fMRI reveals two distinct cerebral networks subserving speech motor control

Riecker, Axel; Mathiak, Klaus; Wildgruber, Dirk; Erb, Michael; Hertrich, Ingo; Grodd, Wolfgang; Ackermann, Hermann

doi:10.1212/01.wnl.0000152156.90779.89

Cited by 294 publications

(217 citation statements)

References 37 publications

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“…It is such an important factor that diadochokinetic rate (where a subject is asked to produce syllables as rapidly as possible) is almost universally used to evaluate oral motor skill and differentially diagnose pathology. Furthermore, speech rate represents a target for therapy in dysarthria (17), has been studied in normal populations with neuroimaging (18)(19)(20), and has known neurological vulnerabilities in development, traumatic brain injury, and stroke. Fig.…”

Section: Resultsmentioning

confidence: 99%

Brain–computer interfaces increase whole-brain signal to noise

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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Brain-computer interfaces (BCIs) can convert mental states into signals to drive real-world devices, but it is not known if a given covert task is the same when performed with and without BCIbased control. Using a BCI likely involves additional cognitive processes, such as multitasking, attention, and conflict monitoring. In addition, it is challenging to measure the quality of covert task performance. We used whole-brain classifier-based real-time functional MRI to address these issues, because the method provides both classifier-based maps to examine the neural requirements of BCI and classification accuracy to quantify the quality of task performance. Subjects performed a covert counting task at fast and slow rates to control a visual interface. Compared with the same task when viewing but not controlling the interface, we observed that being in control of a BCI improved task classification of fast and slow counting states. Additional BCI control increased subjects' whole-brain signal-to-noise ratio compared with the absence of control. The neural pattern for control consisted of a positive network comprised of dorsal parietal and frontal regions and the anterior insula of the right hemisphere as well as an expansive negative network of regions. These findings suggest that real-time functional MRI can serve as a platform for exploring information processing and frontoparietal and insula network-based regulation of whole-brain task signal-to-noise ratio. A lthough overt actions allow us to interact directly with our environment, much of our brain's activity is devoted to covert acts, such as motor planning, rehearsal, and self-directed thought. Indeed, we enjoy a rich inner experience consisting of activities such as visual imagery, inner language, somatosensory awareness, recollection of the past, and planning for the future (1). By definition, covert actions are usually neither observable by a third party nor capable of directly affecting the outside world. Brain-computer interfaces (BCIs), however, provide a technological means for converting thought into action by transducing brain measurements into control signals for devices, such as robots and computer displays. One strategy for BCI control is to provide the subject with task commands, such as "move the cursor to the right by imagining that you are moving your right hand."In effect, BCI control creates a synthetic link between covert action and the role of sensory feedback. The additional cognitive requirements and consequences for BCI control, however, are unknown, and several interrelated cognitive processes could play a role. Examples include multitasking for dual task performance (2-5), conflict and outcome monitoring (6, 7), attention (8), reward monitoring (9, 10), and learning and conditioning (11,12). If present, each of these cognitive processes should have specific neural signatures (prefrontal cortex, anterior cingulate, frontoparietal networks, ventral striatum, etc.).An additional consideration is the performance of the task itself. Evaluat...

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Section: Resultsmentioning

confidence: 99%

Brain–computer interfaces increase whole-brain signal to noise

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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“…1). The first ROI expected to activate during articulation was the middle portion of the primary sensorimotor cortex (Paus et al, 1996;Indefrey and Levelt, 2000;Lotze et al, 2000;Riecker et al, 2000;Shuster and Lemieux, 2005;Riecker et al, 2005). This ROI included the right and left pre-and postcentral gyri, extending from z = 20 mm to 60 mm.…”

Section: Resultsmentioning

confidence: 99%

“…This ROI included the right and left pre-and postcentral gyri, extending from z = 20 mm to 60 mm. The second ROI expected to activate was the SMA (Paus et al, 1996;Indefrey and Levelt, 2000;Lotze et al, 2000;Riecker et al, 2000;Riecker et al, 2005). This ROI was drawn from the brain vertex, superiorly, to the cingulate sulcus, inferiorly, from y = 1 mm to y = −24 mm, and from x = −16 mm to x = 16 mm (Chainay et al, 2004).…”

