Back

Micro-electrode in vivo signatures of human periventricular heterotopia

Frazzini, V.; Whitmarsh, S.; Lambrecq, V.; Lehongre, K.; Yger, P.; Mathon, B.; Adam, C.; Hasboun, D.; Navarro, V.

2019-10-24 pathology
10.1101/816173 bioRxiv
Show abstract

Periventricular nodular heterotopia (PNH) is a malformation of cortical development that frequently causes drug-resistant epilepsy. The epileptogenicity of ectopic neurons in PNH as well as their role in generating interictal and ictal activity is still a matter of debate. We report the first in vivo microelectrode recording of heterotopic neurons in humans. Highly consistent interictal patterns (IPs) were identified within the nodules: 1) Periodic Discharges PLUS Fast activity (PD+F), Sporadic discharges PLUS Fast activity (SD+F), and 3) epileptic spikes (ES). Neuronal firing rates were significantly modulated during all IPs, suggesting that multiple IPs were generated by the same local neuronal populations. Furthermore, firing rates closely followed IP morphologies. Among the different IPs, SD+FA pattern was found only in the three nodules that were actively involved in seizure generation, but was never observed in the nodule that did not take part in ictal discharges. On the contrary, PD+F and ES were identified in all nodules. Units that were modulated during the IPs were also found to participate in seizures, increasing their firing rate at seizure onset and maintaining an elevated rate during the seizures. Together, nodules in PNH are highly epileptogenic, and show several IPs that provide promising pathognomonic signatures of PNH. Furthermore, our results show that PNH nodules may well initiate seizures. HighlightsO_LIFirst in vivo microelectrode description of local epileptic activities in human PNH C_LIO_LIRecordings revealed multiple microscopic epileptic interictal patterns C_LIO_LIFiring rates of all detected units were significantly modulated during all interictal patterns C_LIO_LISeizures recruited the same units that are involved in interictal activity C_LI

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.