18-24.
    Abstract: In this paper an Artificial Neural Network (ANN) model, was developed and tested for predicting the category of an animal. There is a number of factors that influence the classification of animals. Such as the existence of hair/ feather, if the animal gives birth or spawns, it is airborne, aquatic, predator, toothed, backboned, venomous, has –fins, has-tail, cat-sized, and domestic. They were then used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology (...)
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  14. The Neural Basis of Intuitive and Counterintuitive Moral Judgement.Guy Kahane, Katja Wiech, Nicholas Shackel, Miguel Farias, Julian Savulescu & Irene Tracey - 2011 - Social Cognitive and Affective Neuroscience 7 (4):393-402.
    Neuroimaging studies on moral decision-making have thus far largely focused on differences between moral judgments with opposing utilitarian (well-being maximizing) and deontological (duty-based) content. However, these studies have investigated moral dilemmas involving extreme situations, and did not control for two distinct dimensions of moral judgment: whether or not it is intuitive (immediately compelling to most people) and whether it is utilitarian or deontological in content. By contrasting dilemmas where utilitarian judgments are counterintuitive with dilemmas in which they are intuitive, we (...)
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  15.  85
    Neural Mechanisms of Selective Visual Attention.R. Desimone & J. Duncan - 1995 - Annual Review of Neuroscience 18 (1):193-222.
  16. Investigating Neural Representations: The Tale of Place Cells.William Bechtel - 2016 - Synthese 193 (5):1287-1321.
    While neuroscientists often characterize brain activity as representational, many philosophers have construed these accounts as just theorists’ glosses on the mechanism. Moreover, philosophical discussions commonly focus on finished accounts of explanation, not research in progress. I adopt a different perspective, considering how characterizations of neural activity as representational contributes to the development of mechanistic accounts, guiding the investigations neuroscientists pursue as they work from an initial proposal to a more detailed understanding of a mechanism. I develop one illustrative example (...)
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  17. Diabetes Prediction Using Artificial Neural Network.Nesreen Samer El_Jerjawi & Samy S. Abu-Naser - 2018 - International Journal of Advanced Science and Technology 121:54-64.
    Diabetes is one of the most common diseases worldwide where a cure is not found for it yet. Annually it cost a lot of money to care for people with diabetes. Thus the most important issue is the prediction to be very accurate and to use a reliable method for that. One of these methods is using artificial intelligence systems and in particular is the use of Artificial Neural Networks (ANN). So in this paper, we used artificial neural (...)
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  18.  1
    The Neural Basis of Mentalizing.Chris D. Frith & Uta Frith - 2006 - Neuron 50 (4):531-534.
    Mentalizing refers to our ability to read the mental states of other agents and engages many neural processes. The brain's mirror system allows us to share the emotions of others. Through perspective taking, we can infer what a person currently believes about the world given their point of view. Finally, the human brain has the unique ability to represent the mental states of the self and the other and the relationship between these mental states, making possible the communication of (...)
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  19. Neural Representations Observed.Eric Thomson & Gualtiero Piccinini - 2018 - Minds and Machines 28 (1):191-235.
    The historical debate on representation in cognitive science and neuroscience construes representations as theoretical posits and discusses the degree to which we have reason to posit them. We reject the premise of that debate. We argue that experimental neuroscientists routinely observe and manipulate neural representations in their laboratory. Therefore, neural representations are as real as neurons, action potentials, or any other well-established entities in our ontology.
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  20. The Neural Correlates of Consciousness: New Experimental Approaches Needed?Jakob Hohwy - 2009 - Consciousness and Cognition 18 (2):428-438.
    It appears that consciousness science is progressing soundly, in particular in its search for the neural correlates of consciousness. There are two main approaches to this search, one is content-based (focusing on the contrast between conscious perception of, e.g., faces vs. houses), the other is state-based (focusing on overall conscious states, e.g., the contrast between dreamless sleep vs. the awake state). Methodological and conceptual considerations of a number of concrete studies show that both approaches are problematic: the content-based approach (...)
