Anterior temporal lobectomy (ATL) is a highly sucessful treatment for eliminating seizures in patients with
temporal lobe epilepsy (TLE). However, ATL-induced memory decline is frequent and often severe, having a
deleterious impact on quality of life and functional outcomes. Stereotactic laser amygdalohippocampectomy
(SLAH) has been introduced as a minimally-invasive alternative that could minimize risk of memory
decline. However, it is unclear which patients would benefit the most from SLAH and whether SLAH
decreases risk for critical aspects of episodic memory decline compared to ATL. During the previous grant
funding period, we demonstrated the clinical value of combining information from structural (sMRI), diffusion-
weighted (dMRI), and functional (fMRI) imaging to better characterize the neural networks that underlie
preoperative language and memory impairment and (re)organization and in TLE. We propose that the same
multimodal imaging (MMI) approach can be used to quantify risk for postoperative memory decline. In this R01,
we extend our MMI approach, combining sMRI/dMRI/fMRI with intracranial recordings (iEEG), enabling us to
delve deep into the spatial and temporal dynamics of episodic memory networks in TLE. We employ multimodal
associative learning tasks with real-world implications (i.e., pairing a face with a name) that have not before been
studied in the surgical context. In addition, we draw from cognitive neurosicence models of hippocampal
functioning that may inform why many patients struggle to make fine-grain distinctions in memory (i.e., impaired
pattern separation), even when simple item memory appears intact. We propose that our MMI approach will
yield a more complete characterization of episodic memory networks in TLE, reveal patterns of structural and
functional reorganization in individual patients, and enable a personalized approach to risk assessment when
considering surgical options. Finally, we will track cognitive and imaging changes post-ATL and SLAH and identify
patient-specific factors that promote reorganization and improved cognitive outcomes. The goals of this
renewal are perfectly aligned with the 2020 NINDS Benchmarks for Epilepsy Research (Part IV), which
stress the critical need for reseach to limit or prevent adverse consequences of seizures and their
treatments across the lifespan. Our renewal directly addresses this request, striving to improve surgical
decision-making, which will have an immediate and sustained impact on patient care. Epilepsy is a common
neurological disease that costs the healthcare system approximately $15.5 billion annually and can negatively
impact quality of life, employment, and health status. The current project has strong implications for public health
because it strives to improve health outcomes in patients with epilepsy by using advanced, noninvasive
technology to identify individual predictors of memory decline that can help to guide surgical decisions and
possibly reduce morbidity associated with removal or ablation of eloquent brain regions.
