JEAN DECETY, M.SCI., PH.D. Irving B
Total Page：16
File Type：pdf, Size：1020Kb
Load more
Recommended publications
-
Volume 3 Summer 2012
Volume 3 Summer 2012 . Academic Partners . Cover image Magnetic resonance image of the human brain showing colour-coded regions activated by smell stimulus. Editors Ulisses Barres de Almeida Max-Planck-Institut fuer Physik [email protected] Juan Rojo TH Unit, PH Division, CERN [email protected] [email protected] Academic Partners Fondazione CEUR Consortium Nova Universitas Copyright ©2012 by Associazione EURESIS The user may not modify, copy, reproduce, retransmit or otherwise distribute this publication and its contents (whether text, graphics or original research content), without express permission in writing from the Editors. Where the above content is directly or indirectly reproduced in an academic context, this must be acknowledge with the appropriate bibliographical citation. The opinions stated in the papers of the Euresis Journal are those of their respective authors and do not necessarily reflect the opinions of the Editors or the members of the Euresis Association or its sponsors. Euresis Journal (ISSN 2239-2742), a publication of Associazione Euresis, an Association for the Promotion of Scientific Endevour, Via Caduti di Marcinelle 2, 20134 Milano, Italia. www.euresisjournal.org Contact information: Email. [email protected] Tel.+39-022-1085-2225 Fax. +39-022-1085-2222 Graphic design and layout Lorenzo Morabito Technical Editor Davide PJ Caironi This document was created using LATEX 2" and X LE ATEX 2 . Letter from the Editors Dear reader, with this new issue we reach the third volume of Euresis Journal, an editorial ad- venture started one year ago with the scope of opening up a novel space of debate and encounter within the scientific and academic communities. -
Optimization of Deep Architectures for EEG Signal Classification
sensors Article Optimization of Deep Architectures for EEG Signal Classification: An AutoML Approach Using Evolutionary Algorithms Diego Aquino-Brítez 1, Andrés Ortiz 2,* , Julio Ortega 1, Javier León 1, Marco Formoso 2 , John Q. Gan 3 and Juan José Escobar 1 1 Department of Computer Architecture and Technology, University of Granada, 18014 Granada, Spain; [email protected] (D.A.-B.); [email protected] (J.O.); [email protected] (J.L.); [email protected] (J.J.E.) 2 Department of Communications Engineering, University of Málaga, 29071 Málaga, Spain; [email protected] 3 School of Computer Science and Electronic Engineering, University of Essex, Colchester CO4 3SQ, UK; [email protected] * Correspondence: [email protected] Abstract: Electroencephalography (EEG) signal classification is a challenging task due to the low signal-to-noise ratio and the usual presence of artifacts from different sources. Different classification techniques, which are usually based on a predefined set of features extracted from the EEG band power distribution profile, have been previously proposed. However, the classification of EEG still remains a challenge, depending on the experimental conditions and the responses to be captured. In this context, the use of deep neural networks offers new opportunities to improve the classification performance without the use of a predefined set of features. Nevertheless, Deep Learning architec- Citation: Aquino-Brítez, D.; Ortiz, tures include a vast number of hyperparameters on which the performance of the model relies. In this A.; Ortega, J.; León, J.; Formoso, M.; paper, we propose a method for optimizing Deep Learning models, not only the hyperparameters, Gan, J.Q.; Escobar, J.J. -
A Neuroevolution Approach to Imitating Human-Like Play in Ms
A Neuroevolution Approach to Imitating Human-Like Play in Ms. Pac-Man Video Game Maximiliano Miranda, Antonio A. S´anchez-Ruiz, and Federico Peinado Departamento de Ingenier´ıadel Software e Inteligencia Artificial Universidad Complutense de Madrid c/ Profesor Jos´eGarc´ıaSantesmases 9, 28040 Madrid (Spain) [email protected] - [email protected] - [email protected] http://www.narratech.com Abstract. Simulating human behaviour when playing computer games has been recently proposed as a challenge for researchers on Artificial Intelligence. As part of our exploration of approaches that perform well both in terms of the instrumental similarity measure and the phenomeno- logical evaluation by human spectators, we are developing virtual players