scholarly journals Tuning the inner radio: The mental control of musical imagery in everyday environments

2019 ◽  
Vol 48 (6) ◽  
pp. 876-888 ◽  
Author(s):  
Katherine N. Cotter ◽  
Paul J. Silvia
Keyword(s):  
Daily Life ◽  
Recent Model ◽  
Music Students ◽  
Prior Work ◽  
Mental Control ◽  
Musical Imagery

How easily can people tune their inner radio? Musical imagery—hearing music in your mind—is common but little is known about people’s ability to control their musical imagery in daily life. A recent model distinguishes between initiation (starting musical imagery) vs. management (modifying, stopping, or sustaining musical imagery) as facets of control, and the present research examined people’s ability to use these two forms of control in daily life. For seven days, students (29 music students, 29 non-music students) were signaled 10 times daily and asked to initiate musical imagery and to perform manipulations on initiated and ongoing imagery (e.g., increasing the tempo, changing the vocalist’s gender). When asked, people reported exerting control over the initiation and management of their musical imagery most of the time. As expected, music students reported controlling their musical imagery more often and more easily. This work suggests that people’s control over their musical imagery is stronger and more flexible than prior work implies.

scholarly journals Tuning the Inner Radio: The Mental Control of Musical Imagery in Everyday Environments

2018 ◽  
Author(s):  
Katherine Cotter ◽  
Paul Silvia
Keyword(s):  
Daily Life ◽  
Experience Sampling ◽  
Recent Model ◽  
Music Students ◽  
Prior Work ◽  
Mental Control ◽  
Musical Imagery

How easily can people tune their inner radio? Musical imagery—hearing music in your mind—is common and complex, but little is known about people’s ability to control their musical imagery in daily life. A recent model proposed by Cotter, Christensen, and Silvia distinguishes between initiation (starting musical imagery) vs. management (modifying, stopping, or sustaining musical imagery) as distinct facets of control, and the present research examined people’s ability to use the two forms of control in daily life. A sample of students (29 music students, 29 non-music students) participated in an experience-sampling study. For seven days, people were signaled 10 times a day and asked to initiate musical imagery and perform manipulations to initiated and ongoing imagery (e.g., increasing the tempo, changing the gender of a vocalist). When asked, people reported exerting control over the initiation and management of their musical imagery most of the time. As expected, music students reported controlling their musical imagery more often and more easily. This work suggests that people’s control over their musical imagery is stronger and more flexible than prior work implies.

Mental Control of Musical Imagery in the Lab and Everyday Life: Combining Behavioral and Experience-Sampling Approaches

2020 ◽  
Author(s):  
Katherine N. Cotter ◽  
Paul Silvia
Keyword(s):  
Daily Life ◽  
Experience Sampling ◽  
Self Report ◽  
Future Research ◽  
Well Performance ◽  
Mental Control ◽  
Musical Imagery ◽  
Behavioral Assessments ◽  
Type 3 ◽  
The Relationship

Mental control of musical imagery consists of two components: initiation—did you start it on purpose?—and management—did you alter, sustain, or end the experience after it began?. The present research examined these two components of mental control using both behavioral lab-based musical imagery tasks and self-reports of mental control in daily life using experience sampling methods. Both music students and members of the general university community participated. This project had four primary aims: (1) examining the relationship between initiation and management of musical imagery; (2) assessing how mental control abilities differ as a function of stimulus type; (3) describing perceptions of initiation and management in daily life; and (4) evaluating how well performance on lab-based behavioral tasks aligns with self-reported mental control in daily life. The findings suggest that initiation and management abilities are closely related, people perform equivalently when asked to control tonal stimuli and song stimuli, people generally report the ability to control musical imagery in daily life, and self-report and behavioral assessments of mental control of musical imagery show a modest association. These findings have implications for current understandings of control of musical imagery and identify several avenues for future research.

scholarly journals Mental Control of Musical Imagery: Comparing Tonal and Song Stimuli

2019 ◽  
Author(s):  
Katherine Cotter ◽  
Paul Silvia
Keyword(s):  
Undergraduate Students ◽  
Stimulus Type ◽  
Auditory Imagery ◽  
Mental Control ◽  
Musical Imagery ◽  
Musical Expertise ◽  
Management Ability

Mental control of musical imagery is a complex but understudied process that consists of two components: initiation—whether the musical imagery experience began voluntarily or involuntarily—and management—whether instances of control occur after the experience has begun (e.g., changing the song). The present research examined these two components using 11 lab tasks measuring both initiation and management abilities in a sample of 203 undergraduate students. The tasks varied in stimuli composition: 7 tasks used tones and tonal sequences frequently used as stimuli in auditory imagery research, and 4 tasks used stimuli resembling the contents of everyday musical imagery (i.e., song excerpts). Initiation and management abilities were closely related, and people with greater musical expertise showed a smaller difference between initiation and management ability. Similarly, performance on tasks using tones or tonal sequences and tasks using song stimuli were closely related, and people didn’t differ in performance as a function of stimulus type. The present research demonstrates that people’s ability to initiate and to manage musical imagery are strongly linked and that people are equally good at controlling relatively simple musical imagery and imagery of well-known songs.

