Epilepsy-predictive, magnetic resonance imaging changes following experimental Febrile Status Epilepticus: are they translatable to the clinic?

Induction of eFSE:

Experimental FSE was induced as previously described.^8,19–21 Briefly, on P10–11, pups were placed in pairs in a 3.0L glass container lined with absorbent paper. Pups were subjected to a continuous stream of warm air until behavioral seizures began (3–5 minutes), characterized by sudden loss of motion (freezing), oral automatisms, and forelimb clonus. Hyperthermia (39.0–41.5°C) was maintained for 40min (Cohort 1) or 60min (other cohorts), an increased duration aiming to generate seizures lasting longer than 50 min, as suggested by human studies^10,22. Core temperatures were measured at baseline, seizure onset, and every 2min during hyperthermia. Following eFSE, rats were cooled by placing on a cool metal surface or under running water and allowed to recover for 15 minutes before returning to their home cage.

The cohorts of rats studied were:

• Cohort 1: Male only control (n=14) and eFSE rats (n=19) were serially scanned at 2, 18, and 48h at 11.7T, and underwent continuous EEG studies for up to 10 months. Whereas some data from this cohort were reported⁸, the analyses presented are previously unreported (Figure 1).

• Cohort 2: Imaged in vivo at 11.7T 2 and 6h after eFSE (8 controls, 10 eFSE). Both males and females were used and randomly assigned to both groups (Figure 2).

• Cohort 3: Imaged in vivo at 3.0T 4 and 48h after eFSE (7 controls, 9 eFSE). Both males and females were used and randomly assigned to both groups (Figure 3).

• Cohort 4: Imaged in vivo at 11.7T 2, 48, and 96h (10 controls, 11 eFSE). Both males and females were used and randomly assigned to both groups (Figure 4)

• Cohort 5: Imaged ex vivo at 9.4T during early adulthood (3.5m±0.8m; 9 controls, 4 eFSE). Both males and females were used and randomly assigned to both groups (Figures 5, 6)

In vivo MRI Procedure:

For all MRI studies, rats were lightly anesthetized using 1.5% isoflurane in 100% O₂ to minimize motion, and body temperature was maintained at ~37°C with a heated water cushion.

11.7T in vivo MRI:

A single Bruker Avance 11.7T (Bruker Biospin, Billerica, MA) MR scanner (Research Imaging Center, LLU) was used for all 11.7T T₂ studies for cohorts 1, 2, and 4. T₂-weighted images were acquired using a 2D multi-echo-spin-echo sequence with a Bruker Biospin circular RF coil and the following parameters: Field of View (FOV): 2.3×2.3 cm, Slice Thickness: 0.75 mm, TR: 4697ms; TE: 10.21–100.1ms; inter-TE: 10.21ms, matrix size: 192×192, and number of averages (NA): 2.

3.0T in vivo MRI:

Cohort 3 rats underwent 3.0T T₂ imaging on a single Phillips Achieva 3.0T MR scanner (Neuroscience Imaging Center, UCI). T₂-weighted images were acquired using a clinical wrist coil a 2D multi-echo-spin-echo sequence with the following parameters: FOV: 2.3×2.3cm; matrix size: 152×153; slice thickness: 1.0 m; slice interval: 0.1mm; TR: 2000 ms; TE 17.20 – 51.6 ms; inter-TE = 17.20 ms; NA: 2.

In vivo MRI Analysis:

Absolute T₂ relaxation times (ms) were calculated by log transform followed by linear least-squares fit on a pixel-by-pixel basis and T₂ maps were generated using in-house software (MATLAB, Mathworks).

For all in vivo studies, regions were delineated manually without knowledge of treatment group using ImageJ software (versions 1.25–2.0.0). The regions of interest (ROIs) were drawn with a pseudo colored look up table (16 colors) to highlight borders between adjoining regions. All ROIs (shown in Supplemental Figure S1) were delineated by the same investigator (MMC), with a high level of intra-rater reliability (Intraclass Correlation Coefficient; BLA=0.872; MeA=0.832; DMThal=0.978, Whole Brain=0.992). The whole brain ROI was the entire brain on two consecutive slices, with the anterior slice aligning with the anterior BLA. MRI signal changes are often unilateral and always asymmetrical in children after FSE^11,23, which is consistent with our previous findings^8,14. Thus, we performed separate measurements and analysis of each side for all bilateral structures. Based on the results of the Choy et al, (2014) studies, we a priori chose to analyze data only the side with the lower T₂. However, to ensure that there are no differences across time points we present bilateral data in Figure 2. For Cohort 1, the following ROIs were manually drawn: dorsal hippocampus, ventral hippocampus, entorhinal cortex, piriform cortex, cerebellum, medial amygdala, basolateral amygdala, medial thalamus, and corpus callosum. For the remaining in vivo cohorts, only BLA, medial amygdala, and dorsal medial thalamus were delineated.

