Results for 'neural control'

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  1. Adaptive Control using Nonlinear Autoregressive-Moving Average-L2 Model for Realizing Neural Controller for Unknown Finite Dimensional Nonlinear Discrete Time Dynamical Systems.Mustefa Jibril, Mesay Tadesse & Nurye Hassen - 2021 - Journal of Engineering and Applied Sciences 16 (3):130-137.
    This study considers the problem of using approximate way for realizing the neural supervisor for nonlinear multivariable systems. The Nonlinear Autoregressive-Moving Average (NARMA) model is an exact transformation of the input-output behavior of finite-dimensional nonlinear discrete time dynamical organization in a hoodlum of the equilibrium state. However, it is not convenient for intention of adaptive control using neural networks due to its nonlinear dependence on the control input. Hence, quite often, approximate technique are used for realizing (...)
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  2. Comparison of Neural Network NARMA-L2 Model Reference and Predictive Controllers for Electromagnetic Space Vehicle Suspension System.Mustefa Jibril, Mesay Tadesse & Nurye Hassen - 2021 - Journal of Engineering and Applied Sciences 16 (10):313-317.
    Electromagnetic Suspension System (EMS) is mostly used in the field of high-speed vehicle. In this study, a space exploring vehicle quarter electromagnetic suspension system is modelled, designed and simulated using Neural network-based control problem. NARMA-L2, Model reference and predictive controllers are designed to improve the body travel of the vehicle using bump road profile. Comparison between the proposed controllers is done and a promising simulation result have been analyzed.
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  3. Comparison of neural network NARMA-L2 model reference and predictive controllers for nonlinear quarter car active suspension system.Mustefa Jibril - 2020 - International Research Journal of Modernization in Engineering Technology and Science 2 (3):178-188.
    Recently, active suspension system will become important to the vehicle industries because of its advantages in improving road managing and ride comfort. This paper offers the development of mathematical modelling and design of a neural network control approach. The paper will begin with a mathematical model designing primarily based at the parameters of the active suspension system. A nonlinear three by four-way valve-piston hydraulic actuator became advanced which will make the suspension system under the active condition. Then, the (...)
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  4. DC motor speed control with the presence of input disturbance using neural network based model reference and predictive controllers.Mustefa Jibril - 2020 - International Research Journal of Modernization in Engineering Technology and Science 2 (4):103-110.
    In this paper we describe a technical system for DC motor speed control. The speed of DC motor is controlled using Neural Network Based Model Reference and Predictive controllers with the use of Matlab/Simulink. The analysis of the DC motor is done with and without input side Torque disturbance input and the simulation results obtained by comparing the desired and actual speed of the DC motor using random reference and sinusoidal speed inputs for the DC motor with Model (...)
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  5. Comparison of Neural Network Based Controllers for Nonlinear EMS Magnetic Levitation Train.Mustefa Jibril, Elias Alemayehu & Mesay Tadesse - 2020 - International Journal of Advance Research and Innovative Ideas in Education 6 (2):801-807.
    Magnetic levitation system is operated primarily based at the principle of magnetic attraction and repulsion to levitate the passengers and the train. However, magnetic levitation trains are rather nonlinear and open loop unstable which makes it hard to govern. In this paper, investigation, design and control of a nonlinear Maglev train based on NARMA-L2, model reference and predictive controllers. The response of the Maglev train with the proposed controllers for the precise role of a Magnetic levitation machine have been (...)
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  6. Comparison of Neural Network NARMA-L2 Model Reference and Predictive Controllers for Nonlinear EMS Magnetic Levitation Train.Mustefa Jibril & Eliyas Alemayehu - 2020 - Report and Opinion Journal 12 (5):21-25.
    Magnetic levitation system is operated primarily based at the principle of magnetic attraction and repulsion to levitate the passengers and the train. However, magnetic levitation trains are rather nonlinear and open loop unstable which makes it hard to govern. In this paper, investigation, design and control of a nonlinear Maglev train based on NARMA-L2, model reference and predictive controllers. The response of the Maglev train with the proposed controllers for the precise role of a Magnetic levitation machine have been (...)
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  7. Design and Control of Steam Flow in Cement Production Process using Neural Network Based Controllers.Mustefa Jibril - 2020 - Researcher 12 (5):76-84.
