Application of adaptive nonlinear Granger causality: Disclosing network changes before and after absence seizure onset in a genetic rat model

Sysoeva, Marina V.; Sitnikova, Evgenia; Sysoev, Ilya V.; Безручко, Б. П.; Luijtelaar, Gilles van

doi:10.1016/j.jneumeth.2014.01.028

Cited by 43 publications

(27 citation statements)

References 31 publications

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“…A previous depth electrode study in a rat model of absence epilepsy found that thalamus and somatosensory cortex δ‐ and θ‐band spectral density and functional connectivity increased two seconds before the t 0 SWD onset, results that suggested that absence seizures are not instantaneous and unpredictable events. It was thought that the increased prespike thalamocortical δ‐ and θ‐ spectral density and functional connectivity is necessary to produce a “proictal” state required for SWD formation.…”

Section: Discussionmentioning

confidence: 92%

Cortical activation in generalized seizures

et al. 2019

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Objective Patients with generalized epilepsy exhibit different epileptiform events including asymptomatic interictal spikes (IS), absence seizures with spike‐wave discharges (SWDs), and myoclonic seizures (MS). Our objective was to determine the spatiotemporal patterns of cortical activation in SWDs, IS, and MS in the Gabra1+/A322D juvenile myoclonic epilepsy mouse. Methods We fabricated affordable, flexible high‐density electroencephalography (HdEEG) arrays and recorded spontaneous SWD, IS, and MS with video/HdEEG. We determined differences among the events in amplitude spectral density (ASD) in the δ/θ/α/β/γ frequency bands at baseline (3.5‐4.0 seconds before the first spike time, t0) and the prespike period (0.1‐0.5 seconds before t0), and we elucidated the spatiotemporal activation during the t0 spike. Results All three events had an increase in ASD between baseline and prespike in at least one frequency band. During prespike, MS had the largest δ‐band ASD, but SWD had the greatest α/β/γ band ASD. For all three events, the ASD was largest in the anterior regions. The t0 spike voltage was also greatest in the anterior regions for all three events and IS and MS had larger voltages than SWD. From 7.5 to 17.5 msec after t0, MS had greater voltage than IS and SWD, and maximal voltage was in the posterior parietal region. Significance Changes in spectral density from baseline to prespike indicate that none of these generalized events are instantaneous or entirely unpredictable. Prominent engagement of anterior cortical regions during prespike and at t0 suggest that common anterior neural circuits participate in each event. Differences in prespike ASD signify that although the events may engage similar brain regions, they may arise from distinct proictal states with different neuronal activity or connectivity. Prolonged activation of the posterior parietal area in MS suggests that posterior circuits contribute to the myoclonic jerk. Together, these findings identify brain regions and processes that could be specifically targeted for further recording and modulation.

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Section: Discussionmentioning

confidence: 92%

Cortical activation in generalized seizures

et al. 2019

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“…Nevertheless, it is good practice to check if the inequality

c \leq \frac{T - p}{p}

[13] is satisfied to verify that the parameters selected do not encounter such a problem. In GC analysis, BIC and methods similar to it have been commonly applied [36, 37, 38, 39], however, the Akaike’s Criterion [40] has also been used for order estimation [41, 42] and can be applied in lsGC analysis as well.…”

Section: Methodsmentioning

confidence: 99%

Exploring connectivity with large-scale Granger causality on resting-state functional MRI

