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Psychophysical Assessment of Visual Function As an O.D. you will measure (assess) vision. How well does the person see? Results depend on how you make the measurement. You: Any problems with your vision? Pt: Don’t seem to see so well, Doc. - PowerPoint PPT Presentation

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  • Psychophysical Assessment of Visual Function

    As an O.D. you will measure (assess) vision.How well does the person see?Results depend on how you make the measurement

  • You: Any problems with your vision?

    Pt: Dont seem to see so well, Doc.

    What do you do (how do you learn how well the patient sees)?

  • You measure the patients vision.

    This course is about the science that stands behind why you measure vision certain ways in the clinic.

  • Which chart to use?How many letters per line?How far apart are the letters and lines?How much smaller are the letters on the next line?Which letters to use?How far down the chart must the patient try to read?How score the result?There are many different eye charts The acuity you get will differ depending these factors

  • It is a matter of judgment that determines how the visual system is tested and what constitutes normal variation in sensory processes.

    The clinician must understand the scientific basis on which these judgments are made and how they can be made in the future as new tests of visual function are developed.Thats what this course is about and why it is clinically relevant

  • Dr. Tom Norton606 Worrell [email protected]

    Graduate Student Teaching Assistant:Jason Wilson

  • Class Mon- 9-10:50Tues, 9-10:50Wed, 11:0011:50Lab on 4 ThursdaysCheck the schedule for your day and time(Schedule will be distributed tomorrow) This week: Group C 1-3; gp A 3-5

  • Exams #1 Wed. Jan. 19 (100 pts) Ch 1-3 #2 Tues. Feb. 8 (100 pts) Ch 4-5Final during Final Exam Period (130 pts)(110 pts new, 20 pts cumulative)Labs (4 x 10 pts)Possible pop quizzes (up to 30 pts total)

    Total possible points, 370 (up to 400)Letter grade determined @ end of course

  • LabsAttend at the assigned day and time (unless you make other arrangements with Dr. Norton in advance)Lab Reports due at Monday class after your labAccurately recording and graphing your data is an important part of your lab grade

  • Student-submitted exam questionsA way to control your own future!Procedure: Due several days before exam (email or Word files preferred)Norton reviews, corrects, photocopiesDistributed to class (can use as a study guide)Some of the questions will be used on the exam

  • Three main purposes of courseLearn how vision is measured (scientific basis)Basic facts about monocular visual functionWhat is normal?Neural basis of visual functionWhy does the visual system respond as it does?

  • TextbookThe Psychophysical Measurement of Visual Function

    Norton*, Corliss, Bailey

    Richmond Products, Inc

    (*TTNs author royalties [$2420.41 so far] donated to the UABSO)

  • We will cover 9 ChaptersPrinciples of Psychophysical MeasurementAbsolute Threshold of VisionIntensity DiscriminationAdaptation to Light and DarkSpatial AcuitySpatial VisionTemporal Factors in VisionSkip Chapter 8 (color)8) Postnatal Human Vision DevelopmentThe Aging Visual System

  • Overview

    At the beginning of each chapter.

    Contains a summary of the content of the chapter.

  • Declarative section headings summarize the section they precede

    In the Method of Constant Stimuli the examiner randomly presents a set of stimuli with fixed, predetermined values

    Correct for guessing by incorporating catch trials

  • Study Guide

    Questions at the end of each chapter intended to help you clarify your knowledge (not as useful as I had hoped)

    Lecture overlaps with the book a lot

    but questions also come from the book on topics I dont cover in class!

  • Glossary intended to help you know what terms mean for examDefinitions given in the text definite full credit if you know them verbatim

    Equations must tell what the variables mean

  • Equations must tell what the variables meanWhat is the Stevens Power Function?

    where Y (psi) is the sensory magnitude, k (kappa) is an arbitrary constant determining the scale unit, F (phi) is the stimulus magnitude, and a (alpha) is an exponent that is characteristic of the stimulus used.

  • Graphs The hardest part of this class(because they tend to all look alike) but important because they show the relationship between stimuli and responses

  • Graphs how to dissect and learn themWhat is on the X-axis? (& approx. scale)Physical Stimulus on X-axis (Independent Variable)Usual arrangement:

  • Graphs how to dissect and learn themWhat is on the X-axis? (& approx. scale)What is on the Y-axis? (& approx. scale) Response on Y-axisWhat you are measuring(Dependent Variable)Usual arrangement:Physical Stimulus on X-axis (Independent Variable)

  • Graphs how to dissect and learn themWhat is on the X-axis? (& approx. scale)What is on the Y-axis? (& approx. scale)How plot a data point? Physical Stimulus on X-axis(Independent Variable)Usual arrangement:Response on Y-axisWhat you are measuring(Dependent Variable)

  • GraphsWhat is different in each graph in a family of curves?

  • Lots of details to learn.

    Philosophy: better to have learned and forgotten than to not have learned in the first place.

    example

  • Joke break

    Break the monotony

    but remember that the course has a serious purpose, and the exams can be difficult.

