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Ch 31 Sensation & Perception Ch. 3: Vision © Takashi Yamauchi (Dept. of Psychology, Texas A&M University) Main topics –convergence –Inhibition, lateral.

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Presentation on theme: "Ch 31 Sensation & Perception Ch. 3: Vision © Takashi Yamauchi (Dept. of Psychology, Texas A&M University) Main topics –convergence –Inhibition, lateral."— Presentation transcript:

1 ch 31 Sensation & Perception Ch. 3: Vision © Takashi Yamauchi (Dept. of Psychology, Texas A&M University) Main topics –convergence –Inhibition, lateral inhibition and lightness perception –Interactions between neurons –Feature detectors

2 ch 32 Question 1 What do these devices have in common?

3 ch 33 These devices make use of electromagnetic waves Capture electromagnetic waves and transform them into electricity.

4 ch 34 What does the eye do?  Transducing light energy into electrical energy

5 ch 35 Transduction  Light enters the eye  A photon hits a receptor  changes the shape of pigment molecules  triggers massive chemical reactions  generate electrical signals

6 ch 36

7 How big are they? –Power of Ten (10 min) –http://www.youtube.com/watch?feature=player _embedded&v=0fKBhvDjuy0#! ch 37

8 8 Solar cells (photovoltaics) produce electricity in a similar way as our eyes do.

9 ch 39 Rods and cones Morphology Distribution on the retina Dark adaptation Spectral sensitivity

10 ch 310 Photo receptors: Rods and cones Rods have bigger outer segments than cones. Why?

11 ch 311 Outer segments capture photons Bigger outer segments can capture more light. Rods have bigger outer segments. –Rods allow us to see in the dark. –Cones are mainly for day vision. –Cones are for color perception.

12 ch 312 How can we see a book? How can we see a desk? Why don’t we see light? How can we see objects?

13 ch 313 Reflection of light What we see is a reflection of light. Different objects reflect different wavelengths, –  different objects show different colors

14 ch 314 Photo receptors in the eye are geared to capture different wavelengths

15 ch 315 Lens: focuses light rays. Iris: control the size of the pupil  regulating the amount of light reaching the retina Retina: a layer of receptor cells Receptor cells  rods and cones

16 ch 316 Retina:

17 ch 317 Photo receptors are facing away from the light source. The optic nerve carries neural information to this spot. What happens? –No receptors, no vision  blind spot

18 ch 318 Some messages: how to improve your vision Massage your eye muscles Eat carrots Massage the back of your head.

19 ch 319 Rods and cones Morphology Distribution on the retina Dark adaptation Spectral sensitivity

20 ch 320 The distribution of cones and rods on the retina Cones are concentrated mainly on the fovea. There are no rods on the fovea. We move eyes to capture images on the fovea.

21 ch 321 Demonstration Blind spot

22 ch 322 Rods and cones are different In their dark adaptation rates

23 ch 323 Dark adaptation rates of rods and cones When you enter a dark room from outside, you can’t see well at first. But gradually, your eyes are adjusted to the dark, and see better.

24 ch 324 Review

25 ch 325 Visual perception What is the difference between (a) & (b)? What is going on in your head when you see (a) versus when you see (b)? (a) (b)

26 ch 326

27 ch 327

28 ch 328 How about this?

29 ch 329

30 ch 330

31 ch 331

32 ch 332

33 ch 333

34 ch 334

35 ch 335 What’s going on? When you see the square, what’s going on? How do you find out?

36 ch 336 In terms of the activity of neurons, what is the difference between A and B ? Any guess? A. B.

37 ch 337 Measuring the electrical activity of a neuron directly by inserting a thin needle into animal brains.

38 ch 238 Time 0t The frequency of action potential Time 0 t The number of action potential emitted by a neuron is correlated with the intensity of the stimulus. Time 0 t 5 units 10 units 20 units

39 ch 2 39 Physical quantities Time 0 t 0 t 5 units 20 units Perceived quantities

40 ch 340 Neural Processing by Convergence Why are rods more sensitive to light than cones?

41 ch 341 Activities of neurons can be schematically shown as B a1 a2 a3 a4 The firing rate of neuron B is determined by the activation sent by neurons a1-a4.

42 ch 342 Ganglion cell

43 ch 343 Convergence: The ratio of connections with two groups of neurons. Rods vs. Ganglion cells –120:1 Cones vs. Ganglion cells –6:1

44 ch 344

45 ch 345

46 ch 346 Why does this matter? How is this related to the higher sensitivity of rods?

