Low‐cost devices have widened the use of multimodal data in experiments providing a more complete picture of behavioural effects. However, the accurate collection and combination of multimodal and behavioural data in a manner that enables reproducibility is challenging and often requires researchers to refine their approaches. This paper presents a direct replication of a multimodal wordlist experiment. Specifically, we use a low‐cost Emotiv EPOC® to acquire electrophysiological measures of brain activity to investigate whether retrieval during learning facilitates the encoding of subsequent learning as measured by performance on recall tests and reflected by changes in alpha wave oscillations. Behavioural results of the wordlist experiment were replicated, but physiological results were not. We conclude the paper by highlighting the challenges faced in terms of replicating the previous work and in attempting to facilitate the reproducibility of our own experiment.
This chapter presents one way to define Abelian groups of fractional operators isomorphic to the group of integers under addition through a family of sets of fractional operators and a modified Hadamard product, as well as one way to define finite Abelian groups of fractional operators through sets of positive residual classes less than a prime number. Furthermore, it is presented one way to define sets of fractional operators which allow generalizing the Taylor series expansion of a vector-valued function in multi-index notation, as well as one way to define a family of fractional fixed-point methods and determine their order of convergence analytically through sets.
The Autistic Spectrum Disorder (ASD) is characterized by a difficulty in expressing and interpreting others’ emotions. In particular, people with ASD have difficulties when interpreting emotions encoded in facial expressions. In the past, music interventions have been shown to improve autistic individuals’ emotional and social skills. The present study describes a pilot study to explore the usefulness of music as a tool for improving autistic children’s emotion recognition in facial expressions. Twenty-five children (mean age = 8.8 y, SD = 1.24) with high-functioning ASD and normal hearing participated in the study consisting of four weekly sessions of 15 min each. Fifteen participants were randomly divided into an experimental group (N = 14) and a control group (N = 11). During each session, participants in the experimental group were exposed to images of facial expressions for four emotions (happy, sad, angry, and fear). Images were shown in three conditions, with the second condition consisting of music of congruent emotion with the shown images. Participants in the control group were shown only images in all three conditions. For six participants in each group, EEG data were acquired during the sessions, and instantaneous emotional responses (arousal and valence values) were extracted from the EEG data. Inter- and intra-session emotion identification improvement was measured in terms of verbal response accuracy, and EEG response differences were analyzed. A comparison of the verbal responses of the experimental group pre- and post-intervention showed a significant (p = 0.001) average improvement in emotion identification accuracy responses of 26% (SD = 3.4). Furthermore, emotional responses of the experimental group at the end of the study showed a higher correlation with the emotional stimuli being presented, compared with their emotional responses at the beginning of the study. No similar verbal responses improvement or EEG-stimuli correlation was found in the control group. These results seem to indicate that music can be used to improve both emotion identification in facial expressions and emotion induction through facial stimuli in children with high-functioning ASD.
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