using Neuroevolution. This is a form of Machine Learning that employs Evolutionary Algorithms to train Artificial Neural Networks by consider- ing the weights of these networks as chromosomes for the application of genetic algorithms. Results strongly depend on the fitness function that is used, which tries to characterise the human-likeness of a machine- controlled player. Designing this function is complex and it must be implemented for specific games. In this work we use the classic game Ms. Pac-Man as an scenario for comparing two different methodologies. The first one uses raw data extracted directly from human traces, i.e. the set of movements executed by a real player and their corresponding time stamps. The second methodology adds more elaborated game-level parameters as the final score, the average distance to the closest ghost, and the number of changes in the player's route. We assess the impor- tance of these features for imitating human-like play, aiming to obtain findings that would be useful for many other games. -
Neuro-Crítica: Un Aporte Al Estudio De La Etiología, Fenomenología Y Ética Del Uso Y Abuso Del Prefijo Neuro1
JAHR ǀ Vol. 4 ǀ No. 7 ǀ 2013 Professional article Amir Muzur, Iva Rincic Neuro-crítica: un aporte al estudio de la etiología, fenomenología y ética del uso y abuso del prefijo neuro1 ABSTRACT The last few decades, beside being proclaimed "the decades of the brain" or "the decades of the mind," have witnessed a fascinating explosion of new disciplines and pseudo-disciplines characterized by the prefix neuro-. To the "old" specializations of neurosurgery, neurophysiology, neuropharmacology, neurobiology, etc., some new ones have to be added, which might sound somehow awkward, like neurophilosophy, neuroethics, neuropolitics, neurotheology, neuroanthropology, neuroeconomy, and other. Placing that phenomenon of "neuroization" of all fields of human thought and practice into a context of mostly unjustified and certainly too high – almost millenarianistic – expectations of the science of the brain and mind at the end of the 20th century, the present paper tries to analyze when the use of the prefix neuro- is adequate and when it is dubious. Key words: brain, neuroscience, word coinage RESUMEN Las últimas décadas, además de haber sido declaradas "las décadas del cerebro" o "las décadas de la mente", han sido testigos de una fascinante explosión de nuevas disciplinas y pseudo-disciplinas caracterizadas por el prefijo neuro-. A las "antiguas" especializaciones de la neurocirugía, la neurofisiología, la neurofarmacología, la neurobiología, etc., deben agregarse otras nuevas que pueden sonar algo extrañas, como la neurofilosofía, la neuroética, la neuropolítica, la neuroteología, la neuroantropología, la neuroeconomía, entre otras. El presente trabajo coloca ese fenómeno de "neuroización" de todos los campos del pensamiento y la práctica humana en un contexto de expectativas en general injustificadas y sin duda altísimas (y casi milenarias) en la ciencia del cerebro y la mente a fines del siglo XX; e intenta analizar cuándo el uso del prefijo neuro- es adecuado y cuándo es cuestionable. -
Evolving Neural Networks Using Behavioural Genetic Principles
Evolving Neural Networks Using Behavioural Genetic Principles Maitrei Kohli A dissertation submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy Department of Computer Science & Information Systems Birkbeck, University of London United Kingdom March 2017 0 Declaration This thesis is the result of my own work, except where explicitly acknowledged in the text. Maitrei Kohli …………………. 1 ABSTRACT Neuroevolution is a nature-inspired approach for creating artificial intelligence. Its main objective is to evolve artificial neural networks (ANNs) that are capable of exhibiting intelligent behaviours. It is a widely researched field with numerous successful methods and applications. However, despite its success, there are still open research questions and notable limitations. These include the challenge of scaling neuroevolution to evolve cognitive behaviours, evolving ANNs capable of adapting online and learning from previously acquired knowledge, as well as understanding and synthesising the evolutionary pressures that lead to high-level intelligence. This thesis presents a new perspective on the evolution of ANNs that exhibit intelligent behaviours. The novel neuroevolutionary approach presented in this thesis is based on the principles of behavioural genetics (BG). It evolves ANNs’ ‘general ability to learn’, combining evolution and ontogenetic adaptation within a single framework. The ‘general ability to learn’ was modelled by the interaction of artificial genes, encoding the intrinsic properties of the ANNs, and the environment, captured by a combination of filtered training datasets and stochastic initialisation weights of the ANNs. Genes shape and constrain learning whereas the environment provides the learning bias; together, they provide the ability of the ANN to acquire a particular task. -
