What is a receptive field? Why a sensory neuron has such particular RF How a RF was developed?

Size: px
Start display at page:

Download "What is a receptive field? Why a sensory neuron has such particular RF How a RF was developed?"

Transcription

1

2 What is a receptive field? Why a sensory neuron has such particular RF How a RF was developed?

3 x 1 x 2 x 3 y f w 1 w 2 w 3 T x y = f (wx i i T ) i y

4

5

6

7

8

9

10

11

12 The receptive field of a receptor is simply the area of the visual field from which light strikes that receptor. For any other cell in the visual system, the receptive field is determined by which receptors connect to the cell in question.

13 !

14 The solid black curve represents the amount of light being reflected from the figure at the top. The red curve represents the brightness of this figure as it is usually perceived. To the left of the point where the figure just starts to get lighter people usually see a dark bar that is slightly darker that the area to the left of it. At the point where the brightness just stops increasing, people usually perceive a bright bar. This phenomenon was discovered by the famous physicist, Ernst Mach and it is in his honor that these dark and bright bars are called Mach Bands. These Mach Bands can be explaind by center-surround receptive field interactions. " #

15 The receptive fields are represented as a disk (+) and annulus (-). The center disk is an excitatory area and the annulus an inhibitory area. The receptive fields in the uniformly white and uniformly black areas receive about the same stimulation in their excitatory centers and inhibitory surrounds. Therefore the center excitations are in balance with the surround inhibitions. The receptive field over the bright Mach Band gives a stronger response in the center because part of the surround is in the darker area. Therefore it receives less inhibition from the surround than did the center at the extreme left and right ends. The receptive field over the dark band receives more surround inhibition because part of the surround is in the brighter area. Therefore, the excitatory response is less and this results in our seeing that the area as darker. " #

16 You undoubtedly saw a square figure which had a small rather light square area in the center and increasingly darker perimetric strips extending to the edge. You probably also saw bright arms radiating diagonally out from the center. This figure was adapted from a chromatic version designed by V. Vasarely (Arcturus (1970) as reported in Hurvich, $ These brighter diagonal areas are physically not in the figure. That is to say, if you were to use a light measuring instrument (a photometer) and measure the amount of light coming from any of the concentric perimetric strips you would find that the same amount of light is reflected from all points along any one strip. Yes, that includes that part of the strip along the diagonal where it appears brighter. Consequently, that must mean that this brightness illusion is generated in the visual system.

17 $ These curves represent the amount of light reflected from the identified areas. The amount of light is constant around each perimetric strip. These curves represent the perceived brightness. Note that near the diagonal the apparent amount of light increases.

18 Notice in the receptive field on the left that although a small part of the inhibitory surround lies in the white center a small part of it also lies in the darkest part of the figure. With the receptive field placed as it is one might expect that the size of the surround inhibitory response would be about the same as the size of the center excitatory response. Now look at the receptive field on the right. Clearly more of the inhibitory surround lies in either the same gray as the center or in darker areas. Only a small portion lies in a brighter area than the excitatory center. Consequently, one would expect that the excitatory center would have a larger response on the diagonal than for a receptive field not on a diagonal. Hence there appears a brightness enhancement on the diagonals of this diagram. You, of course, noticed that there is no brightness on the diagonals in this figure. $

19

20 %

21 %

22 " &%

23 What is a receptive field? Why a sensory neuron has such particular RF How a RF was developed?

24 Image Analysis?

25 Image Analysis

26 '

27 " " x + y G x, y) = ( πσ σ 2 x + y )exp( 2σ ( ) DOG( e, i ) = [ 1 2 x 2 exp( )] [ 2 2 e 1 2 e x 2 exp( )] 2 2 i

28 ( )* + Computer Vision:,)** - "., Retina: 1,000 MIPS! = 3*5*.../0)

29 = 75,000 # )65& *6*3 #,)** ". = 75,000

30

31 / 7%8 78 σ σ f F 1 2 7%8 78 σ F σ f

32 9 : ; & )+< H Environment 9 -

33 Relative amplitude Relative amplitude 1 * Spatial frequency Spatial frequency 6

34 =

35

36 y e e= y -x =' >?,>,>@A y e x e= y x X e x x

37 y x 1 =' >?,>,>@A x i x 2 y = a 1 x 1 + a 2 x 2 + a 3 x 3 + a 4 x 4 a i = x 1 *y

38 y e x i y = a 1 x 1 + a 2 x 2 + a 3 x 3 + a 4 x 4 x 1 y=xa 9 %,B% ) % 3 % C % D E,B ) 3 C D E ' x 2 $ F G a=(x t x) -1 x t y

39 y e x 1 How to choose basis functions? y = a 1 x 1 + a 2 x 2 + a 3 x 3 + a 4 x 4 x 2 1 -

40 =

41

42 %

43 1!

44 "

45 1!

46 .

47 What is a receptive field? Why a sensory neuron has such particular RF How a RF was developed?

48 $

49 $

50 /$

51 2 x y '=! 7%08, 7%8H 78I.7%08 9.7%08 2G '! % 2 " % 2 7%08.7%08.7%08,* 0%0 7%08,7%878.,.

BASIC VISUAL SCIENCE CORE

BASIC VISUAL SCIENCE CORE BASIC VISUAL SCIENCE CORE Absolute and Increment Thresholds Ronald S. Harwerth Fall, 2016 1. Psychophysics of Vision 2. Light and Dark Adaptation Michael Kalloniatis and Charles Luu 1 The Neuron Doctrine

More information

15 Grossberg Network 1

15 Grossberg Network 1 Grossberg Network Biological Motivation: Vision Bipolar Cell Amacrine Cell Ganglion Cell Optic Nerve Cone Light Lens Rod Horizontal Cell Retina Optic Nerve Fiber Eyeball and Retina Layers of Retina The

More information

Limulus. The Neural Code. Response of Visual Neurons 9/21/2011

Limulus. The Neural Code. Response of Visual Neurons 9/21/2011 Crab cam (Barlow et al., 2001) self inhibition recurrent inhibition lateral inhibition - L16. Neural processing in Linear Systems: Temporal and Spatial Filtering C. D. Hopkins Sept. 21, 2011 The Neural

More information

Surround effects on the shape of the temporal contrast-sensitivity function

Surround effects on the shape of the temporal contrast-sensitivity function B. Spehar and Q. Zaidi Vol. 14, No. 9/September 1997/J. Opt. Soc. Am. A 2517 Surround effects on the shape of the temporal contrast-sensitivity function Branka Spehar School of Psychology, University of

More information

We are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists. International authors and editors

We are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists. International authors and editors We are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists 3,9 6, M Open access books available International authors and editors Downloads Our authors are

More information

Leo Kadanoff and 2d XY Models with Symmetry-Breaking Fields. renormalization group study of higher order gradients, cosines and vortices

Leo Kadanoff and 2d XY Models with Symmetry-Breaking Fields. renormalization group study of higher order gradients, cosines and vortices Leo Kadanoff and d XY Models with Symmetry-Breaking Fields renormalization group study of higher order gradients, cosines and vortices Leo Kadanoff and Random Matrix Theory Non-Hermitian Localization in

More information

Sparse Coding as a Generative Model

Sparse Coding as a Generative Model Sparse Coding as a Generative Model image vector neural activity (sparse) feature vector other stuff Find activations by descending E Coefficients via gradient descent Driving input (excitation) Lateral

More information

Color perception SINA 08/09

Color perception SINA 08/09 Color perception Color adds another dimension to visual perception Enhances our visual experience Increase contrast between objects of similar lightness Helps recognizing objects However, it is clear that

More information

COMPUTATIONAL ROLE OF DISINHIBITION IN BRAIN FUNCTION. A Dissertation YINGWEI YU

COMPUTATIONAL ROLE OF DISINHIBITION IN BRAIN FUNCTION. A Dissertation YINGWEI YU COMPUTATIONAL ROLE OF DISINHIBITION IN BRAIN FUNCTION A Dissertation by YINGWEI YU Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the

More information

Perception of brightness. Perception of Brightness. Physical measures 1. Light Ray. Physical measures 2. Light Source

Perception of brightness. Perception of Brightness. Physical measures 1. Light Ray. Physical measures 2. Light Source Perception of Brightness The physics and psychophysics Perception of brightness psychophysics: relate psychological measures to physical ones perception of brightness is one of the simplest aspects of

More information

Simultaneous lightness contrast with double increments

Simultaneous lightness contrast with double increments Perception, 2001, volume 30, pages 889 ^ 897 DOI:10.1068/p3103 Simultaneous lightness contrast with double increments Paola Bressan, Rossana Actis-Grosso Dipartimento di Psicologia Generale, Universita

More information

Tuning tuning curves. So far: Receptive fields Representation of stimuli Population vectors. Today: Contrast enhancment, cortical processing

Tuning tuning curves. So far: Receptive fields Representation of stimuli Population vectors. Today: Contrast enhancment, cortical processing Tuning tuning curves So far: Receptive fields Representation of stimuli Population vectors Today: Contrast enhancment, cortical processing Firing frequency N 3 s max (N 1 ) = 40 o N4 N 1 N N 5 2 s max

More information

A Neural Model of the Scintillating Grid Illusion: Disinhibition and Self-Inhibition in Early Vision

A Neural Model of the Scintillating Grid Illusion: Disinhibition and Self-Inhibition in Early Vision LETTER Communicated by Sidney Lehky A Neural Model of the Scintillating Grid Illusion: Disinhibition and Self-Inhibition in Early Vision Yingwei Yu yingwei@tamu.edu Yoonsuck Choe choe@tamu.edu Department

More information

Motion Perception 1. PSY305 Lecture 12 JV Stone

Motion Perception 1. PSY305 Lecture 12 JV Stone Motion Perception 1 PSY305 Lecture 12 JV Stone 1 Structure Human visual system as a band-pass filter. Neuronal motion detection, the Reichardt detector. The aperture problem. 2 The visual system is a temporal

More information

Natural Image Statistics

Natural Image Statistics Natural Image Statistics A probabilistic approach to modelling early visual processing in the cortex Dept of Computer Science Early visual processing LGN V1 retina From the eye to the primary visual cortex

More information

Spatial Vision: Primary Visual Cortex (Chapter 3, part 1)

