Fig 1.
(a) Representation of each coupled neuronal population and corresponding subpopulations. Excitatory interneurons are implicitly represented as the self-feedback loop from main pyramidal cells (EXCi to itself). Each model settings consists of either (I) unilateral (s2) or (II) simultaneous bilateral low-frequency probing stimulation (s1 and s2), while slowly changing one parameter towards ictal activity–A1, B1 or K.
Table 1.
Parameter descriptions and values [65].
A, B, and K values are either fixed or varied linearly throughout the simulations.
Fig 2.
Neuronal mass model outputs with and without active probing stimuli.
Simulation changing parameter A1 from 4.30 to 4.95 (B = 40, G = 20) to elicit ictal activity in the end, with (a) passive observation or (b) active probing of both populations. Outputs are shown for population 1 (a.1 and b.1) and population 2 (a.2 and b.2), with tick marks showing stimuli onsets for (b). Ictal-like activity in the form of sustained discharges of spikes is observed for population 1 at the end of both simulations. ILS appear before this transition and are elicited even further in advance by stimulation. (c) Bottom plots show overlapped and mean response waveforms for increasing values of A1 for (c.1) population 1 and (c.2) population 2. Gradual response changes are observed until the appearance of ILS for A1 = 4.5 and ictal activity at A1 = 5.0.
Fig 3.
Feature series and probing efficiency for model setting I-A.
For population 1, excitability increase is correlated with variance even with passive observation. However, increased amplitude probing responses from population 2 reflect gradual changes of A1 towards ictogenesis. (a) shows a simplified illustration of the model setting. For (b) variance, (c) skewness, (d) kurtosis and (e) lag-1 AC features, top rows show feature values extracted from the output of each population, as the excitability gain parameter (A1) is increased. (f) shows the inter-population synchronization as measured by the mutual information feature. Bottom row shows Spearman’s rank correlation between each feature series and the shifted parameter (A1), as stimulus amplitude is increased. Black dots indicate significant differences from passive observation (stim. Amplitude = 0) according to Tukey’s HSD.
Fig 4.
Feature series and probing efficiency for model setting I-B.
Decreased slow inhibition of population 1 is not highlighted by the extracted features if only the “normal” neural mass (set 2) is stimulated. (a) shows a simplified illustration of the model setting. For (b) variance, (c) skewness, (d) kurtosis and (e) lag-1 AC features, top rows show feature values extracted from the output of each population, as the slow inhibition gain parameter (B1) is decreased. (f) shows the inter-population synchronization as measured by the mutual information. Bottom row shows Spearman’s rank correlation between each feature series and the shifted parameter (B1), as stimulus amplitude is increased.
Fig 5.
Feature series and probing efficiency for model setting I-K.
Coupling gain increase is highlighted by features extracted from the stimulated population and by the mutual information between activities of both model subsets. (a) shows a simplified illustration of the model setting. For (b) variance, (c) skewness, (d) kurtosis and (e) lag-1 AC features, top rows show feature values extracted from the output of each population, as the coupling gain gain parameter (K) is increased. (f) shows the inter-population synchronization as measured by the mutual information feature. Bottom row shows Spearman’s rank correlation between each feature series and the shifted parameter (K), as stimulus amplitude is increased.
Fig 6.
Feature series and probing efficiency for model setting II-A.
Active probing effects are visible for population 2, but only for increased stimulation amplitudes. (a) shows a simplified illustration of the model setting. For (b) variance, (c) skewness, (d) kurtosis and (e) lag-1 AC features, top rows show feature values extracted from the output of each population, as the excitability gain parameter (A1) is increased. (f) shows the inter-population synchronization as measured by the mutual information feature. Bottom row shows Spearman’s rank correlation between each feature series and the shifted parameter (A1), as stimulus amplitude is increased.
Fig 7.
Feature series and probing efficiency for model setting II-B.
Active probing provides predictive value for features extracted from both populations, but the effect is limited to increased stimulation amplitudes for population 2. (a) shows a simplified illustration of the model setting. For (b) variance, (c) skewness, (d) kurtosis and (e) lag-1 AC features, top rows show feature values extracted from the output of each population, as the slow inhibitory gain parameter (B1) is decreased. (f) shows the inter-population synchronization as measured by the mutual information feature. Bottom row shows Spearman’s rank correlation between each feature series and the shifted parameter (B1), as stimulus amplitude is increased.
Fig 8.
Feature series and probing efficiency for model setting II-K.
Probing provides predictive value for both stimulated populations. (a) shows a simplified illustration of the model setting. For (b) variance, (c) skewness, (d) kurtosis and (e) lag-1 AC features, top rows show feature values extracted from the output of each population, as the coupling gain parameter (K) is increased. (f) shows the inter-population synchronization as measured by the mutual information feature. Bottom row shows Spearman’s rank correlation between each feature series and the shifted parameter (K), as stimulus amplitude is increased.
Fig 9.
Onset time of ictal-like activity as a function of stimulus amplitude.
Simulations with increased amplitudes did not affect the onset latencies of sustained spike discharges in any model setting.