The impact of rhythm complexity on brain activation during simple singing: An event-related fMRI study

Jungblut, Monika; Huber, W.; Pustelniak, M; Schnitker, Ralph

doi:10.3233/rnn-2011-0619

Cited by 20 publications

(10 citation statements)

References 99 publications

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“…That the pattern of results observed in SMG (i.e., a leftward asymmetry in task-related activity plus a leftward asymmetry in correlation strength with practice time) was not statistically different for melodic versus rhythmic discrimination is consistent with this broader view. It is also consistent with other reports of left SMG activity during the perception (e.g., Grahn et al, 2011; Janata et al, 2002; Limb et al, 2006), imagery (e.g., Zatorre et al, 1996), or overt motor production (Bengtsson and Ullén, 2006; Jungblut et al, 2012; Vuust et al, 2006) of both melodies and rhythms (cf. Ellis et al, 2012, Tables 1a and 1b).…”

Section: Discussionsupporting

confidence: 92%

Training-mediated leftward asymmetries during music processing: A cross-sectional and longitudinal fMRI analysis

et al. 2013

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Practicing a musical instrument has a profound impact on the structure and function of the human brain. The present fMRI study explored how relative hemispheric asymmetries in task-related activity during music processing (same/different discrimination) are shaped by musical training (quantified as cumulative hours of instrument practice), using both a large (N = 84) cross-sectional data set of children and adults, and a smaller (N = 20) two time-point longitudinal data set of children tracked over 3 to 5 years. The cross-sectional analysis revealed a significant leftward asymmetry in task-related activation, with peaks in Heschl's gyrus and supramarginal gyrus (SMG). The SMG peak was further characterized by a leftward asymmetry in the partial correlation strength with subjects' cumulative hours of practice, controlling for subjects' age and task performance. This SMG peak was found to exhibit a similar pattern of response in the longitudinal data set (in this case, with subjects' cumulative hours of practice over the course of the study), controlling for age, scan interval, and amount of instrument practice prior to the first scan. This study presents novel insights into the ways musical instrument training shapes task-related asymmetries in neural activity during music processing.

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Section: Discussionsupporting

confidence: 92%

Training-mediated leftward asymmetries during music processing: A cross-sectional and longitudinal fMRI analysis

et al. 2013

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“…Neuroimaging studies from the past two decades have confirmed that many regions within vocal motor and sensory networks are recruited during various overt speech and song tasks, including: word or letter generation (Paus et al, 1993); syllable repetition (Riecker et al, 2005); singing a note repeatedly (Perry et al, 1999), in a sustained fashion (Zarate and Zatorre, 2008), or while changing vowels in particular rhythms (Jungblut et al, 2012); repeating syllables, spoken words, and sung or hummed melodies (Özdemir et al, 2006); humming, speaking, or singing lyrics of a well-known song (Formby et al, 1989; Jeffries et al, 2003); reciting the months of the year or singing a familiar melody (Riecker et al, 2000); telling a story (Schulz et al, 2005); improvising word phrases, melodies, or harmonies (Brown et al, 2004, 2006); spontaneous and synchronized speaking and singing (Saito et al, 2006); and singing an Italian aria (Kleber et al, 2007). Summarized from the neuroimaging evidence above, a general functional network for human vocalization (including speech and song) is comprised of the brain regions reviewed in the preceding sections: M1, ACC, basal ganglia, thalamus, and cerebellum for vocal motor control; S1 and S2 for somatosensory feedback processing; bilateral auditory cortical regions (primary auditory cortex and a pitch-sensitive region within Heschl's gyrus, various portions of STG and STS) for auditory feedback processing; and the insula presumably during multimodal processing of sensory feedback.…”

Section: Sensory-motor Control Of Vocalizationmentioning

confidence: 99%

The neural control of singing

Zarate¹

2013

Front. Hum. Neurosci.

