Phil Anderson (1972) "More is Different". limitations of “representative individual” “mean field” / continuum / linear way of thinking -conceptual gaps.

Slides:



Advertisements
Similar presentations
Jacob Goldenberg, Barak Libai, and Eitan Muller
Advertisements

Caroline Chisholm College
Cognitive Systems, ICANN panel, Q1 What is machine intelligence, as beyond pattern matching, classification and prediction. What is machine intelligence,
From social psychology to sociology - a physicist’s point of view Katarzyna Sznajd-Weron Institute of Theoretical Physics Wrocław University Praha, November.
G. Alonso, D. Kossmann Systems Group
Spontaneous recovery in dynamic networks Advisor: H. E. Stanley Collaborators: B. Podobnik S. Havlin S. V. Buldyrev D. Kenett Antonio Majdandzic Boston.
Induction of Decision Trees
Simulation.
COMP 3009 Introduction to AI Dr Eleni Mangina
Simulation Models as a Research Method Professor Alexander Settles.
Developing Ideas for Research and Evaluating Theories of Behavior
Teaching with Depth An Understanding of Webb’s Depth of Knowledge
Chapter 12: Simulation and Modeling Invitation to Computer Science, Java Version, Third Edition.
Artificial intelligence. [I]f there had been such machines, possessing the organs and outward form of a monkey or some other animal without reason,
Quantum theory and Consciousness This is an interactive discussion. Please feel free to interrupt at any time with your questions and comments.
Artificial Intelligence
An Automatic Segmentation Method Combined with Length Descending and String Frequency Statistics for Chinese Shaohua Jiang, Yanzhong Dang Institute of.
Business and Management Research
Phil Anderson (1972) "More is Different". limitations of “representative individual” “mean field” / continuum / linear way of thinking -conceptual gaps.
Chapter 12: Simulation and Modeling
Economic Complexity and Econometric Simplicity Prof. Ping Chen Spring /20/2004.
Demand Management and Forecasting
Copyright © Cengage Learning. All rights reserved.
Notes on Complexity NEST meeting May 7, 2003 Sorin Solomon.
Capacity analysis of complex materials handling systems.
Business Forecasting Used to try to predict the future Uses two main methods: Qualitative – seeking opinions on which to base decision making – Consumer.
Complexity Sorin Solomon, Racah Institute of Physics HUJ Israel Complex Multi-Agent Systems Division, ISI Turin Lagrange Interdisciplinary Lab for Excellence.
Battling bacterial evolution: The work of Carl Bergstrom
VISUAL PERCEPTION 1. Developed by the German school called Gestalt Psychology –The relation between the figure and the background –Termination or closure.
Introduction to Science Unit 1. The Nature of Science Attempt to answer questions about the natural world by: Exploring the unknown Explaining the known.
(- ∞ ) General Background: The Microscopic Representation of Complex Macroscopic Phenomena,, Annual Reviews of Computational Physics II p 243, ed D. Stauffer,
(- ∞ ) General Background: The Microscopic Representation of Complex Macroscopic Phenomena,, Annual Reviews of Computational Physics II p 243, ed D. Stauffer,
Complexity Research and Economic Growth Sorin Solomon Racah Institute of Physics HUJ Israel Complex Multi-Agent Systems Division, ISI Turin Lagrange Interdisciplinary.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Chapter 6 The Standard Deviation as a Ruler and the Normal Model.
Executive Abstract Logistic dynamics has been recognized since 200 years to govern a wide range of social, economic, biological and cognitive systems.
Copyright © 2009 Pearson Education, Inc. Chapter 6 The Standard Deviation as a Ruler and the Normal Model.
MBA.782.ForecastingCAJ Demand Management Qualitative Methods of Forecasting Quantitative Methods of Forecasting Causal Relationship Forecasting Focus.
CHAPTER 10: CORE MECHANICS Definitions and Mechanisms.
AP STATISTICS LESSON SIMULATING EXPERIMENTS.
Complexity Emergence in Economics Sorin Solomon, Racah Institute of Physics HUJ Israel Scientific Director of Complex Multi-Agent Systems Division, ISI.
Demand Management and Forecasting Module IV. Two Approaches in Demand Management Active approach to influence demand Passive approach to respond to changing.
Philosophy 4610 Philosophy of Mind Week 8: Can a Computer Think?
T-99 0 CT C T-99 0 CT C T-99 0 CT C.
 What is Modeling What is Modeling  Why do we Model Why do we Model  Models in OMT Models in OMT  Principles of Modeling Principles of Modeling 
The argument from reason. leibniz’s law arguments 1)All Fs are G. 2)o is not G. 3)o is not an F.
Why Impossible Things Happen so Often? The emergence of Macroscopic Complex Objects from Microscopic Noise N.Shnerb Y.Louzoun E.Bettelheim S.Solomon D.
Complexity Emergence in Economics Sorin Solomon, Racah Institute of Physics HUJ Israel Scientific Director of Complex Multi-Agent Systems Division, ISI.
Changing the Rules of the Game Dr. Marco A. Janssen Department of Spatial Economics.
Complexity Sorin Solomon, Multi-Agent Division ISI and Racah Institute of Physics HUJ MORE IS DIFFERENT (Anderson 72) (more is more than more) Complex.
Ch. 1: Introduction: Physics and Measurement. Estimating.
Chapter 7 What Can Computers Do For Me?. How important is the material in this chapter to understanding how a computer works? 4.
Chapter 1: Introduction. Physics The most basic of all sciences! Physics: The “Parent” of all sciences! Physics: The study of the behavior and the structure.
 Developed by the German school called Gestalt Psychology The relation between the figure and the background Termination or closure principle Other perceptive.
Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 6 The Standard Deviation as a Ruler and the Normal Model.
The emergence of Self-Organized Sustainable Ecologies from Individual random interactions D Mazursky (Soc. Sci., Bus. Adm.) Henri Atlan (biology), Irun.
Phil Anderson (1972) "More is Different". limitations of “representative individual” “mean field” / continuum / linear way of thinking -conceptual gaps.
Copyright © 2009 Pearson Education, Inc. Chapter 11 Understanding Randomness.
What is Physics? The study of matter, energy, and the interaction between them Physics is about asking fundamental questions and trying to answer them.
MGT601 SME MANAGEMENT. Lesson 24 Aspects of Financial Management.
Traffic Simulation L2 – Introduction to simulation Ing. Ondřej Přibyl, Ph.D.
Game Art and Design Unit 4 Lesson 1 Game Conceptualization
Chapter 12: Simulation and Modeling
Elementary Statistics
Business and Management Research
Cognitive approach Lesson 6.
Automating Profitable Growth™
Subscript and Summation Notation
Business and Management Research
Functions and Graphing
Presentation transcript:

