학술논문

Automatic identification of successful memory encoding in stereo-eeg of refractory, mesial temporal lobe epilepsy
Document Type
Conference
Source
2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) Biomedical Imaging (ISBI 2017), 2017 IEEE 14th International Symposium on. :587-590 Apr, 2017
Subject
Bioengineering
Encoding
Probes
Hippocampus
Phase measurement
Image edge detection
Epilepsy
stereo EEG
phase synchrony
classification
Language
ISSN
1945-8452
Abstract
Surgical resection of portions of the temporal lobe is the standard of care for patients with refractory mesial temporal lobe epilepsy. While this reduces seizures, it often results in an inability to form new memories, which leads to difficulties in social situations, learning, and suboptimal quality of life. Learning about the success or failure to form new memory in such patients is critical if we are to generate neuromodulation-based therapies. To this end, we tackle the many challenges in analyzing memory formation when their brains are recorded using stereoencephalography (sEEG) in a Free Recall task. Our contributions are threefold. First, we compute a rich measure of brain connectivity by computing the phase locking value statistic (synchrony) between pairs of regions, over hundreds of word memorization trials. Second, we leverage the rich information (over 400 values per pair of probed brain regions) to form consistent length feature vectors for classifier training. Third, we train and evaluate seven different types of classifier models and identify which ones achieve the highest accuracy and which brain features are most important for high accuracy. We assess our approach on data from 37 patients pre-resection surgery. We achieve up to 73% accuracy distinguishing successful from unsuccessful memory formation in the human brain from just 1.6 sec epochs of sEEG data.