The Perceptron: : A Probabilistic Model for Information Storage and Organization in the brain (F. Rosenblatt)
|
|
|
- Tamsin Morgan Arnold
- 5 years ago
- Views:
Transcription
1 The Perceptron: : A Probabilistic Model for Information Storage and Organization in the brain (F. Rosenblatt) Artificial Intelligence Heo, Min-Oh
2 Outline Introduction Probabilistic model on biological Perceptron Predominant phase Postdominant phase Two helpful approach Bivalent systems Temporal organizations Conclusion 3 major points
3 Two Main Questions Q1 : In what form is information stored, or remembered? Q2 : How does information contained in storage, or in memory, influence recognition and behavior?
4 Answers: 2 positions (1) The 1 st position coded representations or images 1-to-1 mapping between sensory stimulus and the stored pattern Able to discover exactly what an organism remembers by reconstructing the original sensory patterns Recognition : matching or systematic comparison of the contents of storage with incoming sensory patterns
5 Answers: 2 positions (2) The 2 nd position The images of stimuli may never be recorded at all. There is never any simple mapping of the stimulus into memory. The information is contained in connections or associations. Recognition : Automatically activating the response without requiring any separate process for their recognition or identification.
6 What is the writer going to do? The need for a suitable language for the mathematical analysis of events. Formulate the current model of perceptron in terms of probability theory.
7 Assumptions for perceptron(1) 5 Assumptions 1. At birth, the construction of the most important networks is largely random, subject to a minimum number of genetic constraints. 2. The probability is likely to change, due to some relatively long-lasting changes in the neurons. 3. Exposure to a large sample of stimuli, Similar thing will tend to form pathways to the same sets of responding cells. Dissimilar thing will tend to develop connections to different sets of responding cells.
8 Assumptions for perceptron(2) 4. The application of positive or negative reinforcement may facilitate or hinder whatever formation of connections is currently in progress. 5. Similarity depends on physical organization of the perceiving system.
9 Modelling Connection Excitatory Inhibitory Level S-Points : stimuli impinge on a retina of sensory units A-Units : impulse are transmitted to a set of association cells R-Units : the Response cells which respond as the A-units. Two phase Predominant Phase Postdominant Phase
10 Models of systems 3 types of systems. Alpha system : an active cell simply gains an increment of value for every impulse, and hold this gain indefinitely. Beta system : the increments being apportioned among the cells of the source-set in proportion to their activity. Gamma system : active cells gain in value, so that the total value of source-set is always constant.
11 Predominant Phase(1) Probability : the Expected proportion of A-units activated by a stimulus of a given size
12 Predominant Phase(2) Conditional Probability : an A-unit which responds to a given stimulus will also respond to another given stimulus
13 Predominant Phase(3) : stability
14 Predominant Phase(4) : learnable
15 Postdominant Phase(1) Mathematical Model for learning Reinforcement learning Two Probabilities Pr : the perceptron will show a bias towards the correct response in preference to any given alternative response. Pg : the Probability of correct generalization. The probability that the correct response will be preferred over all alternatives is designated Pr or Pg.
16 Postdominant Phase(2) : able to find probability Pr, Pg to unity.
17 Two helpful approach Bivalent systems Two types of reinforcement are possible ( positive and negative ) Temporal organizations If the values of the A-units are allowed to decay at a rate proportional to their magnitude, The perceptron becomes capable of spontaneous concept formation. Spontaneously recognize the difference between the two classes.
