Rules by which the brain segments an object from the background: Evaluation of the Gabor model of simple cell receptive fields Beth Tuck Hanover College.

Rules by which the brain Rules by which the brain segments an object from the segments an object from the background: Evaluation of the background: Evaluation of the

Gabor model of simple cell Gabor model of simple cell receptive fieldsreceptive fields

Beth TuckBeth TuckHanover CollegeHanover College

4/13/20074/13/2007

BackgroundBackground

Brain must “make sense” of massive Brain must “make sense” of massive amounts of visual information to amounts of visual information to generate holistic picture of an objectgenerate holistic picture of an object

e.g.e.g.

Task of VisionTask of Vision

Task of VisionTask of Vision

Task of VisionTask of Vision

Task of VisionTask of Vision

Task of VisionTask of Vision

Figure-Ground PerceptionFigure-Ground Perception

World is divided into (1) figure being World is divided into (1) figure being inspected and (2) backgroundinspected and (2) background

SegmentationSegmentation

The process of separating a The process of separating a figure/object from background figure/object from background (Marr, (Marr, 1982) 1982)

Outline needed to segmentOutline needed to segment

Image from Marr (1982)

Simple Cell Receptive FieldsSimple Cell Receptive Fields

Simple cells (orientation specific) Simple cells (orientation specific) may assist in segmentation processmay assist in segmentation process

Krantz (1994). Sensation & Perception Receptive Field Tutorial : http://psych.hanover.edu/krantz/receptive/

Research QuestionResearch Question

How do simple cells (modeled under How do simple cells (modeled under the Gabor function) allow the brain to the Gabor function) allow the brain to segment visual information?segment visual information?– What are the “Rules” by which modeled What are the “Rules” by which modeled

cells segment visual informationcells segment visual information

Step 1: Develop ModelStep 1: Develop Model

Feed stimulus into programFeed stimulus into program Program presents stimulus to cells @ Program presents stimulus to cells @

18 orientations (rotates by 1018 orientations (rotates by 10oo increments)increments)

Program records output @ each Program records output @ each orientationorientation

Orientation and Output of Orientation and Output of ModelModel

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Angle

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Step 2: Bar Stimulus TestStep 2: Bar Stimulus Test

Feed bars of various widthsFeed bars of various widths Attempt to determine rules by Attempt to determine rules by

which these model cells allow which these model cells allow segmentationsegmentation

Example of Generation of Example of Generation of OutputOutput

Rule 1: Orientation of Model Cell Rule 1: Orientation of Model Cell with Greatest (Positive or with Greatest (Positive or

Negative) OutputNegative) Output At each location: find modeled cell At each location: find modeled cell

with maximum outputwith maximum output Plot orientation of that sensitivityPlot orientation of that sensitivity

– Most positive – draw in white Most positive – draw in white – Most negative – draw in red Most negative – draw in red

Most Positive

Most Negative

Rule 2: Greatest Output & Rule 2: Greatest Output & Limited Range of ResponseLimited Range of Response

At many locations, the responses of At many locations, the responses of all orientations are both:all orientations are both:– Relatively strongRelatively strong– All approximately the same valueAll approximately the same value

Limited Range of Model Limited Range of Model OutputOutput

In this case, model In this case, model cells don’t seem to cells don’t seem to indicate orientationindicate orientation

The square at the The square at the location is filled location is filled with an intensity to with an intensity to match the mean match the mean outputoutput

White for positive; White for positive; red for negativered for negative

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Angle

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Most Positive

Most Negative

+ Limited Range Activity

Rule 2 Close-upRule 2 Close-up

So far each location processed So far each location processed independent of surrounding locationsindependent of surrounding locations

What if output also depends upon What if output also depends upon adjacent responses?adjacent responses?

E.g. color where color depends not just E.g. color where color depends not just on response of one cone but all threeon response of one cone but all three– Red alone gives redRed alone gives red– Red and green gives yellowRed and green gives yellow

Rule 3: Local MaximumRule 3: Local Maximum

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Model Output (Putative Firing Rate)

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Plot Orientation of this Maximum

Rule 3: Local MinimumRule 3: Local Minimum

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Model Output (Putative Firing Rate)

X Pos

Y Pos

Plot Orientation of this Minimum

Local Maxima

Local Minima

+ Limited Range Activity

ConclusionsConclusions

Local Maxima/Minima + Limited Local Maxima/Minima + Limited Range seems to most accurately Range seems to most accurately recreate stimulusrecreate stimulus

Hermann-Hering gridHermann-Hering grid– Fovea – does not segment circleFovea – does not segment circle– Periphery – segments circle Periphery – segments circle

Verify with human subjectsVerify with human subjects