    In this paper a NARMA L2, model reference and neural network predictive controller is utilized in order to control the output flow rate of the steam in furnace by controlling the steam flow valve. The steam flow control system is basically a feedback control system which is mostly used in cement production industries. The design of the system with the proposed controllers is done with Matlab/Simulink toolbox. The system is designed for the actual steam flow output (...)
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  8. The Neural Substrates of Conscious Perception without Performance Confounds.Jorge Morales, Brian Odegaard & Brian Maniscalco - forthcoming - In Felipe De Brigard & Walter Sinnott-Armstrong (eds.), Anthology of Neuroscience and Philosophy.
    To find the neural substrates of consciousness, researchers compare subjects’ neural activity when they are aware of stimuli against neural activity when they are not aware. Ideally, to guarantee that the neural substrates of consciousness—and nothing but the neural substrates of consciousness—are isolated, the only difference between these two contrast conditions should be conscious awareness. Nevertheless, in practice, it is quite challenging to eliminate confounds and irrelevant differences between conscious and unconscious conditions. In particular, there (...)
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  9. Artificial Neural Network for Global Smoking Trend.Aya Mazen Alarayshi & Samy S. Abu-Naser - 2023 - International Journal of Academic Information Systems Research (IJAISR) 7 (9):55-61.
    Accurate assessment and comprehension of smoking behavior are pivotal for elucidating associated health risks and formulating effective public health strategies. In this study, we introduce an innovative approach to predict and analyze smoking prevalence using an artificial neural network (ANN) model. Leveraging a comprehensive dataset spanning multiple years and geographic regions, our model incorporates various features, including demographic data, economic indicators, and tobacco control policies. This research investigates smoking trends with a specific focus on gender-based analyses. These findings (...)
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  10. Recentering neuroscience on behavior: The interface between brain and environment is a privileged level of control of neural activity.Igor Branchi - 2022 - Neuroscience and Biobehavioral Reviews 138.
    Despite the huge and constant progress in the molecular and cellular neuroscience fields, our capability to understand brain alterations and treat mental illness is still limited. Therefore, a paradigm shift able to overcome such limitation is warranted. Behavior and the associated mental states are the interface between the central nervous system and the living environment. Since, in any system, the interface is a key regulator of system organization, behavior is proposed here as a unique and privileged level of control (...)
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  11. Control Consciousness.Pete Mandik - 2010 - Topics in Cognitive Science 2 (4):643-657.
    Control consciousness is the awareness or experience of seeming to be in control of one’s actions. One view, which I will be arguing against in the present paper, is that control consciousness is a form of sensory consciousness. In such a view, control consciousness is exhausted by sensory elements such as tactile and proprioceptive information. An opposing view, which I will be arguing for, is that sensory elements cannot be the whole story and must be supplemented (...)
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  12. Neural and Environmental Modulation of Motivation: What's the Moral Difference?Thomas Douglas - forthcoming - In David Birks & Thomas Douglas (eds.), Treatment for Crime: Philosophical Essays on Neurointerventions in Criminal Justice. Oxford: Oxford University Press.
    Interventions that modify a person’s motivations through chemically or physically influencing the brain seem morally objectionable, at least when they are performed nonconsensually. This chapter raises a puzzle for attempts to explain their objectionability. It first seeks to show that the objectionability of such interventions must be explained at least in part by reference to the sort of mental interference that they involve. It then argues that it is difficult to furnish an explanation of this sort. The difficulty is that (...)
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  13. Controlling for performance capacity confounds in neuroimaging studies of conscious awareness.Jorge Morales, Jeffrey Chiang & Hakwan Lau - 2015 - Neuroscience of Consciousness 1:1-11.
    Studying the neural correlates of conscious awareness depends on a reliable comparison between activations associated with awareness and unawareness. One particularly difficult confound to remove is task performance capacity, i.e. the difference in performance between the conditions of interest. While ideally task performance capacity should be matched across different conditions, this is difficult to achieve experimentally. However, differences in performance could theoretically be corrected for mathematically. One such proposal is found in a recent paper by Lamy, Salti and Bar-Haim (...)
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  14. The Grossberg Code: Universal Neural Network Signatures of Perceptual Experience.Birgitta Dresp-Langley - 2023 - Information 14 (2):1-82.