18 Conclusion 3 major points to behaviorism Parsimony characteristics can clearly be stated. Have potentially measurable physical correlate. Verifiability We can be considerably more confident of its validity and of its generality than in the case of a theory which must be hand-tailored to meet each situation Explanatory power and generality
Cognitive Neuroscience History of Neural Networks in Artificial Intelligence The concept of neural network in artificial intelligence
Cognitive Neuroscience History of Neural Networks in Artificial Intelligence The concept of neural network in artificial intelligence To understand the network paradigm also requires examining the history
Prof. Greg Francis 7/31/15
s PSY 200 Greg Francis Lecture 06 How do you recognize your grandmother? Action potential With enough excitatory input, a cell produces an action potential that sends a signal down its axon to other cells
Introduction. Chapter The Perceptual Process
Chapter 1 Introduction Most of us take for granted our ability to perceive the external world. However, this is no simple deed at all. Imagine being given a task of designing a machine that can perceive,
Neuro Q no.2 = Neuro Quotient
TRANSDISCIPLINARY RESEARCH SEMINAR CLINICAL SCIENCE RESEARCH PLATFORM 27 July 2010 School of Medical Sciences USM Health Campus Neuro Q no.2 = Neuro Quotient Dr.Muzaimi Mustapha Department of Neurosciences
Neuromorphic computing
Neuromorphic computing Robotics M.Sc. programme in Computer Science lorenzo.vannucci@santannapisa.it April 19th, 2018 Outline 1. Introduction 2. Fundamentals of neuroscience 3. Simulating the brain 4.
Reading Assignments: Lecture 18: Visual Pre-Processing. Chapters TMB Brain Theory and Artificial Intelligence
Brain Theory and Artificial Intelligence Lecture 18: Visual Pre-Processing. Reading Assignments: Chapters TMB2 3.3. 1 Low-Level Processing Remember: Vision as a change in representation. At the low-level,
Lecture 2.1 What is Perception?
Lecture 2.1 What is Perception? A Central Ideas in Perception: Perception is more than the sum of sensory inputs. It involves active bottom-up and topdown processing. Perception is not a veridical representation
MEMORY. Announcements. Practice Question 2. Practice Question 1 10/3/2012. Next Quiz available Oct 11
Announcements Next Quiz available Oct 11 Due Oct 16 MEMORY Practice Question 1 Practice Question 2 What type of operant conditioning is Stewie using to get attention from his mom? A rercer that acquires
Why is dispersion of memory important*
What is memory* It is a web of connections Research has shown that people who lose their memory also lose the ability to connect things to each other in their mind It is these connections that let us understand
Chapter 5: Learning and Behavior Learning How Learning is Studied Ivan Pavlov Edward Thorndike eliciting stimulus emitted
Chapter 5: Learning and Behavior A. Learning-long lasting changes in the environmental guidance of behavior as a result of experience B. Learning emphasizes the fact that individual environments also play
Introduction to Computational Neuroscience
Introduction to Computational Neuroscience Lecture 5: Data analysis II Lesson Title 1 Introduction 2 Structure and Function of the NS 3 Windows to the Brain 4 Data analysis 5 Data analysis II 6 Single
EEL-5840 Elements of {Artificial} Machine Intelligence
Menu Introduction Syllabus Grading: Last 2 Yrs Class Average 3.55; {3.7 Fall 2012 w/24 students & 3.45 Fall 2013} General Comments Copyright Dr. A. Antonio Arroyo Page 2 vs. Artificial Intelligence? DEF:
Artificial Neural Networks (Ref: Negnevitsky, M. Artificial Intelligence, Chapter 6)
Artificial Neural Networks (Ref: Negnevitsky, M. Artificial Intelligence, Chapter 6) BPNN in Practice Week 3 Lecture Notes page 1 of 1 The Hopfield Network In this network, it was designed on analogy of
Brief History of Work in the area of Learning and Memory
Brief History of Work in the area of Learning and Memory Basic Questions how does memory work are there different kinds of memory what is their logic where in the brain do we learn where do we store what
NCFE Level 2 Certificate in The Principles of Dementia Care
The Principles of Dementia Care S A M P LE NCFE Level 2 Certificate in The Principles of Dementia Care Part A 1 These learning resources and assessment questions have been approved and endorsed by ncfe
Learning to Use Episodic Memory
Learning to Use Episodic Memory Nicholas A. Gorski (ngorski@umich.edu) John E. Laird (laird@umich.edu) Computer Science & Engineering, University of Michigan 2260 Hayward St., Ann Arbor, MI 48109 USA Abstract
M.Sc. in Cognitive Systems. Model Curriculum
M.Sc. in Cognitive Systems Model Curriculum April 2014 Version 1.0 School of Informatics University of Skövde Sweden Contents 1 CORE COURSES...1 2 ELECTIVE COURSES...1 3 OUTLINE COURSE SYLLABI...2 Page
Sperling conducted experiments on An experiment was conducted by Sperling in the field of visual sensory memory.