Phil Anderson (1972) "More is Different". limitations of “representative individual” “mean field” / continuum / linear way of thinking -conceptual gaps between various disciplines. - accompanying mysteries connected to the nature of life, intelligence, culture -arise exactly when "More Is Different". life emerges from chemistry, chemistry from physics, conscience from life, social conscience/ organization from individual conscience etc.

The Microscopic Representation Method. MICRO - the relevant microscopic degrees of freedom INTER - their fundamental interactions MACRO - the macroscopic emerging collective objects Intrinsically interdisciplinary: -Micro belongs to one science -Macro to another science -Mechanisms: statistical mechanics (?) phase transitions, scale invariance, spontaneous symmetry breaking etc At C nothing special happens to one or two H 2 O molecules! or 100 or 1000! How come that 1 Kg of them behave so dramatically?

- Microscopic Customers and Macroscopic Sales MICRO – Customers, products / ideas / information INTER – purchase, inform, learn, hear-say MACRO – global trends, waves of sales (e.g. Tamaguchi), hits, flops, market fluctuations, anomalous diffusion demarketing

- Microscopic Investors and Macroscopic Crashes /Power Laws MICRO - Investors, individual capital,shares INTER - sell/buy orders, gain/loss MACRO - social wealth distribution, market price fluctuations (cycles, crushes, booms, stabilization by noise)

-Microscopic Concepts and Macroscopic Ideas MICRO - concepts, connections between concepts INTER - creating/deleting/activating connections between concepts - Microscopic Seers and Macroscopic Sight MICRO - motion visual sensors for points and line elements. INTER - time and space local data integration. MACRO - Perception of 3 Dimensional global structure.

- Microscopic Picassos and Macroscopic Drawings MICRO - local line / motion features, mental states, mental events INTER - line breaks and mind events(changes) vs line/mind inertia. MACRO - drawing shapes, emergence of representational meaning - Microscopic Doctors and Macroscopic Health MICRO - Cells, Enzimes, Antigens, Antibodies INTER - producing, destroying, changing state of a cell/enzime, MACRO - immunity, health, infection, sickness, inflamation. -Microscopic Drivers / police and Macroscopic Jams MICRO - cars INTER - go ahead/give way at intersections. MACRO - traffic flow, jamming; self-organization; useless police

Microscopic Grimm Brothers and Macroscopic Stories MICRO – persons, relations INTER – change in relations ; acting MACRO –plot, story, meaning

Internet study along the same lines 1. physical, 2. information flow and 3. emergent / cognitive. LAYERS MicroMacro 1. Cognitive / Social Layer Self- Organization Content based service relationships, rings Peer-To-Peer nets Emergence of Collective Complex Institutions with personality and interests 2. WEB Information Layer Sites, links, information storage and flow Distributed Information storage, processing retrieval, control, trust 3.INTERNET Hardware Layer Nodes, cables, data packets Connectivity, robustness

Microscopic Investors and Macroscopic Crashes M. Levy, H. Levy and S. Solomon, Economics Letters 45 (1994)

Fundamentalists believe the market will eventually revert to the fundamental price. Hence, the price they offer will be determined by: Chartists, believe in trends they. The simplest choice for short times is a linear extrapolation Noise-traders are making “ random ” offers at a price randomly distributed around the current price.