  • Student Response SystemTest to see if it worksWill use for feedbackWill not look at who responds

    Set to room code (23)

  • Chapter 1

    Principles of Psychophysical MeasurementObjectives:Psychophysical MethodsThresholdConstant StimuliLimitsAdjustmentSignal detection theorySensory Magnitude

  • We study visual psychophysics, but there also is auditory psychophysics, somatosensory psychophysics, etc.

    Definition:

    Psychophysics is the study

    of the relationship

    between physical stimuli

    and perceptual responses

  • Why are there so many graphs in this course?Because graphs show relationshipsPhysical Stimulus on X-axis(Independent Variable)Usual arrangement:Response on Y-axisWhat you are measuring(Dependent Variable)

  • Two basic types of psychophysical measures

    Threshold measures (Do you see it)

    2) Sensory Magnitude measures (What does it look like)

  • Do you see the light? Physical stimulus light intensityPerceptual response Seeing the light

    Threshold measure:

    Psychophysics is the study of the relationship between physical stimuli and perceptual responses

  • How far down an eye chart can you read? Physical stimulus Letter sizePerceptual response Identifying letters

    Threshold measure:

    Psychophysics is the study of the relationship between physical stimuli and perceptual responses

  • letter size is the stimulusidentifying letters is response

    We use psychophysical tools to find the threshold the letter size you can see 50% of the time

  • Which is better, 1 or 2? Physical stimulus Lens powerPerceptual response Clarity of the image

    Sensory Magnitude:

    Psychophysics is the study of the relationship between physical stimuli and perceptual responses

  • Why study psychophysics?Psychophysical measurements are fundamental in clinical practiceNeed to know the scientific basis for measuring vision The results you get depend on the way you measure visionNew clinical tools will be developed after you graduate you need the knowledge base to understand how they work and evaluate whether they are useful in your practice.Psychophysics questions have been plentiful on the boards

  • Psychophysical measurements

    are used for descriptive and for analytical purposes and to follow the course of treatment

  • Visual thresholds are the most common psychophysical measurement

  • Definition

    Threshold is defined as the minimum value of a stimulus required to elicit a perceptual response or an altered perceptual response.

    Two types of threshold measurement:

    absolute threshold (in vision) is the minimum value of a stimulus required to detect the presence of light under ideal conditions. (Ch. 2)

    A difference (or increment) threshold is defined as the minimum change in stimulus value that must be added or subtracted to a stimulus to elicit an altered perceptual response. (Ch. 3)

  • The task required of a patient or subject during threshold measurements varies in complexity

    detection task (in vision) does the subject or patient see something?

    discrimination task (in vision) distinguishing between two stimuli with regard to some stimulus characteristic when each stimulus is visible by itself.

    recognition task. providing a name or category of a test object that is visible.

    The distinctions among these various types of tasks are not sharp, but are hierarchical.

  • Important Stimulus Dimensions

    intensity

    wavelength

    size

    exposure duration

    frequency

    shape

    relative locations of elements of the stimulus

    cognitive meaning

    In addition,(NOT stimulus Dimensions!)

    location on the subjects retina

    light adaptation of the subjects visual system

  • Key in measuring thresholds: Try to keep all dimensions unchanged except the one being measured

  • Stimulus Configurations

    Spot on an adapting field (increment thresholds)

    Bipartite field

    Bipartite field with an adapting field

    Spatially separated stimuli (difference thresholds)

  • There are many possible values of L, But only 1 value (theoretically) for threshold L

    (demo)

  • Definition

    Threshold is defined as the minimum value of a stimulus required to elicit a perceptual response or an altered perceptual response.

  • Definition

    Threshold is defined as the minimum value of a stimulus required to elicit a perceptual response or an altered perceptual response.

    But threshold can vary over time (somewhat)

  • Psychophysically measured threshold values vary because of

    fluctuations in the stimulus (Ch. 2)

    fluctuations in neural activity

    fluctuations in alertness or attention

    psychological bias

  • Fluctuations in neural activity

  • For us to see, neural signals must leave the retina and travel to central brain structures.

  • In the early retinal cells (photoreceptors, bipolars, horizontal cells, most amacrines), there are only graded potentials (hyperpolarization and depolarization of the cell)In order to send signals out of the retina, action potentials (spikes) must be generated and travel down the ganglion cells axon to the next location (lateral geniculate nucleus, then to visual cortex)

  • Graded potentialsThe signal changes from graded potentials (voltage changes) into a digital signal in which the number of action potentials per second (firing rate) carries the visual signal.

  • We can eavesdrop on the neurons in the visual pathway with a microelectrode, nestled up against a neuron or its axon and record the responses (number of spikes per second) in response to visual stimuli.B: Action potentials recorded from a single LGN neuron. The same stimulus (a spot of light positioned in the receptive field was presented many 20 times. A: a histogram of the cells responses

  • Action potentials recorded from a single LGN neuronNeural fluctuations: the neuron sometimes responds more, sometimes less, to the same stimulus. Also, the neuron has variable background (maintained) activity that makes it hard for the neuron to detect when the stimulus is present.