Levels of category Basic Level Category: Subordinate Category: Superordinate Category: Stages of development of Piaget 1. Sensorimotor stage 0-2 2. Preoperational stage 2-7 3. Concrete operational stage
The Nervous System. We have covered many different body systems which automatically control and regulate our bodies.
The Nervous System The Nervous System We have covered many different body systems which automatically control and regulate our bodies. There is one master system which controls all of these other systems.
Neurons and Hormones 1. How do animals perform the right behaviors at the right time? In the right context?
Neurons and Hormones 1 How do animals perform the right behaviors at the right time? In the right context? Active at night only What if conflicting signals? Magnetic cues are always present But migrate
THE NERVOUS SYSTEM III
THE NERVOUS SYSTEM III Small Review Review What is this? A neuron What does it do? Receives and transmits information Sending a signal How are signals sent in the nervous system? Message travels from neuron
Dr. Braj Bhushan, Dept. of HSS, IIT Guwahati, INDIA
1 Cognition The word Cognitive or Cognition has been derived from Latin word cognoscere meaning to know or have knowledge of. Although Psychology has existed over past 100 years as an independent discipline,
Chapter 3. Perception and Memory. Factors That Affect Teacher s Guidance
Chapter 3 A Key to Guiding children Effectively All rights reserved. Part 1 Perception and Memory 3-2 Factors That Affect Teacher s Guidance Perception-process of organizing information obtained through
J-01 State intervention goals in observable and measureable terms.
BACB 4 th Edition Task List s Content Area J: Intervention J-01 State intervention goals in observable and measureable terms. J-02 Identify potential interventions based on assessment results and the best
INTRODUCTION TO EDUCATIONAL NEUROSCIENCE
INTRODUCTION TO EDUCATIONAL NEUROSCIENCE TRUE OR FALSE? We only use 10% of our brain. Ages zero-three years are more important than any other for learning. There are critical periods for learning important
Chapter 1. Introduction
Chapter 1 Introduction Artificial neural networks are mathematical inventions inspired by observations made in the study of biological systems, though loosely based on the actual biology. An artificial
Perception Lie Paradox: Mathematically Proved Uncertainty about Humans Perception Similarity
Perception Lie Paradox: Mathematically Proved Uncertainty about Humans Perception Similarity Ahmed M. Mahran Computer and Systems Engineering Department, Faculty of Engineering, Alexandria University,
Intelligent Control Systems
Lecture Notes in 4 th Class in the Control and Systems Engineering Department University of Technology CCE-CN432 Edited By: Dr. Mohammed Y. Hassan, Ph. D. Fourth Year. CCE-CN432 Syllabus Theoretical: 2
The Standard Theory of Conscious Perception
The Standard Theory of Conscious Perception C. D. Jennings Department of Philosophy Boston University Pacific APA 2012 Outline 1 Introduction Motivation Background 2 Setting up the Problem Working Definitions
Chapter 3: Information Processing
SENG 5334: Human Factors Engineering & INDH 5931: Research Topics in IH/Safety Chapter 3: Information Processing By: Magdy Akladios, PhD, PE, CSP, CPE, CSHM 1 A Model of Information Processing Def: A model
Artificial Neural Network : Introduction
Artificial Neural Network : Introduction Debasis Samanta IIT Kharagpur dsamanta@iitkgp.ac.in 23.03.2018 Debasis Samanta (IIT Kharagpur) Soft Computing Applications 23.03.2018 1 / 20 Biological nervous
