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North American Journal of Psychology, 1999. PUB DATE 1999-00-00 NOTE 346P.; Published Semi-Annually
DOCUMENT RESUME ED 449 388 CG 029 765 AUTHOR McCutcheon, Lynn E., Ed. TITLE North American Journal of Psychology, 1999. PUB DATE 1999-00-00 NOTE 346p.; Published semi-annually. AVAILABLE FROM NAJP, 240 Harbor Dr., Winter Garden, FL 34787 ($35 per annual subscription). Tel: 407-877-8364. PUB TYPE Collected Works Serials (022) JOURNAL CIT North American Journal of Psychology; vl n1-2 1999 EDRS PRICE MF01/PC14 Plus Postage. DESCRIPTORS *Psychology; *Research Tools; *Scholarly Journals; *Social Science Research ABSTRACT "North American Journal of Psychology" publishes scientific papers of general interest to psychologists and other social scientists. Articles included in volume 1 issue 1 (June 1999) are: "Generalist Looks at His Career in Teaching: Interview with Dr. Phil Zimbardo"; "Affective Information in Videos"; "Infant Communication"; "Defining Projective Techniques"; "Date Selection Choices in College Students"; "Study of the Personality of Violent Children"; "Behavioral and Institutional Theories of Human Resource Practices"; "Self-Estimates of Intelligence:"; "When the Going Gets Tough, the Tough Get Going"; "Behaviorism and Cognitivism in Learning Theory"; "On the Distinction between Behavioral Contagion, Conversion Conformity, and Compliance Conformity"; "Promoting Altruism in Troubled Youth"; The Influence of insecurity on Exchange and Communal Intimates"; "Height as Power in Women"; "Moderator Effects of Managerial Activity Inhibition on the Relation between Power versus Affiliation Motive Dominance and Econdmic Efficiency"; -
Dehaene Et Al (2008)
Log or Linear? Distinct Intuitions of the Number Scale in Western and Amazonian Indigene Cultures Stanislas Dehaene, et al. Science 320, 1217 (2008); DOI: 10.1126/science.1156540 The following resources related to this article are available online at www.sciencemag.org (this information is current as of June 6, 2008 ): Updated information and services, including high-resolution figures, can be found in the online version of this article at: http://www.sciencemag.org/cgi/content/full/320/5880/1217 Supporting Online Material can be found at: http://www.sciencemag.org/cgi/content/full/320/5880/1217/DC1 This article cites 24 articles, 4 of which can be accessed for free: http://www.sciencemag.org/cgi/content/full/320/5880/1217#otherarticles Information about obtaining reprints of this article or about obtaining permission to reproduce this article in whole or in part can be found at: on June 6, 2008 http://www.sciencemag.org/about/permissions.dtl www.sciencemag.org Downloaded from Science (print ISSN 0036-8075; online ISSN 1095-9203) is published weekly, except the last week in December, by the American Association for the Advancement of Science, 1200 New York Avenue NW, Washington, DC 20005. Copyright 2008 by the American Association for the Advancement of Science; all rights reserved. The title Science is a registered trademark of AAAS. REPORTS Before formal schooling, Western children may Log or Linear? Distinct Intuitions of the acquire the number-line concept from Arabic nu- merals seen on elevators, rulers, books, etc. Thus, Number Scale in Western and existing studies do not reveal which aspects of the number-space mapping constitute a basic in- tuition that would continue to exist in the absence Amazonian Indigene Cultures of a structured mathematical language and educa- 1,2,3,4 1,2,4,5 5 6 tion. -
Chicago Section American Chemical
http://chicagoacs.org NOVEMBER • 2008 CHICAGO SECTION AMERICAN CHEMICAL SOCIETY Joint Meeting of the University of Chicago Department of Chemistry and the Chicago Section ACS WEDNESDAY, NOVEMBER 19, 2008 The Parthenon Restaurant Vegetarian Spinach-Cheese Pie, Vege- PRESENTATION OF STIEGLITZ 314 South Halsted Street tarian Pastitsio (Macaroni baked with LECTURE 8:00 P.M. Chicago, IL broccoli, Bechamel sauce and Kefalotiri), 312-726-2407 Dolmades (vine leaves stuffed with rice, meats and herbs), Rotisserie-roasted DIRECTIONS TO THE MEETING lamb served with rice pilaf and roasted potatoes. Desserts: Baklava (flaky layers From Kennedy (I-90) or Edens (I-94): of Phyllo baked with nuts and honey) Drive downtown and exit at Adams and Galaktobouriko (flaky layers of Phyl- Street. Turn right to Halsted. Turn left at lo with vanilla custard and baked with Halsted. Restaurant is approximately syrup. Beverages, bread and butter. 