Evaluation of interpretability for deep learning algorithms in EEG emotion recognition: A case study in autism.

Current models on Explainable Artificial Intelligence (XAI) have shown a lack of reliability when evaluating feature-relevance for deep neural biomarker classifiers. The inclusion of reliable saliency-maps for obtaining trustworthy and interpretable neural activity is still insufficiently mature for practical applications. These limitations impede the development of clinical applications of Deep Learning.

Mechanisms supporting the social regulation of neural threat responding with marital partners: A test of the opioid hypothesis.

Positive social contact predicts better health, but the mechanisms for this association remain debated. One way to explore this link is through the social regulation of emotion, particularly anticipatory anxiety. Previous research finds less neural threat response during partner handholding than when people are alone or stranger handholding.

Interpretable SincNet-based Deep Learning for Emotion Recognition from EEG brain activity.

Machine learning methods, such as deep learning, show promising results in the medical domain. However, the lack of interpretability of these algorithms may hinder their applicability to medical decision support systems. This paper studies an interpretable deep learning technique, called SincNet.

The social regulation of emotion: Inconsistencies suggest no mediation through ventromedial prefrontal cortex.

Physical touch in the form of holding a loved one's hand attenuates the neural response to threat. Speculation regarding the neural mediation of this effect points to the ventromedial prefrontal cortex (vmPFC), which is known to have inhibitory connections with threat responsive brain regions such as the amygdala. Despite the attractiveness of this hypothesis, a link between the vmPFC and diminished threat during handholding has been difficult to demonstrate empirically.

Cognitive Processes Unfold in a Social Context: A Review and Extension of Social Baseline Theory.

Psychologists often assume that social and cognitive processes operate independently, an assumption that prompts research into how social context cognitive processes. We propose that social and cognitive processes are not necessarily separate, and that social context is innate to resource dependent cognitive processes. We review the research supporting social baseline theory, which argues that our default state in physiological, cognitive, and neural processing is to incorporate the relative costs and benefits of acting in our social environment.