Autonomous Mobile Robotics
1 2 3 A reflex arc is a neural pathway that controls a reflex. In vertebrates, most sensory neurons do not pass directly into the brain, but synapse in the spinal cord. This allows for faster reflex actions
Memory, Attention, and Decision-Making
Memory, Attention, and Decision-Making A Unifying Computational Neuroscience Approach Edmund T. Rolls University of Oxford Department of Experimental Psychology Oxford England OXFORD UNIVERSITY PRESS Contents
PIB Ch. 18 Sequence Memory for Prediction, Inference, and Behavior. Jeff Hawkins, Dileep George, and Jamie Niemasik Presented by Jiseob Kim
PIB Ch. 18 Sequence Memory for Prediction, Inference, and Behavior Jeff Hawkins, Dileep George, and Jamie Niemasik Presented by Jiseob Kim Quiz Briefly describe the neural activities of minicolumn in the
Psycholinguistics Psychological Mechanisms
Psycholinguistics Psychological Mechanisms Psychological Mechanisms Information processing system Processing Serial and parallel processing Top-down and bottom-up processing Automatic and controlled processes
CAS Seminar - Spiking Neurons Network (SNN) Jakob Kemi ( )
CAS Seminar - Spiking Neurons Network (SNN) Jakob Kemi (820622-0033) kemiolof@student.chalmers.se November 20, 2006 Introduction Biological background To be written, lots of good sources. Background First
Neuroinformatics. Ilmari Kurki, Urs Köster, Jukka Perkiö, (Shohei Shimizu) Interdisciplinary and interdepartmental
Neuroinformatics Aapo Hyvärinen, still Academy Research Fellow for a while Post-docs: Patrik Hoyer and Jarmo Hurri + possibly international post-docs PhD students Ilmari Kurki, Urs Köster, Jukka Perkiö,
Yuriy Belov, Sergiy Тkachuk, Roman Iamborak
International Journal "Information Theories & Applications" Vol.12 57 Bibliography [1] Z.L.Rabinovich. About mechanisms of thinking and intellectual computers // Cybernetics and system analysis, 1993,
CHAPTER 6: Memory model Practice questions at - text book pages 112 to 113
QUESTIONS AND ANSWERS QUESTIONS AND ANSWERS CHAPTER 6: Memory model Practice questions at - text book pages 112 to 113 1) Which of the following sequences reflects the order in which the human brain processes
COGS 101A: Sensation and Perception
COGS 101A: Sensation and Perception 1 Virginia R. de Sa Department of Cognitive Science UCSD Lecture 4: Coding Concepts Chapter 2 Course Information 2 Class web page: http://cogsci.ucsd.edu/ desa/101a/index.html
Modeling Human Perception
Modeling Human Perception Could Stevens Power Law be an Emergent Feature? Matthew L. Bolton Systems and Information Engineering University of Virginia Charlottesville, United States of America Mlb4b@Virginia.edu
Psychology, Ch. 6. Learning Part 1
Psychology, Ch. 6 Learning Part 1 Two Main Types of Learning Associative learning- learning that certain events occur together Cognitive learning- acquisition of mental information, by observing or listening
PSYC 441 Cognitive Psychology II
PSYC 441 Cognitive Psychology II Session 6 Psychophysics Lecturer: Dr. Benjamin Amponsah, Dept., of Psychology, UG, Legon Contact Information: bamponsah@ug.edu.gh College of Education School of Continuing
ERA: Architectures for Inference
ERA: Architectures for Inference Dan Hammerstrom Electrical And Computer Engineering 7/28/09 1 Intelligent Computing In spite of the transistor bounty of Moore s law, there is a large class of problems
The Schema is Mightier Than the Sword Using Player Cognition to Predict Gaming Behavior
The Schema is Mightier Than the Sword Using Player Cognition to Predict Gaming Behavior Vanessa Hemovich, Ph.D. Associate Professor of Psychology DigiPen Institute of Technology Today s Talk: Cognitive