Ex Vivo 9.4T MRI Acquisition and Analysis:

Cohort 5 rats (~3 months old) were anesthetized with a lethal dose of pentobarbital, perfused with 4% PFA, and brains were removed and post-fixed for 24h in PFA. Post-fixed brains submerged in Fluorinert FC-770 (Sigma-Aldrich) and T₂-weighted images (T₂WI) were acquired on a 9.4T Bruker Biospin MRI scanner (Billerica, MA, Paravision 5.1) (Experimental Imaging Center, Univ. of Calgary). The 10-echo T₂WI images had the following parameters: 50 0.5mm slices, 1.92cm² FOV, 256×256 matrix, TR: 6500ms, TE: 10ms, NA: 4 resulting in a total scan time of 15 min. Quantitative T₂ maps were processed on JIM software (Xinapse Systems Ltd; West Bergholt, Essex; United Kingdom). The Waxholm MRI atlas²⁴ was registered to each individual’s structural image and the Waxholm label atlas (separated by hemisphere in JIM) was transformed to this resulting image using Advanced Normalization Tools (ANTs).²⁵ Native-space T₂ values were extracted using the transformed Waxholm labels, and, consistent with acute measures, only the unilateral lower T₂ values are presented. To create mean images (Figure 5A), the T₂ maps were registered to a representative control rat’s space using FMRIB Software Library’s (FSL) linear registration tool, FLIRT, and averaged by group.

EEG electrode implantation & long-term video-EEG recordings and analysis:

At ~P40, cohort 1 rats had bipolar electrodes (PlasticsOne) implanted bilaterally in the hippocampus (AP:3.3; L:2.3; V: −2.8 mm to bregma), a cortical electrode was placed over the parietal cortex (AP:2; L: −2 mm), and a ground electrode over the cerebellum. EEG recordings were synchronized to video and conducted in freely moving rats beginning 5d after electrode implantation for up to 10 months, progressively increasing monitoring time to optimize seizure detection. Recordings increased from 112h in the first month (15.6% of the time) to 206h in the final month (3–5d segments; 28.6% of the month). Over 37,000h of video EEG were acquired including 595±57h per control rat and 1319±38h per eFSE rat.

EEGs scanned visually for seizures by two experienced investigators who were blinded to group identity and then reanalyzed using a seizure-detection software (LabChart version 7.3; ADInstruments) and concurrent video recordings were analyzed for behavioral manifestations of seizures. These included sudden cessation of activity, facial automatisms, head bobbing, prolonged immobility with staring, alternating or bilateral clonus, rearing and falling.²⁶ Only events with both EEG and behavioral changes that lasted >20s were classified as seizures, and rats with at least one seizure were categorized as epileptic. The analysis and results defining the groups are presented in detail in Choy, et al. (2014).

Statistics:

Statistics and graphs were completed on GraphPad Prism (Version 7.0), except the Intraclass Correlation Coefficients, which were calculated using the VassarStat online calculator.²⁸ Data are presented as box and whisker plots, with bars representing the minimum and maximum, with significance set at p<0.05. Outliers were excluded prior to analysis using the ROUT Test (Q = 1%).²⁷ A list of outliers removed is presented in Supplementary Table S1. To determine whether MRI performed better than chance at predicting epilepsy after eFSE, regional MRI data from eFSE rats underwent receiver operating characteristic (ROC) analysis. Paired T-Test was used to determine significant change in the whole brain T₂ relaxation time over 48h, as well as between 2–6 hours for all regions of interest, as well as measure group effects of the adult T₂ images. MRI T₂ relaxation differences in individual regions were compared using One-way repeated measures ANOVA with Bonferroni correction. To compare the group effects across time, Repeated Measure (RM-)Two-way ANOVA was used with Šidák Multiple Comparison test.

