Results for 'Brain Network Commonality'

960 found
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  1. Brain Network Commonality and the General Empirical Method.Anuj Rastogi - 2014 - Dialogues in Philosophy, Mental and Neuro Sciences 7 (2):68-69.
    The Generalized Empirical Method as outlined by Henman initially seems a cogent approach that should be adopted by cognitive neuroscientists. However, some weaknesses in the presumptions of this method in light of modern neuroscience research may challenge its validity. As I am currently working on mapping cerebral-cerebellar networks using fMRI, I am intrigued by the practical utility of the GEM in experimental work.
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  2. Spontaneous thought-related network connectivity predicts sertraline effects on major depressive disorder.Timothy Joseph Lane - 2021 - Brain Imaging and Behavior 15 (4):1705-1717.
    Sertraline is one of the most commonly prescribed antidepressants. Major depressive disorder (MDD) is characterized by spontaneous thoughts that are laden with negative affect-a "malignant sadness". Prior neuroimaging studies have identified abnormal resting-state functional connectivity (rsFC) in the spontaneous brain networks of MDD patients. But how antidepressant medication acts to relieve the experience of depression as well as adjust its associated spontaneous networks and mood-regulation circuits remains an open question. In this study, we recruited 22 drug-naïve MDD patients along (...)
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  3.  71
    Instability of brain connectivity during nonrapid eye movement sleep reflects altered properties of information integration.Timothy Joseph Lane - 2019 - Human Brain Mapping 40:3192–3202.
    Nonrapid eye movement (NREM) sleep is associated with fading consciousness in humans. Recent neuroimaging studies have demonstrated the spatiotemporal alterations of the brain functional connectivity (FC) in NREM sleep, suggesting the changes of information integration in the sleeping brain. However, the common stationarity assumption in FC does not satisfactorily explain the dynamic process of information integration during sleep. The dynamic FC (dFC) across brain networks is speculated to better reflect the time-varying information propagation during sleep. Accordingly, we (...)
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  4. Varieties of representation in evolved and embodied neural networks.Pete Mandik - 2003 - Biology and Philosophy 18 (1):95-130.
    In this paper I discuss one of the key issuesin the philosophy of neuroscience:neurosemantics. The project of neurosemanticsinvolves explaining what it means for states ofneurons and neural systems to haverepresentational contents. Neurosemantics thusinvolves issues of common concern between thephilosophy of neuroscience and philosophy ofmind. I discuss a problem that arises foraccounts of representational content that Icall ``the economy problem'': the problem ofshowing that a candidate theory of mentalrepresentation can bear the work requiredwithin in the causal economy of a mind and (...)
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  5. Human brain evolution, theories of innovation, and lessons from the history of technology.Alfred Gierer - 2004 - J. Biosci 29 (3):235-244.
    Biological evolution and technological innovation, while differing in many respects, also share common features. In particular, implementation of a new technology in the market is analogous to the spreading of a new genetic trait in a population. Technological innovation may occur either through the accumulation of quantitative changes, as in the development of the ocean clipper, or it may be initiated by a new combination of features or subsystems, as in the case of steamships. Other examples of the latter type (...)
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  6. Classification of Alzheimer's Disease Using Convolutional Neural Networks.Lamis F. Samhan, Amjad H. Alfarra & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (3):18-23.
    Brain-related diseases are among the most difficult diseases due to their sensitivity, the difficulty of performing operations, and their high costs. In contrast, the operation is not necessary to succeed, as the results of the operation may be unsuccessful. One of the most common diseases that affect the brain is Alzheimer’s disease, which affects adults, a disease that leads to memory loss and forgetting information in varying degrees. According to the condition of each patient. For these reasons, it (...)
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  7. "The great mixing machine”: multisensory integration and brain-breath coupling in the cerebral cortex.Varga Somogy & Heck Detlef - 2022 - Pflügers Archiv - European Journal of Physiology 475:5-14.
    It is common to distinguish between “holist” and “reductionist” views of brain function, where the former envisions the brain as functioning as an indivisible unit and the latter as a collection of distinct units that serve different functions. Opposing reductionism, a number of researchers have pointed out that cortical network architecture does not respect functional boundaries, and the neuroanatomist V. Braitenberg proposed to understand the cerebral cortex as a “great mixing machine” of neuronal activity from sensory inputs, (...)
