Physiological Indicators for User Trust in Machine Learning with Influence Enhanced Fact-Checking

© IFIP International Federation for Information Processing 2019. Trustworthy Machine Learning (ML) is one of significant challenges of “black-box” ML for its wide impact on practical applications. This paper investigates the effects of presentation of influence of training data points on machine learning predictions to boost user trust. A framework of fact-checking for boosting user trust is proposed in a predictive decision making scenario to allow users to interactively check the training data points with different influences on the prediction by using parallel coordinates based visualization. This work also investigates the feasibility of physiological signals such as Galvanic Skin Response (GSR) and Blood Volume Pulse (BVP) as indicators for user trust in predictive decision making. A user study found that the presentation of influences of training data points significantly increases the user trust in predictions, but only for training data points with higher influence values under the high model performance condition, where users can justify their actions with more similar facts to the testing data point. The physiological signal analysis showed that GSR and BVP features correlate to user trust under different influence and model performance conditions. These findings suggest that physiological indicators can be integrated into the user interface of AI applications to automatically communicate user trust variations in predictive decision making

Cascade of Neural Events Leading from Error Commission to Subsequent Awareness Revealed Using EEG Source Imaging

The goal of the present study was to shed light on the respective contributions of three important action monitoring brain regions (i.e. cingulate cortex, insula, and orbitofrontal cortex) during the conscious detection of response errors. To this end, fourteen healthy adults performed a speeded Go/Nogo task comprising Nogo trials of varying levels of difficulty, designed to elicit aware and unaware errors. Error awareness was indicated by participants with a second key press after the target key press. Meanwhile, electromyogram (EMG) from the response hand was recorded in addition to high-density scalp electroencephalogram (EEG). In the EMG-locked grand averages, aware errors clearly elicited an error-related negativity (ERN) reflecting error detection, and a later error positivity (Pe) reflecting conscious error awareness. However, no Pe was recorded after unaware errors or hits. These results are in line with previous studies suggesting that error awareness is associated with generation of the Pe. Source localisation results confirmed that the posterior cingulate motor area was the main generator of the ERN. However, inverse solution results also point to the involvement of the left posterior insula during the time interval of the Pe, and hence error awareness. Moreover, consecutive to this insular activity, the right orbitofrontal cortex (OFC) was activated in response to aware and unaware errors but not in response to hits, consistent with the implication of this area in the evaluation of the value of an error. These results reveal a precise sequence of activations in these three non-overlapping brain regions following error commission, enabling a progressive differentiation between aware and unaware errors as a function of time elapsed, thanks to the involvement first of interoceptive or proprioceptive processes (left insula), later leading to the detection of a breach in the prepotent response mode (right OFC)

Down-Regulation of Negative Emotional Processing by Transcranial Direct Current Stimulation: Effects of Personality Characteristics

Evidence from neuroimaging and electrophysiological studies indicates that the left dorsolateral prefrontal cortex (DLPFC) is a core region in emotional processing, particularly during down-regulation of negative emotional conditions. However, emotional regulation is a process subject to major inter-individual differences, some of which may be explained by personality traits. In the present study we used transcranial direct current stimulation (tDCS) over the left DLPFC to investigate whether transiently increasing the activity of this region resulted in changes in the ratings of positive, neutral and negative emotional pictures. Results revealed that anodal, but not cathodal, tDCS reduced the perceived degree of emotional valence for negative stimuli, possibly due to an enhancement of cognitive control of emotional expression. We also aimed to determine whether personality traits (extraversion and neuroticism) might condition the impact of tDCS. We found that individuals with higher scores on the introversion personality dimension were more permeable than extraverts to the modulatory effects of the stimulation. The present study underlines the role of the left DLPFC in emotional regulation, and stresses the importance of considering individual personality characteristics as a relevant variable, although replication is needed given the limited sample size of our study

Seeing Emotion with Your Ears: Emotional Prosody Implicitly Guides Visual Attention to Faces