Realization of Visual Representation Task on a Humanoid Robot
Istanbul Technical University, Robot Intelligence Course Realization of Visual Representation Task on a Humanoid Robot Emeç Erçelik May 31, 2016 1 Introduction It is thought that human brain uses a distributed
Computational Cognitive Neuroscience
Computational Cognitive Neuroscience Computational Cognitive Neuroscience Computational Cognitive Neuroscience *Computer vision, *Pattern recognition, *Classification, *Picking the relevant information
Computational Explorations in Cognitive Neuroscience Chapter 7: Large-Scale Brain Area Functional Organization
Computational Explorations in Cognitive Neuroscience Chapter 7: Large-Scale Brain Area Functional Organization 1 7.1 Overview This chapter aims to provide a framework for modeling cognitive phenomena based
Senses are transducers. Change one form of energy into another Light, sound, pressure, etc. into What?
1 Vision 2 TRANSDUCTION Senses are transducers Change one form of energy into another Light, sound, pressure, etc. into What? Action potentials! Sensory codes Frequency code encodes information about intensity
Single cell tuning curves vs population response. Encoding: Summary. Overview of the visual cortex. Overview of the visual cortex
Encoding: Summary Spikes are the important signals in the brain. What is still debated is the code: number of spikes, exact spike timing, temporal relationship between neurons activities? Single cell tuning
Animal Behavior. Relevant Biological Disciplines. Inspirations => Models
Animal Behavior Relevant Biological Disciplines Neuroscience: the study of the nervous system s anatomy, physiology, biochemistry and molecular biology Psychology: the study of mind and behavior Ethology:
Change Blindness. Change blindness is the inability to recognize changes to objects in the environment
Change Blindness Change blindness is the inability to recognize changes to objects in the environment after interruption, i.e. an object in the environment changes while an individual is looking away,
Session 748 Moving From Function To Dysfunction By: Greg Roskopf, MA
Session 748 Moving From Function To Dysfunction By: Greg Roskopf, MA We Must Determine The Physical Characteristics Of Each Client Proper Assessments will dictate each clients physical capabilities I don
Introduction to Computational Neuroscience
Introduction to Computational Neuroscience Lecture 7: Network models Lesson Title 1 Introduction 2 Structure and Function of the NS 3 Windows to the Brain 4 Data analysis 5 Data analysis II 6 Single neuron
A Neural-Fuzzy Description of Ambiguous Figures in Visual Message
A Neural-Fuzzy Description of Ambiguous Figures in Visual Message Chi-Wei Lee*, Jalin Ko Tsung Huang** *Yuan Ze University C/o Department of Information Communication 135 Yuan-Tung Rd., Chung-Li, Taoyuan
Chapter 3 Tools for Practical Theorizing: Theoretical Maps and Ecosystem Maps
Chapter 3 Tools for Practical Theorizing: Theoretical Maps and Ecosystem Maps Chapter Outline I. Introduction A. Understanding theoretical languages requires universal translators 1. Theoretical maps identify
Sensation vs. Perception
PERCEPTION Sensation vs. Perception What s the difference? Sensation what the senses do Perception process of recognizing, organizing and dinterpreting ti information. What is Sensation? The process whereby
Cognitive & Linguistic Sciences. What is cognitive science anyway? Why is it interdisciplinary? Why do we need to learn about information processors?
