Effects of familiarity with musical style on music-evoked emotions: An EEG study

Learning mechanisms have been postulated to be one of the primary reasons why different individuals have similar or different emotional responses to music. While existing studies have largely examined mechanisms related to learning in terms of cultural familiarity or recognition, few studies have conceptualized it in terms of an individual’s level of familiarity with musical style, which could be a better reflection of an individual’s composite musical experiences. Therefore, the current study aimed to bridge this research gap by investigating the electrophysiological correlates of the effects of familiarity with musical style on music-evoked emotions. 49 non-musicians listened to 12 musical excerpts of a familiar musical style (Japanese animation soundtracks) and eight musical excerpts of an unfamiliar musical style (Greek Laïkó music) with their eyes closed as electroencephalography is being recorded. Participants rated their felt emotions after each musical excerpt is played. Behavioral ratings showed that music of the familiar musical style was felt as significantly more pleasant as compared to the unfamiliar musical style while no significant differences in arousal were observed. In terms of brain activity, music of the unfamiliar musical style elicited higher (1) theta power in all brain regions (including frontal midline), (2) alpha power in frontal region, and (3) beta power in fronto-temporo-occipital regions as compared to the familiar musical style. This is interpreted to reflect the need for greater attentional resources when listening to music of an unfamiliar style, where listeners are less familiar with the syntax and structure of the music as compared to music of a familiar style. In addition, classification analysis showed that unfamiliar and familiar musical styles can be distinguished with 67.86% accuracy, Thus, clinicians should consider the musical profile of the client when choosing an appropriate selection of music in the treatment plan, so as to achieve better efficacy.

Cerebellar and Prefrontal Structures Associated with Executive Functioning in Pediatric Patients with Congenital Heart Defects

Objective: Children, adolescents, and young adults with congenital heart defects (CHD) often display cognitive and behavioral manifestations of executive dysfunction. We consider the prefrontal and cerebellar brain structures as mechanisms for executive dysfunction among those with CHD. Method: 55 participants with CHD (M age = 13.93) and 95 healthy controls (M age = 13.13) completed magnetic resonance imaging (MRI) of the brain, from which we extracted volumetric data on prefrontal and cerebellar regions. Participants also completed neuropsychological tests of executive functioning; their parents completed behavioral ratings of their executive functions. Results: Compared to healthy controls, those with CHD had smaller cerebellums and lateral, medial, and orbital prefrontal regions, they performed more poorly on tests of working memory, inhibitory control, and mental flexibility, and their parents rated them as having poorer executive functions across several indices. Across both groups, there were significant correlations for cerebellar and/or prefrontal volumes with cognitive assessments of working memory, mental flexibility, and inhibitory control and with behavioral ratings of working memory, task initiation, and emotional control. Greater prefrontal volumes were associated with better working memory, among those with larger cerebellums (with group differences based on the measure and the prefrontal region). Greater prefrontal volumes were related to better emotional regulation only among participants with CHD with smaller cerebellar volumes, and with poorer inhibition and emotional regulation only among healthy controls with larger cerebellar volumes. Conclusion: The cerebellum modulates the relationships between prefrontal regions and executive functioning differently for pediatric patients with CHD versus health controls.

Parent and Teacher Ratings of Behavioral Executive Functioning for Students With Dyslexia

Research exploring behavioral ratings of executive functioning (EF) for children and adolescents with dyslexia is scarce, which limits researchers, clinicians, educators, and parents from understanding and best supporting these students at home and/or school. Using the Behavior Rating Inventory of Executive Function, Second Edition (BRIEF-2) rating scale to measure participants’ EF behaviors in home and school settings, a primary objective of this study was to examine the EF of Spanish children and adolescents with dyslexia ( n = 78) and to compare their EF with typically developing (TD) peers ( n = 82). The study also sought to examine agreements and disagreements among teacher and parent raters. One key finding was that children and adolescents with dyslexia were rated by both parents and teachers as having more frequent cognitive, behavioral, and emotional EF difficulties in home and school compared with TD peers. However, teachers often reported greater severity of impairments than parents did across several EF domains, potentially suggesting a differential pattern of EF difficulties between home and school. Results are discussed in relation to multi-informant assessment practices for EF behaviors (e.g., there may be differential patterns of EF difficulties between home and school) and how the findings have implications for supporting children and adolescents with dyslexia.