Dynamic changes over 48 hours in 11.7T T₂ relaxation times are a robust predictor of epileptogenesis

In Cohort 1, 6/19 rats developed spontaneous seizures months after eFSE (31.6%)⁸, outlined in Table 1. As reported previously, T₂ signal 2h after eFSE in the BLA and other limbic regions were good predictors of subsequent epileptogenesis. However, the prediction was incomplete, with the BLA predicting epilepsy at 83.3% sensitivity and 76.9% specificity (Figure 1C, inset).

We extended these early studies by analyzing the longitudinal change in MRI signals 2 and 48h after eFSE by computing the difference in T₂ relaxation times for each region of interest (Figure 1A). Consistent with normal myelination and maturation,^29,30 we found a reduction in T₂ relaxation time in the whole brain of both control rats as well as in the eFSE rats that did not develop epilepsy (eFSE-NoEpi) (Paired T-Test: controls; t=7.94, df=12, p<0.001; eFSE-NoEpi: t=5.54, df=11, p<0.001). Surprisingly, the T₂ relaxation decrease was blunted across the whole brain of the eFSE rats that developed epilepsy later in life (eFSE-Epi) (Paired T-Test, t=2.02, df=5, p=0.10) (Figure 1B). These findings suggest that a disruption in the developmental reduction of T₂ relaxation times throughout the brain may be predictive of epileptogenesis.

In our prior work, the BLA was the strongest predictor of epileptogenesis⁸. Here, we found that the longitudinal difference in T₂ relaxation times from 2 to 48h following eFSE was a better predictor of epilepsy than the BLA at 2h alone. The trajectory of T₂ values in the BLA of eFSE-Epi rats increased over the 48h following eFSE, whereas T₂ relaxation times for both the controls and eFSE-NoEpi rats decreased (One-way ANOVA, eFSE-Epi vs. controls p<0.001; eFSE-Epi vs. eFSE-NoEpi, p<0.001) (Figure 1D).

Examining the potential value of other limbic structures, we discovered that the T₂ difference in medial amygdala (MeA) was an even a better predictor of epilepsy than BLA (Figure 1E). In MeA, like the BLA, the difference in T₂ relaxation times (48h - 2h) increased over time in eFSE-Epi compared to either controls or eFSE-NoEpi rats (One-way AVOVA, eFSE-Epi vs. controls, p<0.001; eFSE-Epi vs. eFSE-NoEpi, p=0.001). The dynamic changes of the dorsal medial thalamus (DMThal) also identifies differences following eFSE (Figure 1F, Ctrl vs eFSE-NoEpi p<0.001; Ctrl vs. eFSE-NoEpi p<0.001; eFSE-NoEpi vs. eFSE-Epi p=0.02).

The findings were selective, as these predictive changes were not observed in other limbic regions such as entorhinal cortex (Figure 1G; Ctrl vs eFSE-NoEpi p>0.99; Ctrl vs. eFSE-NoEpi p=0.07; eFSE-NoEpi vs. eFSE-Epi p=0.11). The same pattern of results was found when comparing the T₂ values using a two-way ANOVA: the BLA, MeA and DMThal had a significant interaction between time and outcome. Notably, no interaction was found in the entorhinal cortex (Supplemental Figure S2). The predictive power of the T₂ trajectory persisted when the individual T₂ values were normalized to the whole brain T₂ values, establishing that the results were not solely due to whole brain reduction of T₂ values. No significant correlation was found when comparing the T₂ change within the whole brain, BLA, MEA or MThal with the seizure burden of the individual animals.

The predictive efficacy of the T₂ difference in the BLA, MeA and DMThal as markers of epileptogenesis was confirmed by the use of an independent unbiased measure, the receiver operating characteristic (ROC) curve analysis. ROC curve analysis is an unbiased measure of how a successful a test is at predicting the outcomes of a group of subjects. We used it to compare the predictions of epileptogenesis vs. the actual outcomes of the eFSE-NoEpi group and eFSE-Epi group. The curve for a test that has 100% sensitivity and 100% specificity will follow the top left corner and will have an area under the curve (AUC) of 1.00, whereas a test that performs as chance will be at 45° across the graph with an AUC of 0.50 (represented by the grey line). Using the ROC, the predictive value of the T₂ differences was very robust (Figure 1C; AUC: BLA 0.99±0.02, p<0.001; MeA 1.00±0.00, p<0.001, DMThal 0.87±0.09, p=0.01).

