Intraoperative hippocampal electrocorticography frequently captures electrographic seizures and correlates with hippocampal pathology

Intraoperative electrocorticography during laser-interstitial thermal therapy predicts seizure outcome in mesial temporal lobe epilepsy

OBJECTIVE

Magnetic resonance-guided laser interstitial thermal therapy (MRLiTT) for treating temporal lobe epilepsy has recently gained popularity. We aimed to investigate the predictive value of pre-and post-MRLiTT epileptiform discharges (EDs) on intraoperative electrocorticography (iECoG) in seizure outcomes for patients with mesial temporal lobe epilepsy (mTLE).

METHODS

We conducted a pilot, prospective single-center cohort study on seven consecutive patients with mTLE that underwent MRLiTT. Pre- and post-MRLiTT iECoG was performed using a 1x8 contact depth electrode along the same trajectory used for the laser catheter.

RESULTS

The responders had a robust reduction in ED frequency compared to pre-MRLiTT iECoG (86% vs 13%, p < 0.01). Clinical characteristics, including risk factors for epilepsy, duration of epilepsy, presence of mesial temporal lobe sclerosis, prior intracranial monitoring, the absolute frequency of pre- or post-MRLiTT EDs, and ablation volume were not significantly associated with responder status.

CONCLUSIONS

This is the first demonstration that intraoperative reduction in EDs during mesial temporal lobe MRLiTT may potentially predict seizure outcomes and may serve as an intraoperative biomarker for satisfactory ablation. However, larger prospective studies are needed to confirm our findings and evaluate the utility of iECoG during MRLiTT.

SIGNIFICANCE

iECoG during mesial temporal lobe MRLiTT may help assess seizure outcomes.

Predictive accuracy of CNN for cortical oscillatory activity in an acute rat model of parkinsonism

In neurological and neuropsychiatric disorders neuronal oscillatory activity between basal ganglia and cortical circuits are altered, which may be useful as biomarker for adaptive deep brain stimulation. We investigated whether changes in the spectral power of oscillatory activity in the motor cortex (MCtx) and the sensorimotor cortex (SMCtx) of rats after injection of the dopamine (DA) receptor antagonist haloperidol (HALO) would be similar to those observed in Parkinson disease. Thereafter, we tested whether a convolutional neural network (CNN) model would identify brain signal alterations in this acute model of parkinsonism. A sixteen channel surface micro-electrocorticogram (ECoG) recording array was placed under the dura above the MCtx and SMCtx areas of one hemisphere under general anaesthesia in rats. Seven days after surgery, micro ECoG was recorded in individual free moving rats in three conditions: (1) basal activity, (2) after injection of HALO (0.5 mg/kg), and (3) with additional injection of apomorphine (APO) (1 mg/kg). Furthermore, a CNN-based classification consisting of 23,530 parameters was applied on the raw data. HALO injection decreased oscillatory theta band activity (4-8 Hz) and enhanced beta (12-30 Hz) and gamma (30-100 Hz) in MCtx and SMCtx, which was compensated after APO injection (P ¡ 0.001). Evaluation of classification performance of the CNN model provided accuracy of 92%, sensitivity of 90% and specificity of 93% on one-dimensional signals. The CNN proposed model requires a minimum of sensory hardware and may be integrated into future research on therapeutic devices for Parkinson disease, such as adaptive closed loop stimulation, thus contributing to more efficient way of treatment.