    Two universal functional principles of Grossberg’s Adaptive Resonance Theory decipher the brain code of all biological learning and adaptive intelligence. Low-level representations of multisensory stimuli in their immediate environmental context are formed on the basis of bottom-up activation and under the control of top-down matching rules that integrate high-level, long-term traces of contextual configuration. These universal coding principles lead to the establishment of lasting brain signatures of perceptual experience in all living species, from aplysiae to primates. They are re-visited (...)
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  15. Cultural Influences on the Neural Correlate of Moral Decision Making Processes.Hyemin Han, Gary H. Glover & Changwoo Jeong - 2014 - Behavioural Brain Research 259:215-228.
    This study compares the neural substrate of moral decision making processes between Korean and American participants. By comparison with Americans, Korean participants showed increased activity in the right putamen associated with socio-intuitive processes and right superior frontal gyrus associated with cognitive control processes under a moral-personal condition, and in the right postcentral sulcus associated with mental calculation in familiar contexts under a moral-impersonal condition. On the other hand, American participants showed a significantly higher degree of activity in the (...)
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  16. The Grossberg Code: Universal Neural Network Signatures of Perceptual Experience.Birgitta Dresp-Langley - 2023 - Information 14 (2):e82 1-17..
    Two universal functional principles of Grossberg’s Adaptive Resonance Theory [19] decipher the brain code of all biological learning and adaptive intelligence. Low-level representations of multisensory stimuli in their immediate environmental context are formed on the basis of bottom-up activation and under the control of top-down matching rules that integrate high-level long-term traces of contextual configuration. These universal coding principles lead to the establishment of lasting brain signatures of perceptual experience in all living species, from aplysiae to primates. They are (...)
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  17. Evolving Self-taught Neural Networks: The Baldwin Effect and the Emergence of Intelligence.Nam Le - 2019 - In AISB Annual Convention 2019 -- 10th Symposium on AI & Games.
    The so-called Baldwin Effect generally says how learning, as a form of ontogenetic adaptation, can influence the process of phylogenetic adaptation, or evolution. This idea has also been taken into computation in which evolution and learning are used as computational metaphors, including evolving neural networks. This paper presents a technique called evolving self-taught neural networks – neural networks that can teach themselves without external supervision or reward. The self-taught neural network is intrinsically motivated. Moreover, the self-taught (...)
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  18. Leveraging Artificial Neural Networks for Cancer Prediction: A Synthetic Dataset Approach.Mohammed S. Abu Nasser & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (11):43-51.
    Abstract: This research explores the application of artificial neural networks (ANNs) in predicting cancer using a synthetically generated dataset designed for research purposes. The dataset comprises 10,000 pseudo-patient records, each characterized by gender, age, smoking history, fatigue, and allergy status, along with a binary indicator for the presence or absence of cancer. The 'Gender,' 'Smoking,' 'Fatigue,' and 'Allergy' attributes are binary, while 'Age' spans a range from 18 to 100 years. The study employs a three-layer ANN architecture to develop (...)
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  19. Beyond cognitive myopia: a patchwork approach to the concept of neural function.Philipp Haueis - 2018 - Synthese 195 (12):5373-5402.
    In this paper, I argue that looking at the concept of neural function through the lens of cognition alone risks cognitive myopia: it leads neuroscientists to focus only on mechanisms with cognitive functions that process behaviorally relevant information when conceptualizing “neural function”. Cognitive myopia tempts researchers to neglect neural mechanisms with noncognitive functions which do not process behaviorally relevant information but maintain and repair neural and other systems of the body. Cognitive myopia similarly affects philosophy of (...)
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  20. The Cognitive Gap, Neural Darwinism & Linguistic Dualism —Russell, Husserl, Heidegger & Quine.Hermann G. W. Burchard - 2014 - Open Journal of Philosophy 4 (3):244-264.
    Guided by key insights of the four great philosophers mentioned in the title, here, in review of and expanding on our earlier work (Burchard, 2005, 2011), we present an exposition of the role played by language, & in the broader sense, λογοζ, the Logos, in how the CNS, the brain, is running the human being. Evolution by neural Darwinism has been forcing the linguistic nature of mind, enabling it to overcome & exploit the cognitive gap between an animal and (...)
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  21. Losing control: the hidden role of motor areas in decision-making.Owen P. O'Sullivan - 2014 - Dialogues in Philosophy, Mental and Neuro Sciences 7 (2):45-49.