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  8. (1 other version)Neuroscience and Normativity: How Knowledge of the Brain Offers a Deeper Understanding of Moral and Legal Responsibility.William Hirstein - 2022 - Criminal Law and Philosophy 16 (2):327-351.
    Neuroscience can relate to ethics and normative issues via the brain’s cognitive control network. This network accomplishes several executive processes, such as planning, task-switching, monitoring, and inhibiting. These processes allow us to increase the accuracy of our perceptions and our memory recall. They also allow us to plan much farther into the future, and with much more detail than any of our fellow mammals. These abilities also make us fitting subjects for responsibility claims. Their activity, or lack (...)
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  9. fMRI reveals reciprocal inhibition between social and physical cognitive domains.Anthony I. Jack, Abigail Dawson, Katelyn Begany, Regina Leckie, Kevin Barry, Angela Ciccia & Abraham Snyder - 2013 - NeuroImage 66:385-401.
    Two lines of evidence indicate that there exists a reciprocal inhibitory relationship between opposed brain networks. First, most attention-demanding cognitive tasks activate a stereotypical set of brain areas, known as the task-positive network and simultaneously deactivate a different set of brain regions, commonly referred to as the task negative or defaultmode network. Second, functional connectivity analyses show that these same opposed networks are anti-correlated in the resting state. Wehypothesize that these reciprocally inhibitory effects reflect two (...)
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  10. Psychedelics and Meditation: A Neurophilosophical Perspective.Chris Letheby - 2022 - In Rick Repetti (ed.), Routledge Handbook on the Philosophy of Meditation. New York, NY: Routledge. pp. 209-223.
    Psychedelic ingestion and meditative practice are both ancient methods for altering consciousness that became widely known in Western society in the second half of the 20th century. Do the similarities begin and end there, or do these methods – as many have claimed over the years – share some deeper common elements? In this chapter I take a neurophilosophical approach to this question and argue that there are, indeed, deeper commonalities. Recent empirical studies show that psychedelics and meditation modulate overlapping (...)
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  11. Examining Phronesis Models with Evidence from the Neuroscience of Morality Focusing on Brain Networks.Hyemin Han - forthcoming - Topoi:1-13.
    In this paper, I examined whether evidence from the neuroscience of morality supports the standard models of phronesis, i.e., Jubilee and Aretai Centre Models. The standard models explain phronesis as a multifaceted construct based on interaction and coordination among functional components. I reviewed recent neuroscience studies focusing on brain networks associated with morality and their connectivity to examine the validity of the models. Simultaneously, I discussed whether the evidence helps the models address challenges, particularly those from the phronesis eliminativism. (...)
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  12. Complexity Reality and Scientific Realism.Avijit Lahiri - manuscript
    We introduce the notion of complexity, first at an intuitive level and then in relatively more concrete terms, explaining the various characteristic features of complex systems with examples. There exists a vast literature on complexity, and our exposition is intended to be an elementary introduction, meant for a broad audience. -/- Briefly, a complex system is one whose description involves a hierarchy of levels, where each level is made of a large number of components interacting among themselves. The time evolution (...)
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  13. The Problem of Induction and the Problem of Free Will.Avijit Lahiri - manuscript
    This essay presents a point of view for looking at `free will', with the purpose of interpreting where exactly the freedom lies. For, freedom is what we mean by it. It compares the exercise of free will with the making of inferences, which usually is predominantly inductive in nature. The making of inference and the exercise of free will, both draw upon psychological resources that define our ‘selves’. I examine the constitution of the self of an individual, especially the involvement (...)
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  14. A Cosmological Neuroscientific Definition of God.Nandor Ludvig - 2023 - Open Journal of Philosophy 13 (2):418-434.
    The main objective of this work was to produce a scientifically reasonable definition of God. The rationale was to generate a definition for filling a small part of the spiritual vacuum of the 21st century and thus initiate a new understanding of the Intelligence that permeates the cosmos with mystery, love, order, direction and morals. This resulted in the following definition: “God may be a-humanly incomprehensible-eternal cosmic existence, intimately related to the endlessness of space, to the nature of the deepest (...)
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  15. Prefrontal lesion evidence against higher-order theories of consciousness.Benjamin Kozuch - 2014 - Philosophical Studies 167 (3):721-746.
