FMRI analysis of contrast polarity in face-selective cortex in humans and monkeys

Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129. Electronic address: .
NeuroImage (Impact Factor: 6.36). 03/2013; 76(1). DOI: 10.1016/j.neuroimage.2013.02.068
Source: PubMed


Recognition is strongly impaired when the normal contrast polarity of faces is reversed. For instance, otherwise-familiar faces become very difficult to recognize when viewed as photographic negatives. Here, we used fMRI to demonstrate related properties in visual cortex: 1) fMRI responses in the human Fusiform Face Area (FFA) decreased strongly (26%) to contrast-reversed faces across a wide range of contrast levels (5.3-100% RMS contrast), in all subjects tested. In a whole brain analysis, this contrast polarity bias was largely confined to the Fusiform Face Area (FFA; p < 0.0001), with possible involvement of a left occipital face-selective region. 2) It is known that reversing facial contrast affects three image properties in parallel (absorbance, shading, and specular reflection). Here, comparison of FFA responses to those in V1 suggests that the contrast polarity bias is produced in FFA only when all three component properties were reversed simultaneously, which suggests a prominent non-linearity in FFA processing. 3) Across a wide range (180(o)) of illumination source angles, 3D face shapes without texture produced response constancy in FFA, without a contrast polarity bias. 4) Consistent with psychophysics, analogous fMRI biases for normal contrast polarity were not produced by non-face objects, with image statistics similar to the face stimuli. 5) Using fMRI, we also demonstrated a contrast polarity bias in awake behaving macaque monkeys, in the cortical region considered homologous to human FFA. Thus common cortical mechanisms may underlie facial contrast processing across ~ 25 million years of primate evolution.

Download full-text


Available from: Roger B Tootell, Feb 25, 2014
  • Source
    • "Four images of human faces (see Figure 1A) were generated using FaceGen 3.4 (Singular Inversions, Canada), as described previously (Yue et al., 2011, 2013; Holt et al., 2014). All four faces (A, B, C and D) were male and caucasian, and achromatic (i.e., all color parameters were set to 0). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Fear generalization is the production of fear responses to a stimulus that is similar – but not identical - to a threatening stimulus. Although prior studies have found that fear generalization magnitudes are qualitatively related to the degree of perceptual similarity to the threatening stimulus, the precise relationship between these two functions has not been measured systematically. Also, it remains unknown whether fear generalization mechanisms differ for social and non-social information. To examine these questions, we measured perceptual discrimination and fear generalization in the same subjects, using images of human faces and non-face control stimuli (“blobs”) that were perceptually matched to the faces. First, each subject’s ability to discriminate between pairs of faces or blobs was measured. Each subject then underwent a Pavlovian fear conditioning procedure, in which each of the paired stimuli were either followed (CS+) or not followed (CS-) by a shock. Skin conductance responses (SCRs) were also measured. Subjects were then presented with the CS+, CS- and five levels of a CS+-to-CS- morph continuum between the paired stimuli, based on individual discrimination thresholds. Finally, subjects rated the likelihood that each stimulus had been followed by a shock. Subjects showed both autonomic (SCR-based) and conscious (ratings-based) fear responses to morphs that they could not discriminate from the CS+ (generalization). For both faces and non-face objects, fear generalization was not found above discrimination thresholds. However, subjects exhibited greater fear generalization in the shock likelihood ratings compared to the SCRs, particularly for faces. These findings reveal that autonomic threat detection mechanisms in humans are highly sensitive to small perceptual differences between stimuli. Also, the conscious evaluation of threat shows broader generalization than autonomic responses, biased towards labeling a stimulus as threatening.
    Frontiers in Human Neuroscience 09/2014; 8:624. DOI:10.3389/fnhum.2014.00624 · 3.63 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this manuscript, using a novel wide-view visual presentation system that we developed for vision research and functional magnetic resonance imaging (fMRI), we studied contrast response functions in regions of the brain that are central and peripheral to the entire set of visual areas (V1, V2, V3, V3A, MT+), regions that have not been all investigated in previous vision research. Under the stimulus conditions which were 0-20 deg, 20-40 deg, and 40-60 deg eccentricity black-and-white checkerboard patterns, we measured the blood oxygenation level-dependent fMRI contrast response at five contrast levels (6, 12, 24, 48, and 96%) in the visual areas. On the basis of these data, the central and pericentral visual areas had low-contrast gain, whereas the peripheral visual areas had high-contrast gain. In addition, our results showed that the signals fundamentally shift during visual processing through posterior visual cortical areas (V1, V2, and V3) to superior visual cortical areas (V3A and MT+).
    Perception 09/2014; 43(7):677-93. DOI:10.1068/p7640 · 0.91 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Fifteen years ago, an intriguing area was found in human visual cortex. This area (the parahippocampal place area [PPA]) was initially interpreted as responding selectively to images of places. However, subsequent studies reported that PPA also responds strongly to a much wider range of image categories, including inanimate objects, tools, spatial context, landmarks, objectively large objects, indoor scenes, and/or isolated buildings. Here, we hypothesized that PPA responds selectively to a lower-level stimulus property (rectilinear features), which are common to many of the above higher-order categories. Using a novel wavelet image filter, we first demonstrated that rectangular features are common in these diverse stimulus categories. Then we tested whether PPA is selectively activated by rectangular features in six independent fMRI experiments using progressively simplified stimuli, from complex real-world images, through 3D/2D computer-generated shapes, through simple line stimuli. We found that PPA was consistently activated by rectilinear features, compared with curved and nonrectangular features. This rectilinear preference was (1) comparable in amplitude and selectivity, relative to the preference for category (scenes vs faces), (2) independent of known biases for specific orientations and spatial frequency, and (3) not predictable from V1 activity. Two additional scene-responsive areas were sensitive to a subset of rectilinear features. Thus, rectilinear selectivity may serve as a crucial building block for category-selective responses in PPA and functionally related areas.
    The Journal of Neuroscience : The Official Journal of the Society for Neuroscience 05/2014; 34(20):6721-35. DOI:10.1523/JNEUROSCI.4802-13.2014 · 6.34 Impact Factor
Show more