The Use of Rhyme, Rhythm, and Melody as a Form of Repetition Priming to Aid in Encoding, Storage, and Retrieval of Semantic Memories in Alzheimer’s Patients

Millions are diagnosed with Alzheimer’s disease annually which can have debilitating effects on patient memory. Thus, finding new ways to help facilitate memory in these patients, especially through non-pharmaceutical means, has become increasingly important. I examined the use of melody, rhyme, and rhythm as encoding mechanisms to aid in the retrieval of long term semantic information by juxtaposing scholarly articles detailing experiments, each of which examined the effects of various facets of memory facilitation; this helped produce an idea of which devices are most effective. Additionally, I surveyed studies highlighting limitations of song implementation to craft an effective plan to aid Alzheimer’s patients. Melody, rhyme, and rhythm provide an organizational structure to facilitate the encoding of information. Specifically, chunking, the grouping of smaller units into larger ‘chunks’, helps facilitate long term encoding in patients, and is the byproduct of the organizational structure of a text. A major drawback of using these devices is the loss in the depth of encoding semantic information; however, it is important to recognize music still assists general content memory. Therefore, Alzheimer’s patients would benefit from the use of melody as it would provide a moral support, helping familiarity with their surroundings, although they would not benefit from instructional song. Future experiments may study the combination of discussed factors in various settings to examine the unique benefits of music on memory in Alzheimer’s patients

Movement Therapy for School Age Children with Autism: A Review of the Literature

One in every 68 children in the United States has autism spectrum disorder (ASD), affecting boys more than girls (4:1). Physical activity is important for children with ASD because it promotes life-long fitness and prevents chronic conditions. The purpose of this synthesis was to determine the most effective research-based movement therapy for children with autism, as well as discuss the advantages and disadvantages of each therapy presented. The literature review used peer-reviewed scholarly articles to examine evidencebased research in the areas of music therapy, dance therapy, yoga therapy and aquatic therapy. Results indicated family-centered music therapy (FCMT) improves the quality of social and parent-child interactions and a motivating social environment for preschool aged children. Yoga therapy displays positive effects for treating behavioral difficulties in elementary school children. Aquatic therapy was recommended for secondary children with ASD, due to the reductions in inappropriate behavior and increased on-task behavior. Recommendations for parents and physical educators include implementing activity schedules, performing tasks in sequential order, modifying instruction, modifying equipment and using visual aids. Overall, research indicated that dance therapy, music therapy, yoga therapy and aquatic therapy have advantages and disadvantages in treating children with ASD. Movement therapies can be used successfully for individuals with ASD but not every individual will experience the same benefits

Affective Music Information Retrieval

Much of the appeal of music lies in its power to convey emotions/moods and to evoke them in listeners. In consequence, the past decade witnessed a growing interest in modeling emotions from musical signals in the music information retrieval (MIR) community. In this article, we present a novel generative approach to music emotion modeling, with a specific focus on the valence-arousal (VA) dimension model of emotion. The presented generative model, called \emph{acoustic emotion Gaussians} (AEG), better accounts for the subjectivity of emotion perception by the use of probability distributions. Specifically, it learns from the emotion annotations of multiple subjects a Gaussian mixture model in the VA space with prior constraints on the corresponding acoustic features of the training music pieces. Such a computational framework is technically sound, capable of learning in an online fashion, and thus applicable to a variety of applications, including user-independent (general) and user-dependent (personalized) emotion recognition and emotion-based music retrieval. We report evaluations of the aforementioned applications of AEG on a larger-scale emotion-annotated corpora, AMG1608, to demonstrate the effectiveness of AEG and to showcase how evaluations are conducted for research on emotion-based MIR. Directions of future work are also discussed.Comment: 40 pages, 18 figures, 5 tables, author versio

Combining music and life story work to enhance participation in family interaction in semantic dementia: a longitudinal study of one family's experience.

