Key Considerations for Designing Clinical Studies to Evaluate Digital Health Solutions.

Evidence of clinical impact is critical to unlock the potential of digital health solutions (DHSs), yet many solutions are failing to deliver positive clinical results. We argue in this viewpoint that this failure is linked to current approaches to DHS evaluation design, which neglect numerous key characteristics (KCs) requiring specific scientific and design considerations. We first delineate the KCs of DHSs: (1) they are implemented at health care system and patient levels; (2) they are "complex" interventions; (3) they can drive multiple clinical outcomes indirectly through a multitude of smaller clinical benefits; (4) their mechanism of action can vary between individuals and change over time based on patient needs; and (5) they develop through short, iterative cycles-optimally within a real-world use context. Following our objective to drive better alignment between clinical evaluation design and the unique traits of DHSs, we then provide methodological suggestions that better address these KCs, including tips on mechanism-of-action mapping, alternative randomization methods, control-arm adaptations, and novel end-point selection, as well as innovative methods utilizing real-world data and platform research.

Balancing the brain of offenders with psychopathy? Resting state EEG and electrodermal activity after a pilot study of brain self-regulation training.

Although investigation of the brains of criminals began quite early in the history of psychophysiological research, little is known about brain plasticity of offenders with psychopathy. Building on our preliminary study reporting successful brain self-regulation using slow cortical potential (SCP) neurofeedback in offenders with psychopathy, we investigated the central nervous and autonomic peripheral changes occurring after brain self-regulation in a group of severe male offenders with psychopathy. Regarding the central nervous system, an overall suppression of the psychopathic overrepresentation of slow frequency bands was found, such as delta and theta band activity, after EEG neurofeedback. In addition, an increase in alpha band activity could be observed after the SCP self-regulation training. Electrodermal activity adaptively changed according to the regulation task, and this flexibility improved over training time. The results of this study point towards a constructive learning process and plasticity in neural and peripheral measures of offenders with psychopathy.

Affective Cortical Asymmetry at the Early Developmental Emergence of Emotional Expression.

Emotions have an important survival function. Vast amounts of research have demonstrated how affect-related changes in physiology promote survival by effecting short-term and long-term changes in adaptive behavior. However, if emotions truly serve such an inherent function, they should be pervasive across species and be established early in life. Here, using electroencephalographic (EEG) brain activity we sought to characterize core neurophysiological features underlying affective function at the emergence of emotional expression [i.e., at the developmental age when human infants start to show reliable stimulus-elicited emotional states (4-6 months)]. Using an approach that eschews traditional EEG frequency band delineations (like theta, alpha), we demonstrate that negative emotional states induce a strong right hemispheric increase in the prominence of the resonant frequency (∼5-6 Hz) in the infant frontal EEG. Increased rightward asymmetry was strongly correlated with increased heart rate responses to emotionally negative states compared with neutral states. We conclude that functional frontal asymmetry is a key component of emotional processing and suggest that the rightward asymmetry in prominence of the resonant frequency during negative emotional states might reflect functional asymmetry in the central representation of anatomically driven asymmetry in the autonomic nervous system. Our findings indicate that the specific mode hallmarking emotional processing in the frontal cortex is established in parallel with the emergence of stable emotional states very early during development, despite the well known protracted maturation of frontal cortex.

Sleep's benefits to emotional processing emerge in the long term.

Sleep benefits the long-term preservation of emotional memories, making them accessible even years after the emotional episode has occurred. However, whether sleep also influences the emotional response that gets elicited while retrieving such memories (e.g., by increasing autonomic activity) remains unclear. Here, we demonstrate that sleep fosters a coherent decrease in both automatic (heart rate deceleration) and more cognitively controlled subjective measures (valence ratings) of the emotional tone associated with memories when they are retrieved after one week. Exploratory analyses suggest that sleep might initiate an enhancement of the neural representation of emotional compared to neutral memories (as reflected in the late positive potential of the electroencephalogram) that becomes pronounced after one week. These long-term effects are in contrast to sleep's immediate influence on the emotional response (i.e., 10 h after encoding), where heart rate deceleration was preserved and the late positive potential decreased when compared to the changes seen over a day of wake. Together, these results suggest that sleeping after an emotional experience has dynamic and protracted influences on the emotional tone associated with memories.

Preferential Consolidation of Emotional Memory During Sleep: A Meta-Analysis.

It is uncertain whether sleep preferentially consolidates emotional over neutral material. Some studies suggest that sleep enhances emotional memory (i.e., that there are large differences in strength of memory for valenced material compared to neutral material after a sleep-filled interval, but that this difference is smaller after a wake-filled interval). Others find no such effect. We attempted to resolve this uncertainty by conducting a meta-analysis that compared valenced to neutral material after both sleep- and wake-filled delays. Standard search strategies identified 31 studies (containing 36 separate datasets) that met our inclusion criteria. Using random effects modeling, we conducted separate analyses for datasets comparing (a) negative vs. neutral material, (b) positive vs. neutral material, or (c) combined negative and positive vs. neutral material. We then specified several subgroup analyses to investigate potential moderators of the relationship between sleep and emotional memory consolidation. Results showed no overall effect for preferential sleep-dependent consolidation of emotional over neutral material. However, moderation analyses provided evidence for stronger effects when (a) studies used free recall rather than recognition outcome measures, or (b) delayed recall or recognition outcomes were controlled for initial learning. Those analyses also suggested that other methodological features (e.g., whether participants experience a full night of sleep and a regular daytime waking control condition rather than a nap and a night-time sleep deprivation control condition) and sample characteristics (e.g. all-male or not, young adult or not) should be carefully addressed in future research in this field. These findings suggest that sleep does enhance emotional memory, but that in the laboratory the effect is only observed under particular methodological conditions. The conditions we identify as being critical to consider are consistent with general theories guiding scientific understanding of memory consolidation during sleep.