    According to higher-order theories of consciousness, a mental state is conscious only when represented by another mental state. Higher-order theories must predict there to be some brain areas (or networks of areas) such that, because they produce (the right kind of) higher-order states, the disabling of them brings about deficits in consciousness. It is commonly thought that the prefrontal cortex produces these kinds of higher-order states. In this paper, I first argue that this is likely correct, meaning that, if (...)
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  16. Measuring the World: Olfaction as a Process Model of Perception.Ann-Sophie Barwich - 2018 - In Daniel J. Nicholson & John Dupré (eds.), Everything Flows: Towards a Processual Philosophy of Biology. Oxford, United Kingdom: Oxford University Press. pp. 337-356.
    How much does stimulus input shape perception? The common-sense view is that our perceptions are representations of objects and their features and that the stimulus structures the perceptual object. The problem for this view concerns perceptual biases as responsible for distortions and the subjectivity of perceptual experience. These biases are increasingly studied as constitutive factors of brain processes in recent neuroscience. In neural network models the brain is said to cope with the plethora of sensory information by (...)
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  17.  94
    Criticism of individualist and collectivist methodological approaches to social emergence.S. M. Reza Amiri Tehrani - 2023 - Expositions: Interdisciplinary Studies in the Humanities 15 (3):111-139.
    ABSTRACT The individual-community relationship has always been one of the most fundamental topics of social sciences. In sociology, this is known as the micro-macro relationship while in economics it refers to the processes, through which, individual actions lead to macroeconomic phenomena. Based on philosophical discourse and systems theory, many sociologists even use the term "emergence" in their understanding of micro-macro relationship, which refers to collective phenomena that are created by the cooperation of individuals, but cannot be reduced to individual actions. (...)
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  18. The Informational Model of Consciousness: Mechanisms of Embodiment/Disembodiment of Information.Florin Gaiseanu - 2019 - Neuroquantology 17 (4):1-17.
    It was shown recently that information is the central concept which it is to be considered to understand consciousness and its properties. Arguing that consciousness is a consequence of the operational activity of the informational system of the human body, it was shown that this system is composed by seven informational components, reflected in consciousness by corresponding cognitive centers. It was argued also that consciousness can be connected to the environment not only by the common senses, but also by a (...)
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  19. A Revolutionary New Metaphysics, Based on Consciousness, and a Call to All Philosophers.Lorna Green - manuscript
    June 2022 A Revolutionary New Metaphysics, Based on Consciousness, and a Call to All Philosophers We are in a unique moment of our history unlike any previous moment ever. Virtually all human economies are based on the destruction of the Earth, and we are now at a place in our history where we can foresee if we continue on as we are, our own extinction. As I write, the planet is in deep trouble, heat, fires, great storms, and record flooding, (...)
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  20. Classification of Alzheimer’s Disease Using Traditional Classifiers with Pre-Trained CNN.Husam R. Almadhoun & Samy S. Abu-Naser - 2021 - International Journal of Academic Health and Medical Research (IJAHMR) 5 (4):17-21.
    Abstract: Alzheimer's disease (AD) is one of the most common types of dementia. Symptoms appear gradually and end with severe brain damage. People with Alzheimer's disease lose the abilities of knowledge, memory, language and learning. Recently, the classification and diagnosis of diseases using deep learning has emerged as an active topic covering a wide range of applications. This paper proposes examining abnormalities in brain structures and detecting cases of Alzheimer's disease especially in the early stages, using features derived (...)
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  21. An Interdisciplinary Perspective Towards Explaining the Visual Aesthetic Experience: The Case of Emotion.Ryan Slaby - 2022 - Itinera 23 (Aesthetics, Technique and Emotio):371- 390.
    This paper discusses the empirical findings concerning the visual aesthetic experience in a neurological context. Accordingly, the aim of this paper is to shed light on the common ground across neuroscience, psychology, and philosophy to pave new roads for empirical research. Cognitive models posit that the brain employs neural networks mediating bottom-up and top- down processes, and in effect, engenders emotion and reward throughout the visual aesthetic experience. Likewise, empathy and its corresponding recruitment of bodily processes may facilitate the (...)
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  22. Networks of Gene Regulation, Neural Development and the Evolution of General Capabilities, Such as Human Empathy.Alfred Gierer - 1998 - Zeitschrift Für Naturforschung C - A Journal of Bioscience 53:716-722.
