Dataset Information

Lower-level stimulus features strongly influence responses in the fusiform face area.

ABSTRACT: An intriguing region of human visual cortex (the fusiform face area; FFA) responds selectively to faces as a general higher-order stimulus category. However, the potential role of lower-order stimulus properties in FFA remains incompletely understood. To clarify those lower-level influences, we measured FFA responses to independent variation in 4 lower-level stimulus dimensions using standardized face stimuli and functional Magnetic Resonance Imaging (fMRI). These dimensions were size, position, contrast, and rotation in depth (viewpoint). We found that FFA responses were strongly influenced by variations in each of these image dimensions; that is, FFA responses were not "invariant" to any of them. Moreover, all FFA response functions were highly correlated with V1 responses (r = 0.95-0.99). As in V1, FFA responses could be accurately modeled as a combination of responses to 1) local contrast plus 2) the cortical magnification factor. In some measurements (e.g., face size or a combinations of multiple cues), the lower-level variations dominated the range of FFA responses. Manipulation of lower-level stimulus parameters could even change the category preference of FFA from "face selective" to "object selective." Altogether, these results emphasize that a significant portion of the FFA response reflects lower-level visual responses.

SUBMITTER: Yue X

PROVIDER: S-EPMC3000561 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Lower-level stimulus features strongly influence responses in the fusiform face area.

Yue Xiaomin X Cassidy Brittany S BS Devaney Kathryn J KJ Holt Daphne J DJ Tootell Roger B H RB

Cerebral cortex (New York, N.Y. : 1991) 20100407 1

An intriguing region of human visual cortex (the fusiform face area; FFA) responds selectively to faces as a general higher-order stimulus category. However, the potential role of lower-order stimulus properties in FFA remains incompletely understood. To clarify those lower-level influences, we measured FFA responses to independent variation in 4 lower-level stimulus dimensions using standardized face stimuli and functional Magnetic Resonance Imaging (fMRI). These dimensions were size, position, ...[more]

PMID: 20375074

Similar Datasets

Project description:Rationale: Face expertise is a pivotal social skill. Developmental prosopagnosia (DP), i.e., the inability to recognize faces without a history of brain damage, affects about 2% of the general population, and is a renowned model system of the face-processing network. Within this network, the right Fusiform Face Area (FFA), is particularly involved in face identity processing and may therefore be a key element in DP. Neural representations within the FFA have been examined with Representational Similarity Analysis (RSA), a data-analytical framework in which multi-unit measures of brain activity are assessed with correlation analysis. Objectives: Our study intended to scrutinize modifications of FFA-activation during face encoding and maintenance based on RSA. Methods: Thirteen participants with DP (23-70 years) and 12 healthy control subjects (19-62 years) participated in a functional MRI study, including morphological MRI, a functional FFA-localizer and a modified Sternberg paradigm probing face memory encoding and maintenance. Memory maintenance of one, two, or four faces represented low, medium, and high memory load. We examined conventional activation differences in response to working memory load and applied RSA to compute individual correlation-matrices on the voxel level. Group correlation-matrices were compared via Donsker's random walk analysis. Results: On the functional level, increased memory load entailed both a higher absolute FFA-activation level and a higher degree of correlation between activated voxels. Both aspects were deficient in DP. Interestingly, control participants showed a homogeneous degree of correlation for successful trials during the experiment. In DP-participants, correlation levels between FFA-voxels were significantly lower and were less sustained during the experiment. In behavioral terms, DP-participants performed poorer and had longer reaction times in relation to DP-severity. Furthermore, correlation levels were negatively correlated with reaction times for the most demanding high load condition. Conclusion: We suggest that participants with DP fail to generate robust and maintained neural representations in the FFA during face encoding and maintenance, in line with poorer task performance and prolonged reaction times. In DP, alterations of neural coding in the FFA might therefore explain curtailing in working memory and contribute to impaired long-term memory and mental imagery.

Project description:Visual attention is thought to be driven by the interplay between low-level visual features and task dependent information content of local image regions, as well as by spatial viewing biases. Though dependent on experimental paradigms and model assumptions, this idea has given rise to varying claims that either bottom-up or top-down mechanisms dominate visual attention. To contribute toward a resolution of this discussion, here we quantify the influence of these factors and their relative importance in a set of classification tasks. Our stimuli consist of individual image patches (bubbles). For each bubble we derive three measures: a measure of salience based on low-level stimulus features, a measure of salience based on the task dependent information content derived from our subjects' classification responses and a measure of salience based on spatial viewing biases. Furthermore, we measure the empirical salience of each bubble based on our subjects' measured eye gazes thus characterizing the overt visual attention each bubble receives. A multivariate linear model relates the three salience measures to overt visual attention. It reveals that all three salience measures contribute significantly. The effect of spatial viewing biases is highest and rather constant in different tasks. The contribution of task dependent information is a close runner-up. Specifically, in a standardized task of judging facial expressions it scores highly. The contribution of low-level features is, on average, somewhat lower. However, in a prototypical search task, without an available template, it makes a strong contribution on par with the two other measures. Finally, the contributions of the three factors are only slightly redundant, and the semi-partial correlation coefficients are only slightly lower than the coefficients for full correlations. These data provide evidence that all three measures make significant and independent contributions and that none can be neglected in a model of human overt visual attention.

Dataset Information

Lower-level stimulus features strongly influence responses in the fusiform face area.

Publications

Lower-level stimulus features strongly influence responses in the fusiform face area.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets