A neurocomputational account of the face configural biederman/presentations/ShahBiederman_  

A neurocomputational account of the face configural biederman/presentations/ShahBiederman_  

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  • Manan P. Shah2*, Xiaokun Xu1, Sarah B. Herald2, Irving Biederman1,2

    1Department of Psychology, 2Neuroscience Program, University of Southern California

    *mananpsh@usc.edu

    http://geon.usc.edu/

    Part-Whole Effect

    A neurocomputational account of the face configural effect

    Gabor-Jet Models

    Conclusions

    Illustration of overlap of medium-

    sized receptor fields of two Gabor

    jets with five scales and eight

    orientations. A jet models aspects of

    the tuning of a V1 hypercolumn.

    A difference in a

    single part

    appears more

    distinct in the

    context of a face

    than it does by

    itself.

    Experiment 3: Can the same theory

    account for the Face Composite Effect?

    Yes

    Experiment 2: Is it large RFs or low SFs?

    Large RFsFace Composite EffectExperiment 1: Is the configural effect largely produced by cells

    with large RFs (low SFs)? Yes

    Identical top halves of two faces look different

    when their different bottom halves are aligned

    rather than offset.

    The face configural and composite effects can be derived from models composed of overlapping

    receptive fields (RFs) characteristic of early cortical simple-cell tuning but also present in face-

    selective areas.

    Because of the overlap in RFs, variation in a single face part or half is propagated to the

    activation values of large RFs throughout the face.

    References

    Face parts (a) and

    composite target

    faces (b) created

    from these parts

    for the current

    replication of the

    part-whole

    identification

    experiment of

    Tanaka and Farah

    (1993).

    (c) Predicting response accuracy

    from large RFs (low SF) versus

    small RFs (high SF) components in

    the Gabor-jet representation (via

    model 1) of faces. A greater

    proportion of the variance is

    predictable from the large RF (low

    SF) components.

    (a)

    (b)

    (c)

    The configural effect (isolated part vs.

    composite) as a function of spatial frequency

    (all SF, high, and low pass). There is only a

    minimal effect of SF. Therefore the configural

    effect is produced by large RFs, not by low SFs.

    Spatial filtering of the part and whole face stimuli in

    Experiment 2. RF held constant, SF varied.

    Version 1. Illustration of the computation of

    dissimilarity for a corresponding pair of jets positioned

    at nodes in a rectangular grid for a pair of face images.

    Version 2. Fiducial point version of

    the Gabor-jet model. Particular jets

    automatically center themselves on

    landmark features of a face like the

    pupil of the right eye.

    This effectan influence of differences in the

    lower halves of the facescan be produced by

    the fiducial point model. Because of a reduction

    in the overlap of the RFs (perhaps also

    requiring the context of a face template) from

    the shift, the influence of the lower half is

    reduced when it is no longer aligned with the

    upper half. Above: Dissimilarity computed via

    Gabor-jet model version 2.

    Hypothesis

    The representation of faces (but not objects)

    retains aspects of the initial multiscale,

    multiorientation tuning of early cortical visual

    stages and the configural effect is produced

    by the overlap of large receptive fields in

    which a change in the shape of one face part

    will affect the activation of many cells with

    large RFs not centered on that face part.

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