Evolving Autonomous Agent Controllers As Analytical Mathematical Models
Evolving Autonomous Agent Controllers as Analytical Mathematical Models Paul Grouchy1 and Gabriele M.T. D’Eleuterio1 1University of Toronto Institute for Aerospace Studies, Toronto, Ontario, Canada M3H 5T6 [email protected] Downloaded from http://direct.mit.edu/isal/proceedings-pdf/alife2014/26/681/1901537/978-0-262-32621-6-ch108.pdf by guest on 27 September 2021 Abstract a significant amount of time and computational resources. Furthermore, any such design decisions introduce additional A novel Artificial Life paradigm is proposed where experimenter bias into the simulation. Finally, complex be- autonomous agents are controlled via genetically- haviors require complex representations, adding to the al- encoded Evolvable Mathematical Models (EMMs). Agent/environment inputs are mapped to agent outputs ready high computational costs of ALife algorithms while via equation trees which are evolved using Genetic Pro- further obfuscating the inner workings of the evolved agents. gramming. Equations use only the four basic mathematical We propose Evolvable Mathematical Models (EMMs), a operators: addition, subtraction, multiplication and division. novel paradigm whereby autonomous agents are evolved via Experiments on the discrete Double-T Maze with Homing GP as analytical mathematical models of behavior. Agent problem are performed; the source code has been made available. Results demonstrate that autonomous controllers inputs are mapped to outputs via a system of genetically with learning capabilities can be evolved as analytical math- encoded equations. Only the four basic mathematical op- ematical models of behavior, and that neuroplasticity and erations (addition, subtraction, multiplication and division) neuromodulation can emerge within this paradigm without are required, as they can be used to approximate any ana- having these special functionalities specified a priori. -
How Do We Empathize with Someone Who Is Not Like Us? a Functional Magnetic Resonance Imaging Study
Lamm, C; Meltzoff, A N; Decety, J (2010). How do we empathize with someone who is not like us? A functional magnetic resonance imaging study. Journal of Cognitive Neuroscience, 22(2):362-376. Postprint available at: http://www.zora.uzh.ch University of Zurich Posted at the Zurich Open Repository and Archive, University of Zurich. Zurich Open Repository and Archive http://www.zora.uzh.ch Originally published at: Journal of Cognitive Neuroscience 2010, 22(2):362-376. Winterthurerstr. 190 CH-8057 Zurich http://www.zora.uzh.ch Year: 2010 How do we empathize with someone who is not like us? A functional magnetic resonance imaging study Lamm, C; Meltzoff, A N; Decety, J Lamm, C; Meltzoff, A N; Decety, J (2010). How do we empathize with someone who is not like us? A functional magnetic resonance imaging study. Journal of Cognitive Neuroscience, 22(2):362-376. Postprint available at: http://www.zora.uzh.ch Posted at the Zurich Open Repository and Archive, University of Zurich. http://www.zora.uzh.ch Originally published at: Journal of Cognitive Neuroscience 2010, 22(2):362-376. How Do We Empathize with Someone Who Is Not Like Us? A Functional Magnetic Resonance Imaging Study Claus Lamm1, Andrew N. Meltzoff2, and Jean Decety1 Abstract & Previous research on the neural underpinnings of empathy control (right inferior frontal cortex). In addition, effective has been limited to affective situations experienced in a simi- connectivity between the latter and areas implicated in af- lar way by an observer and a target individual. In daily life we fective processing was enhanced. -
7 Self and Self-Understanding* Lecture I: Some Origins of Self
