# Lasting and extensive consequences of left mesial temporal lobe seizures on electrical cortical activity.

M. Dhoisne, Nacim Betrouni, S. Hennion, L. Plomhause, Arnaud Delval,

Philippe Derambure

► To cite this version:

M. Dhoisne, Nacim Betrouni, S. Hennion, L. Plomhause, Arnaud Delval, et al. Lasting and extensive consequences of left mesial temporal lobe seizures on electrical cortical activity. NeuroImage, 2024, Neuroimage, 305, pp.120975. 10.1016/j.neuroimage.2024.120975. hal-05291574

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# Lasting and extensive consequences of left mesial temporal lobe seizures on electrical cortical activity

Mathieu Dhoisne<sup>a,b,*</sup>, Nacim Betrouni<sup>b</sup>, Sophie Hennion<sup>a,b</sup>, Lucie Plomhause<sup>a,b</sup>, Arnaud Delval<sup>a,b</sup>, Philippe Derambure<sup>a,b</sup>

<figure><img src="image_3.png" /></figure>

## ARTICLE INFO

**Keywords:**

Functional connectivity

Late postictal

Mesial temporal lobe seizures

Side of seizure onset

## ABSTRACT

**Background and objectives:** Focal epilepsies disrupt long-range networks with seizure recurrence driving both regional and global alterations in connectivity networks. While prior studies have focused on the interictal consequences, limited data exist on the direct aftermath of focal seizures. We hypothesize that mesial temporal lobe seizures lead to enduring cortical disorganization. The aim was to assess the effects of a mesial temporal lobe seizure on cortical activity and understand how the side of seizure onset influences these consequences.

**Methods:** In this retrospective study, high-resolution EEG of patients with mesial temporal lobe epilepsy (mTLE) were analyzed. Groups of patients were identified based on the side of seizure onset. We compared relative powers in different frequency bands between interictal (prior to the seizure) and late postictal (one hour following the seizure) periods. Network-based statistics were employed to compare functional connectivity at source level between periods.

**Results:** Twenty-three patients were included (13 left and 10 right mesial temporal lobe seizures). In patients with left mTLE, we observed a post-seizure increase in the relative spectral power in the delta band ($p = 0.001$) and a decrease in the relative spectral power in the alpha band ($p = 0.013$) over the left temporofrontal regions. We isolated a subnetwork that presented a decrease in connectivity strength in alpha band, primarily involving long-range left hemisphere connections ($p = 0.042$). We also identified a subnetwork that presented a decrease in connectivity strength in theta band, primarily involving interhemispheric connections ($p = 0.039$). No significant post-seizure changes were found in patients with right mTLE.

**Discussion:** Left mesial temporal lobe seizures appear to be associated with lasting and widespread disorganization of cortical activity. We propose that the postictal state is associated with a prolonged functional deaf-ferentation of the affected region in patients with left mTLE. This leads to a widespread disorganization of the functional networks, which may be associated with cognitive impairments and promote the progression of epi-lepsy. Further studies are required to fully understand the functional repercussions.

## 1. Introduction

Focal epilepsy is characterized by an enduring predisposition to seizures and its long-term consequences. Notably, cognitive and psy-chobehavioural impairments are prevalent among epileptic patients and are believed to stem from the disorganization of long-range networks responsible for controlling higher-order functions (Englot et al., 2016).

This disorganization seems to be associated to several factors, including the etiology, comorbidities, and the recurrence of seizures. There are different subtypes of focal epilepsy based on the location of the seizure onset zone (SOZ). Mesial temporal lobe epilepsy (mTLE) is the most prevalent focal epilepsy subtype (Tatum, 2012). While it was initially viewed as a regional disorder, evidence now indicates that focal epi-lepsies are responsible for network alterations extending far beyond the

**Abbreviations:** ASR, artifact subspace reconstruction; BEM, boundary element method; EEG, electroencephalogram; FC, functional connectivity; MRI, magnetic resonance imaging; mTLE, mesial temporal lobe epilepsy; NBS, network-based statistics; PLV, phase locking value; ROI, regions of interest; SEEG, stereoelectroencephalography; SOZ, seizure onset zone; wMNE, weighted minimum norm estimate.

* Corresponding author at: Department of Clinical Neurophysiology, Lille University Hospital, Avenue du professeur Émile Laine, Lille 59037, France.

E-mail address: mathieu.dhoisne@chu-lille.fr (M. Dhoisne).