    Responses of a neuron in the lateral geniculate nucleus of an anesthetized cat to three separate presentations of a near-threshold visual stimulus. Each small vertical line represents an action potential produced by the neuron. Each row shows the responses of the neuron in a 3 s period. From 0 until 2.5 s a background luminance was present. The stimulus (a light) was turned on at 2.5 s and turned off at 3.0 s, so the stimulus was on for only 0.5 s. (Unpublished data from D. W. Godwin and T. T. Norton,.)

  • This leads us to consider threshold as a probability that a stimulus is detected and to find the stimulus value that is detected 50% of the time (or some other criterion value)

    Psychophysically measured threshold values vary because of

    fluctuations in the stimulus

    fluctuations in neural activity

    fluctuations in alertness or attention

    psychological bias

  • Threshold Determination Methods

    Method of Constant Stimuli

    Method of Limits

    -Staircase

    -Tracking

    Method of Adjustment

  • In the Method of Constant Stimuli the examiner randomly presents a set of stimuli with fixed, predetermined values

  • Figure 1-4. Idealized psychometric function for a threshold detection task using the Method of Constant Stimuli. The threshold stimulus value is obtained by drawing a horizontal line from the 50% value on the response axis to the psychometric function and then dropping a vertical line from the function to the test field intensity axis.

  • In Class Demo

  • Rule: Plot straight lines between data points

  • Silliest Plotting ErrorPlot data points from left to right

  • Silliest Plotting ErrorPlot data points from left to right

  • Most Interesting Curves

  • Figure 1-4. Idealized psychometric function for a threshold detection task using the Method of Constant Stimuli. The threshold stimulus value is obtained by drawing a horizontal line from the 50% value on the response axis to the psychometric function and then dropping a vertical line from the function to the test field intensity axis.

  • Chart1

    0.0146341463

    0.1756097561

    0.4195121951

    0.6585365854

    0.8926829268

    0.9609756098

    1

    1

    1

    1

    1

    Stimulus Value

    Frequency of "Yes" Response

    Whole Class 2010

    Sheet1

    Method of constant Stimuli Class Demo Results - 2010

    Stimulus value

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    190.030.310.570.840.961.001.001.001.001.001.00

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    Values copied over

    front012345678910

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    Sheet1

    Stimulus Value

    Fraction of "Yes" Responses

    Back Rows (4-6)

    Stimulus Value

    Frequency of "Yes" Response

    Whole Class 2010

    Stimulus Value

    Frequency of "Yes" Response

    Front Rows (1-3)

  • Chart3

    0.0315789474

    0.3052631579

    0.5684210526

    0.8421052632

    0.9578947368

    1

    1

    1

    1

    1

    1

    Stimulus Value

    Frequency of "Yes" Response

    Front Rows (1-3)

    Sheet1

    Method of constant Stimuli Class Demo Results - 2010

    Stimulus value

    PersonRowside012345678910

    1104455555555

    2101135555555

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    decimal0.010.180.420.660.890.961.001.001.001.001.00

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    Whole0.010.180.420.660.890.961.001.001.001.001.00

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    Values copied over

    front012345678910

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    Sheet1

    Stimulus Value

    Fraction of "Yes" Responses

    Back Rows (4-6)

    Stimulus Value

    Frequency of "Yes" Response

    Whole Class 2010

    Stimulus Value

    Frequency of "Yes" Response

    Front Rows (1-3)

  • Chart2

    0

    0.0736842105

    0.2842105263

    0.4631578947

    0.8315789474

    0.9263157895

    1

    1

    1

    1

    1

    Stimulus Value

    Fraction of "Yes" Responses

    Back Rows (4-6)

    Sheet1

    Method of constant Stimuli Class Demo Results - 2010

    Stimulus value

    PersonRowside012345678910

    1104455555555

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    front012345678910

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    Sheet1

    Stimulus Value

    Fraction of "Yes" Responses

    Back Rows (4-6)

    Stimulus Value

    Frequency of "Yes" Response

    Whole Class 2010

    Stimulus Value

    Frequency of "Yes" Response

    Front Rows (1-3)

  • One point (added to the exam #1 grade) to the first person to correctly tell me:

    Why might the threshold be lower for the front half of the room?

    Hint: think about a stimulus parameter that might change from the front to the back of the room.

  • The Importance of Using Straight Lines to Connect Data Points

    The data points are the only evidence we have of thresholdWe assume a linear progression from one data point to the nextCan use linear interpolation to determine the threshold accurately

  • The Importance of Using Straight Lines to Connect Data Points

    A dramatic example: If you measure vision incorrectly, you get an incorrect answer about how well a person sees.

  • Another way to mis-estimate threshold

    We are looking for the 50% point, not the closest data point, so we use linear interpolation

  • We want to measure threshold as accurately as possible. Why be satisfied with 6 when 5.8 is more accurate?

  • The Method of Constant Stimuli is the most precise method for determining threshold (the Gold Standard).

    But, this method is cumbersome and time-consuming so it is rarely, if ever, used in clinical practice.

