Baby Schema in Infant Faces Induces Cuteness Perception and Motivation for Caretaking in Adults

Ethologist Konrad Lorenz proposed that baby schema (‘Kindchenschema’) is a set of infantile physical features such as the large head, round face and big eyes that is perceived as cute and motivates caretaking behavior in other individuals, with the evolutionary function of enhancing offspring survival. Previous work on this fundamental concept was restricted to schematic baby representations or correlative approaches. Here, we experimentally tested the effects of baby schema on the perception of cuteness and the motivation for caretaking using photographs of infant faces. Employing quantitative techniques, we parametrically manipulated the baby schema content to produce infant faces with high (e.g. round face and high forehead), and low (e. g. narrow face and low forehead) baby schema features that retained all the characteristics of a photographic portrait. Undergraduate students (n = 122) rated these infants’ cuteness and their motivation to take care of them. The high baby schema infants were rated as more cute and elicited stronger motivation for caretaking than the unmanipulated and the low baby schema infants. This is the first experimental proof of the baby schema effects in actual infant faces. Our findings indicate that the baby schema response is a critical function of human social cognition that may be the basis of caregiving and have implications for infant–caretaker interactions

Faster Family-wise Error Control for Neuroimaging with a Parametric Bootstrap

In neuroimaging, hundreds to hundreds of thousands of tests are performed across a set of brain regions or all locations in an image. Recent studies have shown that the most common family-wise error (FWE) controlling procedures in imaging, which rely on classical mathematical inequalities or Gaussian random field theory, yield FWE rates that are far from the nominal level. Depending on the approach used, the FWER can be exceedingly small or grossly inflated. Given the widespread use of neuroimaging as a tool for understanding neurological and psychiatric disorders, it is imperative that reliable multiple testing procedures are available. To our knowledge, only permutation joint testing procedures have been shown to reliably control the FWER at the nominal level. However, these procedures are computationally intensive due to the increasingly available large sample sizes and dimensionality of the images, and analyses can take days to complete. Here, we develop a parametric bootstrap joint testing procedure. The parametric bootstrap procedure works directly with the test statistics, which leads to much faster estimation of adjusted \emph{p}-values than resampling-based procedures while reliably controlling the FWER in sample sizes available in many neuroimaging studies. We demonstrate that the procedure controls the FWER in finite samples using simulations, and present region- and voxel-wise analyses to test for sex differences in developmental trajectories of cerebral blood flow

Classifying spatial patterns of brain activity with machine learning methods: application to lie detection

Patterns of brain activity during deception have recently been characterized with fMRI on the multi-subject average group level. The clinical value of fMRI in lie detection will be determined by the ability to detect deception in individual subjects, rather than group averages. High-dimensional non-linear pattern classification methods applied to functional magnetic resonance (fMRI) images were used to discriminate between the spatial patterns of brain activity associated with lie and truth. In 22 participants performing a forced-choice deception task, 99% of the true and false responses were discriminated correctly. Predictive accuracy, assessed by cross-validation in participants not included in training, was 88%. The results demonstrate the potential of non-linear machine learning techniques in lie detection and other possible clinical applications of fMRI in individual subjects, and indicate that accurate clinical tests could be based on measurements of brain function with fMRI

Telling the truth from lie in individual subjects with fast event-related fMRI

Deception is a clinically important behavior with poorly understood neurobiological correlates. Published functional MRI (fMRI) data on the brain activity during deception indicates that, on a multisubject group level, lie is distinguished from truth by increased prefrontal and parietal activity. These findings are theoretically important; however, their applied value will be determined by the accuracy of the discrimination between single deceptive and truthful responses in individual subjects. This study presents the first quantitative estimate of the accuracy of fMRI in conjunction with a formal forced-choice paradigm in detecting deception in individual subjects. We used a paradigm balancing the salience of the target cues to elicit deceptive and truthful responses and determined the accuracy of this model in the classification of single lie and truth events. The relative salience of the task cues affected the net activation associated with lie in the superior medial and inferolateral prefrontal cortices. Lie was discriminated from truth on a single-event level with an accuracy of 78%, while the predictive ability expressed as the area under the curve (AUC) of the receiver operator characteristic curve (ROC) was 85%. Our findings confirm that fMRI, in conjunction with a carefully controlled query procedure, could be used to detect deception in individual subjects. Salience of the task cues is a potential confounding factor in the fMRI pattern attributed to deception in forced choice deception paradigms

Associations Between Neighborhood SES and Functional Brain Network Development

Higher socioeconomic status (SES) in childhood is associated with stronger cognitive abilities, higher academic achievement, and lower incidence of mental illness later in development. While prior work has mapped the associations between neighborhood SES and brain structure, little is known about the relationship between SES and intrinsic neural dynamics. Here, we capitalize upon a large cross-sectional community-based sample (Philadelphia Neurodevelopmental Cohort, ages 8–22 years, n = 1012) to examine associations between age, SES, and functional brain network topology. We characterize this topology using a local measure of network segregation known as the clustering coefficient and find that it accounts for a greater degree of SES-associated variance than mesoscale segregation captured by modularity. High-SES youth displayed stronger positive associations between age and clustering than low-SES youth, and this effect was most pronounced for regions in the limbic, somatomotor, and ventral attention systems. The moderating effect of SES on positive associations between age and clustering was strongest for connections of intermediate length and was consistent with a stronger negative relationship between age and local connectivity in these regions in low-SES youth. Our findings suggest that, in late childhood and adolescence, neighborhood SES is associated with variation in the development of functional network structure in the human brain

Reduced prefrontal and temporal processing and recall of high sensation value ads

Public service announcements (PSAs) are non-commercial broadcast ads that are an important part of televised public health campaigns. “Message sensation value” (MSV), a measure of sensory intensity of audio, visual, and content features of an ad, is an important factor in PSA impact. Some communication theories propose that higher message sensation value brings increased attention and cognitive processing, leading to higher ad impact. Others argue that the attention-intensive format could compete with ad\u27s message for cognitive resources and result in reduced processing of PSA content and reduced overall effectiveness. Brain imaging during PSA viewing provides a quantitative surrogate measure of PSA impact and addresses questions of PSA evaluation and design not accessible with traditional subjective and epidemiological methods. We used Blood Oxygenation Level Dependent (BOLD) functional Magnetic Resonance Imaging (fMRI) and recognition memory measures to compare high and low MSV anti-tobacco PSAs and neutral videos. In a short-delay, forced-choice memory test, frames extracted from PSAs were recognized more accurately than frames extracted from the NV. Frames from the low MSV PSAs were better recognized than frames from the high MSV PSAs. The accuracy of recognition of PSA frames was positively correlated with the prefrontal and temporal, and negatively correlated with the occipital cortex activation. The low MSV PSAs were associated with greater prefrontal and temporal activation, than the high MSV PSAs. The high MSV PSAs produced greater activation primarily in the occipital cortex. These findings support the “dual processing” and “limited capacity” theories of communication that postulate a competition between ad\u27s content and format for the viewers\u27 cognitive resources and suggest that the “attention-grabbing” high MSV format could impede the learning and retention of an ad. These findings demonstrate the potential of using neuroimaging in the design and evaluation of mass media public health communications