Cognitive & Linguistic Sciences What is cognitive science anyway? Why is it interdisciplinary? Why do we need to learn about information processors? Heather Bortfeld Education: BA: University of California,
LEARNING. Learning. Type of Learning Experiences Related Factors
LEARNING DEFINITION: Learning can be defined as any relatively permanent change in behavior or modification in behavior or behavior potentials that occur as a result of practice or experience. According
Plasticity of Cerebral Cortex in Development
Plasticity of Cerebral Cortex in Development Jessica R. Newton and Mriganka Sur Department of Brain & Cognitive Sciences Picower Center for Learning & Memory Massachusetts Institute of Technology Cambridge,
Learning and Adaptive Behavior, Part II
Learning and Adaptive Behavior, Part II April 12, 2007 The man who sets out to carry a cat by its tail learns something that will always be useful and which will never grow dim or doubtful. -- Mark Twain
Pattern Recognition. Organization of Lectures. Complexities of Perception
Pattern Recognition Complexities Constraints Models Organization of Lectures Complexities of perception Constraints on perception Pattern recognition models Template Distinctive-feature Spatial/configural
Cronicon EC NEUROLOGY. Mini Review. Alzheimer s Living with the Disease- Understanding the Brain. Caron Leid* Aspen University, Aspen, Colorado, USA
Cronicon OPEN ACCESS EC NEUROLOGY Mini Review Alzheimer s Living with the Disease- Understanding the Brain Caron Leid* Aspen University, Aspen, Colorado, USA *Corresponding Author: Caron Leid, Aspen University,
COGS 101A: Sensation and Perception
COGS 101A: Sensation and Perception 1 Virginia R. de Sa Department of Cognitive Science UCSD Lecture 6: Beyond V1 - Extrastriate cortex Chapter 4 Course Information 2 Class web page: http://cogsci.ucsd.edu/
Introduction. Visual Perception Aditi Majumder, UCI. Perception is taken for granted!
Introduction Visual Perception Perception is taken for granted! Slide 2 1 Perception is very complex Perceive Locate Identify/Recognize Different objects Their relationship with each other Qualitative
The Nervous System. The right half of the brain controls the left half of the body. This means that only left handed people are in their right mind.
The Nervous System The right half of the brain controls the left half of the body. This means that only left handed people are in their right mind. Central Nervous System Made up of brain and spinal cord
The Integration of Features in Visual Awareness : The Binding Problem. By Andrew Laguna, S.J.
The Integration of Features in Visual Awareness : The Binding Problem By Andrew Laguna, S.J. Outline I. Introduction II. The Visual System III. What is the Binding Problem? IV. Possible Theoretical Solutions
Lecturer: Dr. Benjamin Amponsah, Dept. of Psychology, UG, Legon Contact Information:
Lecturer: Dr. Benjamin Amponsah, Dept. of Psychology, UG, Legon Contact Information: bamponsah@ug.edu.gh College of Education School of Continuing and Distance Education 2014/2015 2016/2017 Session Overview
Active Sites model for the B-Matrix Approach
Active Sites model for the B-Matrix Approach Krishna Chaithanya Lingashetty Abstract : This paper continues on the work of the B-Matrix approach in hebbian learning proposed by Dr. Kak. It reports the
acquisition associative learning behaviorism B. F. Skinner biofeedback
acquisition associative learning in classical conditioning the initial stage when one links a neutral stimulus and an unconditioned stimulus so that the neutral stimulus begins triggering the conditioned
Lateral Geniculate Nucleus (LGN)
Lateral Geniculate Nucleus (LGN) What happens beyond the retina? What happens in Lateral Geniculate Nucleus (LGN)- 90% flow Visual cortex Information Flow Superior colliculus 10% flow Slide 2 Information
Neurons, Synapses, and Signaling
Neurons, Synapses, and Signaling The Neuron is the functional unit of the nervous system. Neurons are composed of a cell body, which contains the nucleus and organelles; Dendrites which are extensions
Sparse Coding in Sparse Winner Networks