  • Threshold Determination Methods

    Method of Constant Stimuli

    Method of Limits

    -Staircase

    -Tracking

    Method of Adjustment

  • What is another name for the psychometric function?Threshold lineFrequency-of-seeing curveMethod of Constant StimuliPower function

  • In the Method of Limits the examiner sequentially presents a set of stimuli with fixed values

    Trial Number (Stimulus Presentation Direction)

    Stimulus Value

    1

    (Ascending)

    2

    (Descending)

    3

    (Ascending)

    4

    (Descending)

    5

    (Ascending)

    1

    N

    N

    N

    2

    N

    N

    N

    N

    3

    Y

    N

    N

    Y

    4

    N

    Y

    Y

    N

    Y

    5

    N

    Y

    Y

    N

    6

    Y

    Y

    Y

    7

    Y

    Y

    N

    8

    Y

    Y

    9

    Y

    10

    Y

    Average

    Transition

    5.5

    3.5

    3.5

    5.5

    2.5

    4.1

    Table 1- 1. Example of subjects responses over five trials using the method of limits.

  • In Class Demo

  • The Method of Limits is more efficient than the Method of Constant Stimuli because fewer trials are presented.

    Two potential problems:

    anticipation

    perseveration

  • Developed during WWII to test bomb detonators

    Staircase procedure.

  • Staircase procedure.

    Stimulus Value

    Trial Number

    1

    2

    3

    4

    5

    6

    7

    8

    9

    10

    11

    12

    13

    14

    15

    16

    17

    1

    2

    N

    3

    N

    N

    N

    4

    N

    Y

    N

    N

    5

    Y

    Y

    N

    Y

    6

    N

    Y

    7

    Y

    8

    Y

    9

    Y

    Table 1- 2. Example of a subjects responses over 17 trials using the staircase variation on the Method of Limits.

  • Staircase procedure.

    Stimulus Value

    Trial Number

    1

    2

    3

    4

    5

    6

    7

    8

    9

    10

    11

    12

    13

    14

    15

    16

    17

    1

    2

    N

    3

    N

    N

    N

    4

    N

    Y

    N

    N

    5

    Y

    Y

    N

    Y

    6

    N

    Y

    7

    Y

    8

    Y

    9

    Y

    Table 1- 2. Example of a subjects responses over 17 trials using the staircase variation on the Method of Limits.

  • Staircase procedure.

    Stimulus Value

    Trial Number

    1

    2

    3

    4

    5

    6

    7

    8

    9

    10

    11

    12

    13

    14

    15

    16

    17

    1

    2

    N

    3

    N

    N

    N

    4

    N

    Y

    N

    N

    5

    Y

    Y

    N

    Y

    6

    N

    Y

    7

    Y

    8

    Y

    9

    Y

    Table 1- 2. Example of a subjects responses over 17 trials using the staircase variation on the Method of Limits.

  • Staircase procedure.

  • (Developed by Nobel Prize-winning auditory physiologist, Georg von Beksy)

    Tracking procedure

  • Threshold Determination Methods

    Method of Constant Stimuli

    Method of Limits

    -Staircase

    -Tracking

    Method of Adjustment

  • In the Method of Adjustment

    the subject controls the stimulus values

  • In Class Demo

  • Frequency with which LT is seen as equal to L

    The distribution of values of LT that a subject decides are equal to L forms a normal distribution if enough trials are used. The mean of the distribution will be very close to L. The threshold is taken as the value of LT that, when added to or subtracted from L gives an LT that is detectable on 50% of the trials. This occurs 0.68 standard deviations above and below the mean.

  • The Method of Adjustment is most easily used when the stimulus can be changed in a continuous manner, rather than in steps.

    Subjects generally enjoy the Method of Adjustment because they actively participate.

    Boredom and inattention are less of a problem with the Method of Adjustment than with the other methods.

  • Potential problem with the Method of Adjustment

    subjects may use the position of the dial as a cue to where threshold "ought" to be.

    This strategy can by foiled by using a dial that has no numbers and has a variable amount of slip.

  • Controlling response bias and guessing

    Correct for guessing by incorporating catch trials

    Establish the guessing rate by forcing the subject to make choices (forced choice technique)

  • What do you do if the psychometric function doesnt drop down to 0% Yes responses for low stimulus values?

    Assume subject/patient has a bias to guess Yes.

  • Correct for guessing by incorporating catch trials where the stimulus is not presented at all. This gives the guessing rate.

  • The catch trial gives the guessing rate. Then subtract the guessing rate from the data to get the True percent of Yes responses

    Correct for guessing by incorporating catch trials. In this case no stimulus at all was presented for a value of 0, so this was a catch trial.