    A network of gene regulation organized in a hierarchical and combinatorial manner is crucially involved in the development of the neural network, and has to be considered one of the main substrates of genetic change in its evolution. Though qualitative features may emerge by way of the accumulation of rather unspecific quantitative changes, it is reasonable to assume that at least in some cases specific combinations of regulatory parts of the genome initiated new directions of evolution, leading to (...)
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  23. Geometry for a Brain. Optimal Control in a Network of Adaptive Memristors.Ignazio Licata & Germano Resconi - 2013 - Adv. Studies Theor. Phys., (no.10):479-513.
    In the brain the relations between free neurons and the conditioned ones establish the constraints for the informational neural processes. These constraints reflect the systemenvironment state, i.e. the dynamics of homeocognitive activities. The constraints allow us to define the cost function in the phase space of free neurons so as to trace the trajectories of the possible configurations at minimal cost while respecting the constraints imposed. Since the space of the free states is a manifold or a non orthogonal (...)
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  24. Michael A. Arbib, The metaphorical brain 2: Neural networks and beyond.John A. Barnden - 1998 - Artificial Intelligence 101 (1-2):301-309.
    The book is thought-provoking and informative, wide in scope while also being technically detailed, and still relevant to modem AI [at least as of 1998, the time of writing this review, but probably also at the time of posting this entry here, 2023] even though it was published in 1989. This relevance lies mainly in the book’s advocacy of distributed computation at multiple levels of description, its combining of neural networks and other techniques, its emphasis on the interplay between action (...)
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  25. Predictive brains: forethought and the levels of explanation.Giuseppe Boccignone & Roberto Cordeschi - 2012 - Frontiers in Psychology 3.
    Is any unified theory of brain function possible? Following a line of thought dat- ing back to the early cybernetics (see, e.g., Cordeschi, 2002), Clark (in press) has proposed the action-oriented Hierarchical Predictive Coding (HPC) as the account to be pursued in the effort of gain- ing the “Grand Unified Theory of the Mind”—or “painting the big picture,” as Edelman (2012) put it. Such line of thought is indeed appealing, but to be effectively pursued it should be confronted with (...)
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  26. Causal Network Accounts Of Ill-being: Depression & Digital Well-being.Nick Byrd - 2020 - In Christopher Burr & Luciano Floridi (eds.), Ethics of digital well-being: a multidisciplinary approach. Springer. pp. 221-245.
    Depression is a common and devastating instance of ill-being which deserves an account. Moreover, the ill-being of depression is impacted by digital technology: some uses of digital technology increase such ill-being while other uses of digital technology increase well-being. So a good account of ill-being would explicate the antecedents of depressive symptoms and their relief, digitally and otherwise. This paper borrows a causal network account of well-being and applies it to ill-being, particularly depression. Causal networks are found to provide (...)
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  27. Responsible Brains: Neuroscience, Law, and Human Culpability.William Hirstein, Katrina L. Sifferd & Tyler K. Fagan - 2018 - New York, NY, USA: MIT Press. Edited by Katrina Sifferd & Tyler Fagan.
    [This download includes the table of contents and chapter 1.] -/- When we praise, blame, punish, or reward people for their actions, we are holding them responsible for what they have done. Common sense tells us that what makes human beings responsible has to do with their minds and, in particular, the relationship between their minds and their actions. Yet the empirical connection is not necessarily obvious. The “guilty mind” is a core concept of criminal law, but if a defendant (...)
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  28. Liquid Networks and the Metaphysics of Flux: Ontologies of Flow in an Age of Speed and Mobility.Thomas Sutherland - 2013 - Theory, Culture and Society 30 (5):3-23.
    It is common for social theorists to utilize the metaphors of ‘flow’, ‘fluidity’, and ‘liquidity’ in order to substantiate the ways in which speed and mobility form the basis for a new kind of information or network society. Yet rarely have these concepts been sufficiently theorized in order to establish their relevance or appropriateness. This article contends that the notion of flow as utilized in social theory is profoundly metaphysical in nature, and needs to be judged as such. Beginning (...)
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  29. Brain Function on the Basis of Biological Equilibrium - The Triggering Brain (2nd edition).Juergen Stueber - 2023 - Journal of Neurophilosophy 2023 (2(2)):432-452.
    A model of brain function is presented that is consistently based on the biological principle of equilibrium. The neuronal modules of the cerebral cortex are proposed as units in which equilibrium between incoming signals and the synaptic structure is determined or established. Because of the electromagnetic activity of the brain, the electromagnetic properties of thecells are brought into focus. Due to the synaptic changes of the modules -essentially during sleep -an electromagnetic resting balance between the modules is established. (...)
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  30. Brain, mind and limitations of a scientific theory of human consciousness.Alfred Gierer - 2008 - Bioessays 30 (5):499-505.
    In biological terms, human consciousness appears as a feature associated with the func- tioning of the human brain. The corresponding activities of the neural network occur strictly in accord with physical laws; however, this fact does not necessarily imply that there can be a comprehensive scientific theory of conscious- ness, despite all the progress in neurobiology, neuropsychology and neurocomputation. Pre- dictions of the extent to which such a theory may become possible vary widely in the scien- tific community. (...)
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  31. Quantum information theoretic approach to the mind–brain problem.Danko D. Georgiev - 2020 - Progress in Biophysics and Molecular Biology 158:16-32.
    The brain is composed of electrically excitable neuronal networks regulated by the activity of voltage-gated ion channels. Further portraying the molecular composition of the brain, however, will not reveal anything remotely reminiscent of a feeling, a sensation or a conscious experience. In classical physics, addressing the mind–brain problem is a formidable task because no physical mechanism is able to explain how the brain generates the unobservable, inner psychological world of conscious experiences and how in turn those (...)
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  32. Predicting Tumor Category Using Artificial Neural Networks.Ibrahim M. Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic Health and Medical Research (IJAHMR) 3 (2):1-7.
    In this paper an Artificial Neural Network (ANN) model, for predicting the category of a tumor was developed and tested. Taking patients’ tests, a number of information gained that influence the classification of the tumor. Such information as age, sex, histologic-type, degree-of-diffe, status of bone, bone-marrow, lung, pleura, peritoneum, liver, brain, skin, neck, supraclavicular, axillar, mediastinum, and abdominal. They were used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was established and (...)
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  33. Quantum propensities in the brain cortex and free will.Danko D. Georgiev - 2021 - Biosystems 208:104474.
    Capacity of conscious agents to perform genuine choices among future alternatives is a prerequisite for moral responsibility. Determinism that pervades classical physics, however, forbids free will, undermines the foundations of ethics, and precludes meaningful quantification of personal biases. To resolve that impasse, we utilize the characteristic indeterminism of quantum physics and derive a quantitative measure for the amount of free will manifested by the brain cortical network. The interaction between the central nervous system and the surrounding environment is (...)
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  34. 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 networks to (...)
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  35. Meeting the brain on its own terms.Philipp Haueis - 2014 - Frontiers in Human Neuroscience 815 (8):86890.
    In contemporary human brain mapping, it is commonly assumed that the “mind is what the brain does”. Based on that assumption, task-based imaging studies of the last three decades measured differences in brain activity that are thought to reflect the exercise of human mental capacities (e.g., perception, attention, memory). With the advancement of resting state studies, tractography and graph theory in the last decade, however, it became possible to study human brain connectivity without relying on cognitive (...)
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  36. Intrinsic brain activity of subcortical-cortical sensorimotor system and psychomotor alterations in schizophrenia and bipolar disorder.Timothy Joseph Lane - 2020 - Schizophrenia Research 215.
    Objective: Alterations in psychomotor dimension cut across different psychiatric disorders, such as schizophrenia (SCZ) and bipolar disorder (BD). This preliminary study aimed to investigate the organization of intrinsic brain activity in the subcortical-cortical sensorimotor system in SCZ (and BD) as characterized according to psychomotor dimension. -/- Method: In this resting-state functional magnetic resonance imaging (fMRI) study, functional connectivity (FC) between thalamus and sensorimotor network (SMN), along with FC from substantia nigra (SN) and raphe nuclei (RN) to basal ganglia (...)
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  37. Lalumera, E. 2017 Understanding schizophrenia through Wittgenstein: empathy, explanation, and philosophical clarification, in Schizophrenia and Common Sense, Hipólito, I., Gonçalves, J., Pereira, J. (eds.). SpringerNature, Mind-Brain Studies.E. Lalumera - 2018 - In I. Hipolito, Jorge Goncalves & J. Pereira (eds.), Schizophrenia and Common Sense, Hipólito, I., Gonçalves, J., Pereira, J. (eds.). SpringerNature, Mind-Brain Studies. Springer.
