Neuroimaging correlates of language network impairment and reorganization in temporal lobe epilepsy
| Autor: | George Lin, Brianna M. Paul, Carrie R. McDonald, S. Balter, Kelly M. Leyden |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Adult
Male Linguistics and Language Cognitive Neuroscience Neuroimaging Experimental and Cognitive Psychology Article 050105 experimental psychology Language and Linguistics Temporal lobe 03 medical and health sciences Speech and Hearing Epilepsy 0302 clinical medicine medicine Humans 0501 psychology and cognitive sciences In patient Language Brain Mapping Language Disorders medicine.diagnostic_test 05 social sciences Brain medicine.disease Magnetic Resonance Imaging Diffusion Tensor Imaging Epilepsy Temporal Lobe Epilepsy syndromes Female Nerve Net Psychology Functional magnetic resonance imaging Neuroscience 030217 neurology & neurosurgery Language network Diffusion MRI |
| Zdroj: | Brain Lang |
| ISSN: | 0093-934X |
| DOI: | 10.1016/j.bandl.2016.06.002 |
| Popis: | Advanced, noninvasive imaging has revolutionized our understanding of language networks in the brain and is reshaping our approach to the presurgical evaluation of patients with epilepsy. Functional magnetic resonance imaging (fMRI) has had the greatest impact, unveiling the complexity of language organization and reorganization in patients with epilepsy both pre- and postoperatively, while volumetric MRI and diffusion tensor imaging have led to a greater appreciation of structural and microstructural correlates of language dysfunction in different epilepsy syndromes. In this article, we review recent literature describing how unimodal and multimodal imaging has advanced our knowledge of language networks and their plasticity in epilepsy, with a focus on the most frequently studied epilepsy syndrome in adults, temporal lobe epilepsy (TLE). We also describe how new analytic techniques (i.e., graph theory) are leading to a refined characterization of abnormal brain connectivity, and how subject-specific imaging profiles combined with clinical data may enhance the prediction of both seizure and language outcomes following surgical interventions. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect