Robust localization of the contralateral precentral gyrus in hemiparetic patients using the unimpaired ipsilateral hand: a clinical functional magnetic resonance imaging protocol

Stippich, Christoph; Kapfer, Daniel; Hempel, E.; Borgulya, Gábor; Bongers, André; Heiland, Sabine; Sartor, Klaus

doi:10.1016/s0304-3940(00)01045-4

Cited by 39 publications

(16 citation statements)

References 13 publications

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“…Studies involving simple motor tasks did not find SMA activations, but activity focused in the primary motor cortex (Porro et al, 1996). Generally, more complex or new tasks lead to a stronger activation and recruitment of more widespread motor areas at least at initiation of training (Stippich et al, 2000). This may suggest that the differences between high and low aptitude users are caused by the novelity of the imagined movement and the corresponding activation of the SMA.…”

Section: The Role Of Smamentioning

confidence: 97%

Neural mechanisms of brain–computer interface control

et al. 2011

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Section: The Role Of Smamentioning

confidence: 97%

Neural mechanisms of brain–computer interface control

et al. 2011

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“…Baraldi et al (1999) found support for the participation of two separate neural populations in each hemisphere, one in M1 and one in PM1: the first being activated during contralateral finger movements only, whereas the second exhibited signal changes during movements of either hand, indicating that unimanual movements are accompanied by cortical activity in both hemispheres. Compared to paced movements, self-paced rhythmic finger movements generally recruit more and larger neuronal populations that typically include (bilateral) SMA (Halsband et al 1993;Freund 1996;Kaiser et al 2000; and (ipsilateral) PM1 (Stippich et al 2000), especially during difficult tasks (Mayville et al 2002). In addition, several research groups found unilateral cortical activation during discrete and (symmetrical) bihemispheric activation during sequential unimanual motor behaviors (Cheyne and Weinberg 1989;Pulvermüller et al 1995;Manganotti et al 1998;Andrew and Pfurtscheller 1999;Babiloni et al 1999;Pfurtscheller et al 2000), indicating the presence of an active (time-varying) cross-talk between bilateral and mesial central and prefrontal regions.…”

Section: Introductionmentioning

confidence: 99%

Stabilization of bimanual coordination due to active interhemispheric inhibition: a dynamical account

2005

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Abstract. Based on recent brain-imaging data and congruent theoretical insights, a dynamical model is derived to account for the patterns of brain activity observed during stable performance of bimanual multifrequency patterns, as well as during behavioral instabilities in the form of phase transitions between such patterns. The model incorporates four dynamical processes, defined over both motor and premotor cortices, which are coupled through inhibitory and excitatory inter-and intrahemispheric connections. In particular, the model underscores the crucial role of interhemispheric inhibition in reducing the interference between disparate frequencies during stable performance, as well as the failure of this reduction during behavioral transitions. As an aside, the model also accounts for in-and antiphase preferences during isofrequency movements. The viability of the proposed model is illustrated by magnetoencephalographic signals that were recorded from an experienced subject performing a polyrhythmic tapping task that was designed to induce transitions between multifrequency patterns. Consistent with the model's dynamics, contra-and ipsilateral cortical areas of activation were frequency-and phase-locked, while their activation strength changed markedly in the vicinity of transitions in coordination.

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“…The threshold value needed to visualize the activation must be set before the measurement begins and cannot be changed after the measurement is made. The BOLD-contrast signal change of the activated cortex area is strongly dependent on the patient [11][12][13] ; for this reason the activation maps of t-tests with a fixed threshold value are poorly suited to interface with the brain activity of different people. This can mean that allocation of functional activation to anatomical structures is made harder or impossible through large activation clusters flowing together, or that relevant activation is not even depicted.…”

Section: Comparison With Other Evaluation Tools and Methodsmentioning

confidence: 99%

Functional Magnetic Resonance Imaging for Cranial Neuronavigation: Methods for Automated and Standardized Data Processing and Management

et al. 2007

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Preoperative fMRI is one of the best established clinical fMRI applications. Due to the difficulties in recording and coregistration of functional image data, we present methods to standardize and automate these procedures. We used a self-made interactive software package (AFI - Automated Functional Imaging) to automate the time consuming and complex analysis of fMRI data. AFI controls the BrainVoyager program, a postprocessing software package, and furthermore facilitates data management, anonymization of patient data, storage, documentation, data export to neuronavigation systems and the opportunity of spatial transformation of image data for use in group studies. By the end of 2006 we have used this method on 123 patients with brain tumors and 47 patients with trigeminal neuralgia. The fundamental basis of multimodal neuronavigation is precise coregistration. EPI images contain spatial distortions of 5-15 mm. We were able to reduce the misregistration of EPI and FLASH images in a selectable region of interest to 1-2 mm. Furthermore AFI reduces the average evaluation time for a standard clinical fMRI study (four functional measurements, one anatomical data set) by approx. 50% from 140 minutes to about 70 minutes in comparison to manual evaluation by an expert. More importantly, the personal attendance time required for the evaluation decreases by 84% to 23 minutes as the remainder of the program runs automatically. In comparison to currently available online postprocessing software tools which are more limited in use, BrainVoyager can be used for coregistration, data export to neuronavigation systems and spatial transformation.

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Robust localization of the contralateral precentral gyrus in hemiparetic patients using the unimpaired ipsilateral hand: a clinical functional magnetic resonance imaging protocol

Cited by 39 publications

References 13 publications

Neural mechanisms of brain–computer interface control

Neural mechanisms of brain–computer interface control

Stabilization of bimanual coordination due to active interhemispheric inhibition: a dynamical account

Functional Magnetic Resonance Imaging for Cranial Neuronavigation: Methods for Automated and Standardized Data Processing and Management

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