Spatial Vision: Primary Visual Cortex (Chapter 3, part 1) Spatial Vision: Primary Visual Cortex (Chapter 3, part 1) Lecture 6 Jonathan Pillow Sensation & Perception (PSY 345 / NEU 325) Princeton University, Spring 2015 1 Chapter 2 remnants 2 Receptive field:

More information

Brightness induction: Unequal spatial integration with increments and decrements

Brightness induction: Unequal spatial integration with increments and decrements Visual Neuroscience (2004), 21, 353 357. Printed in the USA. Copyright 2004 Cambridge University Press 0952-5238004 $16.00 DOI: 10.10170S0952523804213037 Brightness induction: Unequal spatial integration

More information

Ângelo Cardoso 27 May, Symbolic and Sub-Symbolic Learning Course Instituto Superior Técnico

Ângelo Cardoso 27 May, Symbolic and Sub-Symbolic Learning Course Instituto Superior Técnico BIOLOGICALLY INSPIRED COMPUTER MODELS FOR VISUAL RECOGNITION Ângelo Cardoso 27 May, 2010 Symbolic and Sub-Symbolic Learning Course Instituto Superior Técnico Index Human Vision Retinal Ganglion Cells Simple

More information

CLINICAL VISUAL OPTICS (OPTO 223) Weeks XII & XIII Dr Salwa Alsaleh

CLINICAL VISUAL OPTICS (OPTO 223) Weeks XII & XIII Dr Salwa Alsaleh CLINICAL VISUAL OPTICS (OPTO 223) Weeks XII & XIII Dr Salwa Alsaleh OUTLINE OF WEEKS XII & XIII Temporal resolution Temporal Summation. Broca-Sulzer effect. Critical flicker frequency (CFF). Temporal Contrast

More information

Step brightness changes of distant mountain ridges and their perception

Step brightness changes of distant mountain ridges and their perception Step brightness changes of distant mountain ridges and their perception David K. Lynch When successive ridges of distant mountains are seen, observers often report that, near the ridge where the brightness

More information

Introduction to Neural Networks U. Minn. Psy Lateral inhibition. Introduction. Mach bands & perception. Last time. Today

Introduction to Neural Networks U. Minn. Psy Lateral inhibition. Introduction. Mach bands & perception. Last time. Today Introduction to Neural Networks U. Minn. Psy 5038 Lateral inhibition Introduction Last time Developed a "structure-less, continuous signal, and discrete time" generic neuron model and from there built

More information

arxiv: v3 [q-bio.nc] 1 Sep 2016

arxiv: v3 [q-bio.nc] 1 Sep 2016 Interference of Neural Waves in Distributed Inhibition-stabilized Networks arxiv:141.4237v3 [q-bio.nc] 1 Sep 216 Sergey Savel ev 1, Sergei Gepshtein 2,* 1 Department of Physics, Loughborough University

More information

Effects of Betaxolol on Hodgkin-Huxley Model of Tiger Salamander Retinal Ganglion Cell

Effects of Betaxolol on Hodgkin-Huxley Model of Tiger Salamander Retinal Ganglion Cell Effects of Betaxolol on Hodgkin-Huxley Model of Tiger Salamander Retinal Ganglion Cell 1. Abstract Matthew Dunlevie Clement Lee Indrani Mikkilineni mdunlevi@ucsd.edu cll008@ucsd.edu imikkili@ucsd.edu Isolated

More information

LESSON 1. Solar System

LESSON 1. Solar System Astronomy Notes LESSON 1 Solar System 11.1 Structure of the Solar System axis of rotation period of rotation period of revolution ellipse astronomical unit What is the solar system? 11.1 Structure of the

More information

Theory of colour measurement Contemporary wool dyeing and finishing

Theory of colour measurement Contemporary wool dyeing and finishing Theory of colour measurement Contemporary wool dyeing and finishing Dr Rex Brady Deakin University Colour measurement theory Topics 1. How we see colour 2. Generation of colours 3. Measurement of colour

More information

What is the solar system?

What is the solar system? Notes Astronomy What is the solar system? 11.1 Structure of the Solar System Our solar system includes planets and dwarf planets, their moons, a star called the Sun, asteroids and comets. Planets, dwarf

More information

Introduction to Neural Networks. Lateral inhibition. Introduction. Mach bands & perception. Last time. Today

Introduction to Neural Networks. Lateral inhibition. Introduction. Mach bands & perception. Last time. Today Introduction to Neural Networks Lateral inhibition Introduction Last time Developed a "structure-less, continuous signal, and discrete time" generic neuron model and from there built a network. Basic linear

More information

Phase Response. 1 of of 11. Synaptic input advances (excitatory) or delays (inhibitory) spiking

Phase Response. 1 of of 11. Synaptic input advances (excitatory) or delays (inhibitory) spiking Printed from the Mathematica Help Browser 1 1 of 11 Phase Response Inward current-pulses decrease a cortical neuron's period (Cat, Layer V). [Fetz93] Synaptic input advances (excitatory) or delays (inhibitory)

More information

A Model of Local Adaptation supplementary information

A Model of Local Adaptation supplementary information A Model of Local Adaptation supplementary information Peter Vangorp Bangor University, UK & MPI Informatik, Germany Karol Myszkowski MPI Informatik, Germany Erich W. Graf University of Southampton, United