<footnote><sup>a</sup> Department of Clinical Neurophysiology, Lille University Hospital, Lille 59037, France</footnote>

<footnote><sup>b</sup> INSERM U1172, LilNCog - Lille Neuroscience & Cognition, Lille 59000, France</footnote>
SOZ (Englot et al., 2016; Stasenko et al., 2024). The existing data suggest that consciousness-impairing focal seizures are associated with ictal neocortical deactivation, which, over recurrences, may drive the reorganization of interictal connectivity (Blumenfeld et al., 2004a, 2004b; Englot et al., 2016, 2010). Accumulating evidence suggests a correlation between disease duration and the network disorganization, strongly implying that these alterations develop over time due to the recurrence of seizures (Chiang et al., 2016; Englot et al., 2016; Morgan et al., 2015; Stasenko et al., 2024).

While previous research has primarily focused on the effect of focal epilepsy on the interictal cortical activity, fewer studies have delved into the direct aftermath of a focal seizure. In a prior study, attenuated long-range connectivity and increased local connectivity have been observed 10 min after a focal seizure (Liang et al., 2020). Additionally, network metrics were significantly correlated with the number of seizures in one individual (Liang et al., 2020). However, drawing definitive conclusions was hindered by several limitations: the small sample size, the use of low-resolution EEG data, and the lack of information regarding the SOZ. Another study assessed the postictal slow-wave activity 1 min after a temporal lobe seizure using high-resolution EEG in 28 patients. They found that impaired awareness and secondary generalized temporal lobe seizures were associated with a decreased relative spectral power in the delta band in the ipsilateral temporal region and increased in other regions. Aware temporal lobe seizures were associated with an increased relative delta power in the ipsilateral temporal region (Yang et al., 2012). Another study used stereoelectroencephalography (SEEG) to assess spectral power and global functional connectivity (FC) in 19 children, comparing the immediate preictal and postictal periods (Tomlinson et al., 2018). They found that distributed-network seizures were associated with increased postictal delta power, potentially indicative of cortical deactivation, and increased global connectivity compared to focal-network seizures (Tomlinson et al., 2018). The effect of the location and side of seizure onset was not assessed in this study. Furthermore, these studies evaluated the cortical activity only a short interval after the seizure and did not assess the presence of more prolonged disorganization, while there is data suggesting that the cognitive consequences of a focal seizure could be much more prolonged (Helmstaedter et al., 1994; Pottkämper et al., 2020). Data from neuro-imaging studies demonstrated that the postictal period is associated with relative hypoperfusion lateralized to the side of seizure onset that could last for up to one hour (Leonhardt et al., 2005). Also, available clinical data regarding the consequences of focal seizures suggest that left temporal lobe seizures may have a more prolonged effect compared to right temporal lobe seizures (Fakhoury et al., 1994).

The hypothesis is that a mesial temporal lobe seizure would induce a lasting disorganization of cortical activity and this alteration would be more severe when the seizure arises from the left mesial temporal lobe. The aim was to determine the effects of a mesial temporal lobe seizure on cortical activity around one hour after its occurrence, a time when patients are generally expected to have returned to their baseline state, and to understand how the side of seizure onset influences these consequences.

# 2. Materials and methods

## 2.1. Design, setting and population

We retrospectively reviewed all patients who underwent a high-resolution EEG for presurgical evaluation of focal epilepsy in the clinical neurophysiology unit of the Lille University Hospital from January 2014 to December 2023. We included right-handed patients with mTLE for whom awake EEG recordings were available during both the interictal and late postictal periods. Left-handed patients were excluded to avoid bias related to difference in brain connectivity and network organization between right-handed and left-handed individuals (Tejavibulya et al., 2022).

These two periods were defined relatively to the occurrence of the first electroclinical seizure:

- The interictal period (used as baseline) was defined as the period between admission and the onset of the first seizure.

- The late postictal period was defined as the period between 30 and 90 min after the first seizure.

We excluded recordings in which a seizure had not been recorded or in which the seizure became secondarily generalized. Additionally, generalized and multifocal epilepsies, as well as epilepsies in which the location of the SOZ was outside of the mesial temporal lobe or not determined, were excluded. Patients under 18 years-old and those with a previous history of neurosurgery were also excluded. Recordings archived with a sampling rate < 256 Hz or in which artifacts prevented any analysis were, as well, excluded. None of the included patients objected to the use of their data.

