Publications by authors named "Leonardo Arrano-Carrasco"

Article Synopsis
  • Functional MRI (fMRI) is often used to assess language function but can be inaccurate in patients with brain tumors due to cognitive issues and movement artifacts; gray matter volume (GMV) analysis offers a more stable alternative.
  • This study analyzed MRI data from 22 healthy subjects and 28 patients with left-hemisphere tumors, exploring the link between GMV in language-specific brain regions and results from fMRI language lateralization tasks.
  • Findings indicate that GMV in relevant brain areas is a strong predictor of language lateralization, with predictions achieving accuracy rates from 78% to 94%, suggesting that GMV analysis can enhance preoperative assessments for language function in complex cases.
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Background: The crossed cerebro-cerebellar (CCC) activation facilitates the diagnosis of cortical language lateralization, but needs to be explored with language tasks suitable for patients with different age ranges, educational attainment and eventual presence of language deficits.

Aim: To determine the effect of demographic variables in the performance of three language tasks in healthy volunteers and to determine the CCC activation of these tasks as a functional magnetic resonance imaging (fMRI) paradigm in brain tumor patients.

Material And Methods: The behavioral performance (correct responses and reaction time) of three language tasks (verbal fluency, semantic and phonological decision tasks) was first examined in 76 healthy volunteers balanced by age and educational level.

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Objectives: Crossed cerebro-cerebellar BOLD activations have recently come to light as additional diagnostic features for patients with brain tumors. The covert verb generation (VG) task is a widely used language paradigm to determine these language-related crossed activations. Here we demonstrate these crossed activations in two additional language paradigms, the semantic and phonological association tasks.

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