More information

Adaptation in the Neural Code of the Retina

Adaptation in the Neural Code of the Retina Adaptation in the Neural Code of the Retina Lens Retina Fovea Optic Nerve Optic Nerve Bottleneck Neurons Information Receptors: 108 95% Optic Nerve 106 5% After Polyak 1941 Visual Cortex ~1010 Mean Intensity

More information

Higher -o-o-o- Past Paper questions o-o-o- 3.4 Spectra

Higher -o-o-o- Past Paper questions o-o-o- 3.4 Spectra Higher -o-o-o- Past Paper questions 1991-2010 -o-o-o- 3.4 Spectra 1992 Q37 The diagram below shows the energy levels for the hydrogen atom. (a) Between which two energy levels would an electron transition

More information

A Three-dimensional Physiologically Realistic Model of the Retina

A Three-dimensional Physiologically Realistic Model of the Retina A Three-dimensional Physiologically Realistic Model of the Retina Michael Tadross, Cameron Whitehouse, Melissa Hornstein, Vicky Eng and Evangelia Micheli-Tzanakou Department of Biomedical Engineering 617

More information

Visual Motion Analysis by a Neural Network

Visual Motion Analysis by a Neural Network Visual Motion Analysis by a Neural Network Kansai University Takatsuki, Osaka 569 1095, Japan E-mail: fukushima@m.ieice.org (Submitted on December 12, 2006) Abstract In the visual systems of mammals, visual

More information

12.2. The Earth Moon System KNOW? The Phases of the Moon. Did You

12.2. The Earth Moon System KNOW? The Phases of the Moon. Did You 12.2 The Earth Moon System Did You KNOW? The Moon is Earth s closest neighbour. It is highly influential in our lives because it causes the oceans tides. The Moon is also responsible for eclipses. waxing

More information

8/30/2010. Classifying Stars. Classifying Stars. Classifying Stars

8/30/2010. Classifying Stars. Classifying Stars. Classifying Stars Classifying Stars In the early 1900s, Ejnar Hertzsprung and Henry Russell made some important observations. They noticed that, in general, stars with higher temperatures also have brighter absolute magnitudes.

More information

Vision & Perception. Simple model: simple reflectance/illumination model. image: x(n 1,n 2 )=i(n 1,n 2 )r(n 1,n 2 ) 0 < r(n 1,n 2 ) < 1

Vision & Perception. Simple model: simple reflectance/illumination model. image: x(n 1,n 2 )=i(n 1,n 2 )r(n 1,n 2 ) 0 < r(n 1,n 2 ) < 1 Simple model: simple reflectance/illumination model Eye illumination source i(n 1,n 2 ) image: x(n 1,n 2 )=i(n 1,n 2 )r(n 1,n 2 ) reflectance term r(n 1,n 2 ) where 0 < i(n 1,n 2 ) < 0 < r(n 1,n 2 )

More information

Sensors. Sensory Physiology. Transduction. Types of Environmental Stimuli. Chemoreception. Taste Buds (Contact Chemoreceptors)

Sensors. Sensory Physiology. Transduction. Types of Environmental Stimuli. Chemoreception. Taste Buds (Contact Chemoreceptors) Sensors Sensory Physiology Chapter 13 Detect changes in environmental conditions Primary Sensors neurons modified to undergo action potentials in response to specific stimuli (e.g. chemical, mechanical)

More information

Contrast Sensitivity

Contrast Sensitivity Contrast Sensitivity Performance in a vision based task, such as reading text, recognizing faces, or operating a vehicle, is limited by the overall quality of the image. Image quality depends on many factors,

More information

A Possible Model of Noise EnhancedVisual Perception in Human Vision

A Possible Model of Noise EnhancedVisual Perception in Human Vision A Possible Model of Noise EnhancedVisual Perception in Human Vision Ajanta Kundu Applied Nuclear Physics Division Saha Institute of Nuclear Physics 1/AF Bidhannagar, Kolkata, India ajanta.kundu@saha.ac.in

More information

Opponent Color Spaces

Opponent Color Spaces C. A. Bouman: Digital Image Processing - January 8, 2018 1 Opponent Color Spaces Perception of color is usually not best represented in RGB. A better model of HVS is the so-call opponent color model Opponent

More information

background light falling not only on the tested region, but also on surrounding stimuli, whereas here we were dealing with an adaptation rather

background light falling not only on the tested region, but also on surrounding stimuli, whereas here we were dealing with an adaptation rather J. Physiol. (197), 26, pp. 129-143 129 With 1 text-figures Printed in Great Britain DISTANCE EFFECTS IN HUMAN SCOTOPIC RETINAL INTERACTION BY GERALD WESTHEIMER AND R. W. WILEY* From the Department of Physiology-Anatomy,

More information

Lightness, equivalent backgrounds, and anchoring

Lightness, equivalent backgrounds, and anchoring Perception & Psychophysics 1997, 59 (5), 643-654 Lightness, equivalent backgrounds, and anchoring NICOLA BRUNO and PAOLO BERNARDIS University of Trieste, Trieste, Italy and JAMES SCHIRILLO Wake Forest

More information

Neural Networks 1 Synchronization in Spiking Neural Networks

Neural Networks 1 Synchronization in Spiking Neural Networks CS 790R Seminar Modeling & Simulation Neural Networks 1 Synchronization in Spiking Neural Networks René Doursat Department of Computer Science & Engineering University of Nevada, Reno Spring 2006 Synchronization

More information

Astronomy 1 Winter Lecture 24; March

Astronomy 1 Winter Lecture 24; March Astronomy 1 Winter 2011 Lecture 24; March 7 2011 Previously on Astro-1 Introduction to special relativity Introduction to general relativity Introduction to black holes, stellar and supermassive Today..