Sleep divergently affects cognitive and automatic emotional response in children.

Sleep enhances memory for emotional experiences, but its influence on the emotional response associated with memories is elusive. Here, we compared the influence of nocturnal sleep on memory for negative and neutral pictures and the associated emotional response in 8-11-year-old children, i.e., an age group with heightened levels of emotional memory-related sleep features. During all sessions, emotional responses as measured by subjective ratings, the late positive potential of the EEG (LPP) and heart rate deceleration (HRD) were recorded. Sleep enhanced picture memory. Compared to dynamics across wakefulness, sleep decreased the emotional response in ratings and the LPP, while increasing the emotional response in HRD. We conclude that sleep consolidates immediate emotional meaning by enhancing more automatic emotional responses while concurrently promoting top-down control of emotional responses, perhaps through strengthening respective neocortical representations.

Dissociating Long and Short-term Memory in Three-Month-Old Infants Using the Mismatch Response to Voice Stimuli.

Auditory event-related potentials (ERPs) have been successfully used in adults as well as in newborns to discriminate recall of longer-term and shorter-term memories. Specifically the Mismatch Response (MMR) to deviant stimuli of an oddball paradigm is larger if the deviant stimuli are highly familiar (i.e., retrieved from long-term memory) than if they are unfamiliar, representing an immediate change to the standard stimuli kept in short-term memory. Here, we aimed to extend previous findings indicating a differential MMR to familiar and unfamiliar deviants in newborns (Beauchemin et al., 2011), to 3-month-old infants who are starting to interact more with their social surroundings supposedly based on forming more (social) long-term representations. Using a voice discrimination paradigm, each infant was repeatedly presented with the word "baby" (400 ms, interstimulus interval: 600 ms, 10 min overall duration) pronounced by three different female speakers. One voice that was unfamiliar to the infants served as the frequently presented "standard" stimulus, whereas another unfamiliar voice served as the "unfamiliar deviant" stimulus, and the voice of the infant's mother served as the "familiar deviant." Data collection was successful for 31 infants (mean age = 100 days). The MMR was determined by the difference between the ERP to standard stimuli and the ERP to the unfamiliar and familiar deviant, respectively. The MMR to the familiar deviant (mother's voice) was larger, i.e., more positive, than that to the unfamiliar deviant between 100 and 400 ms post-stimulus over the frontal and central cortex. However, a genuine MMR differentiating, as a positive deflection, between ERPs to familiar deviants and standard stimuli was only found in the 300-400 ms interval. On the other hand, a genuine MMR differentiating, as a negative deflection, between ERPs to unfamiliar deviants from ERPs to standard stimuli was revealed for the 200-300 ms post-stimulus interval. Overall results confirm a differential MMR response to unfamiliar and familiar deviants in 3-month-olds, with the earlier negative MMR to unfamiliar deviants likely reflecting change detection based on comparison processes in short-term memory, and the later positive MMR to familiar deviants reflecting subsequent long-term memory-based processing of stimulus relevance.

EEG Responses to Auditory Stimuli for Automatic Affect Recognition.

Brain state classification for communication and control has been well established in the area of brain-computer interfaces over the last decades. Recently, the passive and automatic extraction of additional information regarding the psychological state of users from neurophysiological signals has gained increased attention in the interdisciplinary field of affective computing. We investigated how well specific emotional reactions, induced by auditory stimuli, can be detected in EEG recordings. We introduce an auditory emotion induction paradigm based on the International Affective Digitized Sounds 2nd Edition (IADS-2) database also suitable for disabled individuals. Stimuli are grouped in three valence categories: unpleasant, neutral, and pleasant. Significant differences in time domain domain event-related potentials are found in the electroencephalogram (EEG) between unpleasant and neutral, as well as pleasant and neutral conditions over midline electrodes. Time domain data were classified in three binary classification problems using a linear support vector machine (SVM) classifier. We discuss three classification performance measures in the context of affective computing and outline some strategies for conducting and reporting affect classification studies.

Thought-based row-column scanning communication board for individuals with cerebral palsy.

Impairment of an individual's ability to communicate is a major hurdle for active participation in education and social life. A lot of individuals with cerebral palsy (CP) have normal intelligence, however, due to their inability to communicate, they fall behind. Non-invasive electroencephalogram (EEG) based brain-computer interfaces (BCIs) have been proposed as potential assistive devices for individuals with CP. BCIs translate brain signals directly into action. Motor activity is no longer required. However, translation of EEG signals may be unreliable and requires months of training. Moreover, individuals with CP may exhibit high levels of spontaneous and uncontrolled movement, which has a large impact on EEG signal quality and results in incorrect translations. We introduce a novel thought-based row-column scanning communication board that was developed following user-centered design principles. Key features include an automatic online artifact reduction method and an evidence accumulation procedure for decision making. The latter allows robust decision making with unreliable BCI input. Fourteen users with CP participated in a supporting online study and helped to evaluate the performance of the developed system. Users were asked to select target items with the row-column scanning communication board. The results suggest that seven among eleven remaining users performed better than chance and were consequently able to communicate by using the developed system. Three users were excluded because of insufficient EEG signal quality. These results are very encouraging and represent a good foundation for the development of real-world BCI-based communication devices for users with CP.