Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome

EEG-Based Emotion Classification for Alzheimer's Disease Patients Using Conventional Machine Learning and Recurrent Neural Network Models

As the number of patients with Alzheimer's disease (AD) increases, the effort needed to care for these patients increases as well. At the same time, advances in information and sensor technologies have reduced caring costs, providing a potential pathway for developing healthcare services for AD patients. For instance, if a virtual reality (VR) system can provide emotion-adaptive content, the time that AD patients spend interacting with VR content is expected to be extended, allowing caregivers to focus on other tasks. As the first step towards this goal, in this study, we develop a classification model that detects AD patients' emotions (e.g., happy, peaceful, or bored). We first collected electroencephalography (EEG) data from 30 Korean female AD patients who watched emotion-evoking videos at a medical rehabilitation center. We applied conventional machine learning algorithms, such as a multilayer perceptron (MLP) and support vector machine, along with deep learning models of recurrent neural network (RNN) architectures. The best performance was obtained from MLP, which achieved an average accuracy of 70.97%; the RNN model's accuracy reached only 48.18%. Our study results open a new stream of research in the field of EEG-based emotion detection for patients with neurological disorders.

Prefrontal Cortex Response to Threat: Race by Age Variation in 9-10 Year Old Children

BACKGROUND

Considerable research has suggested that race and age are two major determinants of brain development, including but not limited to development of the prefrontal cortex (PFC). Minorities' Diminished Returns (MDRs), however, suggests that race (as a proxy of racism) may interact with various determinants of human and brain development. Minimal knowledge, however, exists on whether age and race also interact on shaping PFC response to threat among American children.

PURPOSE

Using data from a task-based functional brain imaging study and considering race as a sociological rather than a biological construct, we investigated combined effects of race and age on prefrontal cortical (PFC) response to threat. We explored racial heterogeneities in the association between age and PFC response to threat by comparing Black and White children.

METHODS

This study used the task-based functional Magnetic Resonance Imaging (fMRI) data from the Adolescents Brain Cognitive Development (ABCD) study, a national, landmark, multi-center brain imaging investigation of 9-10 years old children in the US. The primary outcomes were mean beta weights of n-back runs measuring PFC response to threating versus neutral face contrast in the following regions of interest (ROIs): left hemisphere-lateral orbito-frontal, left hemisphere -superior-frontal, right hemisphere -caudal middle frontal, and right hemisphere -superior frontal cortex. The independent variable was age. Covariates were sex, ethnicity, family socioeconomic status, and neighborhood socioeconomic status. Race was the focal moderator. To analyze the data, we used linear regression models without and with interactions and SES as covariates.

RESULTS

We included 5,066 9-10 years old children. Age and race did not show direct effects on PFC response to threatening relative to neutral faces. While ethnicity, sex, and socioeconomic status were controlled, age and race showed a systematic interaction on PFC response to threatening relative to neutral faces.

CONCLUSIONS

For American children, race and age do not have direct effects but multiplicative effects on PFC response to threat. The results may be reflective of social inequalities in how Black and White children are socialized and developed. The results are important given the role of the PFC in regulating the limbic system response to threat. Coordinated work of the limbic system and PFC is a core element of children's behavioral and emotional development. Future research is needed on how social stratification and racism shape emotion processing and regulation of American children in response to threat.

Neurobiological Aspects of Face Recognition: The Role of Oxytocin

Face recognition is an important index in the formation of social cognition and neurodevelopment in humans. Changes in face perception and memory are connected with altered sociability, which is a symptom of numerous brain conditions including autism spectrum disorder (ASD). Various brain regions and neuropeptides are implicated in face processing. The neuropeptide oxytocin (OT) plays an important role in various social behaviors, including face and emotion recognition. Nasal OT administration is a promising new therapy that can address social cognition deficits in individuals with ASD. New instrumental neurotechnologies enable the assessment of brain region activation during specific social tasks and therapies, and can characterize the involvement of genes and peptides in impaired neurodevelopment. The present review sought to discuss some of the mechanisms of the face distinguishing process, the ability of OT to modulate social cognition, as well as new perspectives and technologies for research and rehabilitation of face recognition.