Interpersonal communication involves the processing of multimodal emotional cues, particularly facial expressions (visual modality) and emotional speech prosody (auditory modality) which can interact during information processing. Here, we investigated whether the implicit processing of emotional prosody systematically influences gaze behavior to facial expressions of emotion. We analyzed the eye movements of 31 participants as they scanned a visual array of four emotional faces portraying fear, anger, happiness, and neutrality, while listening to an emotionally-inflected pseudo-utterance (Someone migged the pazing) uttered in a congruent or incongruent tone. Participants heard the emotional utterance during the first 1250 milliseconds of a five-second visual array and then performed an immediate recall decision about the face they had just seen. The frequency and duration of first saccades and of total looks in three temporal windows ([0–1250 ms], [1250–2500 ms], [2500–5000 ms]) were analyzed according to the emotional content of faces and voices. Results showed that participants looked longer and more frequently at faces that matched the prosody in all three time windows (emotion congruency effect), although this effect was often emotion-specific (with greatest effects for fear). Effects of prosody on visual attention to faces persisted over time and could be detected long after the auditory information was no longer present. These data imply that emotional prosody is processed automatically during communication and that these cues play a critical role in how humans respond to related visual cues in the environment, such as facial expressions

Financial and Psychological Risk Attitudes Associated with Two Single Nucleotide Polymorphisms in the Nicotine Receptor (CHRNA4) Gene

With recent advances in understanding of the neuroscience of risk taking, attention is now turning to genetic factors that may contribute to individual heterogeneity in risk attitudes. In this paper we test for genetic associations with risk attitude measures derived from both the psychology and economics literature. To develop a long-term prospective study, we first evaluate both types of risk attitudes and find that the economic and psychological measures are poorly correlated, suggesting that different genetic factors may underlie human response to risk faced in different behavioral domains. We then examine polymorphisms in a spectrum of candidate genes that affect neurotransmitter systems influencing dopamine regulation or are thought to be associated with risk attitudes or impulsive disorders. Analysis of the genotyping data identified two single nucleotide polymorphisms (SNPs) in the gene encoding the alpha 4 nicotine receptor (CHRNA4, rs4603829 and rs4522666) that are significantly associated with harm avoidance, a risk attitude measurement drawn from the psychology literature. Novelty seeking, another risk attitude measure from the psychology literature, is associated with several COMT (catechol-O-methyl transferase) SNPs while economic risk attitude measures are associated with several VMAT2 (vesicular monoamine transporter) SNPs, but the significance of these associations did not withstand statistical adjustment for multiple testing and requires larger cohorts. These exploratory results provide a starting point for understanding the genetic basis of risk attitudes by considering the range of methods available for measuring risk attitudes and by searching beyond the traditional direct focus on dopamine and serotonin receptor and transporter genes

Processing of Body Odor Signals by the Human Brain

Brain development in mammals has been proposed to be promoted by successful adaptations to the social complexity as well as to the social and non-social chemical environment. Therefore, the communication via chemosensory signals might have been and might still be a phylogenetically ancient communication channel transmitting evolutionary significant information. In humans, the neuronal underpinnings of the processing of social chemosignals have been investigated in relation to kin recognition, mate choice, the reproductive state and emotional contagion. These studies reveal that human chemosignals are probably not processed within olfactory brain areas but through neuronal relays responsible for the processing of social information. It is concluded that the processing of human social chemosignals resembles the processing of social signals originating from other modalities, except that human social chemosignals are usually communicated without the allocation of attentional resources, that is below the threshold of consciousness. Deviances in the processing of human social chemosignals might be related to the development and maintenance of mental disorders

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Neural substrates of individual differences in human fear learning: Evidence from concurrent fMRI, fear-potentiated startle, and US-expectancy data

To provide insight into individual differences in fear learning, we examined the emotional and cognitive expressions of discriminative fear conditioning in direct relation to its neural substrates. Contrary to previous behavioral–neural (fMRI) research on fear learning—in which the emotional expression of fear was generally indexed by skin conductance—we used fear-potentiated startle, a more reliable and specific index of fear. While we obtained concurrent fear-potentiated startle, neuroimaging (fMRI), and US-expectancy data, healthy participants underwent a fear-conditioning paradigm in which one of two conditioned stimuli (CS(+) but not CS(–)) was paired with a shock (unconditioned stimulus [US]). Fear learning was evident from the differential expressions of fear (CS(+) > CS(–)) at both the behavioral level (startle potentiation and US expectancy) and the neural level (in amygdala, anterior cingulate cortex, hippocampus, and insula). We examined individual differences in discriminative fear conditioning by classifying participants (as conditionable vs. unconditionable) according to whether they showed successful differential startle potentiation. This revealed that the individual differences in the emotional expression of discriminative fear learning (startle potentiation) were reflected in differential amygdala activation, regardless of the cognitive expression of fear learning (CS–US contingency or hippocampal activation). Our study provides the first evidence for the potential of examining startle potentiation in concurrent fMRI research on fear learning