7 Self and Self-Understanding* Lecture I: Some Origins of Self I will reflect on constitutive features of selves—especially a certain sort of self- understanding. This self-understanding is the main topic of these lectures. I ‘Self ’ is a technical term, refined from ordinary usage. Ordinary usage is, however, very close to what I want. A definition from the Oxford English Dictionary runs, ‘Self: a person’s essential being that distinguishes the person from others, especially considered as the object of introspection or reflexive action; a person’s particular nature.’ Kant characterized a person as ‘what is conscious of its numerical identity, of its self, in different times’.1 This * This essay is a revision, with some expansion, of the Dewey Lectures, given at Columbia University, December 2007. I am grateful to Christopher Peacocke for valuable criticisms in spring 2011 of the last section of Lecture I and all of Lecture III; and to Denis Bu¨hler for saving me from an error and prompting an argument in Lecture II. 1 Immanuel Kant, Critique of Pure Reason, A361; see also Metaphysics Mrongovius 29: 911 in Karl Ameriks and Steve Naragon (eds.), Lectures on Metaphysics (New York: Cambridge University Press, 1997), p. 276. Kant’s formulation in the Critique is not ideally specific and might qualify as ambiguous. It is clear from context that Kant means the consciousness to include consciousness at a given time of the self as it is at different times. It is also clear that Kant intends the consciousness to be noninferential, and in my terms de re. -
Giovanni Berlucchi
BK-SFN-NEUROSCIENCE-131211-03_Berlucchi.indd 96 16/04/14 5:21 PM Giovanni Berlucchi BORN: Pavia, Italy May 25, 1935 EDUCATION: Liceo Classico Statale Ugo Foscolo, Pavia, Maturità (1953) Medical School, University of Pavia, MD (1959) California Institute of Technology, Postdoctoral Fellowship (1964–1965) APPOINTMENTS: University of Pennsylvania (1968) University of Siena (1974) University of Pisa (1976) University of Verona (1983) HONORS AND AWARDS: Academia Europaea (1990) Accademia Nazionale dei Lincei (1992) Honorary PhD in Psychology, University of Pavia (2007) After working initially on the neurophysiology of the sleep-wake cycle, Giovanni Berlucchi did pioneering electrophysiological investigations on the corpus callosum and its functional contribution to the interhemispheric transfer of visual information and to the representation of the visual field in the cerebral cortex and the superior colliculus. He was among the first to use reaction times for analyzing hemispheric specializations and interactions in intact and split brain humans. His latest research interests include visual spatial attention and the representation of the body in the brain. BK-SFN-NEUROSCIENCE-131211-03_Berlucchi.indd 97 16/04/14 5:21 PM Giovanni Berlucchi Family and Early Years A man’s deepest roots are where he has spent the enchanted days of his childhood, usually where he was born. My deepest roots lie in the ancient Lombard city of Pavia, where I was born 78 years ago, on May 25, 1935, and in that part of the province of Pavia that lies to the south of the Po River and is called the Oltrepò Pavese. The hilly part of the Oltrepò is covered with beautiful vineyards that according to archaeological and historical evidence have been used to produce good wines for millennia. -
Michalska, Emotion Understanding in Developmental Disorders
Volume 10, No 1, Spring 2015 ISSN 1932-1066 Emotion Understanding in Developmental Disorders What Can Neuroscience Teach Us? Kalina J. Michalska National Institute of Mental Health, Bethesda [email protected] Abstract: Empathy is thought to play a key role in motivating helping behavior and providing the affective basis for moral development. Neuroimaging studies clearly document that watching someone in pain elicits a negative arousal response in the observer to a stronger degree in children than in young adults. Findings indicate that although children and adults have similar patterns of brain response to perceiving other people in pain, there are important changes in the functional organization in the neural structures implicated in empathy and sympathy that occur over an extended period from childhood through adulthood. Keywords: Emotion sharing; moral development; empathy; disorder, developmental; distress; neuroatanomy, fuctional; neuroimaging. Emotion understanding has many facets. Emotional in neuroscience that is not readily available from other empathy—the ability to recognize, share, and make measures. The use of neural indices, in addition to the inferences about another person's emotional state—is more traditional self-report indices, allows to address one form of emotion understanding that is fundamental questions of clinical and developmental interest. to meaningful social interactions. Responses related Based on empirical findings from psychology to emotional empathy, such as feelings of sympathy and cognitive neuroscience, -