    Decision-making has traditionally been viewed as detached from the neural systems of sensory perception and motor function. Consequently, motor areas have played a relatively minor role in discussions surrounding the control processes and neural origins of decision-making. Empiric evidence, catalysed by technological advances in the past two decades, has proven that motor areas have an integral role in decision-making. They are involved in the generation, modulation, maintenance and execution of decisions and actions. They also take part in (...)
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    Vascular-metabolic and GABAergic Inhibitory Correlates of Neural Variability Modulation. A Combined fMRI and PET Study.Timothy J. Lane - 2018 - Neuroscience 379:142-151.
    Neural activity varies continually from moment to moment. Such temporal variability (TV) has been highlighted as a functionally specific brain property playing a fundamental role in cognition. We sought to investigate the mechanisms involved in TV changes between two basic behavioral states, namely having the eyes open (EO) or eyes closed (EC) in vivo in humans. To these ends we acquired BOLD fMRI, ASL, and [18F]-fluoro-deoxyglucose PET in a group of healthy participants (n = 15), along with BOLD fMRI (...)
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  23.  27
    Pistachio Variety Classification using Convolutional Neural Networks.Ahmed S. Sabah & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):113-119.
    Abstract: Pistachio nuts are a valuable source of nutrition and are widely cultivated for commercial purposes. The accurate classification of different pistachio varieties is important for quality control and market analysis. In this study, we propose a new model for the classification of different pistachio varieties using Convolutional Neural Networks (CNNs). We collected a dataset of pistachio images form Kaggle depository with two varieties (Kirmizi and Siirt). The images were then preprocessed and used to train a CNN model (...)
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  24. Novel Tool Development and the Dynamics of Control: The Rodent Touchscreen Operant Chamber as a Case Study.Jacqueline Anne Sullivan - 2022 - Philosophy of Science 89 (5):1-19.
    In the quest to discover the neural bases of cognition, rigorous behavioral tools are equally as important as sophisticated tools for neural intervention. This paper evaluates several episodes in the development of a novel behavioral tool for rodent cognitive testing, the rodent touchscreen operant chamber. Using conceptual tools on offer in the philosophical literature on exploratory experimentation and control, I illuminate how optimization of this behavioral tool and an understanding of the causal knowledge it may be used (...)
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  25. Inverted Pendulum Control using NARMA-l2 with Resilient Backpropagation and Levenberg Marquardt Backpropagation Training Algorithm.Mustefa Jibril, Mesay Tadesse & Nurye Hassen - 2021 - Journal of Engineering and Applied Sciences 16 (10):324-330.
    In this study, the performance of inverted pendulum has been Investigated using neural network control theory. The proposed controllers used in this study are NARMA-L2 with Resilient backpropagation and Levenberg Marquardt backpropagation algorithm controllers. The mathematical model of Inverted Pendulum on a Cart driving mechanism have been done successfully. Comparison of an inverted pendulum with NARMA-L2 with Resilient backpropagation and Levenberg Marquardt backpropagation algorithm controllers for a control target deviation of an angle from vertical of the inverted (...)
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  26. 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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  27. Punishment and psychopathy: a case-control functional MRI investigation of reinforcement learning in violent antisocial personality disordered men.Sarah Gregory, R. James Blair, Dominic Ffytche, Andrew Simmons, Veena Kumari, Sheilagh Hodgins & Nigel Blackwood - 2014 - Lancet Psychiatry 2:153–160.
    Background Men with antisocial personality disorder show lifelong abnormalities in adaptive decision making guided by the weighing up of reward and punishment information. Among men with antisocial personality disorder, modifi cation of the behaviour of those with additional diagnoses of psychopathy seems particularly resistant to punishment. Methods We did a case-control functional MRI (fMRI) study in 50 men, of whom 12 were violent off enders with antisocial personality disorder and psychopathy, 20 were violent off enders with antisocial personality disorder (...)
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  28. Semantics and Metaphysics in Informatics: Toward an Ontology of Tasks (a Reply to Lenartowicz et al. 2010, Towards an Ontology of Cognitive Control).Carrie Figdor - 2011 - Topics in Cognitive Science 3 (2):222-226.