47 ch 347 The cones result in better detail vision than the rods Visual acuity –How far apart are two dots?

48 ch 348 Time 0t The frequency of action potential Time 0t 0t The number of action potential emitted by a neuron is correlated with the intensity of the stimulus.

49 ch 349

50 ch 350

51 ch 351 Fig. 2.11, p.53

52 ch 352

53 ch 353

54 ch 354

55 ch 355 Demonstration: On a scratch paper, draw two vertical lines of about 2 inches (1/2 inch apart). Close your left eye, and focus your right eye on your index figure, and move the figure. At some point, you can’t distinguish the two vertical lines.

56 ch 356 The distribution of cones and rods on the retina Cones are concentrated mainly on the fovea. There are no rods on the fovea. We move eyes to capture images on the fovea.

57 ch 357 Visual Cortex

58 ch 358

59 ch 359

60 ch 360 The cones result in better detail vision than the rods Visual acuity –How far apart are two dots?

61 ch 361 Neurons How do you detect there are two separate dots (lights)?

62 ch 362

63 ch 363 How do you detect there are two separate dots (lights)?

64 ch 364 Rods are bigger than cones Convergence:

65 ch 365 Lateral Inhibition & Mach bands

66 ch 366 Herman grid

67 ch 367 10, 10, 10, 10, 10, 10, 10, Physical quantities 10, 5, 10, 5, 10, 5, 10, Perceived quantities  Something is going on inside your brain.  What is it?  Can you explain “something” in terms of the way neurons talk to each other?

68 ch 368  Something is going on inside your brain.  What is it?  Can you explain “something” in terms of the way neurons talk to each other? Some neurons send excitatory (+) signals (transmitter), and other neurons send inhibitory (-) signals.

69 ch 369

70 ch 370

71 ch 271 Time 0t The frequency of action potential Time 0 t The number of action potential emitted by a neuron is correlated with the intensity of the stimulus. Time 0 t 5 units 10 units 20 units

72 ch 372 Questions: What happens to B? 0 t

73 ch 373 Questions: What happens to B? ExcitatoryInhibitory

74 ch 374 Receptive field The receptive field of a neuron in the visual system is the area on the retina that influences the firing rate (action potential) of the neuron. Measuring the receptive field of a ganglion cell

75 ch 375 Receptive field of a ganglion cell Measuring the frequency of action potentials elicited by this ganglion cell. Cones Ganglion cell B

76 ch 376 Receptive field of a ganglion cell Cones Ganglion cell B 12 3 4 5 6 7 Firing rate of B 43-52-62-7

77 ch 377 Questions: What happens to B?

78 ch 378 Measuring the receptive field of a ganglion cell Change the size of the stimulus and see the way a ganglion cell respond

79 ch 379 Cones Ganglion cell B 12 3 4 5 6 7

80 ch 380 ExcitatoryInhibitory Excitatory- center- inhibitory- surround receptive field

81 ch 381 Questions: What happens to B? ExcitatoryInhibitory

82 ch 382 Excitatory and inhibitory connections What neurons transmit is electricity. Some neurons send positive (excitatory) signals (+)  increase the firing rate of the target neuron. some neurons send negative (inhibitory) signals (-)  depress the firing rate of the target neuron.

83 ch 383 Spatial Summation c1 c2 c3 c4 B a1 a2 a3 a4 + + = 4 + + B a1 a2 a3 a4 + + = 0 + + - - - - The firing rate of neuron B can be expressed by the overall summation of the signals that B receives.

84 ch 384

85 ch 385

86 ch 386 How does this happen?

87 ch 387 =sum(B)

88 ch 388 Fig. 3-6, p. 50

89 ch 389 Fig. 3-7, p. 51

90 ch 390 Why is this important?  help you to detect the edge of a figure

91 ch 391

92 ch 392 Light intensity location Perceived Light intensity location

93 ch 393 Physical stimuliYour perception

94 ch 394 Lateral inhibition

95 ch 395 + -- + -- 10020 + -- + --

96 ch 396

97 ch 397

98 ch 398 White’s illusion Can you explain this by lateral inhibition?

99 ch 399

100 ch 3100

101 ch 3101

102 ch 3102

103 ch 3103

104 ch 3104

105 ch 3105

106 ch 3106 Application: Machine vision Implementing lateral inhibition into a computer program.

107 ch 3107 Image

108 ch 3108

109 ch 3109

110 ch 3110

111 ch 3111 Edge detection algorithm –Zero-crossing


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