    Wittgenstein’s concepts shed light on the phenomenon of schizophrenia in at least three different ways: with a view to empathy, scientific explanation, or philosophical clarification. I consider two different “positive” wittgensteinian accounts―Campbell’s idea that delusions involve a mechanism of which different framework propositions are parts, Sass’ proposal that the schizophrenic patient can be described as a solipsist, and a Rhodes’ and Gipp’s account, where epistemic aspects of schizophrenia are explained as failures in the ordinary background of certainties. I argue that (...)
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  38. Effectiveness of Brain-Based Learning Toward Improving Students’ Conceptual Understanding: A Meta-Analysis (17th edition).Aaron Funa, Jhonner Ricafort, Frances Grace Jetomo & Nestor Lasala - 2024 - International Journal of Instruction 7 (1):361-380.
    This study explores the effectiveness of brain-based learning (BBL) as a pedagogical approach to address the challenges of poor conceptual understanding, which may have worsened due to the COVID-19 pandemic aftermath. In this meta- analysis, 14 studies qualified using the Publish or Perish software and the Preferred Reporting Items for Systematic Reviews and Meta-analyses. Statistical analysis conducted using Comprehensive Meta-Analysis (CMA) Version 4 software by Biostat, Inc. Based on the results, the overall effect size (ES = 3.135) indicates that (...)
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  39. Seven properties of self-organization in the human brain.Birgitta Dresp-Langley - 2020 - Big Data and Cognitive Computing 2 (4):10.
    The principle of self-organization has acquired a fundamental significance in the newly emerging field of computational philosophy. Self-organizing systems have been described in various domains in science and philosophy including physics, neuroscience, biology and medicine, ecology, and sociology. While system architecture and their general purpose may depend on domain-specific concepts and definitions, there are (at least) seven key properties of self-organization clearly identified in brain systems: 1) modular connectivity, 2) unsupervised learning, 3) adaptive ability, 4) functional resiliency, 5) functional (...)
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  40. Detection of Brain Tumor Using Deep Learning.Hamza Rafiq Almadhoun & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (3):29-47.
    Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and reacts like humans, some of the computer activities with artificial intelligence are designed to include speech, recognition, learning, planning and problem solving. Deep learning is a collection of algorithms used in machine learning, it is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is used as a (...)
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  41. Brain-Inspired Conscious Computing Architecture.Wlodzislaw Duch - 2005 - Journal of Mind and Behavior 26 (1-2):1-22.
    What type of artificial systems will claim to be conscious and will claim to experience qualia? The ability to comment upon physical states of a brain-like dynamical system coupled with its environment seems to be sufficient to make claims. The flow of internal states in such systems, guided and limited by associative memory, is similar to the stream of consciousness. A specific architecture of an artificial system, termed articon, is introduced that by its very design has to claim being (...)
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  42. Scientism, Philosophy and Brain-Based Learning.Gregory M. Nixon - 2013 - Northwest Journal of Teacher Education 11 (1):113-144.
    [This is an edited and improved version of "You Are Not Your Brain: Against 'Teaching to the Brain'" previously published in *Review of Higher Education and Self-Learning* 5(15), Summer 2012.] Since educators are always looking for ways to improve their practice, and since empirical science is now accepted in our worldview as the final arbiter of truth, it is no surprise they have been lured toward cognitive neuroscience in hopes that discovering how the brain learns will provide (...)
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  43. The Reality of Using Social Networks in Technical Colleges in Palestine.Samy S. Abu-Naser, Mazen J. Al Shobaki, Youssef M. Abu Amuna & Suliman A. El Talla - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (1):142-158.
    The study aimed to identify the reality of the use of social networks in the technical colleges in Palestine, where the variables of social networks were included. The analytical descriptive method was used in the study. A questionnaire consisting of (12) items was randomly distributed to college workers Technology in the Gaza Strip. The sample of the study consisted of (205) employees of these colleges. The response rate was 74.5%. The results showed a high degree of approval for the dimensions (...)
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  44. Group Argumentation Development through Philosophical Dialogues for Persons with Acquired Brain Injuries.Ylva Backman, Teodor Gardelli, Viktor Gardelli & Caroline Strömberg - 2020 - International Journal of Disability, Development and Education 67 (1):107-123.