## 2.2. Data collection

### 2.2.1. Demographic and clinical data

We gathered demographic information (age and sex), as well as details on manual laterality, past medical history (preterm birth, history of birth complications, febrile seizures, central nervous system infections, and head trauma), and family history from the medical records.

Additionally, we documented characteristics of the epilepsy: age of onset, duration, seizure frequency, treatments, localization of the seizure onset zone, secondary generalization and etiology. The epilepsy was categorized as right mTLE, or left mTLE based on the results of the presurgical assessment (seizure semiology, scalp recording, MRI and brain PET) and, when available, on the results of the stereoelectroencephalographic recording and/or on the clinical results of the surgery.

### 2.2.2. Electroencephalographic recording and preprocessing

All patients hospitalized for presurgical evaluation underwent a high-resolution scalp EEG (55 electrodes) in our unit. The scalp electrodes (M.E.I., La Farlède, France) were positioned according to the international 10/10 electrode placement system by trained EEG technicians (eFig. 1) (Chatrian et al., 1985). The signal was digitalized at a sampling rate of 256 or 512 Hz with impedances maintained below 20 kΩ using System Plus Evolution Software® (Micromed, S.p.A., Mogliano Veneto, Treviso, Italy). We selected 3 to 5 min of awake, eyes-open EEG recordings during both the interictal and late postictal periods. The behavioral state of the subject was presumptive and based on EEG characteristics alone, as no video recordings were available to confirm it.

A summary of the main steps of the preprocessing and EEG data analysis is available in eFig. 2. Preprocessing was performed using the EEGLAB 2023.1 toolbox in MATLAB (Delorme and Makeig, 2004). Electroencephalographic data digitalized at a sampling rate of 512 Hz were downsampled to 256 Hz to ensure homogeneity of the data. The signal underwent high-pass filtering at 1 Hz and low-pass filtering at 40 Hz (Hamming windowed sinc finite impulse response filters) ensuring the elimination of 50 Hz line noise and its higher harmonics. The EEGLAB plugin Clean_rawdata was then employed to automatically remove artifacted channels (electrodes correlated at <70 % to their reconstruction based on nearby channels) and flat channels (with a maximum tolerated flatline duration of 5 s). Visual inspection was then conducted to reject any remaining artifacted channels. Subsequently, rejected electrodes were spherically interpolated with the condition that the interpolation did not exceed six electrodes (10 % of the initial number of electrodes). The artifact subspace reconstruction (ASR) method was applied to eliminate large-amplitude transient artifacts (Mullen et al., 2015). The ASR parameter (the standard deviation cut-off relative to the covariance of the calibration dataset for removal of
bursts) was set to 20 (Chang et al., 2018). The channels were then re-referenced to the average reference. Independent component analysis decomposition with the Infomax algorithm was performed to address stationary artifacts (Bell and Sejnowski, 1995; Delorme et al., 2012). The EEGLAB plugin ILabel helped in identifying artifactual components before manual inspection, flagging, and rejection of these components (Pion-Tonachini et al., 2019). Visual inspection of the recordings was then conducted to retain 2 minutes of recordings free of major artifacts. The recordings were segmented into 4-s epochs, and manual removal of epochs containing any remaining artifacts was carried out, ensuring at least 1 minutes of preserved recording.

### 2.2.3. Electroencephalographic data analysis

We conducted both spectral and functional connectivity analyses on the preprocessed EEG data. Together, these approaches provide a comprehensive insight of brain rhythms, capturing both the amplitude of oscillatory activity and the synchronization between distinct brain regions.

To perform spectral analysis, we conducted spectral decomposition of the scalp signal using a fast Fourier transform with a 1-s Hamming window and no overlapping employing the EEGLAB toolbox in MATLAB (Delorme and Makeig, 2004). Subsequently, absolute spectral power was computed in the delta (1–4 Hz), theta (4–8 Hz), alpha 1 (8–10 Hz), alpha 2 (10–13 Hz), beta 1 (13–20) and beta 2 (20–30 Hz) bands. Relative spectral power was calculated by normalizing each value by the sum of the absolute spectral power in all the bands.

To perform functional connectivity analysis, we reconstructed the EEG data in the source space using the Brainstorm toolbox in MATLAB (Tadel et al., 2011). First, a head model was computed employing the symmetric boundary element method (BEM) from the OpenMEEG software, using a MRI template anatomy (ICBM152) (Fonov et al., 2009; Gramfort et al., 2011). Subsequently, the inverse problem was solved using the weighted minimum norm estimate (wMNE) with dipole orientations constrained to the cortex (Baillet et al., 2001). The EEG data in the source space were then downsampled into 148 regions of interest (ROI) using the Destrieux atlas (Destrieux et al., 2010). Phase locking values (PLV) were computed between these ROI in the theta (4–7 Hz), alpha (8–12 Hz) and beta (13–30 Hz) bands using the EEGNET toolbox in MATLAB (Hassan et al., 2015).

