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Licensed Unlicensed Requires Authentication Published by De Gruyter September 14, 2019

Seizure initiation in infantile spasms vs. focal seizures: proposed common cellular mechanisms

  • Roger D. Traub EMAIL logo , Friederike Moeller , Richard Rosch , Torsten Baldeweg , Miles A. Whittington and Stephen P. Hall


Infantile spasms (IS) and seizures with focal onset have different clinical expressions, even when electroencephalography (EEG) associated with IS has some degree of focality. Oddly, identical pathology (with, however, age-dependent expression) can lead to IS in one patient vs. focal seizures in another or even in the same, albeit older, patient. We therefore investigated whether the cellular mechanisms underlying seizure initiation are similar in the two instances: spasms vs. focal. We noted that in-common EEG features can include (i) a background of waves at alpha to delta frequencies; (ii) a period of flattening, lasting about a second or more – the electrodecrement (ED); and (iii) often an interval of very fast oscillations (VFO; ~70 Hz or faster) preceding, or at the beginning of, the ED. With IS, VFO temporally coincides with the motor spasm. What is different between the two conditions is this: with IS, the ED reverts to recurring slow waves, as occurring before the ED, whereas with focal seizures the ED instead evolves into an electrographic seizure, containing high-amplitude synchronized bursts, having superimposed VFO. We used in vitro data to help understand these patterns, as such data suggest cellular mechanisms for delta waves, for VFO, for seizure-related burst complexes containing VFO, and, more recently, for the ED. We propose a unifying mechanistic hypothesis – emphasizing the importance of brain pH – to explain the commonalities and differences of EEG signals in IS versus focal seizures.


This study was funded by IBM Corp. and NINDS/NIH NS044133 (R.D.T.; from the National Institute of Neurological Diseases and Stroke/National Institutes of Health); Wellcome Trust Funder Id:, 209164/Z/17/Z (M.A.W. and S.P.H.); with infrastructure support through the National Institute for Health Research Biomedical Research Centre at Great Ormond Street Hospital for Children, NHS Foundation Trust and University College London (R.R.); and Great Ormond Street Hospital Children’s Charity (T.B.). We acknowledge the helpful discussions with Drs. Yoshio Okada, Sufi Zafar, Sam Berkovic, David Grayden, and Mark Cook. We thank Drs. Joefon Jann and Robert Walkup (IBM Corp.) for the invaluable computing support.

Appendix: Methods

Clinical intracranial SEEG recordings

Intracranial EEG data recorded here were routine clinical recordings performed as part of the comprehensive pediatric epilepsy surgery program at Great Ormond Street Hospital (London, UK) and were conducted entirely based on clinical need. SEEG was recorded via depth electrodes placed in the brain parenchyma through burr holes placed to record electrical activity from the epileptogenic network during telemetry in hospital stay. Recordings were performed at sampling frequencies of 1 kHz and displayed in bipolar reference for visualization purposes. The use of anonymized SEEG data for research purposes was reviewed and approved by the UK National Health Regulatory Authority and the local hospital research and development office.

In vitro methods

Coronal slices (450 μm thick) containing secondary somatosensory/parietal area S2/Par2 were prepared from adult male Wistar rats (~150 g) and maintained at 34°C at the interface between humidified 95% O2/5% CO2 and ACSF containing 126 mm NaCl, 3 mm KCl, 1.25 mm NaH2PO4, 1 mm MgSO4, 1.2 mm CaCl2, 24 mm NaHCO3 and 10 mm glucose. All surgical procedures were in accordance with the regulations of the UK Animals (Scientific Procedures) Act of 1986. Persistent, spontaneous delta rhythms were induced by perfusion of the cholinergic agonist carbachol (2 μm) and the D1 dopamine receptor antagonist SCH23390 (10 μm) according to the methods of Carracedo et al. (2013). Delta-based epileptiform activity was generated by bath application of TMA (1 mm) to alkalinize neuronal cytosol and dTC (10 μm) to selectively reduce superficial layer inhibition (Hall et al., 2015). Extracellular field potential recordings were taken with micropipettes (2–5 MΩ) filled with ACSF. Intracellular recordings used pipettes with 2 M potassium acetate (50–100 MΩ). Extracellular data were bandpass filtered at 0.1 Hz to 0.5 kHz, with intracellular DC recordings low-passed filtered at 2.5 kHz.

Model structure

The simulation program used was called plateauVFO.f, written in Fortran to run on 10 processors in the mpi parallel environment, Linux operating system. The processors resided in a Power8 chip in the Cognitive Computing Cluster at the IBM Thomas J. Watson Research Center. The structure of the program was similar to that of spikewaveS.f used by Hall et al. (2018), with these modifications:

  1. Deep-layer low-threshold spiking (LTS) interneurons were removed; instead, there were VIP interneurons (see Hall et al., 2018), which produce GABAA receptor-mediated inhibitory postsynaptic potentials (IPSPs) in various interneuron types, and small GABAA and GABAB receptor-mediated IPSPs in pyramidal cell dendrites in the superficial cortical layers.

  2. The numbers of neurons of different types were adjusted so that the program would run on 10 processors for computational efficiency. The neurons are superficial interneurons (100 basket, 100 axoaxonic, 100 LTS, 100 VIP, and 100 neurogliaform), deep interneurons (200 basket, 100 axoaxonic, and 200 neurogliaform), spiny stellate (500), nontufted deep pyramids (500), RS tufted deep pyramids (500), IB deep pyramids (500), and superficial RS pyramids (1000). As before, neurogliaform interneurons produce GABAA and GABAB receptor-mediated IPSPs.

  3. The code was added to allow for time-dependent alterations in membrane conductance densities (intrinsic and/or synaptic) of IB pyramidal cells; this was done to explore the conditions that result in plateau potentials. For the details of the alterations used here, see Figures 10 and 11.

The source code can be obtained from (and will be deposited in ModelDB.


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Received: 2019-03-05
Accepted: 2019-06-01
Published Online: 2019-09-14
Published in Print: 2020-01-28

©2020 Walter de Gruyter GmbH, Berlin/Boston

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