MAPPING LANGUAGE FUNCTION AND PREDICTING CORTICAL STIMULATION RESULTS WITH INTRACRANIAL ELECTROENCEPHALOGRAPHY
Crone, Nathan E
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To avoid post-operative language impairments after surgery for drug-resistant epilepsy, clinicians rely primarily on electrocortical stimulation mapping (ESM), but this can trigger afterdischarges, clinical seizures, or cause uncomfortable sensations. Moreover, ESM can be time-consuming and the results are usually all-or-none, complicating their interpretation. These practical limitations have long motivated spatial-temporal analysis of passive intracranial electroencephalographic (iEEG) recordings as an alternative or complementary technique that can map cortical function at all sites simultaneously, resulting in significant time savings without adverse side-effects. However, there has not yet been widespread clinical adoption of passive iEEG for pre-operative language mapping, largely because of a failure to realize the potential advantages of iEEG over ESM and other methods for language mapping. The overall goals of this dissertation were to improve and validate passive iEEG as a method for mapping human language function prior to surgical resection for epilepsy and other brain disorders. This was accomplished through three separate aims. First, a spatial-temporal functional mapping (STFM) system was developed and tested for online passive iEEG mapping, providing immediate mapping feedback to both clinicians and researchers. The system output was compared to ESM and to canonical regions of interest in the human language network. In the second aim, the STFM system was used to study the fine temporal dynamics by which Broca’s area is activated and interacts with other areas of language network during a sentence completion task. This study showed that Broca’s area plays a pivotal role in the coordination of language networks responsible for lexical selection. Finally, the third aim sought to reconcile inconsistencies between the results of STFM and ESM. Agreement between these methods has not been as good for language mapping as it has been for motor mapping, which may be due to propagation of ESM effects to cortical areas connected to the site of stimulation. We used cortico-cortical evoked potentials to estimate the effective connectivity of stimulation sites to other sites in the language network. We found that this method improved the accuracy of STFM in predicting ESM results and helped explain similarities and differences between STFM and ESM language maps.