Core language brain network for fMRI language task used in clinical applications
| Autor: | Gino Del Ferraro, Luca Pasquini, Qiongge Li, Andrei I. Holodny, Kyung K. Peck, Hernán A. Makse |
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| Rok vydání: | 2020 |
| Předmět: |
Functional language networks
Computer science Presurgical langugage mapping Task-based fMRI lcsh:RC321-571 Task (project management) 03 medical and health sciences 0302 clinical medicine Artificial Intelligence medicine Healthy controls k-core Control (linguistics) lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry Research Articles 030304 developmental biology Brain network Cognitive science 0303 health sciences Functional programming medicine.diagnostic_test Applied Mathematics General Neuroscience Cognition Computer Science Applications Graph theory Identification (information) Functional magnetic resonance imaging Centrality 030217 neurology & neurosurgery |
| Zdroj: | Network Neuroscience, Vol 4, Iss 1, Pp 134-154 (2020) Network Neuroscience |
| ISSN: | 2472-1751 |
| DOI: | 10.1162/netn_a_00112 |
| Popis: | Functional magnetic resonance imaging (fMRI) is widely used in clinical applications to highlight brain areas involved in specific cognitive processes. Brain impairments, such as tumors, suppress the fMRI activation of the anatomical areas they invade and, thus, brain-damaged functional networks present missing links/areas of activation. The identification of the missing circuitry components is of crucial importance to estimate the damage extent. The study of functional networks associated with clinical tasks but performed by healthy individuals becomes, therefore, of paramount concern. These “healthy” networks can, indeed, be used as control networks for clinical studies. In this work we investigate the functional architecture of 20 healthy individuals performing a language task designed for clinical purposes. We unveil a common architecture persistent across all subjects under study, that we call “core” network, which involves Broca’s area, Wernicke’s area, the premotor area, and the pre-supplementary motor area. We study the connectivity of this circuitry by using the k-core centrality measure, and we find that three of these areas belong to the most robust structure of the functional language network for the specific task under study. Our results provide useful insights on primarily important functional connections. Author Summary Neurosurgeons employ language fMRI to localize important language areas for patients with brain impairment. Yet, brain pathologies (e.g., brain tumors, strokes, epilepsy) affect functional connectivity by disrupting functional links and suppressing the activation of brain areas. Thus, although clinical tasks are designed to guarantee robust activation, the functional connectivity of patients with brain pathologies is ultimately damaged by brain impairments. To better quantify the damage produced by the brain pathology on the functional connectivity, it is paramount to have, as a benchmark, functional networks of healthy individuals who perform a task for clinical cases. Our findings identify a group of functional regions of interest linked together in a functional circuitry that have a decisive role for the language task used in clinical applications. |
| Databáze: | OpenAIRE |
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