Dataset Information

A computer-generated animated face stimulus set for psychophysiological research.

ABSTRACT: Human faces are fundamentally dynamic, but experimental investigations of face perception have traditionally relied on static images of faces. Although naturalistic videos of actors have been used with success in some contexts, much research in neuroscience and psychophysics demands carefully controlled stimuli. In this article, we describe a novel set of computer-generated, dynamic face stimuli. These grayscale faces are tightly controlled for low- and high-level visual properties. All faces are standardized in terms of size, luminance, location, and the size of facial features. Each face begins with a neutral pose and transitions to an expression over the course of 30 frames. Altogether, 222 stimuli were created, spanning three different categories of movement: (1) an affective movement (fearful face), (2) a neutral movement (close-lipped, puffed cheeks with open eyes), and (3) a biologically impossible movement (upward dislocation of eyes and mouth). To determine whether early brain responses sensitive to low-level visual features differed between the expressions, we measured the occipital P100 event-related potential, which is known to reflect differences in early stages of visual processing, and the N170, which reflects structural encoding of faces. We found no differences between the faces at the P100, indicating that different face categories were well matched on low-level image properties. This database provides researchers with a well-controlled set of dynamic faces, controlled for low-level image characteristics, that are applicable to a range of research questions in social perception.

SUBMITTER: Naples A

PROVIDER: S-EPMC4297263 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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A computer-generated animated face stimulus set for psychophysiological research.

Naples Adam A Nguyen-Phuc Alyssa A Coffman Marika M Kresse Anna A Faja Susan S Bernier Raphael R McPartland James C JC

Behavior research methods 20150601 2

Human faces are fundamentally dynamic, but experimental investigations of face perception have traditionally relied on static images of faces. Although naturalistic videos of actors have been used with success in some contexts, much research in neuroscience and psychophysics demands carefully controlled stimuli. In this article, we describe a novel set of computer-generated, dynamic face stimuli. These grayscale faces are tightly controlled for low- and high-level visual properties. All faces ar ...[more]

PMID: 25028164

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Project description:The authors previously reported on a three-dimensional computer-generated breast phantom, based on empirical human image data, including a realistic finite-element based compression model that was capable of simulating multimodality imaging data. The computerized breast phantoms are a hybrid of two phantom generation techniques, combining empirical breast CT (bCT) data with flexible computer graphics techniques. However, to date, these phantoms have been based on single human subjects. In this paper, the authors report on a new method to generate multiple phantoms, simulating additional subjects from the limited set of original dedicated breast CT data. The authors developed an image morphing technique to construct new phantoms by gradually transitioning between two human subject datasets, with the potential to generate hundreds of additional pseudoindependent phantoms from the limited bCT cases. The authors conducted a preliminary subjective assessment with a limited number of observers (n = 4) to illustrate how realistic the simulated images generated with the pseudoindependent phantoms appeared.Several mesh-based geometric transformations were developed to generate distorted breast datasets from the original human subject data. Segmented bCT data from two different human subjects were used as the "base" and "target" for morphing. Several combinations of transformations were applied to morph between the "base' and "target" datasets such as changing the breast shape, rotating the glandular data, and changing the distribution of the glandular tissue. Following the morphing, regions of skin and fat were assigned to the morphed dataset in order to appropriately assign mechanical properties during the compression simulation. The resulting morphed breast was compressed using a finite element algorithm and simulated mammograms were generated using techniques described previously. Sixty-two simulated mammograms, generated from morphing three human subject datasets, were used in a preliminary observer evaluation where four board certified breast radiologists with varying amounts of experience ranked the level of realism (from 1 = "fake" to 10 = "real") of the simulated images.The morphing technique was able to successfully generate new and unique morphed datasets from the original human subject data. The radiologists evaluated the realism of simulated mammograms generated from the morphed and unmorphed human subject datasets and scored the realism with an average ranking of 5.87 ± 1.99, confirming that overall the phantom image datasets appeared more "real" than "fake." Moreover, there was not a significant difference (p > 0.1) between the realism of the unmorphed datasets (6.0 ± 1.95) compared to the morphed datasets (5.86 ± 1.99). Three of the four observers had overall average rankings of 6.89 ± 0.89, 6.9 ± 1.24, 6.76 ± 1.22, whereas the fourth observer ranked them noticeably lower at 2.94 ± 0.7.This work presents a technique that can be used to generate a suite of realistic computerized breast phantoms from a limited number of human subjects. This suite of flexible breast phantoms can be used for multimodality imaging research to provide a known truth while concurrently producing realistic simulated imaging data.

Dataset Information

A computer-generated animated face stimulus set for psychophysiological research.

Publications

A computer-generated animated face stimulus set for psychophysiological research.

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