Sparse Coding in Sparse Winner Networks Janusz A. Starzyk 1, Yinyin Liu 1, David Vogel 2 1 School of Electrical Engineering & Computer Science Ohio University, Athens, OH 45701 {starzyk, yliu}@bobcat.ent.ohiou.edu
Admission Test Example. Bachelor in Law + Bachelor in Global Governance - BIG
Admission Test Example Bachelor in Law + Bachelor in Global Governance - BIG Admission Test for the ESADE Bachelor in Law + Bachelor in Global Governance The Admission Test consists of the following parts:
Certificate in the Principles of Dementia Care
CACHE Level 2 Certificate in the Principles of Dementia Care LE EQUALITY AND DIVERSITY ACTIVITIES P INTERACTION M PERSON-CENTRED SA MEDICATION Workbook 1 COMMUNICATION In this section, you will learn about
After Rescorla-Wagner
After Rescorla-Wagner W. Jeffrey Wilson March 6, 2013 RW Problems STM-LTM & Learning SOP Model Configural vs Elemental Nodes Problems with Rescorla-Wagner Model Extinction: No Spontaneous Recovery or Rapid
TEMPORAL PRECISION OF SENSORY RESPONSES Berry and Meister, 1998
TEMPORAL PRECISION OF SENSORY RESPONSES Berry and Meister, 1998 Today: (1) how can we measure temporal precision? (2) what mechanisms enable/limit precision? A. 0.1 pa WHY SHOULD YOU CARE? average rod
Phil 490: Consciousness and the Self Handout [16] Jesse Prinz: Mental Pointing Phenomenal Knowledge Without Concepts
![Phil 490: Consciousness and the Self Handout [16] Jesse Prinz: Mental Pointing Phenomenal Knowledge Without Concepts](/thumbs/88/117469450.jpg "Phil 490: Consciousness and the Self Handout [16] Jesse Prinz: Mental Pointing Phenomenal Knowledge Without Concepts")
Phil 490: Consciousness and the Self Handout [16] Jesse Prinz: Mental Pointing Phenomenal Knowledge Without Concepts Main Goals of this Paper: Professor JeeLoo Liu 1. To present an account of phenomenal
Diagnosing and curing diseases using Chemical Intents and Machine Learning
Diagnosing and curing diseases using Chemical Intents and Machine Learning Dr. Satyendra Singh 1, Divyansh Srivastava 2 Shri. Vishwanath P.G. College, Kalan, Sultanpur, Uttar Pradesh, India 1 Founder and
Baserate Judgment in Classification Learning: A Comparison of Three Models
Baserate Judgment in Classification Learning: A Comparison of Three Models Simon Forstmeier & Martin Heydemann Institut für Psychologie, Technische Universität Darmstadt, Steubenplatz 12, 64293 Darmstadt
Chapter 2--Introduction to the Physiology of Perception
Chapter 2--Introduction to the Physiology of Perception Student: 1. Our perception of the environment depends on A. the properties of the objects in the environment. B. the properties of the electrical
Chapter 11: Sound, The Auditory System, and Pitch Perception
Chapter 11: Sound, The Auditory System, and Pitch Perception Overview of Questions What is it that makes sounds high pitched or low pitched? How do sound vibrations inside the ear lead to the perception
Neurobiology and Information Processing Theory: the science behind education
Educational Psychology Professor Moos 4 December, 2008 Neurobiology and Information Processing Theory: the science behind education If you were to ask a fifth grader why he goes to school everyday, he
0-3 DEVELOPMENT. By Drina Madden. Pediatric Neuropsychology 1
0-3 DEVELOPMENT By Drina Madden DrinaMadden@hotmail.com www.ndcbrain.com 1 PHYSICAL Body Growth Changes in height and weight are rapid in the first two years of life. Development moves from head to tail
Artificial Intelligence
Artificial Intelligence COMP-241, Level-6 Mohammad Fahim Akhtar, Dr. Mohammad Hasan Department of Computer Science Jazan University, KSA Chapter 2: Intelligent Agents In which we discuss the nature of
Sensation is the conscious experience associated with an environmental stimulus. It is the acquisition of raw information by the body s sense organs
Sensation is the conscious experience associated with an environmental stimulus. It is the acquisition of raw information by the body s sense organs Perception is the conscious experience of things and
Rolls,E.T. (2016) Cerebral Cortex: Principles of Operation. Oxford University Press.
Digital Signal Processing and the Brain Is the brain a digital signal processor? Digital vs continuous signals Digital signals involve streams of binary encoded numbers The brain uses digital, all or none,
Information Processing & Storage in the Brain
Information Processing & Storage in the Brain Jaekyun Moon KAIST Oct 16, 2012 @ NVRAMOS Is the doll turning clock-wise or counter-clock-wise? 2 Left Brain ( 지성적 ) vs Right Brain ( 감성적 ) LEFT BRAIN FUNCTIONS
CS/NEUR125 Brains, Minds, and Machines. Due: Friday, April 14
CS/NEUR125 Brains, Minds, and Machines Assignment 5: Neural mechanisms of object-based attention Due: Friday, April 14 This Assignment is a guided reading of the 2014 paper, Neural Mechanisms of Object-Based
Consolidating working memory: Enhancing cognitive performance through effective encoding
Consolidating working memory: Enhancing cognitive performance through effective encoding Donna Bayliss Neurocognitive Development Unit School of Psychology University of Western Australia 1 Consolidation
Biological Cybernetics 9 Springer-Verlag 1984
Biol. Cybern. 50,32-336 (184) Biological Cybernetics Springer-Verlag 184 A Computer Model for Learning Processes and the Role of the Cerebral Commissures P. A. Anninos, P. Argyrakis, and A. Skouras Department
Beyond the Psychologist s Report. Nancy Foster, PhD Institute for Brain-Behavior Integration
Beyond the Psychologist s Report human mental processes are complex functional systems that are not localized in narrow, circumscribed areas of the brain, but take place through the participation of groups
Review Questions. Know how Aristotle and Plato differed in their ideas of universals and particulars.
Review Questions Chapter 1 What is cognition? What is cognitive psychology? What is the distinction between structure and process? Who was Diogenes of Apollania? What is the transcendental method proposed
1. A type of learning in which behavior is strengthened if followed by a reinforcer or diminished if followed by a punisher.
1. A stimulus change that increases the future frequency of behavior that immediately precedes it. 2. In operant conditioning, a reinforcement schedule that reinforces a response only after a specified
Neurons-Parts, functions, types, neurotransmitters Divisions of the nervous system-cns, PNS-somatic, autonomicsympathetic,
AP Psychology Semester Exam Review Chapter 1. Perspectives/History Historical perspectives-structuralism, functionalism, Gestalt, behaviorism, psychoanalysis-know who the major names are associated with
Exploring the Structure and Function of Brain Networks
Exploring the Structure and Function of Brain Networks IAP 2006, September 20, 2006 Yoonsuck Choe Brain Networks Laboratory Department of Computer Science Texas A&M University choe@tamu.edu, http://research.cs.tamu.edu/bnl
Theoretical Neuroscience: The Binding Problem Jan Scholz, , University of Osnabrück
The Binding Problem This lecture is based on following articles: Adina L. Roskies: The Binding Problem; Neuron 1999 24: 7 Charles M. Gray: The Temporal Correlation Hypothesis of Visual Feature Integration:
Human cogition. Human Cognition. Optical Illusions. Human cognition. Optical Illusions. Optical Illusions
Human Cognition Fang Chen Chalmers University of Technology Human cogition Perception and recognition Attention, emotion Learning Reading, speaking, and listening Problem solving, planning, reasoning,
The Nervous System and the Endocrine System
The Nervous System and the Endocrine System Neurons: The Building Blocks of the Nervous System Nervous System The electrochemical communication system of the body Sends messages from the brain to the