L.Muchnick and S.Solomon Physica Scripta, in press

Stock market shock explained Physicists model recent trading frenzy. 1 October 2002 Market makers Market 'spikes' are seen by traders as freak events. Physicists expect them, Thursday October 3, 2002 Newton (after loosing 20 K Pounds in stock market) “I can calculate the motions of heavenly bodies, but not the madness of people.“

Levy, Solomon and Levy's Microscopic Simulation of Financial Markets points us towards the future of financial economics." Harry M. Markowitz, Nobel Laureate in Economics

How do we see it? A matter of 2 points of view. Restricted Ability to Recover 3D Global Motion from 1 D Motion Signals: Theoretical Observations, N. Rubin, S. Hochstein and S. Solomon, Vision Research 35 (1995) Restricted Ability to Recover 3D Global Motion from 1 D Motion Signals: Psychophysical Observations, N. Rubin, S. Hochstein and S. Solomon, Vision Research 35 (1995)

To what elementary receptors are sensitive? - line-like features such as contours or frontiers passing through the or - point-like features such as corners or line-ends? - the position and velocity of the microscopic features, or - also to their acceleration -Answer: - micros: corners and line-ends - use mainly positions and velocities -instead of the complicated exact algorithms, approximate ad-hoc ones -=> macroscopic illusions predicted and confirmed T=1 T=2 T=3

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Image Speed and assumption x~y~z NOT Image Speed and acceleration (3 times formulae) LOST of 3D rigidity feeling 3D rigidity perception insenstive to large up to x2 deformations Vision Research 35 (1995)

TRACES OF MIND Emergence of Representation in Drawing: The Relation Between Kinematic and Referential Aspects Ester Adi-Japha, Iris Levin and S. Solomon Cognitive Development 13, (1998)

We identified and characterized children 2-3 yrs When / how do they first associate representational meaning to their drawings? Breaks. discrete sharp corners in their own drawings: not to the drawings of other children only shortly having experienced the act of drawing Breaks discrete mental events

Our findings can be summarized as follows - In the drawing process one can identify inertial periods of a few seconds in which nothing happens with respect to representation -During these periods the motion is characterized by a simple kinematic rule.

These inertial kinematical periods are interrupted by discrete events characterized by a Break in the continuity of the velocity and direction of the pencil motion Breaks turn out to be the central element of the present work

representational meaning  Breaks smooth kinematic inertial parts  nonsignicant Breaks are correlated with a posteriori representation

Creative Sparks Jacob Goldenberg, David Mazursky, and Sorin Solomon Science 285: , 1999;

Figure 2b: General scheme underlying the replacement version of the pictorial analogy template

Communication at the speed of sound

NY Times

Herald Tribune

Examples of Replacement computer produced ideas · Image of Apple Computer Terminal/ handing of Flowers (for advertising Apple computers friendliness) · Texture of Tennis Ball / Temple Mountain Mosque (for advertising World Cup Tennis Tournament in Jerusalem). · Shape of Plane/ Coo-coo in Coo-coo Clock (for advertising the time accuracy of a flight company). · Picture of Jeeps/ Speaking in Sign Language (for silent car engine) shape of car/ bullet (for fast car).

Table 2: Idea Ratings for the Four Sources Creativity RatingsMeanS.D. Winning Ads Magazine Ads Routine-Generated Ads Laymen-Generated Ads Originality RatingsMeanS.D. Winning Ads Magazine Ads Routine-Generated Ads Laymen-Generated Ads

What Are Stories Made Of? Quantitative Categorical Deconstruction of Creation Y. Stolov, M. Idel, S. Solomon, Int. J. Mod. Phys. C 11 (2000) 1 ;

EVENT EVENT NO EVENT TOTAL DENSITY but and NO LINK LENGTH NO LINK LINK RAVEN % PRINCESS % (Lost Princess story has no end) 21 commentators, 29 events Ordered in nr of commentators. Highest one diagonal was only rank 14 Only one non-link below it.

Testing the Turing Test Do Men pass it?