1.5 blocks on the west side of the street. The cost is $30 to Section members who From Eisenhower (I-290): Drive east have paid their local section dues, mem- to Chicago. Exit at Racine and turn left. bers' families, and visiting ACS members. Go to Jackson Boulevard and turn right. The cost to members who have NOT Take Jackson to Halsted. Turn right at paid their local section dues and to non- Halsted. Restaurant is approximately Section members is $32. The cost to stu- 1/2 block on the west side of the street. dents and unemployed members is $15. Seating will be available for those who PARKING: Free valet parking. Parking wish to attend the meeting without dinner. -
Functions of Memory Across Saccadic Eye Movements
Functions of Memory Across Saccadic Eye Movements David Aagten-Murphy and Paul M. Bays Contents 1 Introduction 2 Transsaccadic Memory 2.1 Other Memory Representations 2.2 Role of VWM Across Eye Movements 3 Identifying Changes in the Environment 3.1 Detection of Displacements 3.2 Object Continuity 3.3 Visual Landmarks 3.4 Conclusion 4 Integrating Information Across Saccades 4.1 Transsaccadic Fusion 4.2 Transsaccadic Comparison and Preview Effects 4.3 Transsaccadic Integration 4.4 Conclusion 5 Correcting Eye Movement Errors 5.1 Corrective Saccades 5.2 Saccadic Adaptation 5.3 Conclusion 6 Discussion 6.1 Optimality 6.2 Object Correspondence 6.3 Memory Limitations References Abstract Several times per second, humans make rapid eye movements called saccades which redirect their gaze to sample new regions of external space. Saccades present unique challenges to both perceptual and motor systems. During the move- ment, the visual input is smeared across the retina and severely degraded. Once completed, the projection of the world onto the retina has undergone a large-scale spatial transformation. The vector of this transformation, and the new orientation of D. Aagten-Murphy (*) and P. M. Bays University of Cambridge, Cambridge, UK e-mail: [email protected] © Springer Nature Switzerland AG 2018 Curr Topics Behav Neurosci DOI 10.1007/7854_2018_66 D. Aagten-Murphy and P. M. Bays the eye in the external world, is uncertain. Memory for the pre-saccadic visual input is thought to play a central role in compensating for the disruption caused by saccades. Here, we review evidence that memory contributes to (1) detecting and identifying changes in the world that occur during a saccade, (2) bridging the gap in input so that visual processing does not have to start anew, and (3) correcting saccade errors and recalibrating the oculomotor system to ensure accuracy of future saccades. -
Binding of Visual Features in Human Perception and Memory
BINDING OF VISUAL FEATURES IN HUMAN PERCEPTION AND MEMORY SNEHLATA JASWAL Thesis presented for the degree of Doctor of Philosophy The University of Edinburgh 2009 Dedicated to my parents PhD – The University of Edinburgh – 2009 DECLARATION I declare that this thesis is my own composition, and that the material contained in it describes my own work. It has not been submitted for any other degree or professional qualification. All quotations have been distinguished by quotation marks and the sources of information acknowledged. Snehlata Jaswal 31 August 2009 PhD – The University of Edinburgh – 2009 ACKNOWLEDGEMENTS Adamant queries are a hazy recollection Remnants are clarity, insight, appreciation A deep admiration, love, infinite gratitude For revered Bob, John, and Jim One a cherished guide, ideal teacher The other a personal idol, surrogate mother Both inspiring, lovingly instilled certitude Jagat Sir and Ritu Ma’am A sister sought new worlds to conquer A daughter left, enticed by enchanter Yet showered me with blessings multitude My family, Mum and Dad So many more, whispers the breeze Without whom, this would not be Mere mention is an inane platitude For treasured friends forever PhD – The University of Edinburgh – 2009 1 CONTENTS ABSTRACT.......................................................................................................................................... 5 LIST OF FIGURES ............................................................................................................................. 6 LIST OF ABBREVIATIONS............................................................................................................. -
Machine Learning for Neuroscience Geoffrey E Hinton
Hinton Neural Systems & Circuits 2011, 1:12 http://www.neuralsystemsandcircuits.com/content/1/1/12 QUESTIONS&ANSWERS Open Access Machine learning for neuroscience Geoffrey E Hinton What is machine learning? Could you provide a brief description of the Machine learning is a type of statistics that places parti- methods of machine learning? cular emphasis on the use of advanced computational Machine learning can be divided into three parts: 1) in algorithms. As computers become more powerful, and supervised learning, the aim is to predict a class label or modern experimental methods in areas such as imaging a real value from an input (classifying objects in images generate vast bodies of data, machine learning is becom- or predicting the future value of a stock are examples of ing ever more important for extracting reliable and this type of learning); 2) in unsupervised learning, the meaningful relationships and for making accurate pre- aim is to discover good features for representing the dictions. Key strands of modern machine learning grew input data; and 3) in reinforcement learning, the aim is out of attempts to understand how large numbers of to discover what action should be performed next in interconnected, more or less neuron-like elements could order to maximize the eventual payoff. learn to achieve behaviourally meaningful computations and to extract useful features from images or sound What does machine learning have to do with waves. neuroscience? By the 1990s, key approaches had converged on an Machine learning has two very different relationships to elegant framework called ‘graphical models’, explained neuroscience. As with any other science, modern in Koller and Friedman, in which the nodes of a graph machine-learning methods can be very helpful in analys- represent variables such as edges and corners in an ing the data. -
Race in the Age of Obama Making America More Competitive
american academy of arts & sciences summer 2011 www.amacad.org Bulletin vol. lxiv, no. 4 Race in the Age of Obama Gerald Early, Jeffrey B. Ferguson, Korina Jocson, and David A. Hollinger Making America More Competitive, Innovative, and Healthy Harvey V. Fineberg, Cherry A. Murray, and Charles M. Vest ALSO: Social Science and the Alternative Energy Future Philanthropy in Public Education Commission on the Humanities and Social Sciences Reflections: John Lithgow Breaking the Code Around the Country Upcoming Events Induction Weekend–Cambridge September 30– Welcome Reception for New Members October 1–Induction Ceremony October 2– Symposium: American Institutions and a Civil Society Partial List of Speakers: David Souter (Supreme Court of the United States), Maj. Gen. Gregg Martin (United States Army War College), and David M. Kennedy (Stanford University) OCTOBER NOVEMBER 25th 12th Stated Meeting–Stanford Stated Meeting–Chicago in collaboration with the Chicago Humanities Perspectives on the Future of Nuclear Power Festival after Fukushima WikiLeaks and the First Amendment Introduction: Scott D. Sagan (Stanford Introduction: John A. Katzenellenbogen University) (University of Illinois at Urbana-Champaign) Speakers: Wael Al Assad (League of Arab Speakers: Geoffrey R. Stone (University of States) and Jayantha Dhanapala (Pugwash Chicago Law School), Richard A. Posner (U.S. Conferences on Science and World Affairs) Court of Appeals for the Seventh Circuit), 27th Judith Miller (formerly of The New York Times), Stated Meeting–Berkeley and Gabriel Schoenfeld (Hudson Institute; Healing the Troubled American Economy Witherspoon Institute) Introduction: Robert J. Birgeneau (Univer- DECEMBER sity of California, Berkeley) 7th Speakers: Christina Romer (University of Stated Meeting–Stanford California, Berkeley) and David H. -
Visual Scene Perception