Individual differences in mental control predict involuntary musical imagery

2013 ◽  
Vol 17 (4) ◽  
pp. 398-409 ◽  
Author(s):  
C. Philip Beaman ◽  
Tim I. Williams
Keyword(s):  
Individual Differences ◽  
Mental Control ◽  
Musical Imagery

scholarly journals Mental control of musical imagery: Comparing tonal and song stimuli.

2020 ◽  
Vol 30 (3) ◽  
pp. 145-158
Author(s):  
Katherine N. Cotter ◽  
Paul J. Silvia
Keyword(s):  
Mental Control ◽  
Musical Imagery

Ecologies

2020 ◽  
pp. 56-85
Author(s):  
Arnold Michael
Keyword(s):  
Theoretical Approach ◽  
Critical Analysis ◽  
Social Values ◽  
Daily Life ◽  
Prior Work ◽  
Communications Technologies ◽  
Social Uses

This chapter details the authors’ theoretical approach to understanding materiality and media of the home. It presents a framework for considering how technologies do not simply serve social uses or express social values but have a presence and performativity and interact with one another and with householders, and how they are embedded within the infrastructures of the home and daily life. This chapter explicitly builds on prior work in the field of media domestication and extends it through critical analysis of media ecologies. The authors describe their novel fieldwork approaches used to conceptually explore the “thingness” of the things that mediate the physical and spatial aspects of communications technologies in the ecology of the home.

Resisting, Recognizing, and Returning: A Three-Component Model and Review of Persistence in Episodic Goals

2018 ◽  
Author(s):  
Hannah Moshontz ◽  
Rick H. Hoyle
Keyword(s):  
Daily Life ◽  
Implementation Intentions ◽  
Continuous Process ◽  
Empirical Work ◽  
Goal Pursuit ◽  
The Other ◽  
Component Model ◽  
Prior Work ◽  
Effective Strategies ◽  
Will Power

According to prior work, persistent goal pursuit is a continuous process where persisting is a matter of resisting the urge to give up. In everyday goals, however, persistence is often episodic, and its causes are more complex. People pause and resume pursuit many times. Whether people persist reflects more than will power and motivation, it also reflects the other goals they pursue, their resources, and the attentional demands of daily life. People can fail to persist not just because they gave up, but also because they failed to act. We propose a general model of persistence that accommodates the complexity of episodic goals. We argue that persistent goal pursuit is a function of three processes: resisting the urge to give up, recognizing opportunities for pursuit, and returning to pursuit. The broad factors that help and hurt persistence can be organized within these components. These components can also explain the mechanisms of four effective strategies for persistence: removing distractions, using reminders, using implementation intentions, and forming habits. The recognizing-resisting-returning model integrates and improves on extant theories of persistence and goal pursuit and is consistent with empirical work from laboratory and naturalistic settings.

scholarly journals Automated meal detection from continuous glucose monitor data through simulation and explanation

2019 ◽  
Vol 26 (12) ◽  
pp. 1592-1599 ◽  
Author(s):  
Min Zheng ◽  
Baohua Ni ◽  
Samantha Kleinberg
Keyword(s):  
Physical Activity ◽  
Insulin Pump ◽  
Daily Life ◽  
Artificial Pancreas ◽  
Simulated Data ◽  
Prior Work ◽  
Real World Data ◽  
Continuous Glucose Monitor ◽  
Monitor Data

Abstract Background Artificial pancreas systems aim to reduce the burden of type 1 diabetes by automating insulin dosing. These systems link a continuous glucose monitor (CGM) and insulin pump with a control algorithm, but require users to announce meals, without which the system can only react to the rise in blood glucose. Objective We investigate whether CGM data can be used to automatically infer meals in daily life even in the presence of physical activity, which can raise or lower blood glucose. Materials and Methods We propose a novel meal detection algorithm that combines simulations with CGM, insulin pump, and heart rate monitor data. When observed and predicted glucose differ, our algorithm uses simulations to test whether a meal may explain this difference. We evaluated our method on simulated data and real-world data from individuals with type 1 diabetes. Results In simulated data, we detected meals earlier and with higher accuracy than was found in prior work (25.7 minutes, 1.2 g error; compared with 48.3 minutes, 17.2 g error). In real-world data, we discovered a larger number of plausible meals than was found in prior work (30 meals, 76.7% accepted; compared with 33 meals, 39.4% accepted). Discussion Prior research attempted meal detection from CGM, but had delays and lower accuracy in real data or did not allow for physical activity. Our approach can be used to improve insulin dosing in an artificial pancreas and trigger reminders for missed meal boluses. Conclusions We demonstrate that meal information can be robustly inferred from CGM and body-worn sensor data, even in challenging environments of daily life.

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