To avoid post-neurosurgical language deficits, intraoperative mapping of the language function in the brain can be complemented with preoperative mapping with functional magnetic resonance imaging. The validity of an fMRI “language localizer” paradigm crucially depends on the choice of an optimal language task and baseline condition. This study presents a new fMRI “language localizer” in Russian using overt sentence completion, a task that comprehensively engages the language function by involving both production and comprehension at the word and sentence level. The (...) paradigm was validated in 18 neurologically healthy volunteers who participated in two scanning sessions, for estimating test–retest reliability. For the first time, two baseline conditions for the sentence completion task were compared. At the group level, the paradigm significantly activated both anterior and posterior language-related regions. Individual-level analysis showed that activation was elicited most consistently in the inferior frontal regions, followed by posterior temporal regions and the angular gyrus. Test–retest reliability of activation location, as measured by Dice coefficients, was moderate and thus comparable to previous studies. Test–retest reliability was higher in the frontal than temporo-parietal region and with the most liberal statistical thresholding compared to two more conservative thresholding methods. Lateralization indices were expectedly left-hemispheric, with greater lateralization in the frontal than temporo-parietal region, and showed moderate test-retest reliability. Finally, the pseudoword baseline elicited more extensive and more reliable activation, although the syllable baseline appears more feasible for future clinical use. Overall, the study demonstrated the validity and reliability of the sentence completion task for mapping the language function in the brain. The paradigm needs further validation in a clinical sample of neurosurgical patients. Additionally, the study contributes to general evidence on test–retest reliability of fMRI. (shrink)

ABSTRACT Discourse Diversity Database (3D) is a corpus designed for clinical linguistics research. It consists of oral speech samples of three different genres: picture-elicited narratives, personal stories, and picture-based instructions. The sub-sections of 3D include recordings by Russian speakers from three independent groups: people with brain tumors before and after tumor removal, people with schizophrenia, and neurologically healthy individuals. This article is devoted to the description of the data collection, the annotation scheme, and the specific characteristics of each sub-section of (...) the corpus. (shrink)

High-frequency oscillations (HFO) are a promising biomarker for the identification of epileptogenic tissue. While HFO rates have been shown to predict seizure outcome, it is not yet clear whether their morphological features might improve this prediction. We validated HFO rates against seizure outcome and delineated the distribution of HFO morphological features. We collected stereo-EEG recordings from 20 patients (231 electrodes; 1,943 contacts). We computed HFO rates (the co-occurrence of ripples and fast ripples) through a validated automated detector during non-rapid eye (...) movement sleep. Applying machine learning, we delineated HFO morphological features within and outside epileptogenic tissue across mesial temporal lobe (MTL) and Neocortex. HFO rates predicted seizure outcome with 85% accuracy, 79% specificity, 100% sensitivity, 100% negative predictive value, and 67% positive predictive value. The analysis of HFO features showed larger amplitude in the epileptogenic tissue, similar morphology for epileptogenic HFO in MTL and Neocortex, and larger amplitude for physiological HFO in MTL. We confirmed HFO rates as a reliable biomarker for epilepsy surgery and characterized the potential clinical relevance of HFO morphological features. Our results support the prospective use of HFO in epilepsy surgery and contribute to the anatomical mapping of HFO morphology. (shrink)

RESUMO O Discourse Diversity Database (3D) é um corpus desenvolvido para a pesquisa em linguística clínica. Ele consiste de amostras de fala oral de três gêneros diferentes: narrativas induzidas por imagens, histórias pessoais e instruções baseadas em imagens. As subdivisões do 3D incluem gravações de falantes de russo de três grupos independentes: pessoas com tumores cerebrais antes e depois da remoção do tumor, pessoas com esquizofrenia e indivíduos neurologicamente saudáveis. O presente artigo é dedicado à descrição do procedimento de coleta (...) de dados, do esquema de anotação e das características específicas de cada subdivisão do corpus. (shrink)