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  21.  41
    The Neural Correlates of Visual Imagery: A Co-Ordinate-Based Meta-Analysis.C. Winlove, F. Milton, J. Ranson, J. Fulford, M. MacKisack, Fiona Macpherson & A. Zeman - 2018 - Cortex 105 (August 2018):4-25.
    Visual imagery is a form of sensory imagination, involving subjective experiences typically described as similar to perception, but which occur in the absence of corresponding external stimuli. We used the Activation Likelihood Estimation algorithm (ALE) to identify regions consistently activated by visual imagery across 40 neuroimaging studies, the first such meta-analysis. We also employed a recently developed multi-modal parcellation of the human brain to attribute stereotactic co-ordinates to one of 180 anatomical regions, the first time this approach has been combined (...)
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  22. Neural Plasticity and Consciousness: Reply to Block.Susan Hurley & Alva Noë - 2003 - Trends in Cognitive Sciences 7 (8):342.
    Susan Hurley Susan Hurley Susan Hurley Susan Hurley1111 andAlva Noë andAlva Noë andAlva Noë andAlva Noë2222.
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  23.  64
    The Neural and Cognitive Mechanisms of Knowledge Attribution: An EEG Study.Adam Michael Bricker - 2020 - Cognition 203:104412.
    Despite the ubiquity of knowledge attribution in human social cognition, its associated neural and cognitive mechanisms are poorly documented. A wealth of converging evidence in cognitive neuroscience has identified independent perspective-taking and inhibitory processes for belief attribution, but the extent to which these processes are shared by knowledge attribution isn't presently understood. Here, we present the findings of an EEG study designed to directly address this shortcoming. These findings suggest that belief attribution is not a component process in knowledge (...)
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  24. Some Neural Networks Compute, Others Don't.Gualtiero Piccinini - 2008 - Neural Networks 21 (2-3):311-321.
    I address whether neural networks perform computations in the sense of computability theory and computer science. I explicate and defend
    the following theses. (1) Many neural networks compute—they perform computations. (2) Some neural networks compute in a classical way.
    Ordinary digital computers, which are very large networks of logic gates, belong in this class of neural networks. (3) Other neural networks
    compute in a non-classical way. (4) Yet other neural networks do not perform computations. Brains may well (...)
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  25. Neural Network Approach to Predict Forest Fires Using Meteorological Data.Mutasim Mahmoud Al-Kahlout, Ahmed Mahmoud Abu Ghaly, Donia Zaher Mudawah & Samy S. Abu-Naser - 2020 - International Journal of Academic Engineering Research (IJAER) 4 (9):68-72.
    Forest fires are a major environmental issue, creating economical and ecological damage while endangering human lives. Fast detection is a key element for controlling such phenomenon. To achieve this, one alternative is to use automatic tools based on local sensors, such as provided by meteorological stations. In effect, meteorological conditions (e.g. temperature, wind) are known to influence forest fires and several fire indexes, such as the forest Fire Weather Index (FWI), use such data. In this work, we explore a Just (...)
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  26.  37
    Neural Geographies: Feminism and the Microstructure of Cognition.Elizabeth A. Wilson - 1998 - Routledge.
    Neural Geographies draws together recent feminist and deconstructive theories, early Freudian neurology and contemporary connectionist theories of cognition. In this original work, Elizabeth A. Wilson explores the convergence between Derrida, Freud and recent cognitive theory to pursue two important issues: the nature of cognition and neurology, and the politics of feminist and critical interventions into contemporary scientific psychology. This book seeks to reorient the usual presumptions of critical studies of the sciences by addressing the divisions between the static and (...)
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  27. Neural Darwinism and Consciousness.Anil K. Seth & Bernard J. Baars - 2005 - Consciousness and Cognition 14 (1):140-168.
    Neural Darwinism (ND) is a large scale selectionist theory of brain development and function that has been hypothesized to relate to consciousness. According to ND, consciousness is entailed by reentrant interactions among neuronal populations in the thalamocortical system (the ‘dynamic core’). These interactions, which permit high-order discriminations among possible core states, confer selective advantages on organisms possessing them by linking current perceptual events to a past history of value-dependent learning. Here, we assess the consistency of ND with 16 widely (...)