## 2.4. Statistical analysis

Qualitative variables were expressed as number (percentage). Quantitative variables were expressed as mean (standard deviation) if the histogram showed a symmetrical distribution and as median [first quartile; third quartile] otherwise. Normality of distributions was assessed through visual inspection of histograms. Regarding the clinical characteristics, the independence between the quantitative variables and the group was assessed using two-sample Welch's *t*-tests or Mann-Whitney *U* tests as appropriate. The independence between the qualitative variables and the group was assessed using $X^2$ tests or Fisher's exact tests as appropriate. These statistical analyses were performed using R statistical software (R Core Team, 2023). All tests were two-sided.

The independence between the relative spectral power in the different frequency bands and the period was assessed using EEGLAB toolbox with paired permutation tests (Delorme and Makeig, 2004). The number of permutations was set to 10,000.

Network-based statistics (NBS) were employed to assess the independence between the functional networks and periods. We used 10,000 permutations and a primary threshold corresponding to *p* < 0.05 (Zalesky et al., 2010). Topological clusters that attained statistical significance were then reconstructed in the frontal, transverse and sagittal planes using the BrainNet Viewer toolbox in MATLAB (Xia et al., 2013).

The threshold for statistical significance level was set at *p* < 0.05.

## 2.5. Ethics

This study was approved by the French institutional data protection board (reference DEC23-232) according to the French law. All the participants received a detailed information note explaining the aims of the study and the nature of the collected data. Patients who refused to participate were not included. This study complies with the declaration of Helsinki's ethical principles.

## 2.6. Data availability

Anonymized data supporting the findings of this study are not publicly available but are available from the corresponding author upon reasonable requests.

# 3. Results

## 3.1. Population characteristics

From January 2014 to December 2023, 407 patients were hospitalized for presurgical assessment of focal epilepsy in the clinical neurophysiology unit of the Lille University Hospital. Among these patients, 94 patients over 18 years-old presented a mesial temporal lobe seizure during their hospitalization, of which 23 patients were included in the present study (Fig. 1).

Of the included patients, 17 (74 %) were female, and the median age was 36 [33; 49]. The overall population characteristics are detailed in Table 1. The most prevalent etiologies of epilepsy were unknown and structural with hippocampal sclerosis, each affecting 10 patients (43 %). Ten patients (43 %) had right mTLE while 13 patients (57 %) had left mTLE. The epileptic focus was confirmed *a posteriori* by SEEG in eight patients (35 %) (four patients with left mTLE (31 %) vs. four patients with right mTLE (40 %), *p* = 0.685). Epilepsy surgery was performed in 12 patients (52 %) after their presurgical assessment (four patients with left mTLE (31 %) vs. eight patients with right mTLE (80 %), *p* = 0.036). There were no significant differences in clinical characteristics between the two groups except for epilepsy surgery and hippocampal sclerosis.

The median duration between the seizure and the selected late postictal recording was 57 min [46; 63]. This duration did not differ between the two groups (57 min [51; 67] in patients with left mTLE vs. 56 min [46; 60] in patients with right mTLE, *p* = 0.438).

## 3.2. Spectral analysis

One hour after the seizure, there was an increase in relative spectral power in the delta band over the left temporal and lateral frontal regions in patients with left mTLE (31.7 % vs. 47.2 % over T7, *p* = 0.001). This increase was associated with a concomitant decrease in relative spectral power in the alpha band over the exact same region (17.5 % vs. 12.2 % over T7, *p* = 0.013). Conversely, no significant modification was found in relative spectral power in the delta and alpha bands in patients with right mTLE (Figs. 2, 3). Moreover, patients with left mTLE showed a less pronounced decrease in relative spectral power in the beta band over the bilateral frontotemporoparietal lateral regions. (6.2 % vs. 4.4 % over FT8, *p* = 0.048; 5.4 % vs. 3.7 % over TP9, *p* = 0.043) (eFig. 3). There were no significant modifications of the relative spectral power in the theta band after the seizure in either group (eFig. 4).