More information

Remodelling colour contrast: implications for visual processing and colour representation

Remodelling colour contrast: implications for visual processing and colour representation Vision Research 39 (1999) 1329 1345 Remodelling colour contrast: implications for visual processing and colour representation A.J. Shepherd * Department of Psychology, Birkbeck College, Uni ersity of London,

More information

SENSORY PROCESSES PROVIDE INFORMATION ON ANIMALS EXTERNAL ENVIRONMENT AND INTERNAL STATUS 34.4

SENSORY PROCESSES PROVIDE INFORMATION ON ANIMALS EXTERNAL ENVIRONMENT AND INTERNAL STATUS 34.4 SENSORY PROCESSES PROVIDE INFORMATION ON ANIMALS EXTERNAL ENVIRONMENT AND INTERNAL STATUS 34.4 INTRODUCTION Animals need information about their external environments to move, locate food, find mates,

More information

University of California, Berkeley, California, U.S.A. (Received 14 June 1965)

University of California, Berkeley, California, U.S.A. (Received 14 June 1965) J. Phy8iol. (1965), 181, pp. 881-894 881 With 8 text-ftgure8 Printed in Great Britain SPATIAL INTERACTION IN THE HUMAN RETINA DURING SCOTOPIC VISION BY G. WESTHEIMER From the Neurosensory Laboratory, School

More information

Properties of Stars (continued) Some Properties of Stars. What is brightness?

Properties of Stars (continued) Some Properties of Stars. What is brightness? Properties of Stars (continued) Some Properties of Stars Luminosity Temperature of the star s surface Mass Physical size 2 Chemical makeup 3 What is brightness? Apparent brightness is the energy flux (watts/m

More information

Neural Networks. Fundamentals of Neural Networks : Architectures, Algorithms and Applications. L, Fausett, 1994

Neural Networks. Fundamentals of Neural Networks : Architectures, Algorithms and Applications. L, Fausett, 1994 Neural Networks Neural Networks Fundamentals of Neural Networks : Architectures, Algorithms and Applications. L, Fausett, 1994 An Introduction to Neural Networks (nd Ed). Morton, IM, 1995 Neural Networks

More information

Simple Cell Receptive Fields in V1.

Simple Cell Receptive Fields in V1. Simple Cell Receptive Fields in V1. The receptive field properties of simple cells in V1 were studied by Hubel and Wiesel [65][66] who showed that many cells were tuned to the orientation of edges and

More information

Gradient representation and perception in the early visual system A novel account of Mach band formation

Gradient representation and perception in the early visual system A novel account of Mach band formation Vision Research 46 (2006) 2659 2674 www.elsevier.com/locate/visres Gradient representation and perception in the early visual system A novel account of Mach band formation Matthias S. Keil a, *, Gabriel

More information

Overview Organization: Central Nervous System (CNS) Peripheral Nervous System (PNS) innervate Divisions: a. Afferent

Overview Organization: Central Nervous System (CNS) Peripheral Nervous System (PNS) innervate Divisions: a. Afferent Overview Organization: Central Nervous System (CNS) Brain and spinal cord receives and processes information. Peripheral Nervous System (PNS) Nerve cells that link CNS with organs throughout the body.

More information

Chapter 26: Properties of Light

Chapter 26: Properties of Light Lecture Outline Chapter 26: Properties of Light This lecture will help you understand: Electromagnetic Waves The Electromagnetic Spectrum Transparent Materials Opaque Materials Seeing Light The Eye Electromagnetic

More information

Colour Part One. Energy Density CPSC 553 P Wavelength 700 nm

Colour Part One. Energy Density CPSC 553 P Wavelength 700 nm Colour Part One Energy Density 400 Wavelength 700 nm CPSC 553 P 1 Human Perception An Active Organising Process Many illusions experiments from psychology Colour not just a matter of measuring wavelength

More information

Nervous Systems: Neuron Structure and Function

Nervous Systems: Neuron Structure and Function Nervous Systems: Neuron Structure and Function Integration An animal needs to function like a coherent organism, not like a loose collection of cells. Integration = refers to processes such as summation

More information

AST 102 chapter 5. Radiation and Spectra. Radiation and Spectra. Radiation and Spectra. What is light? What is radiation?