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  28. The Neural Basis of Predicate-Argument Structure.James R. Hurford - 2003 - Behavioral and Brain Sciences 26 (3):261-283.
    Neural correlates exist for a basic component of logical formulae, PREDICATE(x). Vision and audition research in primates and humans shows two independent neural pathways; one locates objects in body-centered space, the other attributes properties, such as colour, to objects. In vision these are the dorsal and ventral pathways. In audition, similarly separable “where” and “what” pathways exist. PREDICATE(x) is a schematic representation of the brain's integration of the two processes of delivery by the senses of the location of (...)
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  29. Artificial Neural Network for Predicting Car Performance Using JNN.Awni Ahmed Al-Mobayed, Youssef Mahmoud Al-Madhoun, Mohammed Nasser Al-Shuwaikh & Samy S. Abu-Naser - 2020 - International Journal of Engineering and Information Systems (IJEAIS) 4 (9):139-145.
    In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Buying, Maint, Doors, Persons, Lug_boot, Safety, and Overall. ANN was used in forecasting car acceptability. The results showed that ANN model was able to predict the car acceptability with 99.12 %. The factor of Safety has the most influence on car acceptability evaluation. Comparative study method (...)
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  30. Neural Systems Supporting Interoceptive Awareness.Hugo D. Critchley, Stefan Wiens, Pia Rotshtein, Arne Öhman & Raymond J. Dolan - 2004 - Nature Neuroscience 7 (2):189-195.
  31. Neural Correlates of Consciousness and the Nature of the Mind.Matthew Owen - 2019 - In Mihretu P. Guta (ed.), Consciousness and the Ontology of Properties. New York: Routledge. pp. 241-260.
    It is often thought that contemporary neuroscience provides strong evidence for physicalism that nullifies dualism. The principal data is neural correlates of consciousness (for brevity NCC). In this chapter I argue that NCC are neutral vis- à-vis physicalist and dualist views of the mind. First I clarify what NCC are and how neuroscientists identify them. Subsequently I discuss what NCC entail and highlight the need for philosophical argumentation in order to conclude that physicalism is true by appealing to NCC. (...)
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  32.  71
    Neural Representationalism, the Hard Problem of Content and Vitiated Verdicts. A Reply to Hutto & Myin.Matteo Colombo - 2014 - Phenomenology and the Cognitive Sciences 13 (2):257-274.
    Colombo’s (Phenomenology and the Cognitive Sciences, 2013) plea for neural representationalism is the focus of a recent contribution to Phenomenology and Cognitive Science by Daniel D. Hutto and Erik Myin. In that paper, Hutto and Myin have tried to show that my arguments fail badly. Here, I want to respond to their critique clarifying the type of neural representationalism put forward in my (Phenomenology and the Cognitive Sciences, 2013) piece, and to take the opportunity to make a few (...)
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  33. What is a Neural Correlate of Consciousness?David J. Chalmers - 2000 - In Thomas Metzinger (ed.), Neural Correlates of Consciousness. MIT Press. pp. 17--39.
    The search for neural correlates of consciousness (or NCCs) is arguably the cornerstone in the recent resurgence of the science of consciousness. The search poses many difficult empirical problems, but it seems to be tractable in principle, and some ingenious studies in recent years have led to considerable progress. A number of proposals have been put forward concerning the nature and location of neural correlates of consciousness. A few of these include.
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  34.  43
    Neural Plasticity, Neuronal Recycling and Niche Construction.Richard Menary - 2014 - Mind and Language 29 (3):286-303.
    In Reading in the Brain, Stanislas Dehaene presents a compelling account of how the brain learns to read. Central to this account is his neuronal recycling hypothesis: neural circuitry is capable of being ‘recycled’ or converted to a different function that is cultural in nature. The original function of the circuitry is not entirely lost and constrains what the brain can learn. It is argued that the neural niche co-evolves with the environmental niche in a way that does (...)
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  35.  54
    The Neural Correlates of Visual Self-Recognition.Christel Devue & Serge Brédart - 2011 - Consciousness and Cognition 20 (1):40-51.