## 3.3. Functional connectivity

In patients with left mTLE, as compared to the interictal period, the late postictal period was associated with a decrease in PLV in the theta band within an extended subnetwork identified using NBS (*p* = 0.039). This subnetwork mainly encompassed extensive interhemispheric connections, particularly between the frontal lobes and between the temporal and frontal lobes. It also included long-range connections mainly
<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Flowchart.
Abbreviations: mTLE, mesial temporal lobe epilepsy.</figcaption></figure>

within the left, but also within the right hemisphere (Fig. 4). In contrast, in patients with right mTLE, no significant modifications were found using NBS after the seizure.

In the alpha band, using NBS, we isolated an extended subnetwork that presented a decrease in connectivity strength during the late postictal period as compared to the interictal period in patients with left mTLE (p = 0.042). This subnetwork encompassed long-range connections within the left hemisphere, particularly between the occipitoparietal regions and the orbitofrontal region and to a lesser extent within the right hemisphere. It also included interhemispheric connections, mainly between the right parieto-occipital regions and the left temporal lobe, and between bilateral cingulate gyrus and the left frontotemporal regions (Fig. 5). No significant modifications between interictal and late postictal periods were found in patients with right mTLE.

No significant modification of the connectivity strength in the beta band was found between the interictal and late postictal periods in either group.

## 4. Discussion

The present study investigated the effect of a mesial temporal lobe seizure on electrical cortical activity and the influence of the side of seizure onset. We found that left temporal lobe seizures were associated with a lasting and extensive disruption of cortical activity. One hour after a left-sided seizure, we observed:

- Increased relative spectral power levels in the delta band over the left temporal and lateral frontal regions.

- Decreased relative spectral power levels in the alpha band over the same region.

- Widespread alterations of long-range intrahemispheric and interhemispheric connectivity in theta and alpha bands.

Conversely, we did not find significant modifications between interictal and late postictal periods in patients with right mTLE.

### 4.1. Effect of a mesial temporal lobe seizure on the cortical activity

In patients with left mTLE, our study revealed that the late postictal period is associated with a lasting disorganization of cortical activity. Specifically, regarding the relative spectral power in different frequency bands, left-sided mesial temporal lobe seizures were associated with an increase in the delta band activity and a simultaneous decrease in alpha band activity over the left temporal and lateral frontal regions. Regional delta slowing after a seizure is a well-described feature in focal epilepsies and carries lateralizing value (Pottkämper et al., 2020; So and Blume, 2010). However, its true duration remains questioned. Our findings suggest that the side of seizure onset could have an effect on this duration. The absence of significant modifications in patients with right mTLE does not definitively prove that right mTLE is not associated with lasting consequences. However, this difference between left and right mTLE aligns with previous clinical data, which suggest that seizures originating in the left temporal lobe could have a more prolonged effect than those originating in the right temporal lobe (Fakhoury et al., 1994).