Longevity of MRI changes of T₂ relaxation times after experimental FSE

A challenge to the clinical translation of our original findings in Choy, et al., (2014) was the potential need to image children sustaining FSE within 2–4 hours after the initial insult. Therefore, we imaged a cohort of rats at both 2 and 6h after eFSE (Figure 2A, B). There was a strong correlation within each rat and no effect of time between 2 and 6h at a group level for T₂ values in the BLA, MeA, DMThal, and whole brain (Figure 2C-H; Paired T-Test: BLA; p=0.45, t=0.78 df=17, correlation r=0.72, p<0.001; MeA: p=0.11, t=1.691, df=19, correlation r=0.81, p<0.001; DMThal: T-Test p=0.99, t=1.36, df=15, correlation r=0.89, p<0.001; Whole Brain [Supplemental Figure S3], T-Test: p=0.61, t=0.53, df=9, correlation r=0.75, p=0.01). These data demonstrate the stability of the epilepsy-predicting signal between 2h and 6h and indicate that imaging children at 6h after FSE could enable prediction of epilepsy.

Detection of T₂ changes after eFSE is feasible in a clinically relevant low-field scanner

We imaged rat pups at 4 and 48h after eFSE on a 3.0T human scanner, the current standard for clinical MRIs (Figure 3A). The whole brain T₂ trajectories recapitulated those observed from a high-field scanner (11.7T): controls had a significant and consistent reduction across the two days (Figure 3B; Paired T-Test: Ctrl: p<0.001, t=17.23, df=5). The eFSE group also had a significant decrease, but with increased variance (p<0.001, t=6.177, df=8). When analyzing whole brain T₂ changes (48h - 4h), two distinct eFSE groups became apparent, which we termed eFSE-vulnerable and eFSE-resilient (Figure 3B). The eFSE-resilient rats fell within 2SD of the controls, demonstrating the expected reduction of T₂ relaxation time similar to the controls (One-way ANOVA: p>0.99). The eFSE-vulnerable rats were characterized by a minimal reduction of T₂ and was significantly different from both controls and eFSE-resilient groups (One-way ANOVA, eFSE-Vulnerable vs. eFSE-Resilient: p<0.01; eFSE-Vulnerable vs. Control p<0.001). There was no significant difference between either the T₂ relaxation times (Figure 3D, F) or the change over time (Figure 3E, G, Supplemental Figure S4) in the BLA or MeA, likely a result of their small volume and the lower resolution inherent in imaging at 3T (two-way ANOVA, no significant interaction between treatment group and time; significant effect of time for both BLA and MeA. BLA: F_(1,14) = 12.62, p<0.01; MeA: F_(1,14) = 39.54, p<0.0001).

MRI T₂ trajectory from days to months after eFSE

To extend our understanding of the acute and chronic effects of eFSE on T₂ relaxation time trajectories, we imaged eFSE rats at additional acute time points and in adulthood. Delineating acute trajectories, (4, 48, and 96h after eFSE, Figure 4A) we found differing developmental patterns for control and eFSE rats across the whole brain and within specific limbic regions. Control rats had consistent reductions in individual T₂ whole brain trajectories across 96h, whereas the eFSE group were more variable (Figure 4B). At a group level, there was a significant interaction for the whole brain between the effect of eFSE and imaging time-point (RM-Two-way ANOVA, Significant interaction, F_(2,36) = 3.84, p<0.05), specifically at 96h (Šidák Multiple Comparison, p<0.01). Developmental patterns of T₂ relaxation times within the BLA and MeA resembled those of whole brain. Notably, patterns within DMThal differed from those of amygdala nuclei: the age-dependent reduction of T₂ in controls appeared delayed, commencing mainly after 48h, and the eFSE-induced inflection of the developmental trajectory, found in BLA, MeA and whole brain, was not observed. (Figures 4D-F, Supplemental Figure S5A-D), BLA: Significant interaction F_(2,36) = 5.05, p<0.05, 96h Šidák p<0.001; MeA: Significant interaction F_(2,36) = 5.40, p<0.01, 96h Šidák p<0.001; DMThal, no interaction, significant effect of time F_(2,36) = 22.5, p<0.001).