Galley: Article - 00632 Level 1 Visual Scene Perception Helene Intraub, University of Delaware, Newark, Delaware, USA CONTENTS Introduction Transsaccadic memory Scene comprehension and its influence on object Perception of `gist' versus details detection Boundary extension When studying a scene, viewers can make as many a single glimpse without any bias from prior con- as three or four eye fixations per second. A single text. Immediately after viewing a rapid sequence fixation is typically enough to allow comprehension like this, viewers participate in a recognition test. of a scene. What is remembered, however, is not a The pictures they just viewed are mixed with new photographic replica, but a more abstract mental pictures and are slowly presented one at a time. representation that captures the `gist' and general The viewers' task is to indicate which pictures they layout of the scene along with a limited amount of detail. remember seeing before. Following rapid presenta- tion, memory for the previously seen pictures is rather poor. For example, when 16 pictures were INTRODUCTION presented in this way, moments later, viewers were only able to recognize about 40 to 50 per 0632.001 The visual world exists all around us, but physio- logical constraints prevent us from seeing it all at cent in the memory test. One explanation is that once. Eye movements (called saccades) shift the they were only able to perceive about 40 to 50 per position of the eye as quickly as three or four cent of the scenes that had flashed by and those times per second. Vision is suppressed during were the scenes they remembered. -
The Consequences of Infelicity: the Effects of Unhappinesson
AN ABSTRACT OF THE THESIS OF Jorge R. Martinez for the degree of Master of Arts in Interdisciplinary Studies in Political Science, History and Foreign Languages and Literaturespresented on June 5, 1991. Title: The Consequences of Infelicity: The Effects of Unhappinesson Biological and Social Evolution Redacted for Privacy Abstract approved: Glen C. Dealy In social and biological evolution, infelicitycan operate as a driving motor to force change. In this essay, for life other than human, infelicity is equated with physical unfitness to compete for theresources of a specific niche. For humanity it is defined as the result ofan incongruity between a nation's culture and its government. The purpose of this study is to investigate how, for irrational life,unfitness can stimulate the creation of a new species and, for men, how the unhappiness of a nation may enhance its opportunity to enter a new socio-economic order. An evolutionary account about a possible way in which life could have evolved is offered, concentrating mainly on the transition from ape to a less remote ancestor of man, but also taking into consideration other life forms. Then, a parallel to social evolution is established. A study of the rise of capitalism in England, as well as the recent attempts to institute socialism in Latin America, are also explained as consequences of infelicity. c Copyright by Jorge R. Martinez June 5, 1991 All Rights Reserved The Consequences of Infelicity: the Effects of Unhappiness on Biological and Social Evolution by Jorge R. Martinez A THESIS -
Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning
Deep Neuroevolution: Genetic Algorithms are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning Felipe Petroski Such Vashisht Madhavan Edoardo Conti Joel Lehman Kenneth O. Stanley Jeff Clune Uber AI Labs ffelipe.such, [email protected] Abstract 1. Introduction Deep artificial neural networks (DNNs) are typ- A recent trend in machine learning and AI research is that ically trained via gradient-based learning al- old algorithms work remarkably well when combined with gorithms, namely backpropagation. Evolution sufficient computing resources and data. That has been strategies (ES) can rival backprop-based algo- the story for (1) backpropagation applied to deep neu- rithms such as Q-learning and policy gradients ral networks in supervised learning tasks such as com- on challenging deep reinforcement learning (RL) puter vision (Krizhevsky et al., 2012) and voice recog- problems. However, ES can be considered a nition (Seide et al., 2011), (2) backpropagation for deep gradient-based algorithm because it performs neural networks combined with traditional reinforcement stochastic gradient descent via an operation sim- learning algorithms, such as Q-learning (Watkins & Dayan, ilar to a finite-difference approximation of the 1992; Mnih et al., 2015) or policy gradient (PG) methods gradient. That raises the question of whether (Sehnke et al., 2010; Mnih et al., 2016), and (3) evolution non-gradient-based evolutionary algorithms can strategies (ES) applied to reinforcement learning bench- work at DNN scales. Here we demonstrate they marks (Salimans et al., 2017). One common theme is can: we evolve the weights of a DNN with a sim- that all of these methods are gradient-based, including ES, ple, gradient-free, population-based genetic al- which involves a gradient approximation similar to finite gorithm (GA) and it performs well on hard deep differences (Williams, 1992; Wierstra et al., 2008; Sali- RL problems, including Atari and humanoid lo- mans et al., 2017). -