    This paper presents a review of studies that were aimed at determining which brain regions are recruited during visual self-recognition, with a particular focus on self-face recognition. A complex bilateral network, involving frontal, parietal and occipital areas, appears to be associated with self-face recognition, with a particularly high implication of the right hemisphere. Results indicate that it remains difficult to determine which specific cognitive operation is reflected by each recruited brain area, in part due to the variability of used control (...)
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  36. The Neural Mechanisms of Moral Cognition: A Multiple-Aspect Approach to Moral Judgment and Decision-Making. [REVIEW]William D. Casebeer & Patricia S. Churchland - 2003 - Biology and Philosophy 18 (1):169-194.
    We critically review themushrooming literature addressing the neuralmechanisms of moral cognition (NMMC), reachingthe following broad conclusions: (1) researchmainly focuses on three inter-relatedcategories: the moral emotions, moral socialcognition, and abstract moral reasoning. (2)Research varies in terms of whether it deploysecologically valid or experimentallysimplified conceptions of moral cognition. Themore ecologically valid the experimentalregime, the broader the brain areas involved.(3) Much of the research depends on simplifyingassumptions about the domain of moral reasoningthat are motivated by the need to makeexperimental progress. This is a (...)
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  37. The Neural Basis of the Interaction Between Theory of Mind and Moral Judgment.Liane Young, Fiery Cushman, Marc Hauser & and Rebecca Saxe - 2007 - Proceedings of the National Academy of Sciences 104 (20):8235-8240.
    Is the basis of criminality an act that causes harm, or an act undertaken with the belief that one will cause harm? The present study takes a cognitive neuroscience approach to investigating how information about an agent’s beliefs and an action’s conse- quences contribute to moral judgment. We build on prior devel- opmental evidence showing that these factors contribute differ- entially to the young child’s moral judgments coupled with neurobiological evidence suggesting a role for the right tem- poroparietal junction (RTPJ) (...)
     
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  38.  4
    Neural Dynamics of Planned Arm Movements: Emergent Invariants and Speed-Accuracy Properties During Trajectory Formation.Daniel Bullock & Stephen Grossberg - 1988 - Psychological Review 95 (1):49-90.
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  39. The Neural-Cognitive Basis of the Jamesian Stream of Thought.Russell Epstein - 2000 - Consciousness and Cognition 9 (4):550-575.
    William James described the stream of thought as having two components: (1) a nucleus of highly conscious, often perceptual material; and (2) a fringe of dimly felt contextual information that controls the entry of information into the nucleus and guides the progression of internally directed thought. Here I examine the neural and cognitive correlates of this phenomenology. A survey of the cognitive neuroscience literature suggests that the nucleus corresponds to a dynamic global buffer formed by interactions between different regions (...)
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  40.  10
    The Neural Mechanism of Pure and Pseudo-Insight Problem Solving.Ching-Lin Wu, Meng-Ning Tsai & Hsueh-Chih Chen - 2019 - Thinking and Reasoning 26 (4):479-501.
    Only problems that cannot be solved without representational changes can be regarded as pure insight problems; others are classified as pseudo-insight problems. Existing studies using neuroimaging...
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  41.  33
    Neural Information and the Problem of Objectivity.Charles Rathkopf - 2017 - Biology and Philosophy 32 (3):321-336.
    A fascinating research program in neurophysiology attempts to quantify the amount of information transmitted by single neurons. The claims that emerge from this research raise new philosophical questions about the nature of information. What kind of information is being quantified? Do the resulting quantities describe empirical magnitudes like those found elsewhere in the natural sciences? In this article, it is argued that neural information quantities have a relativisitic character that makes them distinct from the kinds of information typically discussed (...)
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  42. Neural Synchrony and the Causal Efficacy of Consciousness.David Yates - 2020 - Topoi 39 (5):1057-1072.
    The purpose of this paper is to address a well-known dilemma for physicalism. If mental properties are type identical to physical properties, then their causal efficacy is secure, but at the cost of ruling out mentality in creatures very different to ourselves. On the other hand, if mental properties are multiply realizable, then all kinds of creatures can instantiate them, but then they seem to be causally redundant. The causal exclusion problem depends on the widely held principle that realized properties (...)