The large variance within the eFSE group, especially in T₂ for BLA and MeA at 48h following eFSE, prompted us to examine if the eFSE group was comprised of eFSE-resilient and vulnerable subsets. We separated the rats that were within 2SD of controls at 48h following eFSE (eFSE-resilient; BLA/MeA, n=6) from those outside of that range (eFSE-vulnerable, BLA/MeA, n=4). For both BLA and MeA, this stratification resulted two distinctive trajectories over the 48h between the eFSE-vulnerable and eFSE-resilient groups which converged at 96h (Figure 4D’, 4E’; Supplemental Figure S5B’-C’). For both the BLA and MeA, interaction was significant between time and treatment (RM-Two-way ANOVA, Šidák significant interaction, BLA: F_(4,34) = 5.46, p<0.01; 48h Ctrl vs. eFSE-vulnerable p<0.01, eFSE-vulnerable vs. eFSE-resilient p <0.001; 96h Ctrl vs. eFSE-vulnerable p<0.01, Ctrl vs. eFSE-resilient p<0.05; MeA: F_(4,34) = 6.60, p<0.001; 48h Ctrl vs. eFSE-vulnerable p<0.01, eFSE-vulnerable vs. eFSE-resilient p <0.01; 96h Ctrl vs. eFSE-vulnerable p<0.05, Ctrl vs. eFSE-resilient p<0.001). Whereas the basis for these apparent subgroups is unclear, it may suggest that the eFSE-vulnerable group demonstrated an immediate (0–48h) delay in the developmental trajectory of T₂ relaxation, whereas a disruption of this T₂ developmental trajectory emerged later in the “resilient” group.

The long-term temporal profile of eFSE-induced changes in T₂ was examined in adults on a 9.4T scanner (age = 3.5m±0.8m). We found a brain-wide T₂ increase in adult eFSE rats compared to controls, as apparent from the group averaged T₂ maps (Figure 5A). When whole brain regions were parsed, there was a significant effect of eFSE (Figure 5B, two-way ANOVA, effect of eFSE, F_(1,11) = 7.17, p<0.05). T₂ increases were observed in eFSE rats in the limbic regions that predicted epileptogenesis (Figure 6A-E), particularly the BLA (T-Test, p<0.05, t=2.63, df=11). Interestingly, similar findings were noted for the CA1 and CA3 of the hippocampus, regions which had not shown acute changes (CA1: p<0.05, t=2.80, df=11, CA3; p<0.05, t=2.25, df=11). In contrast, T₂ relaxation times in the MeA, medial dorsal thalamic nuclei, and dentate gyrus were not significantly different between eFSE and control groups. A group comparison of the aggregate BLA, MeA, hippocampal regions, and MeDLThal between eFSE and control rats did provide a robust measure of the consequences of eFSE, revealing a significant effect of eFSE on T₂ values (Figure 6F, two-way ANOVA, effect of eFSE, F_(1,11) = 5.87, p<0.05).

Progressive changes in T₂ following eFSE offer improved prediction of epileptogenesis

Our work previously discovered high-field T₂ signal changes as predictive marker of epileptogenesis immediately (2h) following a single episode of eFSE.⁸ This was a critical first step in the ability to predict epilepsy before the first spontaneous seizure occurred. While the prediction was robust, the positive predictive value (PPV) was imperfect: one-third of rats that were predicted to become epileptic did not have a spontaneous seizure. By analyzing the change in T₂ rather than at a single time point, our new data demonstrates that the repeated longitudinal T₂ changes (48h – 2h) increased prediction of epileptogenesis, increasing the PPV to 100% and 85.7% in the MeA and BLA, respectively. Additionally, this work revealed dynamic MRI differences at multiple time points (48 and 96h), reflecting the fluid process of epileptogenesis. We believe that the improved predictive value is based on the ability of serial MR imaging to differentiate how the temporal profile of T₂ relaxation values of each individual rat either reflects that normal developmental decrease in T₂ relaxation or differs from it, and that it is a lack of developmental T₂ reduction that is the marker of early processes of epileptogenesis. Further studies are required to uncover the biological mechanisms that underlie the relationship between “normal” T₂ decreases and the flattened trajectory of rats in the early stages of epileptogenesis.