We observed that this increase in the relative spectral power in the delta band was associated with a concomitant decrease in alpha band activity over the left temporal and lateral frontal regions. Our results suggest that cortical activity in this region shifts from alpha to delta following the seizure. Delta oscillations have long been associated with states of altered consciousness, such as anesthesia or generalized seizures, and sleep. However, delta activity has also been observed in awake patients in various conditions, including neurological disorders
<table><caption>**Table 1**
Clinical characteristics.</caption><thead><tr><th>Variables</th><th>Left mTLE<br>(n = 13)</th><th>Right mTLE<br>(n = 10)</th><th>p-value</th></tr></thead><tbody><tr><td><strong>Demographics</strong></td><td></td><td></td><td></td></tr><tr><td>Female, n (%)</td><td>9 (69.2)</td><td>8 (80.0)</td><td>0.660</td></tr><tr><td>Age, median [Q1; Q3]</td><td>36 [32; 46]</td><td>39 [34; 53]</td><td>0.456</td></tr><tr><td><strong>Past medical history</strong></td><td></td><td></td><td></td></tr><tr><td>Preterm birth, n (%)</td><td>1 (7.7)</td><td>0 (0.0)</td><td>1.000</td></tr><tr><td>Birth complications, n (%)</td><td>0 (0.0)</td><td>0 (0.0)</td><td></td></tr><tr><td>Febrile seizures, n (%)</td><td>5 (38.5)</td><td>1 (10.0)</td><td>0.179</td></tr><tr><td>Central nervous system infection, n (%)</td><td>0 (0.0)</td><td>0 (0.0)</td><td></td></tr><tr><td>Head trauma, n (%)</td><td>1 (7.7)</td><td>3 (30.0)</td><td>0.281</td></tr><tr><td>Family history of epilepsy, n (%)</td><td>5 (38.5)</td><td>1 (10.0)</td><td>0.179</td></tr><tr><td><strong>Characteristics of the epilepsy</strong></td><td></td><td></td><td></td></tr><tr><td>Age of onset, median [Q1; Q3]</td><td>19 [11; 30]</td><td>14 [9; 22]</td><td>0.335</td></tr><tr><td>Duration of evolution, median [Q1; Q3]</td><td>12 [9; 30]</td><td>30 [20; 34]</td><td>0.136</td></tr><tr><td>Secondary generalization, n (%)</td><td>10 (76.9)</td><td>8 (80.0)</td><td>1.000</td></tr><tr><td>Seizure frequency, n (%)</td><td></td><td></td><td></td></tr><tr><td>Monthly</td><td>8 (61.2)</td><td>3 (30.0)</td><td>0.214</td></tr><tr><td>Weekly</td><td>5 (38.5)</td><td>7 (70.0)</td><td>0.214</td></tr><tr><td>Etiology, n (%)</td><td></td><td></td><td></td></tr><tr><td>Unknown</td><td>8 (61.5)</td><td>2 (20.0)</td><td>0.090</td></tr><tr><td>Hippocampal sclerosis</td><td>3 (23.1)</td><td>7 (70.0)</td><td><strong>0.040</strong></td></tr><tr><td>Malformations of cortical development</td><td>2 (15.4)</td><td>0 (0.0)</td><td>0.486</td></tr><tr><td>PLNTY</td><td>0 (0.0)</td><td>1 (10.0)</td><td>0.435</td></tr><tr><td><strong>Seizure characteristics</strong></td><td></td><td></td><td></td></tr><tr><td>Duration (seconds), median [Q1; Q3]</td><td>71 [56; 81]</td><td>59 [51; 79]</td><td>0.598</td></tr><tr><td>Impaired awareness<sup>a</sup>, n (%)</td><td>4 (50.0)</td><td>6 (66.7)</td><td>0.637</td></tr><tr><td><strong>Anti-seizure medication during presurgical assessment<sup>b</sup></strong></td><td></td><td></td><td></td></tr><tr><td>Number of ASM, median [Q1; Q3]</td><td>2 [2; 3]</td><td>2 [2; 3]</td><td>0.971</td></tr><tr><td>Levetiracetam, n (%)</td><td>6 (46.2)</td><td>2 (22.2)</td><td>0.380</td></tr><tr><td>Lacosamide, n (%)</td><td>4 (30.8)</td><td>4 (44.4)</td><td>0.662</td></tr><tr><td>lamotrigine (Lamictal), n (%)</td><td>7 (53.8)</td><td>1 (11.1)</td><td>0.074</td></tr><tr><td>Carbamazepine, n (%)</td><td>2 (15.4)</td><td>3 (33.3)</td><td>0.609</td></tr><tr><td>Oxcarbazepine, n (%)</td><td>2 (15.4)</td><td>1 (11.1)</td><td>1.000</td></tr><tr><td>Eslicarbazepine, n (%)</td><td>0 (0.0)</td><td>3 (33.3)</td><td>0.055</td></tr><tr><td>Clobazam, n (%)</td><td>3 (23.1)</td><td>3 (33.3)</td><td>0.655</td></tr><tr><td>Others ASM, n (%)</td><td>5 (38.5)</td><td>3 (33.3)</td><td>1.000</td></tr></tbody></table>

Abbreviations: mTLE, mesial temporal lobe epilepsy; Q1, first quartile; Q3 third quartile; PLNTY, polymorphous low-grade neuroepithelial tumor of the young.

and dissociative states. Overall, delta waves are thought to have inhibitory effects, and it has been suggested that they are associated with a functional cortical deafferentation (Frohlich et al., 2021; Harmony, 2013). Available data regarding seizure termination suggest that it relies, among several factors, on an increase of inhibitory signals (Lado and Moshé, 2008). This view is supported by data from neuroimaging studies which demonstrated that the late postictal period is associated with a relative hypoperfusion lateralized to the side of seizures onset (Leonhardt et al., 2005). The associated decrease in alpha band activity over the left temporal and lateral frontal regions and the extended disruption of long-range connections in alpha band could reflect a regional functional deafferentation from widespread cortical regions.