    This article clarifies three principles that should guide the development of any cognitive ontology. First, that an adequate cognitive ontology depends essentially on an adequate task ontology; second, that the goal of developing a cognitive ontology is independent of the goal of finding neural implementations of the processes referred to in the ontology; and third, that cognitive ontologies are neutral regarding the metaphysical relationship between cognitive and neural processes.
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  29. Using neurons to maintain autonomy: Learning from C. elegans.William Bechtel & Leonardo Bich - 2023 - Biosystems 232:105017.
    Understanding how biological organisms are autonomous—maintain themselves far from equilibrium through their own activities—requires understanding how they regulate those activities. In multicellular animals, such control can be exercised either via endocrine signaling through the vasculature or via neurons. In C. elegans this control is exercised by a well-delineated relatively small but distributed nervous system that relies on both chemical and electric transmission of signals. This system provides resources to integrate information from multiple sources as needed to maintain the (...)
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  30. Neurodemocracy: Self-Organization of the Embodied Mind.Linus Huang - 2017 - Dissertation, University of Sydney
    This thesis contributes to a better conceptual understanding of how self-organized control works. I begin by analyzing the control problem and its solution space. I argue that the two prominent solutions offered by classical cognitive science (centralized control with rich commands, e.g., the Fodorian central systems) and embodied cognitive science (distributed control with simple commands, such as the subsumption architecture by Rodney Brooks) are merely two positions in a two-dimensional solution space. I outline two alternative positions: (...)
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  31. The Idea of Will.M. M. Dorenbosch - 2015 - Journal of Consciousness Exploration and Research 6 (7):449-472.
    This article presents a new conceptual view on the conscious will. This new concept approaches our will from the perspective of the requirements of our neural-muscular system and not from our anthropocentric perspective. This approach not only repositions the will at the core of behavior control, it also integrates the studies of Libet and Wegner, which seem to support the opposite. The will does not return as an instrument we use to steer, but rather as part of the (...)
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  32. The CNS-independent consciousness system: the model system of all nature and the framework of all sciences.Jin Ma -
    This paper presents the unification of all knowledge and the framework of all sciences, so it goes the theory of consciousness, the method to measure consciousness, and the three keys of the Strong AI. “Logicality and non-absoluteness” is found out to be the intrinsicality of nature, so the “Fundamental Law of Nature” is discovered. Then, the “general methodology of research” and the “model system of nature” are developed to explain everything, especially consciousness. The Coupling Theory of Consciousness tells that nature (...)
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  33. Why we may not find intentions in the brain.Sebo Uithol, Daniel C. Burnston & Pim Haselager - 2014 - Neuropsychologia 56 (5):129-139.
    Intentions are commonly conceived of as discrete mental states that are the direct cause of actions. In the last several decades, neuroscientists have taken up the project of finding the neural implementation of intentions, and a number of areas have been posited as implementing these states. We argue, however, that the processes underlying action initiation and control are considerably more dynamic and context sensitive than the concept of intention can allow for. Therefore, adopting the notion of ‘intention’ in (...)
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  34. The role of experience in demonstrative thought.Michael Barkasi - 2019 - Mind and Language 34 (5):648-666.
    Attention plays a role in demonstrative thought: It sets the targets. Visual experience also plays a role. I argue here that it makes visual information available for use in the voluntary control of focal attention. To do so I use both introspection and neurophysiological evidence from projections between areas of attentional control and neural correlates of consciousness. Campbell and Smithies also identify roles for experience, but they further argue that only experience can play those roles. In contrast, (...)
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  35. How Subjects Can Emerge from Neurons.Eric LaRock & Mostyn Jones - 2019 - Process Studies 48 (1):40-58.
    We pose a foundational problem for those who claim that subjects are ontologically irreducible, but causally reducible (weak emergence). This problem is neuroscience’s notorious binding problem, which concerns how distributed neural areas produce unified mental objects (such as perceptions) and the unified subject that experiences them. Synchrony, synapses and other mechanisms cannot explain this. We argue that this problem seriously threatens popular claims that mental causality is reducible to neural causality. Weak emergence additionally raises evolutionary worries about how (...)
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  36. The 'Hard Problem' of Phenomenal Perception.Dieter Wandschneider - 2015 - Zeitschrift für Philosophische Forschung 69:550–568.