  • The correction factor is:

  • Do not memorize the formula! It isnt used much. Instead, people use the forced choice procedure

  • Establish the guessing rate by forcing the subject to make choices

    The Forced Choice procedure

  • In Class Demo Two-alternative forced choice

  • But if there are two alternatives (two-alternative forced-choice) you know the guessing rate is 0.5

    The correction factor is still:

  • Figure 1-4. Idealized psychometric function for a threshold detection task using the Method of Constant Stimuli. The threshold stimulus value is obtained by drawing a horizontal line from the 50% value on the response axis to the psychometric function and then dropping a vertical line from the function to the test field intensity axis. Results from yesterdays Method of Constant Stimuli Threshold Measurement

  • Chart1

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    1

    1

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    Stimulus Value

    Fraction of "Yes" Responses

    Whole Class, 2009

    Sheet1

    Method of constant Stimuli Class Demo Results - 2009

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    count45

    sum03103395218223225225225225

    decimal0.000.010.040.150.420.970.991.001.001.001.00

    012345678910

    Whole0.000.010.040.150.420.970.991.001.001.001.00

    012345678910

    front0262053112115115115115115

    230.000.020.050.170.460.971.001.001.001.001.00

    012345678910

    back0141342106108110110110110

    220.000.010.040.120.380.960.981.001.001.001.00

    Values copied over

    012345678910

    front

    2300000111111

    012345678910

    back

    2100000111111

    Sheet1

    Stimulus Value

    Fraction of "Yes" Responses

    Whole Class, 2009

    Stimulus Value

    Fraction of "Yes" Responses

    Front Rows

    Stimulus Value

    Fraction of "Yes" Responses

    Back Rows

    Stimulus Value

    Fraction of "Yes" Responses

    Back Rows

  • Chart2

    00

    10.0173913043

    20.052173913

    30.1739130435

    40.4608695652

    50.9739130435

    61

    71

    81

    91

    101

    Stimulus Value

    Fraction of "Yes" Responses

    Front Rows

    Sheet1

    Method of constant Stimuli Class Demo Results - 2009

    Stimulus value

    PersonRowside012345678910

    1100004555555

    2100102555555

    3100212355555

    4100022555555

    5100035555555

    6200022555555

    7200015555555

    8201221555555

    9200013555555

    10200003555555

    11200002555555

    12201134555555

    13300000555555

    14300013555555

    15300001555555

    16300014555555

    17300022555555

    18300001455555

    19400002555555

    20400000555555

    21400002555555

    22400003555555

    23400010555555

    24400003555555

    25400005555555

    26400014555555

    27500002445555

    28500003555555

    29500000555555

    30500000555555

    31500222555555

    32500002555555

    33500014555555

    34500012555555

    35500011555555

    36500001445555

    37600003555555

    38600023555555

    39600000555555

    40601112455555

    41600000555555

    42600000555555

    43600001555555

    44600001455555

    45600143555555

    count45

    sum03103395218223225225225225

    decimal0.000.010.040.150.420.970.991.001.001.001.00

    012345678910

    Whole0.000.010.040.150.420.970.991.001.001.001.00

    012345678910

    front0262053112115115115115115

    230.000.020.050.170.460.971.001.001.001.001.00

    012345678910

    back0141342106108110110110110

    220.000.010.040.120.380.960.981.001.001.001.00

    Values copied over

    012345678910

    front

    2300000111111

    012345678910

    back

    2100000111111

    Sheet1

    Stimulus Value

    Fraction of "Yes" Responses

    Whole Class, 2009

    Stimulus Value

    Fraction of "Yes" Responses

    Front Rows

    Stimulus Value

    Fraction of "Yes" Responses

    Back Rows

    Stimulus Value

    Fraction of "Yes" Responses

    Back Rows

  • Chart4

    00

    10.0090909091

    20.0363636364

    30.1181818182

    40.3818181818

    50.9636363636

    60.9818181818

    71

    81

    91

    101

    Stimulus Value

    Fraction of "Yes" Responses

    Back Rows

    Sheet1

    Method of constant Stimuli Class Demo Results - 2009

    Stimulus value

    PersonRowside012345678910

    1100004555555

    2100102555555

    3100212355555

    4100022555555

    5100035555555

    6200022555555

    7200015555555

    8201221555555

    9200013555555

    10200003555555

    11200002555555

    12201134555555

    13300000555555

    14300013555555

    15300001555555

    16300014555555

    17300022555555

    18300001455555

    19400002555555

    20400000555555

    21400002555555

    22400003555555

    23400010555555

    24400003555555

    25400005555555

    26400014555555

    27500002445555

    28500003555555

    29500000555555

    30500000555555

    31500222555555

    32500002555555

    33500014555555

    34500012555555

    35500011555555

    36500001445555

    37600003555555

    38600023555555

    39600000555555

    40601112455555

    41600000555555

    42600000555555

    43600001555555

    44600001455555

    45600143555555

    count45

    sum03103395218223225225225225

    decimal0.000.010.040.150.420.970.991.001.001.001.00

    012345678910

    Whole0.000.010.040.150.420.970.991.001.001.001.00

    012345678910

    front0262053112115115115115115

    230.000.020.050.170.460.971.001.001.001.001.00

    012345678910

    back0141342106108110110110110

    220.000.010.040.120.380.960.981.001.001.001.00

    Values copied over

    012345678910

    front

    2300000111111

    012345678910

    back

    2100000111111

    Sheet1

    Stimulus Value

    Fraction of "Yes" Responses

    Whole Class, 2009

    Stimulus Value

    Fraction of "Yes" Responses

    Front Rows

    Stimulus Value

    Fraction of "Yes" Responses

    Back Rows

  • Results from yesterdays Two-alternative Forced Choice Measurement

  • Intensity Discrimination Lab tomorrowGroups C (1 3) and A (3 5)List posted on bulletin board