DSouza

Abidin

Leistritz

et al. 2017

Journal of Neuroscience Methods

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Background Large-scale Granger causality (lsGC) is a recently developed, resting-state functional MRI (fMRI) connectivity analysis approach that estimates multivariate voxel-resolution connectivity. Unlike most commonly used multivariate approaches, which establish coarse-resolution connectivity by aggregating voxel time-series avoiding an underdetermined problem, lsGC estimates voxel-resolution, fine-grained connectivity by incorporating an embedded dimension reduction. New Method We investigate application of lsGC on realistic fMRI simulations, modeling smoothing of neuronal activity by the hemodynamic response function and repetition time (TR), and empirical resting-state fMRI data. Subsequently, functional subnetworks are extracted from lsGC connectivity measures for both datasets and validated quantitatively. We also provide guidelines to select lsGC free parameters. Results Results indicate that lsGC reliably recovers underlying network structure with Area Under receiver operator characteristic Curve (AUC) of 0.93 at TR=1.5s for a 10-minute session of fMRI simulations. Furthermore, subnetworks of closely interacting modules are recovered from the aforementioned lsGC networks. Results on empirical resting-state fMRI data demonstrate recovery of visual and motor cortex in close agreement with spatial maps obtained from (i) visuo-motor fMRI stimulation task-sequence (Accuracy=0.76) and (ii) independent component analysis (ICA) of resting-state fMRI (Accuracy=0.86). Comparison with Existing Method(s) Compared with conventional Granger causality approach (AUC=0.75), lsGC produces better network recovery on fMRI simulations. Furthermore, it cannot recover functional subnetworks from empirical fMRI data, since quantifying voxel-resolution connectivity is not possible as consequence of encountering an underdetermined problem. Conclusions Functional network recovery from fMRI data suggests that lsGC gives useful insight into connectivity patterns from resting-state fMRI at a multivariate voxel-resolution.

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“…However, predicting the transition to induced seizures/afterdischarges on the basis of neural signals, as opposed to behavior, had not been demonstrated so far. Previous studies in WAG/Rij rats have identified preictal oscillations in the delta and theta range ) and network changes assessed by nonlinear Granger causality (Sysoeva et al 2014) up to 3 s before seizure onset. Our classification results of induced seizures agree with these previous observations, although in our case most changes occurred during the second just before seizure onset.…”

Section: Probability Of Induced Ictal Transitions Is Modulated By Ongmentioning

confidence: 99%

Spatiotemporal dynamics of optogenetically induced and spontaneous seizure transitions in primary generalized epilepsy

Wagner

Truccolo

Wang

et al. 2015

Journal of Neurophysiology

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Wagner FB, Truccolo W, Wang J, Nurmikko AV. Spatiotemporal dynamics of optogenetically induced and spontaneous seizure transitions in primary generalized epilepsy. J Neurophysiol 113: 2321-2341, 2015. First published December 31, 2014 doi:10.1152/jn.01040.2014.-Transitions into primary generalized epileptic seizures occur abruptly and synchronously across the brain. Their potential triggers remain unknown. We used optogenetics to causally test the hypothesis that rhythmic population bursting of excitatory neurons in a local neocortical region can rapidly trigger absence seizures. Most previous studies have been purely correlational, and it remains unclear whether epileptiform events induced by rhythmic stimulation (e.g., sensory/ electrical) mimic actual spontaneous seizures, especially regarding their spatiotemporal dynamics. In this study, we used a novel combination of intracortical optogenetic stimulation and microelectrode array recordings in freely moving WAG/Rij rats, a model of absence epilepsy with a cortical focus in the somatosensory cortex (SI). We report three main findings: 1) Brief rhythmic bursting, evoked by optical stimulation of neocortical excitatory neurons at frequencies around 10 Hz, induced seizures consisting of self-sustained spikewave discharges (SWDs) for about 10% of stimulation trials. The probability of inducing seizures was frequency-dependent, reaching a maximum at 10 Hz. 2) Local field potential power before stimulation and response amplitudes during stimulation both predicted seizure induction, demonstrating a modulatory effect of brain states and neural excitation levels. 3) Evoked responses during stimulation propagated as cortical waves, likely reaching the cortical focus, which in turn generated self-sustained SWDs after stimulation was terminated. Importantly, SWDs during induced and spontaneous seizures propagated with the same spatiotemporal dynamics. Our findings demonstrate that local rhythmic bursting of excitatory neurons in neocortex at particular frequencies, under susceptible ongoing brain states, is sufficient to trigger primary generalized seizures with stereotypical spatiotemporal dynamics.

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Application of adaptive nonlinear Granger causality: Disclosing network changes before and after absence seizure onset in a genetic rat model

Cited by 43 publications

References 31 publications

Cortical activation in generalized seizures

Cortical activation in generalized seizures

Exploring connectivity with large-scale Granger causality on resting-state functional MRI

Spatiotemporal dynamics of optogenetically induced and spontaneous seizure transitions in primary generalized epilepsy

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