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Singing provides a unique opportunity to examine music performance—the musical instrument is contained wholly within the body, thus eliminating the need for creating artificial instruments or tasks in neuroimaging experiments. Here, more than two decades of voice and singing research will be reviewed to give an overview of the sensory-motor control of the singing voice, starting from the vocal tract and leading up to the brain regions involved in singing. Additionally, to demonstrate how sensory feedback is integrated with vocal motor control, recent functional magnetic resonance imaging (fMRI) research on somatosensory and auditory feedback processing during singing will be presented. The relationship between the brain and singing behavior will be explored also by examining: (1) neuroplasticity as a function of various lengths and types of training, (2) vocal amusia due to a compromised singing network, and (3) singing performance in individuals with congenital amusia. Finally, the auditory-motor control network for singing will be considered alongside dual-stream models of auditory processing in music and speech to refine both these theoretical models and the singing network itself.

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“…Using functional magnetic resonance imaging (fMRI), researchers investigated (1) isolated voluntary tongue movements, such as tongue protrusion (Arima et al, 2011), horizontal tongue movements (Riecker et al, 2000), and tongue elevation (Martin et al, 2004), and (2) tongue movements as part of speaking (Riecker et al, 2005;Sörös et al, 2006), singing (Jungblut et al, 2012;Ozdemir et al, 2006), and swallowing (Sörös et al, 2009;Lowell et al, 2012). A detailed comparison of the neural correlates of different tongue movements in all three directions has not been performed yet (but see the study by Watanabe et al (2004), comparing tongue protrusions in different directions with tongue retraction).…”

Section: Introductionmentioning

confidence: 99%

Model-based and model-free analyses of the neural correlates of tongue movements

Sörös

Schäfer

Witt

2019

Preprint

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The tongue performs movements in all directions to subserve its diverse functions in chewing, swallowing, and speech production. The aims of the present study were twofold: using task-based functional MRI in a group of 17 healthy young participants, we studied (1) potential differences in the cerebral control of frontal, horizontal, and vertical tongue movements and (2) potential inter-individual differences in tongue motor control. To investigate differences between different tongue movements, we performed voxel-wise multiple linear regressions. To investigate inter-individual differences, we applied a novel approach, spatio-temporal filtering of independent components. For this approach, individual functional data sets were decomposed into spatially independent components and corresponding time courses using ICA. A temporal filter (correlation with the expected brain response) was used to identify independent components time-locked to the tongue motor task. A spatial filter (cross-correlation with established neurofunctional systems) was used to identify brain activity not time-locked to the task. Our results confirm the importance of an extended bilateral cortical and subcortical network for the control of tongue movements, including the lateral primary sensorimotor cortex, supplementary motor cortex, anterior cingulate gyrus, insula, basal ganglia, thalamus, and cerebellum. Frontal tongue movements, highly overlearned movements related to speech production, showed less activity in parts of the frontal and parietal lobes compared to horizontal and vertical movements and greater activity in parts of the left frontal and temporal lobes compared to vertical movements. The investigation of inter-individual differences revealed a component representing the tongue primary sensorimotor cortex time-locked to the task in all participants. Using the spatial filter, we found the default mode network in 16 of 17 participants, the left fronto-parietal network in 16, the right fronto-parietal network in 8, and the executive control network in 4 participants. Further detailed analyses of speech-related tongue movements are warranted to increase our understanding of tongue motor control as a crucial part of articulation. Spatio-temporal filtering of independent components appears to be a powerful approach to study inter-individual differences in task-based functional MRI. This approach may be particularly useful for the assessment of individual patients and may be related to individual clinical, behavioral, and genetic information.

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The impact of rhythm complexity on brain activation during simple singing: An event-related fMRI study

Cited by 20 publications

References 99 publications

Training-mediated leftward asymmetries during music processing: A cross-sectional and longitudinal fMRI analysis

Training-mediated leftward asymmetries during music processing: A cross-sectional and longitudinal fMRI analysis

The neural control of singing

Model-based and model-free analyses of the neural correlates of tongue movements

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