AST 102 chapter 5. Radiation and Spectra. Radiation and Spectra. Radiation and Spectra. What is light? What is radiation? 5 Radiation and Spectra 1 Radiation and Spectra What is light? According to Webster: a.something that makes vision possible b.the sensation aroused by stimulation of the visual receptors c.electromagnetic

More information

Station 1 - Applicability Reading Total Solar Eclipse

Station 1 - Applicability Reading Total Solar Eclipse Station 1 - Applicability Reading Total Solar Eclipse Instructions : Read the following information article and answer the associated questions found below. Total solar eclipses occur when the Moon comes

More information

COLOR SCIENCE. Concepts and Methods, Quantitative Data and Formulae, 2nd Edition. John Wiley & Sons New York Chichester Brisbane Toronto Singapore

COLOR SCIENCE. Concepts and Methods, Quantitative Data and Formulae, 2nd Edition. John Wiley & Sons New York Chichester Brisbane Toronto Singapore COLOR SCIENCE Concepts and Methods, Quantitative Data and Formulae, 2nd Edition GÜNTER WYSZECKI National Research Council, Ottawa, Ontario, Canada W. S. STILES Richmond, Surrey, England t^- n M 1982 A

More information

The functional organization of the visual cortex in primates

The functional organization of the visual cortex in primates The functional organization of the visual cortex in primates Dominated by LGN M-cell input Drosal stream for motion perception & spatial localization V5 LIP/7a V2 V4 IT Ventral stream for object recognition

More information

MRI Physics I: Spins, Excitation, Relaxation

MRI Physics I: Spins, Excitation, Relaxation MRI Physics I: Spins, Excitation, Relaxation Douglas C. Noll Biomedical Engineering University of Michigan Michigan Functional MRI Laboratory Outline Introduction to Nuclear Magnetic Resonance Imaging

More information

THE PERCEPTUAL CONFLICT IN BINOCULAR RIVALRY. W. J. M. Levelt*

THE PERCEPTUAL CONFLICT IN BINOCULAR RIVALRY. W. J. M. Levelt* V THE PERCEPTUAL CONFLICT IN BINOCULAR RIVALRY W. J. M. Levelt* Normally, the human mind makes a portrait of the visual world with the aid of both eyes. The small differences between the retinal images,

More information

Detectable Warnings: Synthesis of U.S. and International Practice 12 May 2000

Detectable Warnings: Synthesis of U.S. and International Practice 12 May 2000 Detectable Warnings: Synthesis of U.S. and International Practice 12 May 2000 Accessible Design for the Blind U.S. Access Board, 1331 F Street, NW, Suite 1000, Washington, DC 20004-1111 Please feel free

More information

Dendrites - receives information from other neuron cells - input receivers.

Dendrites - receives information from other neuron cells - input receivers. The Nerve Tissue Neuron - the nerve cell Dendrites - receives information from other neuron cells - input receivers. Cell body - includes usual parts of the organelles of a cell (nucleus, mitochondria)

More information

Self-correcting Symmetry Detection Network

Self-correcting Symmetry Detection Network Self-correcting Symmetry Detection Network Wonil hang 1,yunAhSong 2, Sang-oon Oh 3, and Soo-Young Lee 1,2 1 Department of Bio and Brain Engineering, 2 Department of Electrical Engineering, KAIST, Daejeon

More information

Tissue Characteristics Module Three

Tissue Characteristics Module Three Tissue Characteristics Module Three 1 Equilibrium State Equilibrium State At equilibrium, the hydrogen vector is oriented in a direction parallel to the main magnetic field. Hydrogen atoms within the vector

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION Figure S1 Multiplicative scaling of the granule cell input-output relation is not dependent on input rate. Input-output relations with short-term depression (STD) from Fig. 1d after normalizing by the

More information

A thermodynamic origin of a universal mass-angular momentum relationship

A thermodynamic origin of a universal mass-angular momentum relationship A thermodynamic origin of a universal mass-angular momentum relationship Astrophysics and Space Science, v133, pp 403-410 (1987) M. N. Macrossan Department of Mechanical Engineering University of Queensland,

More information

How Complex Cells Are Made in a Simple Cell Network

How Complex Cells Are Made in a Simple Cell Network How Complex Cells Are Made in a Simple Cell Network Louis Tao Courant Institute, New York University Collaborators: Michael Shelley (Courant, NYU) Robert Shapley (CNS, NYU) David McLaughlin (Courant, NYU)

More information

Assignment #12 The Milky Way

Assignment #12 The Milky Way Name Date Class Assignment #12 The Milky Way For thousands of years people assumed that the stars they saw at night were the entire universe. Even after telescopes had been invented, the concept of a galaxy

More information

A Tour of the Messier Catalog. ~~ in ~~ Eight Spellbinding and Enlightening Episodes. ~~ This Being Episode Three ~~

A Tour of the Messier Catalog. ~~ in ~~ Eight Spellbinding and Enlightening Episodes. ~~ This Being Episode Three ~~ A Tour of the Messier Catalog ~~ in ~~ Eight Spellbinding and Enlightening Episodes ~~ This Being Episode Three ~~ Globulars and Galaxies Warm-up for The Realm M83 Spiral Galaxy Constellation Hydra

More information

Linear Combinations of Optic Flow Vectors for Estimating Self-Motion a Real-World Test of a Neural Model

Linear Combinations of Optic Flow Vectors for Estimating Self-Motion a Real-World Test of a Neural Model Linear Combinations of Optic Flow Vectors for Estimating Self-Motion a Real-World Test of a Neural Model Matthias O. Franz MPI für biologische Kybernetik Spemannstr. 38 D-72076 Tübingen, Germany mof@tuebingen.mpg.de

