Task-based functional magnetic resonance imaging prediction of postsurgical cognitive outcomes in temporal lobe epilepsy: A systematic review, meta-analysis, and new data.

Task-based functional magnetic resonance imaging (tfMRI) has developed as a common alternative in epilepsy surgery to the intracarotid amobarbital procedure, also known as the Wada procedure. Prior studies have implicated tfMRI as a comparable predictor of postsurgical cognitive outcomes. However, the predictive validity of tfMRI has not been established. This preregistered systematic review and meta-analysis (CRD42020183563) synthesizes the literature predicting postsurgical cognitive outcomes in temporal lobe epilepsy (TLE) using tfMRI. The PubMed and PsycINFO literature databases were queried for English-language articles published between January 1, 2009 and December 31, 2020 associating tfMRI laterality indices or symmetry of task activation with outcomes in TLE. Their references were reviewed for additional relevant literature, and unpublished data from our center were incorporated. Nineteen studies were included in the meta-analysis. tfMRI studies predicted postsurgical cognitive outcomes in left TLE

Multiple-brain systems dynamically interact during tonic and phasic states to support language integrity in temporal lobe epilepsy

An epileptogenic focus in the dominant temporal lobe can result in the reorganization of language systems in order to compensate for compromised functions. We studied the compensatory reorganization of language in the setting of left temporal lobe epilepsy (TLE), taking into account the interaction of language (L) with key non-language (NL) networks such as dorsal attention (DAN), fronto-parietal (FPN) and cingulo-opercular (COpN), with these systems providing cognitive resources helpful for successful language performance. We applied tools from dynamic network neuroscience to functional MRI data collected from 23 TLE patients and 23 matched healthy controls during the resting state (RS) and a sentence completion (SC) task to capture how the functional architecture of a language network dynamically changes and interacts with NL systems in these two contexts. We provided evidence that the brain areas in which core language functions reside dynamically interact with non-language functional networks to carry out linguistic functions. We demonstrated that abnormal integrations between the language and DAN existed in TLE, and were present both in tonic as well as phasic states. This integration was considered to reflect the entrainment of visual attention systems to the systems dedicated to lexical semantic processing. Our data made clear that the level of baseline integrations between the language subsystems and certain NL systems (e.g., DAN, FPN) had a crucial influence on the general level of task integrations between L/NL systems, with this a normative finding not unique to epilepsy. We also revealed that a broad set of task L/NL integrations in TLE are predictive of language competency, indicating that these integrations are compensatory for patients with lower overall language skills. We concluded that RS establishes the broad set of L/NL integrations available and primed for use during task, but that the actual use of those interactions in the setting of TLE depended on the level of language skill. We believe our analyses are the first to capture the potential compensatory role played by dynamic network reconfigurations between multiple brain systems during performance of a complex language task, in addition to testing for characteristics in both the phasic/task and tonic/resting state that are necessary to achieve language competency in the setting of temporal lobe pathology. Our analyses highlighted the intra- versus inter-system communications that form the basis of unique language processing in TLE, pointing to the dynamic reconfigurations that provided the broad multi-system support needed to maintain language skill and competency