Robust compression and detection of epileptiform patterns in ECoG using a real-time spiking neural network hardware framework.

Interictal Epileptiform Discharges (IED) and High Frequency Oscillations (HFO) in intraoperative electrocorticography (ECoG) may guide the surgeon by delineating the epileptogenic zone. We designed a modular spiking neural network (SNN) in a mixed-signal neuromorphic device to process the ECoG in real-time. We exploit the variability of the inhomogeneous silicon neurons to achieve efficient sparse and decorrelated temporal signal encoding. We interface the full-custom SNN device to the BCI2000 real-time framework and configure the setup to detect HFO and IED co-occurring with HFO (IED-HFO). We validate the setup on pre-recorded data and obtain HFO rates that are concordant with a previously validated offline algorithm (Spearman's ρ = 0.75, p = 1e-4), achieving the same postsurgical seizure freedom predictions for all patients. In a remote on-line analysis, intraoperative ECoG recorded in Utrecht was compressed and transferred to Zurich for SNN processing and successful IED-HFO detection in real-time. These results further demonstrate how automated remote real-time detection may enable the use of HFO in clinical practice.

Spatial and temporal properties of intra-operatively recorded spikes and high frequency oscillations in focal cortical dysplasia.

OBJECTIVE: Focal cortical dysplasias (FCD) are characterized by distinct interictal spike patterns and high frequency oscillations (HFOs; ripples: 80-250 Hz; fast ripples: 250-500 Hz) in the intra-operative electrocorticogram (ioECoG). We studied the temporal relation between intra-operative spikes and HFOs and their relation to resected tissue in people with FCD with a favorable outcome. METHODS: We included patients who underwent ioECoG-tailored epilepsy surgery with pathology confirmed FCD and long-term Engel 1A outcome. Spikes and HFOs were automatically detected and visually checked in 1-minute pre-resection-ioECoG. Channels covering resected and non-resected tissue were compared using a logistic mixed model, assessing event numbers, co-occurrence ratios, and time-based properties. RESULTS: We found pre-resection spikes, ripples in respectively 21 and 20 out of 22 patients. Channels covering resected tissue showed high numbers of spikes and HFOs, and high ratios of co-occurring events. Spikes, especially with ripples, have a relatively sharp rising flank with a long descending flank and early ripple onset over resected tissue. CONCLUSIONS: A combined analysis of event numbers, ratios, and temporal relationships between spikes and HFOs may aid identifying epileptic tissue in epilepsy surgery. SIGNIFICANCE: This study shows a promising method for clinically relevant properties of events, closely associated with FCD.

Spikes and High Frequency Oscillations in Lateral Neocortical Temporal Lobe Epilepsy: Can They Predict the Success Chance of Hippocampus-Sparing Resections?

Purpose: We investigated the distribution of spikes and HFOs recorded during intraoperative electrocorticography (ioECoG) and tried to elaborate a predictive model for postsurgical outcomes of patients with lateral neocortical temporal lobe epilepsy (TLE) whose mesiotemporal structures are left in situ. Methods: We selected patients with temporal lateral neocortical epilepsy focus who underwent ioECoG-tailored resections without amygdalo-hippocampectomies. We visually marked spikes, ripples (80-250 Hz), and fast ripples (FRs; 250-500 Hz) on neocortical and mesiotemporal channels before and after resections. We looked for differences in event rates and resection ratios between good (Engel 1A) and poor outcome groups and performed logistic regression analysis to identify outcome predictors. Results: Fourteen out of 24 included patients had a good outcome. The poor-outcome patients showed higher rates of ripples on neocortical channels distant from the resection in pre- and post-ioECoG than people with good outcomes (p pre = 0.04, p post = 0.05). Post-ioECoG FRs were found only in poor-outcome patients (N = 3). A prediction model based on regression analysis showed low rates of mesiotemporal post-ioECoG ripples (OR mesio = 0.13, p mesio = 0.04) and older age at epilepsy onset (OR = 1.76, p = 0.04) to be predictors of good seizure outcome. Conclusion: HFOs in ioECoG may help to inform the neurosurgeon of the hippocampus-sparing resection success chance in patients with lateral neocortical TLE.

The spatial relationship between the MRI lesion and intraoperative electrocorticography in focal epilepsy surgery.

MRI and intraoperative electrocorticography are often used in tandem to delineate epileptogenic tissue in resective surgery for focal epilepsy. Both the resection of the MRI lesion and tissue with high rates of electrographic discharges on electrocorticography, e.g. spikes and high-frequency oscillations (80-500 Hz), lead to a better surgical outcome. How MRI and electrographic markers are related, however, is currently unknown. The aim of this study was to find the spatial relationship between MRI lesions and spikes/high-frequency oscillations. We retrospectively included 33 paediatric and adult patients with lesional neocortical epilepsy who underwent electrocorticography-tailored surgery (14 females, median age = 13.4 years, range = 0.6-47.0 years). Mesiotemporal lesions were excluded. We used univariable linear regression to find correlations between pre-resection spike/high-frequency oscillation rates on an electrode and its distance to the MRI lesion. We tested straight lines to the centre and the edge of the MRI lesion, and the distance along the cortical surface to determine which of these distances best reflects the occurrence of spikes/high-frequency oscillations. We conducted a moderator analysis to investigate the influence of the underlying pathology type and lesion volume on our results. We found spike and high-frequency oscillation rates to be spatially linked to the edge of the MRI lesion. The underlying pathology type influenced the spatial relationship between spike/high-frequency oscillation rates and the MRI lesion (P spikes < 0.0001, P ripples < 0.0001), while the lesion volume did not (P spikes = 0.64, P ripples = 0.89). A higher spike rate was associated with a shorter distance to the edge of the lesion for cavernomas [F(1,64) = -1.37, P < 0.0001, η 2 = 0.22], focal cortical dysplasias [F(1,570) = -0.25, P < 0.0001, η 2 = 0.05] and pleomorphic xanthoastrocytomas [F(1,66) = -0.18, P = 0.01, η 2 = 0.09]. In focal cortical dysplasias, a higher ripple rate was associated with a shorter distance [F(1,570) = -0.35, P < 0.0001, η 2 = 0.05]. Conversely, low-grade gliomas showed a positive correlation; the further an electrode was away from the lesion, the higher the rate of spikes [F(1,75) = 0.65, P < 0.0001, η 2 = 0.37] and ripples [F(1,75) = 2.67, P < 0.0001, η 2 = 0.22]. Pathophysiological processes specific to certain pathology types determine the spatial relationship between the MRI lesion and electrocorticography results. In our analyses, non-tumourous lesions (focal cortical dysplasias and cavernomas) seemed to intrinsically generate spikes and high-frequency oscillations, particularly at the border of the lesion. This advocates for a resection of this tissue. Low-grade gliomas caused epileptogenicity in the peritumoural tissue. Whether a resection of this tissue leads to a better outcome is unclear. Our results suggest that the underlying pathology type should be considered when intraoperative electrocorticography is interpreted.