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  43. Temporal Binding and the Neural Correlates of Sensory Awareness.Andreas K. Engel & Wolf Singer - 2001 - Trends in Cognitive Sciences 5 (1):16-25.
    Theories of binding have recently come into the focus of the consciousness debate. In this review, we discuss the potential relevance of temporal binding mechanisms for sensory awareness. Specifically, we suggest that neural synchrony with a precision in the millisecond range may be crucial for conscious processing, and may be involved in arousal, perceptual integration, attentional selection and working memory. Recent evidence from both animal and human studies demonstrates that specific changes in neuronal synchrony occur during all of these (...)
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  44.  5
    Neural Dynamics of Form Perception: Boundary Completion, Illusory Figures, and Neon Color Spreading.Stephen Grossberg & Ennio Mingolla - 1985 - Psychological Review 92 (2):173-211.
  45. Distributed Neural Systems for Face Perception.James V. Haxby & M. Ida Gobbini - 2011 - In Andy Calder, Gillian Rhodes, Mark Johnson & Jim Haxby (eds.), Oxford Handbook of Face Perception. Oxford University Press. pp. 93--110.
    Face perception plays a central role in social communication and is, arguably, one of the most sophisticated visual perceptual skills in humans. The organization of neural systems for face perception has stimulated intense debate. This article presents an updated model of distributed human neural systems for face perception. It opens up with a discussion of the Core System for visual analysis of faces with an emphasis on the distinction between perception of invariant features for identity recognition and changeable (...)
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  46. Glass Classification Using Artificial Neural Network.Mohmmad Jamal El-Khatib, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic Pedagogical Research (IJAPR) 3 (23):25-31.
    As a type of evidence glass can be very useful contact trace material in a wide range of offences including burglaries and robberies, hit-and-run accidents, murders, assaults, ram-raids, criminal damage and thefts of and from motor vehicles. All of that offer the potential for glass fragments to be transferred from anything made of glass which breaks, to whoever or whatever was responsible. Variation in manufacture of glass allows considerable discrimination even with tiny fragments. In this study, we worked glass classification (...)
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  47.  25
    The Neural Dynamics of Seeing-In.Gabriele Ferretti - 2019 - Erkenntnis 84 (6):1285-1324.
    Philosophers have suggested that, in order to understand the particular visual state we are in during picture perception, we should focus on experimental results from vision neuroscience—in particular, on the most rigorous account of the functioning of the visual system that we have from vision neuroscience, namely, the ‘Two Visual Systems Model’. According to the initial version of this model, our visual system can be dissociated, from an anatomo-functional point of view, into two streams: a ventral stream subserving visual recognition, (...)
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  48.  91
    Identifying Neural Correlates of Consciousness: The State Space Approach.Juergen Fell - 2004 - Consciousness and Cognition 13 (4):709-29.
    This article sketches an idealized strategy for the identification of neural correlates of consciousness. The proposed strategy is based on a state space approach originating from the analysis of dynamical systems. The article then focuses on one constituent of consciousness, phenomenal awareness. Several rudimentary requirements for the identification of neural correlates of phenomenal awareness are suggested. These requirements are related to empirical data on selective attention, on completely intrinsic selection and on globally unconscious states. As an example, neuroscientific (...)
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  49.  14
    The Neural Basis of Human Error Processing: Reinforcement Learning, Dopamine, and the Error-Related Negativity.Clay B. Holroyd & Michael G. H. Coles - 2002 - Psychological Review 109 (4):679-709.
  50. Email Classification Using Artificial Neural Network.Ahmed Alghoul, Sara Al Ajrami, Ghada Al Jarousha, Ghayda Harb & Samy S. Abu-Naser - 2018 - International Journal of Academic Engineering Research (IJAER) 2 (11):8-14.
    Abstract: In recent years email has become one of the fastest and most economical means of communication. However increase of email users has resulted in the dramatic increase of spam emails during the past few years. Data mining -classification algorithms are used to categorize the email as spam or non-spam. Numerous email spam messages are marketable in nature but might similarly encompass camouflaged links that seem to be for acquainted websites but actually lead to phishing web sites or sites that (...)
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