Section: Resultsmentioning

confidence: 99%

“…This ROI was drawn from the brain vertex, superiorly, to the cingulate sulcus, inferiorly, from y = 1 mm to y = −24 mm, and from x = −16 mm to x = 16 mm (Chainay et al, 2004). The third ROI expected to activate was the left insula (Wise et al, 1999;Riecker et al, 2000;Shuster and Lemieux, 2005;Ackermann and Riecker, 2004;Riecker et al, 2005). This ROI was drawn around the gray matter region bounded by the temporal lobe and frontal lobe, extending from z = −6 mm to z = 21 mm.…”

Section: Resultsmentioning

confidence: 99%

“…There is much interest in conducting fMRI studies to examine the neurological control for the articulation of speech (Lotze et al, 2000;Riecker et al, 2000;Shuster and Lemieux, 2005;Riecker et al, 2005). Thus far, these experiments have relied on event-related designs and/or subject averaging to reduce the presence of false activation caused by task-correlated orofacial motion.…”

Section: Introductionmentioning

confidence: 99%

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High spatial resolution increases the specificity of block-design BOLD fMRI studies of overt vowel production

Soltysik

Hyde

2008

NeuroImage

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Functional MRI (fMRI) studies of tasks involving orofacial motion, such as speech, are prone to problems related to motion-induced magnetic field variations. Orofacial motion perturbs the static magnetic field, leading to signal changes that correlate with the task and corrupt activation maps with false positives or signal loss. These motion-induced signal changes represent a contraindication for the implementation of fMRI to study the neurophysiology of orofacial motion. An fMRI experiment of a structured, non-semantic vowel production task was performed using four different voxel volumes and three different slice orientations in an attempt to find a set of acquisition parameters leading to activation maps with maximum specificity. Results indicate that the use of small voxel volumes (2×2×3 mm 3 ) yielded a significantly higher percentage of true positive activation compared to the use of larger voxel volumes. Slice orientation did not have as great an impact as spatial resolution, although coronal slices appeared superior at high spatial resolutions. Furthermore, it was found that combining the strategy of high spatial resolution with an optimum task duration and postprocessing methods for separating true and false positives greatly improved the specificity of singlesubject, block-design fMRI studies of structured, overt vowel production.

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What Role does the Cerebellum Play in Language Processing?

Kellett

Stevenson

Gernsbacher

2012

The Handbook of the Neuropsychology of Language

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Beginning with Rolando and Flourens' early nineteenth-century documentation of the role of cerebellar lesions in disturbances of gait, posture, and voluntary coordi nation of movement, the cerebellum has been considered a primary player in motor behavior (Schmahmann, 1997). In 1922, Holmes was the first to document that focal cerebellar lesions produce speech motor de ficits, suggesting a role for the cerebellum in speech production (Holmes, 1922). However, only recently has inter est arisen in exploring the nonmotor roles the cerebellum might play in cognition, including language processing (Schmahmann, 1997).Neuroanatomically, it is plausible that the cerebellum plays a role in language processing, given the reciprocal loops that link the cerebellum directly to or near the vicinity oflanguage association regions in prefrontal cortex and temporal cortex. Output from the ventral dentate nucleus of the cerebellum projects to the ventro lateral nucleus of the thalamus and continues upward toward prefrontal regions (Leiner, Leiner, & Dow, 1986, 1991. Conversely, input to the cerebellum originates from the prefrontal cortex, as well as the upper bank of the temporal lobe's superior temporal sulcus, and traverses down through the pons and on to the lateral cerebel lar hemispheres (Schmahmann, 1991;Schmahmann & Pandya, 1997). These cerebro-cerebellar loops may allow the cerebellum to act as an "adjunct of the cer ebral cortex" (Leiner et al., 1986(Leiner et al., , p. 1006.In the late 1980s, Petersen, Fox, Posner, Mintun, and Raichle (1989) conducted a pioneering study using positron emission tomography (PET). Not only was their collection of PET data a technological advance, but also their use of a high-level baseline condition, to control for the cerebellum's participation in speech motorThe Handbook of the Neuropsychology o f Language, First Edition. Edited by Miriam Faust.

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fMRI reveals two distinct cerebral networks subserving speech motor control

Cited by 294 publications

References 37 publications

Brain–computer interfaces increase whole-brain signal to noise

Brain–computer interfaces increase whole-brain signal to noise

High spatial resolution increases the specificity of block-design BOLD fMRI studies of overt vowel production

What Role does the Cerebellum Play in Language Processing?

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