    Planning to have the lab unless UAB cancels classes due to snow

    Snow amount is predicted to be small

  • 20095 4 3 2

    Chart1

    53.33333333336.6666666667

    47.619047619-4.7619047619

    96.666666666793.3333333333

    99.047619047698.0952380952

    Obtained percent correct

    True percent correct

    Stimulus

    Percent Correct Responses

    Two-alternative Forced-choice in-class Demo2010

    Sheet1

    Forced Choice in-class Demo

    personStimulus

    5432

    12255

    25155

    31355

    42255

    53255

    65355

    73344

    82455

    93355

    104255

    mg112355

    124455

    131255

    144445

    151355

    163355

    172055

    184335

    192255

    202255

    212355

    222355

    234155

    242355

    253155

    265245

    273354

    283255

    293245

    302055

    313045

    322355

    333455

    343355

    352255

    361255

    371255

    384355

    394255

    400255

    412355

    423355

    43

    44

    45

    sum112100203208

    count42424242

    mean2.72.44.85.0

    percent corr53.347.696.799.0

    corrected6.67-4.7693.3398.10

    stimulus1234

    Obtained percent correct53.347.696.799.0

    True percent correct6.67-4.7693.3398.10

    Sheet1

    Obtained percent correct

    True percent correct

    Stimulus

    Percent Correct Responses

    Two-alternative Forced-choice in-class Demo2010

    Sheet2

    Sheet3

  • 5 4 3 2

    Chart1

    53.33333333336.6666666667

    47.619047619-4.7619047619

    96.666666666793.3333333333

    99.047619047698.0952380952

    Obtained percent correct

    True percent correct

    Stimulus

    Percent Correct Responses

    Two-alternative Forced-choice in-class Demo2010

    Sheet1

    Forced Choice in-class Demo

    personStimulus

    5432

    12255

    25155

    31355

    42255

    53255

    65355

    73344

    82455

    93355

    104255

    mg112355

    124455

    131255

    144445

    151355

    163355

    172055

    184335

    192255

    202255

    212355

    222355

    234155

    242355

    253155

    265245

    273354

    283255

    293245

    302055

    313045

    322355

    333455

    343355

    352255

    361255

    371255

    384355

    394255

    400255

    412355

    423355

    43

    44

    45

    sum112100203208

    count42424242

    mean2.72.44.85.0

    percent corr53.347.696.799.0

    corrected6.67-4.7693.3398.10

    stimulus1234

    Obtained percent correct53.347.696.799.0

    True percent correct6.67-4.7693.3398.10

    Sheet1

    Obtained percent correct

    True percent correct

    Stimulus

    Percent Correct Responses

    Two-alternative Forced-choice in-class Demo2010

    Sheet2

    Sheet3

  • 5 4 3 2Either way gives the same threshold, but it is easier to use a 75% threshold and not bother to correct

    Chart1

    53.33333333336.6666666667

    47.619047619-4.7619047619

    96.666666666793.3333333333

    99.047619047698.0952380952

    Obtained percent correct

    True percent correct

    Stimulus

    Percent Correct Responses

    Two-alternative Forced-choice in-class Demo2010

    Sheet1

    Forced Choice in-class Demo

    personStimulus

    5432

    12255

    25155

    31355

    42255

    53255

    65355

    73344

    82455

    93355

    104255

    mg112355

    124455

    131255

    144445

    151355

    163355

    172055

    184335

    192255

    202255

    212355

    222355

    234155

    242355

    253155

    265245

    273354

    283255

    293245

    302055

    313045

    322355

    333455

    343355

    352255

    361255

    371255

    384355

    394255

    400255

    412355

    423355

    43

    44

    45

    sum112100203208

    count42424242

    mean2.72.44.85.0

    percent corr53.347.696.799.0

    corrected6.67-4.7693.3398.10

    stimulus1234

    Obtained percent correct53.347.696.799.0

    True percent correct6.67-4.7693.3398.10

    Sheet1

    Obtained percent correct

    True percent correct

    Stimulus

    Percent Correct Responses

    Two-alternative Forced-choice in-class Demo2010

    Sheet2

    Sheet3

  • http://www.opt.uab.edu/nortonpsychophysics/

  • Chapter 1

    Principles of Psychophysical MeasurementObjectives:Psychophysical MethodsThresholdConstant StimuliLimitsAdjustmentSignal detection theorySensory Magnitude

  • Using Signal Detection Theory

    1) to Understand Threshold Variability and

    2) to Control Subject Bias

  • Big point!!

    Lesser point

    Using Signal Detection Theory

    1) to Understand Threshold Variability and

    2) to Control Subject Bias

  • Stimuli that are near threshold always are difficult to see! Did I see that, or didnt I?The brain (comprised of neurons) must decide if a stimulus was present against a background of neural noise.

    At threshold, neurons must decide whether a stimulus is present against a background of noise

  • Your brain causes perception. Cells in the brain do not respond to light. They respond because they are activated by a chain of cells that start with photoreceptors, which do see light.

