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Dataset results
18 results for “Musical Imagery”
"Mapping specific mental content during musical imagery" - Musical stimuli
<p>Six instrumental melodies composed by Joe Hisaishi, used as stimuli in the paper "<strong>Mapping the contents of consciousness during musical imagery"</strong></p>
music_imagery_data
<p><strong>Data for the study reported in:</strong></p> <ul> <li>Martinez, D. R. Q., Rubio, G. F., Bonetti, L., Achyutuni, K. G., Tzovara, A., Knight, R. T., & Vuust, P. (2024). <br>Decoding reveals the neural representation of perceived and imagined musical sounds (p. 2023.08.15.553456). <br>bioRxiv. https://doi.org/10.1101/2023.08.15.553456</li> </ul> <p><strong>Description</strong></p> <ul> <li><strong>demographics.csv</strong>: Participant demographics.</li> <li><strong>decoding_accuracies</strong>: Time-generalized neural decoding accuracy per participant stored as Python dict containing 2d arrays (training_times x testing_times), with each entry indexing a condition or contrast of interest.</li> <li><strong>decoding_patterns</strong>: Decoding patterns per participant obtained from model coefficients stored as dict containing mne.Epochs arrays indexed by condition or contrast name.</li> <li><strong>epochs</strong>: Per participant single-trial epochs stored as dict containing mne.Epochs arrays after preprocessing (ica removed, high-pass >= 0.05Hz, smoothing with tstep= 25ms and twin=50ms, sfreq=40Hz).</li> <li><strong>figures_data</strong>: Values plotted in each figure and/or the data necessary to obtain them. Excel sheets or csv.</li> <li><strong>inverse_solutions</strong>: Inverse operator per participant to project sensor data into source space (mne inverse class).</li> <li><strong>logs</strong>: Experiment log files. Recall=recognize, manipulation=invert.</li> <li><strong>MNI_transforms</strong>: Transformation matrices per subject to convert source data into common MNI space.</li> <li><strong>neural_accuracy</strong>: Diagonal neural decoding accuracies per subject and time-point, together with behavioral and demographic data.</li> <li><strong>statistics</strong>: Statistical output for the different tests. Dictionaries with entries containing t-statisitcs, p-values, clusters, etc...</li> </ul>
Data from: The music of silence. Part I: Responses to musical imagery encode melodic expectations and acoustics
<p>Musical imagery is the voluntary internal hearing of music in the mind without the need for physical action or external stimulation. Numerous studies have already revealed brain areas activated during imagery. However, it remains unclear to what extent imagined music responses preserve the detailed temporal dynamics of the acoustic stimulus envelope and, crucially, whether melodic expectations play any role in modulating responses to imagined music, as they prominently do during listening. These modulations are important as they reflect aspects of the human musical experience, such as its acquisition, engagement, and enjoyment. This study explored the nature of these modulations in imagined music based on EEG recordings from 21 professional musicians (6 females and 15 males). Regression analyses were conducted to demonstrate that imagined neural signals can be predicted accurately, similarly to the listening task, and were sufficiently robust to allow for accurate identification of the imagined musical piece from the EEG. In doing so, our results indicate that imagery and listening tasks elicited an overlapping but distinctive topography of neural responses to sound acoustics, which is in line with previous fMRI literature. Melodic expectation, however, evoked very similar frontal spatial activation in both conditions, suggesting that they are supported by the same underlying mechanisms. Finally, neural responses induced by imagery exhibited a specific transformation from the listening condition, which primarily included a relative delay and a polarity inversion of the response. This transformation demonstrates the top-down predictive nature of the expectation mechanisms arising during both listening and imagery.</p>
Data from: The music of silence. Part I: Responses to musical imagery encode melodic expectations and acoustics
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Data from: Implicit violent imagery processing among fans and non-fans of violent music
It is suggested that long-term exposure to violent media may decrease sensitivity to depictions of violence. However, it is unknown whether persistent exposure to music with violent themes affects implicit violent imagery processing. Using a binocular rivalry paradigm, we investigated whether the presence of violent music influences conscious awareness of violent imagery among fans and non-fans of such music. Thirty-two fans and 48 non-fans participated in the study. Violent and neutral pictures were simultaneously presented one to each eye, and participants indicated which picture they perceived (i.e. violent percept, neutral percept, or blend of two) via key presses, while they heard Western popular music with lyrics that expressed happiness or Western extreme-metal music with lyrics that expressed violence. We found both fans and non-fans of violent music exhibited a general negativity bias for violent imagery over neutral imagery regardless of the music genres. For non-fans, this bias was stronger while listening to music that expressed violence than while listening to music that expressed happiness. For fans of violent music, however, the bias was the same while listening to music that expressed either violence or happiness. We discussed these results in view of current debates on the impact of violent media.
Therapeutic Instrumental Music Performance With Sensory-Enhanced Motor Imagery in Chronic Post-Stroke Rehabilitation
ClinicalTrials.gov study NCT03246217. IPD Sharing: NO. Countries: 1. Publications: 1.
The Bonny Method of Guided Imagery and Music (GIM) in the Treatment of Depression
ClinicalTrials.gov study NCT03917979. IPD Sharing: NO. Countries: 1. Publications: 8.
Guided Imagery and Music for the Reduction of Side Effects of Chemotherapy in Teenagers
ClinicalTrials.gov study NCT02583126. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Music Therapy Model "The Bonny Method of Guided Imagery and Music" on Patients With Rheumatoid Arthritis
ClinicalTrials.gov study NCT04380129. IPD Sharing: UNDECIDED. Countries: 1. Publications: 29.
The Effect of Guided Imagery and Music Play on Labor Pain, Anxiety, and Birth Experience
ClinicalTrials.gov study NCT06035172. IPD Sharing: NO. Countries: 1. Publications: 5.
Data from: Implicit violent imagery processing among fans and non-fans of violent music
Open the record for dataset details and reuse information.
Trauma-focused Group Music and Imagery With Traumatized Women
ClinicalTrials.gov study NCT03503526. IPD Sharing: NO. Countries: 0. Publications: 11.
Dataset from the article, "Interference by linguistic processes in the occurrence of lyrics in involuntary musical imagery"
<p>Dataset from the article, "Interference by linguistic processes in the occurrence of lyrics in involuntary musical imagery", in Journal of Cognitive Psychology.</p>
Music Imagery for Patients Receiving Chemotherapy for Leukemia or Non-Hodgkin's Lymphoma
ClinicalTrials.gov study NCT00082303. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Stepped-Care Intervention of Music and Imagery to Assess Relief (SCIMITAR) Trial
ClinicalTrials.gov study NCT07217821. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
The Effect of Guided Imagery and Music Therapy on Post-Operative Recovery After Gynecological Oncology Surgery
ClinicalTrials.gov study NCT01284075. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Guided Imagery & Music in Cancer
ClinicalTrials.gov study NCT03936075. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Music and Imagery for Veterans With Migraine Headache
ClinicalTrials.gov study NCT06440876. IPD Sharing: NO. Countries: 0. Publications: 0.
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