Jeannerod and Jean Decety
Mental motor imagery: a window into the representational stages of action Marc Jeannerod and Jean Decety INSERM Unit6 94, Bron, France The physiological basis of mental states can be effectively studied by combining cognitive psychology with human neuroscience. Recent research has employed mental motor imagery in normal and brain-damaged subjects to decipher the content and the structure of covert processes preceding the execution of action. The mapping of brain activity during motor imagery discloses a pattern of activation similar to that of an executed action. Current Opinion in Neurobiology 1995, 5:727-732 Introduction: motor representations increases with respect to rest. When this is the case, elec- trornyographic (EMG) activity is limited to those muscles Most of our actions are driven indirectly by internally that participate in the simulated action, and tends to be reprsesented goals, rather than directly by the external proportional to the amount of imagined effort [lo]. The environment. Until recently, the existence and structure fact that muscular activity is only partially blocked during of such motor representations were inferred from the simulation of movement suggests that motoneurons are duration and timing of a reaction, or from the pattern of close to threshold. executed movements [l]. Now, however, a more direct approach has been adopted that exploits the unique In several other motor imagery experiments, however, ability of human subjects to image and simulate actions EMG is quiescent (e.g. [ll]). This does not necessarily consciously [P-4]. Motor imag,ery is a cognitive state that contradict the link between motor imagery and muscular can be experienced by virtually everyone with minimal activity, as it may merely reflect better inhibition of training. -
The Social Neuroscience of Empathy Tania Singer and Claus Lamm University of Zurich, Laboratory for Social and Neural Systems Research, Zurich, Switzerland
THE YEAR IN COGNITIVE NEUROSCIENCE 2009 The Social Neuroscience of Empathy Tania Singer and Claus Lamm University of Zurich, Laboratory for Social and Neural Systems Research, Zurich, Switzerland The phenomenon of empathy entails the ability to share the affective experiences of others. In recent years social neuroscience made considerable progress in revealing the mechanisms that enable a person to feel what another is feeling. The present review pro- vides an in-depth and critical discussion of these findings. Consistent evidence shows that sharing the emotions of others is associated with activation in neural structures that are also active during the first-hand experience of that emotion. Part of the neural activation shared between self- and other-related experiences seems to be rather auto- matically activated. However, recent studies also show that empathy is a highly flexible phenomenon, and that vicarious responses are malleable with respect to a number of factors—such as contextual appraisal, the interpersonal relationship between em- pathizer and other, or the perspective adopted during observation of the other. Future investigations are needed to provide more detailed insights into these factors and their neural underpinnings. Questions such as whether individual differences in empathy can be explained by stable personality traits, whether we can train ourselves to be more empathic, and how empathy relates to prosocial behavior are of utmost relevance for both science and society. Key words: empathy; social neuroscience; pain; fMRI; anterior insula (AI); anterior cingulate cortex (ACC); prosocial behavior; empathic concern, altruism; emotion contagion Introduction ultimately results in a better understanding of the present and future mental states and actions Being able to understand our conspecifics’ of the people around us and possibly promotes mental and affective states is a cornerstone of prosocial behavior.