In theta band, we observed a significant alteration of functional networks after the seizure in patients with left mTLE. The networks involved in this disorganization were clearly different from those affected by the desynchronization in alpha band. The asymmetry was less marked, and the disorganization mainly affected interhemispheric connections, particularly between the frontal and temporal lobes. While, the left frontotemporal region still appeared to be among the main regions involved, it was to a lesser extent compared to the alterations seen in the alpha band. Theta oscillations have particularly been associated to learning and memory (Karakaş, 2020). The hippocampus has been identified as a critical structure in the generation of this specific rhythm. Theta oscillations are found in distributed cortical and subcortical

regions (Karakaş, 2020). This distributed theta network has been theorized to result from a cortico-hippocampal interplay (Colgin, 2013; Karakaş, 2020). We suggest that the inhibitory mechanisms associated with the termination of the seizure could disrupt the ability of the hippocampus to integrate incoming information and to generate synchronized theta oscillations in this distributed theta network (Gollo et al., 2011).

The late postictal period was associated with a significant decrease of the relative spectral power in the beta band over the lateral frontotemporoparietal regions. This decrease was mild and more spatially extended that in alpha band. Beta oscillations have traditionally been associated with sensorimotor processing, but a wide range of other functions such as visual perception, language processing or decision-making has since been related to beta rhythm (Rassi et al., 2023). However, the exact functional significance of beta oscillations still remain unclear (Engel and Fries, 2010).

One question we could not address is whether these modifications are reversible, and if so, to what extent. Indeed, previous studies have found a correlation between disease severity and network disorganization, suggesting that network disorganization develops over time due to the recurrence of seizures (Chiang et al., 2016; Englot et al., 2016; Morgan et al., 2015; Stasenko et al., 2024). Temporal lobe epilepsy is associated with altered functional and structural interictal connectivity. Studies investigating structural connectivity in TLE have identified extensive changes among temporolimbic tracts, where this alteration was asymmetric and more pronounced on the side of the epileptic focus. Changes were also observed in more distant tracts, where alterations were bilateral (Hermann et al., 2021; Stasenko et al., 2024). Previous studies assessing FC have also found interictal disorganization of functional networks that were not restricted to the SOZ. In these studies, patients with mTLE particularly displayed decreased connectivity in default mode regions and frontoparietal association cortices (Englot et al., 2016, 2015; Haneef et al., 2014). Interestingly, the subnetworks that we identified partly correspond to these structural and functional changes observed during the interictal period. In a study a previous study, white matter changes were significantly correlated with disease duration in patients with left TLE but not in those with right TLE (Chiang et al., 2016). Another study found that patients with left mTLE exhibited more widespread and asymmetrical white matter alterations than patients with right mTLE (Kemmotsu et al., 2011). Similarly, studies using functional MRI found that left mTLE was associated with more widespread and severe alterations of connectivity than right mTLE (Chiang et al., 2016; Pereira et al., 2010). Taken together these data raise questions about the exact contribution of seizure recurrence to the progression of interictal network disorganization.

In summary, we propose a model in which the termination of a left mesial temporal lobe seizure is responsible for a prolonged inhibition and disorganization of the cortical activity in the ipsilateral frontoparietal regions. The associated cortical manifestation is the appearance of a focal delta activity. This inhibition is associated with functional deafferentation of the affected region, which, in turn, leads to alterations in long-range connectivity in alpha band between this region and widespread cortical areas. The local disorganization of the hippocampus activity disrupts its capacity to integrate information and to generate synchronized theta oscillations in a distributed theta network. Further studies are needed to confirm this hypothesis and determine if these late postictal modifications are specific to left mesial temporal lobe seizures or if they are found in other subtypes of focal epilepsy. We hypothesize that seizures are associated with modifications of the cortical activity that are not entirely reversible, that partially contribute to the progression of functional network disorganization and that vary according to the side of seizure onset. This progression could promote the development of cognitive impairments.

