Authors :
Presenting Author: Derek Doss, BE – Vanderbilt University
Graham Johnson, PhD – Vanderbilt University; Aarushi Negi, BS – Vanderbilt University; Jared Shless, BS – Vanderbilt University Medical Center; Danika Paulo, MD – Vanderbilt University Medical Center; Abhijeet Gummadavelli, MD – Vanderbilt University Medical Center; Shawniqua Williams Roberson, MD – Vanderbilt University Medical Center; Kevin Haas, MD – Vanderbilt University Medical Center; Sarah Bick, MD – Vanderbilt University Medical Center; Catie Chang, PhD – Vanderbilt University; Victoria Morgan, PhD – Vanderbilt University; Dario Englot, MD, PhD – Vanderbilt University Medical Center
Rationale:
Seizures can drastically impact patients’ lives but the loss of consciousness in focal impaired awareness seizures (FIAS) and focal to bilateral tonic clonic (FBTC) seizures can be particularly devastating. Surgical neurostimulation therapy has been effective in medically refractory focal epilepsy and, as proposed in a recent clinical trial, it may be possible for neurostimulation to help preserve consciousness. However, it is uncertain what networks should be targeted and it is unclear if FIAS and FBTC seizures share similar mechanisms for loss of consciousness. In this work, we seek to analyze network changes in focal aware seizures (FAS), FIAS, and FBTC seizures to identify network changes associated with loss of consciousness.
Methods:
Stereotactic electroencephalography (SEEG) recordings of 79 patients with continuous video monitoring from the Vanderbilt University Epilepsy Monitoring Unit were obtained. For each patient, all FAS, FIAS, and FBTC seizures were analyzed with a five minute resting state recording acting as a baseline. Seizure types were designated through behavioral changes observed on video monitoring, resulting in 192 FAS,170 FIAS, and 104 FBTC seizures. Bandpower and network segregation was computed for the delta (1-4Hz) and gamma (31-80Hz) frequency bands between all bipolar pairs. The data was then parcellated into frontoparietal association cortex (FPAC), mesial temporal lobe, and lateral temporal lobe. All regions were split into ipsilateral and contralateral to seizure onset. The segregation for all seizures were z-scored to the patient’s resting state.
Results:
Both FIAS and FBTC seizures exhibited significantly increased bandpower than FAS in the ipsilateral FPAC (one way ANOVA with post-hoc multcompare, p=1.05e-5), likely representing slow delta waves associated with loss of consciousness (
Fig. 1A-B). FBTC seizures exhibited significantly increased gamma bandpower than both FAS and FIAS in the ipsilateral FPAC (
Fig 1C-D, p=1.04e-6). Network segregation was significantly increased in the ipsilateral FPAC delta band for FBTC seizures alone (
Fig 2A-B, p=0.039). However, segregation in the gamma band was significantly decreased in FIAS (
Fig 2C-D, p=0.002), suggesting more homogeneity in cortical areas during FIAS, like that seen in sleep states.
Conclusions:
Loss of consciousness in FIAS and FBTC seizures can greatly affect the lives of those with medically refractory focal epilepsy. Surgical therapies have the possibility to reduce the loss of consciousness through modulation of the networks involved with loss of consciousness, but the stimulation targets are difficult to identify. Network approaches may aid in identifying these targets and this work is the first, to our knowledge, to analyze network differences in FAS, FIAS, and FBTC seizures. We demonstrate that FIAS share properties with both FAS and FBTC seizures, but network segregation decreases are unique to FIAS. These results may be used to guide future neuromodulation therapy to prevent the loss of consciousness in FIAS and FBTC seizures.
Funding:
This work was funded by NIH grants T32EB021937, T32GM007347, F31NS120401, R01NS112252.