More information

OBSERVATIONS OF THE RED SPOT ON JUPITER. Bradford A. Smith and Clyde W. Tombaugh. Research Center New Mexico State University

OBSERVATIONS OF THE RED SPOT ON JUPITER. Bradford A. Smith and Clyde W. Tombaugh. Research Center New Mexico State University OBSERVATIONS OF THE RED SPOT ON JUPITER Bradford A. Smith and Clyde W. Tombaugh Research Center New Mexico State University Photographic observations of the Red Spot on Jupiter have been made on 33 dates

More information

Module 4: Astronomy - The Solar System Topic 2 Content: Solar Activity Presentation Notes

Module 4: Astronomy - The Solar System Topic 2 Content: Solar Activity Presentation Notes The Sun, the largest body in the Solar System, is a giant ball of gas held together by gravity. The Sun is constantly undergoing the nuclear process of fusion and creating a tremendous amount of light

More information

Bio 449 Fall Exam points total Multiple choice. As with any test, choose the best answer in each case. Each question is 3 points.

Bio 449 Fall Exam points total Multiple choice. As with any test, choose the best answer in each case. Each question is 3 points. Name: Exam 1 100 points total Multiple choice. As with any test, choose the best answer in each case. Each question is 3 points. 1. The term internal environment, as coined by Clause Bernard, is best defined

More information

thebiotutor.com A2 Biology Unit 5 Responses, Nervous System & Muscles

thebiotutor.com A2 Biology Unit 5 Responses, Nervous System & Muscles thebiotutor.com A2 Biology Unit 5 Responses, Nervous System & Muscles 1 Response Mechanism tropism Definition A growth movement of part of plant in response to a directional stimulus examples Positive:

More information

Star Systems and Galaxies

Star Systems and Galaxies Star Systems and Galaxies Why Does the Milky Way Look Hazy? 1. Using a pencil, carefully poke at least 20 holes close together in a sheet of white paper. 2. Tape the paper to a chalkboard or dark-colored

More information

Consider the following spike trains from two different neurons N1 and N2:

Consider the following spike trains from two different neurons N1 and N2: About synchrony and oscillations So far, our discussions have assumed that we are either observing a single neuron at a, or that neurons fire independent of each other. This assumption may be correct in

More information

2.0 Lesson Plan. Answer Questions. Summary Statistics. Histograms. The Normal Distribution. Using the Standard Normal Table

2.0 Lesson Plan. Answer Questions. Summary Statistics. Histograms. The Normal Distribution. Using the Standard Normal Table 2.0 Lesson Plan Answer Questions 1 Summary Statistics Histograms The Normal Distribution Using the Standard Normal Table 2. Summary Statistics Given a collection of data, one needs to find representations

More information

Tilt-aftereffect and adaptation of V1 neurons

Tilt-aftereffect and adaptation of V1 neurons Tilt-aftereffect and adaptation of V1 neurons Dezhe Jin Department of Physics The Pennsylvania State University Outline The tilt aftereffect (TAE) Classical model of neural basis of TAE Neural data on

More information

Prentice Hall EARTH SCIENCE

Prentice Hall EARTH SCIENCE Prentice Hall EARTH SCIENCE Tarbuck Lutgens Chapter 25 Beyond Our Solar System 25.1 Properties of Stars Characteristics of Stars A constellation is an apparent group of stars originally named for mythical

More information

Lecture 07, 13 Sept 2005 Chapters 12 and 13. Vertebrate Physiology ECOL 437 (aka MCB 437, VetSci 437) University of Arizona Fall 2005

Lecture 07, 13 Sept 2005 Chapters 12 and 13. Vertebrate Physiology ECOL 437 (aka MCB 437, VetSci 437) University of Arizona Fall 2005 Lecture 07, 13 Sept 2005 Chapters 12 and 13 Vertebrate Physiology ECOL 437 (aka MCB 437, VetSci 437) University of Arizona Fall 2005 instr: Kevin Bonine t.a.: Kristen Potter Vertebrate Physiology 437 Chapter

More information

(Received 16 December 1975)

(Received 16 December 1975) J. Phyeiol. (1976), 262, pp. 265-284 265 With 10 text-figure8 Printed in Great Britain LINEAR AND NONLINEAR SPATIAL SUBUNITS IN Y CAT RETINAL GANGLION CELLS BY S. HOCHSTEIN* AND R. M. SHAPLEY From the

More information

Exercises. Chapter 1. of τ approx that produces the most accurate estimate for this firing pattern.

Exercises. Chapter 1. of τ approx that produces the most accurate estimate for this firing pattern. 1 Exercises Chapter 1 1. Generate spike sequences with a constant firing rate r 0 using a Poisson spike generator. Then, add a refractory period to the model by allowing the firing rate r(t) to depend

More information

Basic Pulse Sequences I Saturation & Inversion Recovery UCLA. Radiology

Basic Pulse Sequences I Saturation & Inversion Recovery UCLA. Radiology Basic Pulse Sequences I Saturation & Inversion Recovery Lecture #5 Learning Objectives Explain what the most important equations of motion are for describing spin systems for MRI. Understand the assumptions

More information

Introduction to Neural Networks Linear representations of high-dimensional patterns Lateral inhibition

Introduction to Neural Networks Linear representations of high-dimensional patterns Lateral inhibition Introduction to Neural Networks Linear representations of high-dimensional patterns Lateral inhibition Introduction Last time Developed a generic neuron model and from there built a network. The model

More information

Note on Posted Slides. History of Light. History of Light

Note on Posted Slides. History of Light. History of Light Note on Posted Slides These are the slides that I intended to show in class on Wed. Mar. 27, 2013. They contain important ideas and questions from your reading. Due to time constraints, I was probably

More information

Stars and Galaxies 1

Stars and Galaxies 1 Stars and Galaxies 1 Characteristics of Stars 2 Star - body of gases that gives off great amounts of radiant energy as light and heat 3 Most stars look white but are actually different colors Antares -

More information

Limb Darkening. Limb Darkening. Limb Darkening. Limb Darkening. Empirical Limb Darkening. Betelgeuse. At centre see hotter gas than at edges

Limb Darkening. Limb Darkening. Limb Darkening. Limb Darkening. Empirical Limb Darkening. Betelgeuse. At centre see hotter gas than at edges Limb Darkening Sun Betelgeuse Limb Darkening Stars are both redder and dimmer at the edges Sun Limb Darkening Betelgeuse Limb Darkening Can also be understood in terms of temperature within the solar photosphere.

More information

A Neuromorphic Model for Achromatic and Chromatic Surface Representation of Natural Images

A Neuromorphic Model for Achromatic and Chromatic Surface Representation of Natural Images Neuromorphic Model for chromatic and Chromatic Surface Representation of Natural Images Simon Hong + and Stephen Grossberg * Department of Cognitive and Neural Systems nd Center for daptive Systems Boston

More information

ADVANCED IMAGE PROCESSING CELLULAR NEURAL NETWORKS

ADVANCED IMAGE PROCESSING CELLULAR NEURAL NETWORKS Papers International Journal of Bifurcation and Chaos Vol. 17 No. 4 (2007) 1109 1150 c World Scientific Publishing Company ADVANCED IMAGE PROCESSING CELLULAR NEURAL NETWORKS MAKOTO ITOH Department of Information

More information

Color-Magnitude Diagram Lab Manual

Color-Magnitude Diagram Lab Manual Color-Magnitude Diagram Lab Manual Due Oct. 21, 2011 1 Pre-Lab 1.1 Photometry and the Magnitude Scale The brightness of stars is represented by its value on the magnitude scale. The ancient Greek astronomer

More information

The Sine Wave. You commonly see waves in the environment. Light Sound Electricity Ocean waves

The Sine Wave. You commonly see waves in the environment. Light Sound Electricity Ocean waves The Sine Wave Mathematically, a function that represents a smooth oscillation For example, if we drew the motion of how the weight bobs on the spring to the weight we would draw out a sine wave. The Sine

More information

Laboratory: Milky Way

Laboratory: Milky Way Department of Physics and Geology Laboratory: Milky Way Astronomy 1402 Equipment Needed Quantity Equipment Needed Quantity Milky Way galaxy Model 1 Ruler 1 1.1 Our Milky Way Part 1: Background Milky Way

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION Supplementary discussion 1: Most excitatory and suppressive stimuli for model neurons The model allows us to determine, for each model neuron, the set of most excitatory and suppresive features. First,

More information

JNDs, adaptation, and ambient illumination

JNDs, adaptation, and ambient illumination JNDs, adaptation, and ambient illumination Giovanni Ramponi IPL, University of Trieste, Italy Rev. Jul 2012 The observations we make are based on: some properties of the Human Visual System (HVS), the

More information

Modeling Surround Suppression in V1 Neurons with a Statistically-Derived Normalization Model

Modeling Surround Suppression in V1 Neurons with a Statistically-Derived Normalization Model Presented at: NIPS-98, Denver CO, 1-3 Dec 1998. Pulished in: Advances in Neural Information Processing Systems eds. M. S. Kearns, S. A. Solla, and D. A. Cohn volume 11, pages 153--159 MIT Press, Cambridge,

More information

V2 Thin Stripes Contain Spatially Organized Representations of Achromatic Luminance Change

V2 Thin Stripes Contain Spatially Organized Representations of Achromatic Luminance Change Cerebral Cortex January 2007;17:116-129 doi:10.1093/cercor/bhj131 Advance Access publication February 8, 2006 V2 Thin Stripes Contain Spatially Organized Representations of Achromatic Luminance Change

More information

Motion Perception, Perceptual Constancy, Perceptual Interpretation, and ESP (it s not real )

Motion Perception, Perceptual Constancy, Perceptual Interpretation, and ESP (it s not real ) Motion Perception, Perceptual Constancy, Perceptual Interpretation, and ESP (it s not real ) Motion Perception & Perceptual Constancy Which car is bigger? What is in my hand? Motion Perception Stroboscopic

More information

Fundamentals of Computational Neuroscience 2e

Fundamentals of Computational Neuroscience 2e Fundamentals of Computational Neuroscience 2e January 1, 2010 Chapter 10: The cognitive brain Hierarchical maps and attentive vision A. Ventral visual pathway B. Layered cortical maps Receptive field size

More information