  • We can eavesdrop on the neurons in the visual pathway with a microelectrode, nestled up against a neuron or its axon and record the responses (number of spikes per second) in response to visual stimuli.B: Action potentials recorded from a single LGN neuron. The same stimulus (a spot of light positioned in the receptive field was presented many 20 times. A: a histogram of the cells responses

  • The visual system has to decide if a stimulus is present on the fly as events happenIn studying how the visual system responds, we have the luxury of studying neural responses over many repeated trialsUse this information to understand why thresholds can be affected by bias

  • NoiseSignal + Noise

    Responses of a neuron in the lateral geniculate nucleus of an anesthetized cat to three presentations of a near-threshold visual stimulus. Each small vertical line represents an action potential produced by the neuron. Each row shows the responses of the neuron in a 3 s period. From 0 until 2.5 s a background luminance was present. The stimulus (a light) was turned on at 2.5 s and turned off at 3.0 s, so the stimulus was on for only 0.5 s. (Unpublished data from D. W. Godwin and T. T. Norton,.)

  • Below is a peristimulus histogram made from the responses to 30 stimulus repetitions like the three lines shown above. We want to compare responses during noise and signal + Noise

    Responses of a neuron in the lateral geniculate nucleus of an anesthetized cat to three presentations of a near-threshold visual stimulus. Each small vertical line represents an action potential produced by the neuron. Each row shows the responses of the neuron in a 3 s period. From 0 until 2.5 s a background luminance was present. The stimulus (a light) was turned on at 2.5 s and turned off at 3.0 s, so the stimulus was on for only 0.5 s. (Unpublished data from D. W. Godwin and T. T. Norton,.)

  • We are interested in how many action potentials are generated, over many stimulus presentations, during a 50 msec period when there is no stimulus (maintained discharge) and a 50 msec period when the stimulus is present.Why 50 msec? Arbitrary, but it is about the amount of time the CNS seems to use.

    Responses of a neuron in the lateral geniculate nucleus of an anesthetized cat to three presentations of a near-threshold visual stimulus. Each small vertical line represents an action potential produced by the neuron. Each row shows the responses of the neuron in a 3 s period. From 0 until 2.5 s a background luminance was present. The stimulus (a light) was turned on at 2.5 s and turned off at 3.0 s, so the stimulus was on for only 0.5 s. (Unpublished data from D. W. Godwin and T. T. Norton,.)

  • 28303215

    Making a frequency distribution of neural responses during noise and signal + noise50 ms binsNumber of action potentials in each binnoiseStimulus + noiseDuring noise, 0 spikes occur 1 time, 3 spikes occur 1 time, 2 occur 1 timeDuring signal + noise, 3 spikes occur 1 time, 8 spikes occur 1 time, 15 occur 1 timeDo this across 30 stimulus presentations to get a distribution of the frequency with which a certain number of spikes occurs

  • How can the brain decide if a near-threshold stimulus is present? If a strong stimulus is presented, it produces many more action potentials during the signal + noise than are produced during the noise. But when a stimulus is near threshold, there is overlap between the number of spikes produced during noise and signal + noise

    There is no single optimal criterion number of action potentials that the nervous system (such as a cell in the visual cortex) should use to decide whether to respond as though a stimulus was present, or to respond as though a stimulus was not present.

  • One can try various criteria Changing the criterion (the threshold one adopts) affects the pattern of hits, misses, false alarms and correct rejections

    The saga of the snake in the grassThis changing threshold is partly responsible for fluctuations in threshold.

  • Imagine the situation faced by a mouse, needing to forage for food, but worrying that a snake might be hanging around and eat the mouse when the mouse goes out to eat

  • Set criterion low, to always detect the snakeIf 6 or more action potentials, decide snake!!

  • Set criterion low, to always detect the snakeIf 6 or more action potentials, decide snake!!Problem: will also see snake some times when it is just the noise of the visual system

  • Out of the four possible outcomes there are two ways to be correct:

    by deciding the stimulus is there when it is present (a Hit)

    and by deciding that it is not there when it is absent (a Correct Rejection).

    There are also two ways to be wrong:

    by deciding the stimulus is present when it is absent (a False Alarm)

    and by deciding it is not present when it is (a Miss).

  • Many false alarmsIf set a low criterion (threshold), hit rate is perfect, but

  • 10

  • So, try changing the criterion mouse gets hungrier, willing to take a chance If set a high criterion (threshold) have no false alarms but also fewer hits (more misses)

  • 10

  • Can calculate hit rate and false alarm rate for ANY criterion

  • Receiver Operating Characteristic (ROC) curve

    Receiver Operating Characteristic (ROC) curve for the responses shown in the previous figure. If the threshold is set at 15 action potentials, there are 0 Hits and 0 False Alarms. If it is set at 14, there will be a few Hits, but 0 False Alarms. As the threshold is decreased further, the P(Hit) increases but the P(False Alarm) remains at 0 until the threshold reaches 9, at which point False Alarms begin to increase. As the threshold is further lowered, through the overlap region in the previous figure, the probability of both Hits and False Alarms increase. For thresholds below 6, there is no further increase in hit rate, but the false alarm rate climbs toward 1.0.