Jerrold Meinwald Wins National Medal of Science by Anne Ju [email protected]
Oct. 3, 2014 Jerrold Meinwald wins National Medal of Science By Anne Ju [email protected] Jerrold Meinwald, the Goldwin Smith Professor of Chemistry Emeritus, has received the National Medal of Science, the nation’s highest honor for achievement in science and engineering. Meinwald received the medal in chemistry; other awards were bestowed in behavioral and social sciences, biology, engineering, mathematics and physical sciences, the White House announced Oct. 3. University Photography file photo Over his long career, Meinwald, Jerrold Meinwald, the Goldwin Smith Professor of Chemistry Emeritus, has received the National Medal of Science in chemistry. who joined Cornell’s faculty in 1952 as an instructor in chemistry, has made fundamental discoveries of how chemicals act as repellants and attractants between organisms. He and the late Thomas Eisner, a longtime friend and colleague who won the National Medal of Science in 1994, are credited with establishing the feld of “chemical ecology” – the science that deals with the many ways animals, plants and microorganisms chemically interact. “It’s a very nice thing,” Meinwald said of the award. “It’s maybe a representation of a growing interest in the feld of chemical ecology.” Meinwald’s research has involved the isolation and identifcation of biologically active compounds from insect and other arthropod sources; pheromone systems of some amphibian and mammal species; and identifcation of messenger molecules involved in such systems and the understanding of underlying signal transduction pathways. Meinwald has helped decipher the intricate chemical strategies that insects use for a variety of activities: mating, location of food, protection of ofspring and defense against attackers. -
Acetylcholine in Cortical Inference
Neural Networks 15 (2002) 719–730 www.elsevier.com/locate/neunet 2002 Special issue Acetylcholine in cortical inference Angela J. Yu*, Peter Dayan Gatsby Computational Neuroscience Unit, University College London, 17 Queen Square, London WC1N 3AR, UK Received 5 October 2001; accepted 2 April 2002 Abstract Acetylcholine (ACh) plays an important role in a wide variety of cognitive tasks, such as perception, selective attention, associative learning, and memory. Extensive experimental and theoretical work in tasks involving learning and memory has suggested that ACh reports on unfamiliarity and controls plasticity and effective network connectivity. Based on these computational and implementational insights, we develop a theory of cholinergic modulation in perceptual inference. We propose that ACh levels reflect the uncertainty associated with top- down information, and have the effect of modulating the interaction between top-down and bottom-up processing in determining the appropriate neural representations for inputs. We illustrate our proposal by means of an hierarchical hidden Markov model, showing that cholinergic modulation of contextual information leads to appropriate perceptual inference. q 2002 Elsevier Science Ltd. All rights reserved. Keywords: Acetylcholine; Perception; Neuromodulation; Representational inference; Hidden Markov model; Attention 1. Introduction medial septum (MS), diagonal band of Broca (DBB), and nucleus basalis (NBM). Physiological studies on ACh Neuromodulators such as acetylcholine (ACh), sero- indicate that its neuromodulatory effects at the cellular tonine, dopamine, norepinephrine, and histamine play two level are diverse, causing synaptic facilitation and suppres- characteristic roles. One, most studied in vertebrate systems, sion as well as direct hyperpolarization and depolarization, concerns the control of plasticity. The other, most studied in all within the same cortical area (Kimura, Fukuda, & invertebrate systems, concerns the control of network Tsumoto, 1999).