Reconciliation of early T₂ reduction and chronic T₂ increases following eFSE

There has been a significant body of work that has found T₂ increases in the brain (particularly hippocampus) following FSE in both humans and rodents.^10–16 Because of this, the results of Choy, et al., (2014) which revealed a decrease in T₂ after FSE 2h after eFSE and no changes at 48h were unexpected, though there were two important differences between it and previous work. First, the imaging was completed much earlier after eFSE. Secondly, the rats were imaged on an 11.7T scanner, which has a higher magnetic field and is affected by paramagnetic changes (T₂*) which can be measured as decreased T₂ values.⁸

By analyzing the longitudinal change of T₂ values between 2 to 96h after eFSE, it became clear that a T₂ increase in the days after eFSE was potentially masked by typical development. This developmental reduction in T₂ relaxation times was measured across the entire brain and occurs as a result of normal myelination and maturation.^29,30 The trajectory is more rapid in infant rats than it is in humans, thus the developmental reduction in infants would not play as important a role clinically. Whereas the underlying cellular mechanisms that lead to FSE-induced increased T₂ are not fully understood, they have been postulated to involved edema, based on volumetric human studies,^10,15 or gliosis, as our previous work has reported an increased number and activation of astrocytes following eFSE.^12,20

Importantly, the trajectory between 4, 48 and 96h after eFSE reconciles the early and late T₂ changes. The current findings demonstrate divergent developmental paths of eFSE rats compared with their control littermates. The same regions that have an early T₂ decrease predictive of epileptogenesis demonstrate a later T₂ increase in adulthood. Interestingly, early imaging of the hippocampus was not predictive of epileptogenesis⁸, but late increases in T₂ are robust in both human and rodent images.^{11–13,17,18}

Clinical translation of predictive T₂ signal changes

The present study addresses two main hurdles for translating the predictive MRI signal to clinic: timeline and scanner strength. The original time-point, 2h after FSE, would be difficult to achieve in an emergency department setting, due to access to MRI and time required for consent. Our new findings that the early T₂ signal decrease remains stable for up to 6h makes future clinical imaging of children feasible.

Additionally, our initial study was performed on research scanners (4.7T-11.7T), which have higher magnetic fields and smaller coils than the human scanners (1.5T-3.0T) that are typically available. To demonstrate that similar results would be likely found in children, we imaged eFSE rat pups on a 3.0T human scanner. Using a clinical human wrist coil, we observed measurable differences in the brains of rat pups following eFSE, similar to the findings in the high-field scanner. These differences were measurable at the whole brain level, not in specific limbic regions, but this is not too surprising due to resolution differences: the voxel volume at 11.7T was 0.011 mm³, but 0.023 mm³ in the 3.0T. This inherent resolution difference should not play as critical a role when imaging children, as the whole brain of P12 rat (which had measurable differences at 3.0T) is ~1 cm³ in volume, roughly the same volume of an amygdala of a one-year-old infant.^31,32 Thus, it is likely the whole brain differences in the rat pup will translate to even stronger measurements when analyzing individual brain regions in children, mirroring the results found in rats on the animal scanners.

In addition to the noted resolution differences, it is important to remember that T₂ relaxation properties are modulated by field strengths, age at imaging and acquisition parameters. Human and rodent T₂ values are known to decrease with increasing field strength,^33,34 (see Choy et al., [2014] for discussion). In the rodent brain, it has been suggested that signal to noise ratio’s may actually decrease as field strength increases,³⁴ thus imaging at the clinically relevant 3T as we did in this study may in fact enhance our findings at this field strength. In addition, the influence of T₂ values by field strength is similar in white and gray matter even if acquisition parameters differ.³⁴ Of course, the use of high signal to noise RF coils and purpose-built coils would enhance the acquisition of T₂ signals in neonates and adults.

Overall, this study clearly demonstrates the value of quantitative T₂ MR imaging as a marker for the alterations in the brain following eFSE which occur at the onset of epileptogenesis. Whereas long term EEG recording was only completed in one group of rats following eFSE, the strength of the longitudinal MRI results in the EEG cohort allows us to predict the epileptogenic group utilizing short term MRI changes in the other cohorts. Moving forward, it will be important to both confirm these findings with a long-term EEG cohort and study the mechanisms underlying the MRI signal changes. This continued research will inform us how epilepsy develops, help us understand how we can prevent it, and move us towards translating these findings to the clinic.