  • Signal Detection Theory also applies to human perceptual responses

    Distribution of hypothetical perceptual response in a human subject over many trials when the stimulus was absent (top) and when the stimulus was present (bottom). The criterion value (vertical line) indicates the criterion a subject would adopt if Hits, Misses, False Alarms and Correct Rejections had the rewards and costs listed in another figure.

  • False Alarm Rate0.00.20.40.60.81.0Hit Rate0.00.20.40.60.81.0Receiver Operating Characteristic(ROC) CurveThe distributions on the previous slide would produce this

  • d (d prime) is a measure of the separation of two normal distributions. d = the difference between the means of the noise and signal plus noise distributions divided by the common standard deviation of the two distributions.d quantifies the detectability of the signal (small d = signal is hard to detect)

  • Big point: Where a neuron, or an entire creature (human or animal) sets its criterion depends on circumstances (fear vs. hunger which causes a change in bias). This contributes to threshold variability.

    Can Use Signal Detection Theory to control bias when measuring threshold (This is the minor point)

  • Use the Payoff Game

    To control a subjects criterion, the examiner provides the subject, in advance, with:

    the payoff amounts

    and

    information on the frequency of stimulus presentation

  • Use the Payoff Game

    To control a subjects criterion, the examiner provides the subject, in advance, with:

    the payoff amounts

    and

    information on the frequency of stimulus presentation

  • Skip the text on pages 24, 26, 27 and top of 28

    Signal detection theory can be used to control bias when measuring threshold

  • Screening for refractive error: Hits: Correct detection of refractive errorCorrect rejection: pass the screening because child is emmetropicFalse alarm (false positive): incorrectly refer for full exam based on screening (cost, concern, inconvenience)Misses (false negative): fail to detect refractive error

    Minimize false positives even though some refractive error is missed

    The concepts of Signal Detection Theory form the basis of rational clinical decision making

  • Detecting ocular melanoma: Hits: Correct detection of melanoma (refer for possible surgery)Correct rejection: pass because no melanomaFalse positive incorrectly refer based on screening (alarm, cost, inconvenience)Misses (false negatives): fail to detect melanoma (possible death)

    Minimize false negatives even though some false positives occur

    The concepts of Signal Detection Theory form the basis of rational clinical decision making

  • You will hear in clinic about the sensitivity and specificity of diagnostic techniques.

    Sensitivity is the hit rateSpecificity is the absence of false alarmsSo plot (1 specificity) on an ROC curveWant a diagnostic tool that has high sensitivity and high specificity

  • Do you see it?As was said the first day of classVisual thresholds are the most common psychophysical measurement

  • What does it look like?

    The other major type of

    psychophysical measurement:

    Measuring the magnitude of sensations

  • Increased light intensity is brighter but how much brighter? Increased spot size is larger, but how much larger?

    Perceptual responses (sensations) have magnitude but no obvious scale or units

  • To measure sensory magnitude above threshold, use scales that do not rely on any particular units of measurement

  • 1) Ratio Production - the subject is presented with a reference stimulus and is asked to adjust the intensity of a test stimulus so that it appears to be some fraction or multiple of the reference stimulus.

    2) Ratio Estimation - the examiner sets the physical intensities of a reference and test stimulus and asks the subject to estimate the ratio of the test to the reference stimulus.

  • 3) Magnitude Estimation (two variants)

    a) an observer is presented with a reference stimulus and told that it has a certain value (10, 100 etc.) A series of test stimuli are then presented and the observer assigns a number to these stimuli to indicate their perceived magnitude relative to the reference stimulus

    b) (dont bother with this)

    4) Magnitude Production a subject is presented with a reference stimulus and is asked to adjust a test stimulus so that is appears to be some fraction or multiple of the reference stimulus.

  • Stevens' Power Law relates sensory magnitude to the magnitude of the stimulus:

    where (psi) is the sensory magnitude, (kappa) is an arbitrary constant determining

    the scale unit, (phi) is the stimulus magnitude, and (alpha) is an exponent that

    is characteristic of the stimulus used.

    Sensory magnitude is proportional to the stimulus magnitude raised to some power

  • When plotted on a log-log scale.

    _927461079.unknown

  • Value of Some Vision-related Exponents in the Stevens Power Law Equation

    Sensation

    Exponent

    Stimulus Condition

    Brightness

    0.33

    5SYMBOL 176 \f "Symbol" target in the dark

    Brightness

    0.50

    Point source

    Brightness

    0.50

    Brief flash

    Visual Area

    0.70

    Projected square

    Brightness

    1.00

    Point source briefly flashed

    Visual Length

    1.00

    Projected line

  • Clinicians rely on sensory magnitudes

    to make judgments about pathologies

  • What does it look like?

    Measuring the magnitude of sensations

  • Chapter 1

    Principles of Psychophysical MeasurementObjectives:Psychophysical MethodsThresholdConstant StimuliLimitsAdjustmentSignal detection theorySensory Magnitude

    *