    The high prevalence of brain injury incidents in adolescence and adulthood demands effective models for re-learning lost cognitive abilities. Impairment in brain injury survivors’ higher-level cognitive functions is common and a negative predictor for long-term outcome. We conducted two small-scale interventions (N = 12; 33.33% female) with persons with acquired brain injuries in two municipalities in Sweden. Age ranged from 17 to 65 years (M = 51.17, SD = 14.53). The interventions were dialogic, inquiry-based, and inspired by (...)
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  45. The social brain in psychiatric and neurological disorders.Daniel P. Kennedy & Ralph Adolphs - 2012 - Trends in Cognitive Sciences 16 (11):559-572.
    Psychiatric and neurological disorders have historically provided key insights into the structure-function rela- tionships that subserve human social cognition and behavior, informing the concept of the ‘social brain’. In this review, we take stock of the current status of this concept, retaining a focus on disorders that impact social behavior. We discuss how the social brain, social cognition, and social behavior are interdependent, and emphasize the important role of development and com- pensation. We suggest that the social (...), and its dysfunction and recovery, must be understood not in terms of specific structures, but rather in terms of their interaction in large-scale networks. (shrink)
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  46. Empiricism without Magic: Transformational Abstraction in Deep Convolutional Neural Networks.Cameron Buckner - 2018 - Synthese (12):1-34.
    In artificial intelligence, recent research has demonstrated the remarkable potential of Deep Convolutional Neural Networks (DCNNs), which seem to exceed state-of-the-art performance in new domains weekly, especially on the sorts of very difficult perceptual discrimination tasks that skeptics thought would remain beyond the reach of artificial intelligence. However, it has proven difficult to explain why DCNNs perform so well. In philosophy of mind, empiricists have long suggested that complex cognition is based on information derived from sensory experience, often appealing to (...)
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  47. Mathematical Cognition: Brain and Cognitive Research and Its Implications for Education.Qi Dong, Hong-Chuan Zhang & Xin-lin Zhou - 2019 - Journal of Human Cognition 3 (1):25-40.
    Mathematical cognition is one of the most important cognitive functions of human beings. The latest brain and cognitive research have shown that mathematical cognition is a system with multiple components and subsystems. It has phylogenetic root, also is related to ontogenetic development and learning, relying on a large-scale cerebral network including parietal, frontal and temporal regions. Especially, the parietal cortex plays an important role during mathematical cognitive processes. This indicates that language and visuospatial functions are both key to (...)
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  48. Is there an Aesthetic Brain? A brief Essay on the Neuroaesthetic Quantification of beauty.Paulo Alexandre E. Castro - 2021 - In Joaquim Braga & Simone Guidi (eds.), Quantifying Bodies and Health. Interdisciplinary Approaches. Coimbra: Instituto de Estudos Filosóficos. pp. 127-138.
    It is possible today to determine, with some precision (according to the most recent studies in neuroscience and evolutionary psychology), the areas of the brain and the neural networks involved when an individual contemplates art, when feeling pleasure, or when judging about aesthetic experience. However, many questions remain open. First, the philosophical question about the subjective nature of this kind of judgments. Then, what happens in the mind (or should it be said, in the brain?) of the beholder (...)
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  49. Persons Versus Brains: Biological Intelligence in Human Organisms.E. Steinhart - 2001 - Biology and Philosophy 16 (1):3-27.
    I go deep into the biology of the human organism to argue that the psychological features and functions of persons are realized by cellular and molecular parallel distributed processing networks dispersed throughout the whole body. Persons supervene on the computational processes of nervous, endocrine, immune, and genetic networks. Persons do not go with brains.
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  50. Science Meets Philosophy: Metaphysical Gap & Bilateral Brain.Hermann G. W. Burchard - 2020 - Philosophy Study 10 (10):599-614.
    The essay brings a summation of human efforts seeking to understand our existence. Plato and Kant & cognitive science complete reduction of philosophy to a neural mechanism, evolved along elementary Darwinian principles. Plato in his famous Cave Allegory explains that between reality and our experience of it there exists a great chasm, a metaphysical gap, fully confirmed through particle-wave duality of quantum physics. Kant found that we have two kinds of perception, two senses: By the spatial outer sense we perceive (...)
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