Some like it, some do not: behavioral responses and central processing of olfactory–trigeminal mixture perception

Exploring the potential of eucalyptol as a masking agent for aversive odors, we found that eucalyptol masks the olfactory but not the trigeminal sensation of ammonia in a previous study. Here, we further investigate the processing of a mixture consisting of eucalyptol and ammonia, two olfactory–trigeminal stimuli. We presented the two pure odors and a mixture thereof to 33 healthy participants. The nostrils were stimulated alternately (monorhinal application). We analyzed the behavioral ratings (intensity and pleasantness) and functional brain images. First, we replicated our previous finding that, within the mixture, the eucalyptol component suppressed the olfactory intensity of the ammonia component. Second, mixture pleasantness was rated differently by participants depending on which component dominated their mixture perception. Approximately half of the volunteers rated the eucalyptol component as more intense and evaluated the mixture as pleasant (pleasant group). The other half rated the ammonia component as more intense and evaluated the mixture as unpleasant (unpleasant group). Third, these individual differences were also found in functional imaging data. Contrasting the mixture either to eucalyptol or to both single odors, neural activation was found in the unpleasant group only. Activation in the anterior insula and SII was interpreted as evidence for an attentional shift towards the potentially threatening mixture component ammonia and for trigeminal enhancement. In addition to insula and SII, further regions of the pain matrix were involved when assessing all participant responses to the mixture. Both a painful sensation and an attentional shift towards the unpleasant mixture component complicates the development of an efficient mask because a pleasant perception is an important requirement for malodor coverage.

Precision Telemedicine through Crowdsourced Machine Learning: Testing Variability of Crowd Workers for Video-Based Autism Feature Recognition

Mobilized telemedicine is becoming a key, and even necessary, facet of both precision health and precision medicine. In this study, we evaluate the capability and potential of a crowd of virtual workers—defined as vetted members of popular crowdsourcing platforms—to aid in the task of diagnosing autism. We evaluate workers when crowdsourcing the task of providing categorical ordinal behavioral ratings to unstructured public YouTube videos of children with autism and neurotypical controls. To evaluate emerging patterns that are consistent across independent crowds, we target workers from distinct geographic loci on two crowdsourcing platforms: an international group of workers on Amazon Mechanical Turk (MTurk) (N = 15) and Microworkers from Bangladesh (N = 56), Kenya (N = 23), and the Philippines (N = 25). We feed worker responses as input to a validated diagnostic machine learning classifier trained on clinician-filled electronic health records. We find that regardless of crowd platform or targeted country, workers vary in the average confidence of the correct diagnosis predicted by the classifier. The best worker responses produce a mean probability of the correct class above 80% and over one standard deviation above 50%, accuracy and variability on par with experts according to prior studies. There is a weak correlation between mean time spent on task and mean performance (r = 0.358, p = 0.005). These results demonstrate that while the crowd can produce accurate diagnoses, there are intrinsic differences in crowdworker ability to rate behavioral features. We propose a novel strategy for recruitment of crowdsourced workers to ensure high quality diagnostic evaluations of autism, and potentially many other pediatric behavioral health conditions. Our approach represents a viable step in the direction of crowd-based approaches for more scalable and affordable precision medicine.

Relationship Between Physiologically Measured Attention and Behavioral Task Engagement in Persons With Chronic Aphasia

Purpose Persons with aphasia (PWAs) have been shown to have impaired attention skills that may interfere with their ability to successfully participate in speech and language therapy. Fluctuations in attention can be detected using physiological measures such as electroencephalography (EEG), but these measures can be impractical for clinical use. The primary purpose of this study was to investigate observable behavioral signs of attention as a means of measuring within-session fluctuations in attention by comparing behavioral ratings to physiological changes. Other aims were to understand the relationship between observable behaviors and task performance and to determine whether syntactic complexity influences behavioral attention. Method Ten PWAs and 10 neurologically healthy adults underwent a sentence-reading task with 45 active and 45 passive sentences while video/audio and EEG data were recorded continuously. EEG data for each trial were classified into one of four levels of attention using a classification algorithm (Berka et al., 2004), and video/audio data were scored for accuracy and behavioral engagement by two trained speech-language pathologist students using a behavioral rating scale of inattention (Whyte et al., 1996). Results Results showed that behavioral engagement was significantly correlated with task performance, with higher engagement scores associated with fewer errors. Behavioral engagement did not differ based on syntactic complexity for either group, but PWAs had significantly lower behavioral engagement scores when they were in lower/distracted states of physiologically measured vigilant attention. Conclusion Behavioral observation may provide an alternative means of detecting clinically significant lapses in attention during aphasia therapy.

Using users’ physiological responses for the estimation of websites’ aesthetic judgments

The aesthetic appearance of websites can influence the perception of their usability, reliability,and trustworthiness. Several studies investigated the relationship between single aestheticfeatures and explicit aesthetic judgments, demonstrating the existence of an attribution bias.However, only a limited amount of studies focused on the interaction between multiple visualproperties and have considered not only explicit ratings, but also implicit judgments. In thiswork, we employ a novel approach, based on the analysis of physiological signals (implicitmeasures) and the application of machine learning and neural network models to predict users’perceived aesthetic pleasure from the empirical analysis of web pages’ advanced visual properties(e.g. symmetry, visual complexity, colorfulness, ratio between visual and textual areas). Youngadults (N=59, 33 females, Mean age = 21.52 years) assessed the aesthetic appeal of websitesand emotional pictures while their physiological activity was recorded. Results using recursivepartitioning and generalized linear models demonstrate the possibility of predicting the averageaesthetic rating of a website using both explicit (behavioral ratings) and implicit measures(physiological activities).