    The center of this investigation is the hard problem of phenomenal perception. To be clear, hereby it is thought of higher animals; accordingly the problem of Human consciousness will explicitly not be treated. The so-called explanatory gap (Levine), i.e. missing a neural explanation of experiences, here is emergence-theoretically countered: It is argued that systems own properties and laws different from those of their components. Applied to the brain the phenomenal character of perception is explained as an emergence effect from (...)
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  37. Conscious Action/Zombie Action.Joshua Shepherd - 2016 - Noûs 50 (2):419-444.
    I argue that the neural realizers of experiences of trying are not distinct from the neural realizers of actual trying . I then ask how experiences of trying might relate to the perceptual experiences one has while acting. First, I assess recent zombie action arguments regarding conscious visual experience, and I argue that contrary to what some have claimed, conscious visual experience plays a causal role for action control in some circumstances. Second, I propose a multimodal account (...)
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  38. Fisiologia do Ciclo Estral dos Animais Domésticos.Emanuel Isaque Cordeiro da Silva -
    FISIOLOGIA DO CICLO ESTRAL DOS ANIMAIS -/- Departamento de Zootecnia – UFRPE Embrapa Semiárido e IPA -/- • _____OBJETIVO -/- O cio ou estro é a fase reprodutiva dos animais, onde as fêmeas apresentam receptividade sexual seguida de ovulação. Para tanto, é necessário entender a fisiologia do estro para a realização do manejo reprodutivo dos animais. Em geral, as fêmeas manifestam comportamentos fora do comum quando estão ciclando, tais comportamentos devem ser observados para que não percam o pico de ovulação (...)
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  39. Agency, qualia and life: connecting mind and body biologically.David Longinotti - 2017 - In Vincent C. Müller (ed.), Philosophy and theory of artificial intelligence 2017. Berlin: Springer. pp. 43-56.
    Many believe that a suitably programmed computer could act for its own goals and experience feelings. I challenge this view and argue that agency, mental causation and qualia are all founded in the unique, homeostatic nature of living matter. The theory was formulated for coherence with the concept of an agent, neuroscientific data and laws of physics. By this method, I infer that a successful action is homeostatic for its agent and can be caused by a feeling - which does (...)
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  40. A property cluster theory of cognition.Cameron Buckner - 2013 - Philosophical Psychology (3):1-30.
    Our prominent definitions of cognition are too vague and lack empirical grounding. They have not kept up with recent developments, and cannot bear the weight placed on them across many different debates. I here articulate and defend a more adequate theory. On this theory, behaviors under the control of cognition tend to display a cluster of characteristic properties, a cluster which tends to be absent from behaviors produced by non-cognitive processes. This cluster is reverse-engineered from the empirical tests that (...)
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  41. The Problem of Mental Action.Thomas Metzinger - 2017 - Philosophy and Predicitive Processing.
    In mental action there is no motor output to be controlled and no sensory input vector that could be manipulated by bodily movement. It is therefore unclear whether this specific target phenomenon can be accommodated under the predictive processing framework at all, or if the concept of “active inference” can be adapted to this highly relevant explanatory domain. This contribution puts the phenomenon of mental action into explicit focus by introducing a set of novel conceptual instruments and developing a first (...)
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  42. Domain-general and Domain-specific Patterns of Activity Support Metacognition in Human Prefrontal Cortex.Jorge Morales, Hakwan Lau & Stephen M. Fleming - 2018 - The Journal of Neuroscience 38 (14):3534-3546.
    Metacognition is the capacity to evaluate the success of one's own cognitive processes in various domains; for example, memory and perception. It remains controversial whether metacognition relies on a domain-general resource that is applied to different tasks or if self-evaluative processes are domain specific. Here, we investigated this issue directly by examining the neural substrates engaged when metacognitive judgments were made by human participants of both sexes during perceptual and memory tasks matched for stimulus and performance characteristics. By comparing (...)
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  43. Forecasting COVID-19 cases Using ANN.Ibrahim Sufyan Al-Baghdadi & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (10):22-31.
    Abstract: The COVID-19 pandemic has posed unprecedented challenges to global healthcare systems, necessitating accurate and timely forecasting of cases for effective mitigation strategies. In this research paper, we present a novel approach to predict COVID-19 cases using Artificial Neural Networks (ANNs), harnessing the power of machine learning for epidemiological forecasting. Our ANNs-based forecasting model has demonstrated remarkable efficacy, achieving an impressive accuracy rate of 97.87%. This achievement underscores the potential of ANNs in providing precise and data-driven insights into the (...)