Background: Semantic dementia is a rarer dementia, classified as a type of frontotemporal dementia and a variant of primary progressive aphasia. Studies examining conversation in this condition and interventions to enhance participation in family life present as gaps in the research literature. Methods: Working with one family on a longitudinal basis, this study used conversation analysis and narrative analysis to provide a detailed assessment of communication . This information was used to design an individually tailored life story intervention to facilitate family interaction: a co-produced life story music DVD. Results: This intervention offered the family a resource that allowed the person with semantic dementia to display areas of retained competence and enhanced participation in interaction in a way that was not typically present in everyday conversation. Conclusions: It is argued that fostering greater opportunities for such in-the-moment connections is an important goal for intervention, particularly when language may be significantly compromised

Content Analysis of Reasons for Song Choices Among Individuals Receiving Hospice Care

The purpose of this study was to describe the reasons for song choices of patients and their loved ones in a hospice setting. In all, 21 patients and caregivers participated in semi-structured interviews that were embedded in music therapy sessions at a Midwest hospice. A content analysis applied to participants' interviews revealed four categories and 14 subcategories related to participants' reasons for their song choices. Categories included (a) concrete connections, (b) intangible connections, (c) music, and (d) relationships. Subcategories related to the four main categories were organized as follows: under concrete connections (a) connections with the past, (b) connections with the present, and (c) connections with the future; under intangible connections (a) beliefs, (b) feelings and desires, and (c) images and stories; under music (a) affective responses and beliefs about music/songs, (b) general references to music/songs, (c) instruments, (d) lyrics, (e) structural elements, and (f) style; and under relationships (a) loved ones and (b) self. These categories and subcategories provide a framework that may be useful in expediting assessment processes and clarifying areas where there is a need for musical or verbal validation by the therapist

An Exploration into Art Therapists\u27 Experiences of Collaboration with Music Therapists to Treat People with Autistic Spectrum Disorder

This study explored the experiences of art therapists who used music in art therapy sessions with and without the presence of a music therapist. Two participants were selected through purposeful sampling and participated in a 45-minute, virtual, semi-structured individual interview. Participants met the following criteria: (a) board-certified art therapist (ATR-BC), (b) a minimum of two years of professional work experience as an art therapist, (c) experience in working with music therapists and using pre-recorded music without the presence of a music therapist during the art therapy sessions for people with autism spectrum disorders (ASD), and (d) speaks Korean and/or English. Interviews were recorded, transcribed verbatim, and analyzed using interpretative phenomenological analysis. Data analysis revealed five themes: the rationale for the use of music, using multiple creative means to meet the needs of clients, experience of working with a music therapist, limitations to using music in art therapy sessions, and perspective on collaborating with a music therapist. The results indicate that collaborative music and art therapy can lead to positive outcomes in achieving therapeutic goals. However, some knowledge gaps about music therapy were identified, which should be considered to enhance future art and music collaboration. The study’s findings have implications for art and music therapists working with individuals with ASD, highlighting the need to expand their perspectives and therapeutic interventions. By promoting accurate knowledge of collaborative practices, therapists can improve the quality of care for individuals with ASD

Manufacturing “Hits”: A Data-Driven AI Approach to Releasing a Pop Song in 2022

Technology is radically transforming the music industry through the use of big data, artificial intelligence and machine learning algorithms. This paper presents a pilot study that examines the impact of data-driven approaches in creating, predicting, and marketing music. A machine learning algorithm is used to determine the optimal characteristics of the most popular songs and is used as the basis for creating the next song. Next, an AI technique was used to generate the inspiration of the instrumentation and lyrics of the song. Finally, a listener survey is used to determine the trend which included the mood, preference and context for the song. The song is then released on Spotify. The success of the song is determined by comparing the number of streams to two songs released the previous without the use of data. The results show that creating and marketing a song using AI models, Spotify listener data analysis, and listener questionnaires strongly positively impact a song’s streaming success. While this is a pilot study, the findings of this study can be used more extensively to determine success of music videos and releases and serve as a guidance to artists with more quantitative insight