Turing test: ‘ imitation game’“ I propose to consider the question “ Can machines think?”... I shall replace the question by another... The new form of the problem can be described in terms of a game which we call the ‘ imitation game’. (A.M Turing (1950) Computing Machinery and Intelligence. Mind 49 :

The participate in the test: Interrogator : Needs to discover who is the human and who is the computer. Human: Aims to help the interrogator. Computer: aims to fool the interrogator. The interrogator is allowed only to ask them questions. But can ask any and as many questions as he wants.

“… in about fifty years’ time … interrogator will not have more than 70 percent chance of making the right identification … ” A.M Turing, Computing Machinery and Intelligence, Mind 49 (1950) 433,

Method: between a man and a womanDoing the imitation game not between human and computer but between a man and a woman. Interrogator: needs to discover who is the man and who is the woman. Turing said – can be of either sex Woman: Aim to help the interrogator. Man: Aim to fool the interrogator. Turing himself talks about imitation game between man and woman!

“ We now ask the question “What will happen when a machine takes the part of A in this game? “Will the interrogator decide wrongly as often when the game is played like this as he does when the game is played between a man and a woman? These questions replace our original, “Can machines think?” ”

Turing assumed that humans can pass the test – but this assumption has not been tested

results: The men in the imitation game are reveled (80%). In this case, an intelligent creature can’t imitate another intelligent creature. Turing test is not valid. Turing deduced his test from the imitation game.

Losing All Battles and Wining the War HIV time hierarchy: U Hershberg, Y Louzoun, H Atlan and S Solomon Physica A: 289 (1-2) (2001) pp ;

A = antigens (virons) B = cells of the immune system i = index of the particular characteristic shape of virus/immune cell A i  A i  1 Virons can mutate (actually in a n-dim space) A i +B *  A i Immune cells of any type are destroyed when infected by viruses of any type A i +B i  A i +B i +B i Immune cells multiply when they meet virons with complementary shape to theirs A i  A i +A i Virons multiply B i +A i  B i Virons are destroyed when detected by immune cells of complementary shape

B B B B B B B B The immune system generates cells with various characteristic shapes to probe for the presence of antigens with complementary shapes. Shape space

B B B B B B B B Once some virons get in the system, they multiply unhindered as long as none of them meets an immune system cell with complementary shape. Infection Shape space B

B B B B B B B B B Once one viron (individual from the strain) meets an immune system cell the cell keeps multiplying and its descendents meet more virons and multiply too. Some mutant virons with different shape (and therefore undetectable by the present strain of immune cells) are produced.

B The virons from the strain detected by the cells with complementary shape are destroyed. The mutant ones have different shape. They are not detected (yet) so they multiply unhindered.

B The detected viron strain is destroyed by the immune system. Shape space

B The detected viron strain is destroyed by the immune system. Shape space

B The detected viron strain is destroyed by the immune system. Shape space

B Before being completely destroyed, the detected strain is able to generate randomly more mutants, with different characteristic shape. Shape space

B B B The initial strain is decimated but the mutants are still undetected and multiply unhindered. Shape space

B B B The initial strain has now disappeared. The acute phase: primary infection, is finished. The mutants are still undetected. This strain has so small population that even an immune cell with complementary shape doesn’t meet/detect any of its individuals.

B B B After the initial strain is destroyed, the immune cells with complementary shape do not meet any excitation and they die without multiplying. Some “memory cells” with the information of the initial strain shape are left (forever). In the meantime one of the mutant strains is detected 

B  Shape space

B B B B B  The immune cells with the complementary shape to the detected strain multiply. They are not many enough yet to stop the multiplication of the strain and in particular the generation of some mutants. Shape space

B B B B The detected strain is being decimated but its mutants do well and in fact produce mutants of themselves. Shape space 

B B B B B The detected strain is about to disappear and another strain is just being detected. 

B B The antibodies corresponding to the destroyed strain disappear. Only memory cells are left. Antibodies corresponding to the newly detected strain are being produced.  

B B  

B  

B  

B  

B The virus looses another battle but the number of strains keeps increasing.   

The virus looses another battle but the number of strains keeps increasing until it overcomes the immune system. X X X XXX XX X X XXX X X X XXX X X X XXX X X X XX XXX    

New strains appear and are destroyed within weeks. Many new small strains accumulate and destroy many immune system cells. The system collapses The strains of the first invasion are completely wiped out REALITY SIMULATION

Transistors -> chips -> boards-> computer -> clusters -> internet Currents-> digital I/O -> coded I/O -> interrupts, packets

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

NOW WITHOUT OBSTRUCTION

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Now obstructing lines

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)

Corners essential Lines Not RECEPTORS Vision Research 35 (1995)