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  44. Costs and Benefits of Realism and Optimism.Lisa Bortolotti & Magdalena Antrobus - 2015 - Current Opinion in Psychiatry 28 (2):194-198.
    Purpose of review: What is the relationship between rationality and mental health? By considering the psychological literature on depressive realism and unrealistic optimism it was hypothesized that, in the context of judgments about the self, accurate cognitions are psychologically maladaptive and inaccurate cognitions are psychologically adaptive. Recent studies recommend being cautious in drawing any general conclusion about style of thinking and mental health. Recent findings: Recent investigations suggest that people with depressive symptoms are more accurate than controls in tasks involving (...)
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  45. From Biological Synapses to "Intelligent" Robots.Birgitta Dresp-Langley - 2022 - Electronics 11:1-28.
    This selective review explores biologically inspired learning as a model for intelligent robot control and sensing technology on the basis of specific examples. Hebbian synaptic learning is discussed as a functionally relevant model for machine learning and intelligence, as explained on the basis of examples from the highly plastic biological neural networks of invertebrates and vertebrates. Its potential for adaptive learning and control without supervision, the generation of functional complexity, and control architectures based on self-organization is (...)
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  46. Psychopower and Ordinary Madness: Reticulated Dividuals in Cognitive Capitalism.Ekin Erkan - 2019 - Cosmos and History 15 (1):214-241.
    Despite the seemingly neutral vantage of using nature for widely-distributed computational purposes, neither post-biological nor post-humanist teleology simply concludes with the real "end of nature" as entailed in the loss of the specific ontological status embedded in the identifier "natural." As evinced by the ecological crises of the Anthropocene—of which the 2019 Brazil Amazon rainforest fires are only the most recent—our epoch has transfixed the “natural order" and imposed entropic artificial integration, producing living species that become “anoetic,” made to serve (...)
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  47. From what to how: an initial review of publicly available AI ethics tools, methods and research to translate principles into practices.Jessica Morley, Luciano Floridi, Libby Kinsey & Anat Elhalal - 2020 - Science and Engineering Ethics 26 (4):2141-2168.
    The debate about the ethical implications of Artificial Intelligence dates from the 1960s :741–742, 1960; Wiener in Cybernetics: or control and communication in the animal and the machine, MIT Press, New York, 1961). However, in recent years symbolic AI has been complemented and sometimes replaced by Neural Networks and Machine Learning techniques. This has vastly increased its potential utility and impact on society, with the consequence that the ethical debate has gone mainstream. Such a debate has primarily focused (...)
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  48. Sculpting the space of actions. Explaining human action by integrating intentions and mechanisms.Machiel Keestra - 2014 - Dissertation, University of Amsterdam
    How can we explain the intentional nature of an expert’s actions, performed without immediate and conscious control, relying instead on automatic cognitive processes? How can we account for the differences and similarities with a novice’s performance of the same actions? Can a naturalist explanation of intentional expert action be in line with a philosophical concept of intentional action? Answering these and related questions in a positive sense, this dissertation develops a three-step argument. Part I considers different methods of explanations (...)
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  49. Optogenetics, Pluralism, and Progress.Jacqueline Anne Sullivan - 2018 - Philosophy of Science 85 (00):1090-1101.
    Optogenetic techniques are described as “revolutionary” for the unprecedented causal control they allow neuroscientists to exert over neural activity in awake behaving animals. In this paper, I demonstrate by means of a case study that optogenetic techniques will only illuminate causal links between the brain and behavior to the extent that their error characteristics are known and, further, that determining these error characteristics requires comparison of optogenetic techniques with techniques having well known error characteristics and consideration of the (...)
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  50. Psychophysical evidence for low-level processing of illusory contours and surfaces in the Kanizsa square.Birgitta Dresp & Claude Bonnet - 1991 - Vision Research 31:1813-1817.
    Light increment thresholds were measured on either side of one of the illusory contours of a white-on-black Kanizsa square and on the illusory contour itself. The data show that thresholds are elevated when measured on either side of the illusory border. These elevations diminish with increasing distance of the target spot from the white elements which induce the illusory figure. The most striking result, however, is that threshold elevations are considerably lower or even absent when the target is located on (...)
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