<footnote>a In six patients the seizure was not examined (right mTLE: 1; left mTLE: 5).</footnote>

<footnote>b One missing value The independence between the qualitative variables and the group was assessed using Fisher's exact tests. The independence between the quantitative variables and the group was assessed using Mann-Whitney U tests. Statistically significant values are highlighted in bold.</footnote>
<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Scalp distribution maps of the relative electroencephalogram spectral power in the delta band. The independence between the relative spectral power and the period was assessed using paired permutation tests. Abbreviations: mTLE, mesial temporal lobe epilepsy.</figcaption></figure>

## 4.2. Clinical implications

Our results could have important clinical implications. Indeed, we demonstrated that seizures arising from the left mesial temporal lobe are associated with a prolonged and widespread disorganization of the cortical activity. While we lack data regarding the clinical correlation of these consequences, the extent of the subnetworks altered after a left temporal lobe seizure suggests potential postictal cognitive effects that could be not entirely reversible. Indeed, previous studies have suggested that cognitive impairments are related to the disorganization of long-range networks in epileptic patients (Englot et al., 2016). It is difficult to make precise assumptions regarding the cognitive repercussions. Further studies are needed to determine the exact correlates of these modifications and to understand how they evolve over time. Should we confirm that these consequences are effectively associated with cognitive, behavioral and emotional impairments, this would have important clinical implications.

Another potential clinical implication is the risk of recurrent seizures and the progression of epilepsy. Epilepsies are regarded as network disorders. A previous study found that left-sided lesions were associated with a greater probability of developing seizures, and that in patients

with TLE, left-sided foci occurred more frequently than right-sided foci (Scott, 1985). This difference between left- and right-sided lesions could, in part, be related to the difference in the consequences of focal seizures depending on the side of onset. The occurrence of left-sided seizures could progressively alter networks, hence promoting the risk of seizure recurrence and the progression of the epilepsy. The first symptomatic seizures could act as primers and lead to the development of epilepsy, particularly when originating from the left hemisphere.

As previously stated, the absence of significant modifications between the interictal period and the late postictal period in patients with right mTLE in our sample does not definitely indicate the absence of lasting consequences of their seizure. If right mesial temporal lobe seizures are indeed associated with lasting modifications of cortical activity, these modifications may be more subtle and/or less prolonged than those observed in patients with left mTLE (Fakhoury et al., 1994). This effect of the side of seizure onset is consistent with a previous study that demonstrated a slower return to baseline in patients with left temporal lobe seizures compared to those with right temporal lobe seizures. Studies with larger samples are needed to effectively determine the effect of right temporal lobe seizures. Likewise, we did not assess the consequences of other subtypes of seizures, thus studies specifically
<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Scalp distribution maps of the relative electroencephalogram spectral power in the alpha band. The independence between the relative spectral power and the period was assessed using paired permutation tests. Abbreviations: mTLE, mesial temporal lobe epilepsy.</figcaption></figure>

assessing these other subtypes are required in order to fully understand the effect of the location of seizure onset on the cortical activity. Additionally, the use of scalp EEG data limited our ability to determine the propagation of the seizure and identify the specific anatomical structures involved in the discharge, which could also influence the consequences of the seizure.

### 4.3. Methodological considerations

The retrospective and monocentric design of our study is associated with several limitations. The EEG data were available only for a limited number of patients, thereby restricting our sample size and statistical power. Also, the difference in sample size could partially account for the absence of significant findings in right-sided seizures. Clinical data were extracted from medical records. However, the included patients were hospitalized for a presurgical assessment, with most undergoing several clinical assessments during follow-up in our unit. Thus, while the possibility of information bias exists, it is unlikely. Although the monocentric design limits the generalizability of our findings, the clinical characteristics of our sample align with the standard profile observed in patients hospitalized for presurgical assessment of focal epilepsy. The

significantly different characteristics between the two groups were hippocampal sclerosis and epilepsy surgery which were more frequent in patients with right mTLE. The difference in epilepsy surgery after the presurgical assessment is likely explained by the side of seizure onset. Indeed, left temporal lobe resections carry the greatest risk regarding cognitive outcomes particularly on language functions (Sherman et al., 2011). The difference in the proportion of hippocampal sclerosis is probably directly related to this difference in epilepsy surgery. Indeed, a considerable proportion of patients with left mTLE had unknown epilepsy, while several studies have reported that hippocampal sclerosis accounts for 20 to 30 % of cases in MRI-negative TLE (Muhlhofer et al., 2017). Higher prevalence of hippocampal sclerosis in patients with right mTLE may also indicate a more localized pathology and could contribute to the observed asymmetry in seizure impacts.

Another limitation of our study is the lack of video recordings to precisely determine the activities of the patients during the selected EEG segments. However, we mitigated this limitation by carefully examining the EEG data visually and selecting awake periods devoid of major movements or muscular artifacts. This approach aimed to minimize the likelihood of activities such as walking or speaking occurring during the selected recordings. Furthermore, functional brain networks exhibit
<figure><img src="image_7.png" /><figcaption>**Fig. 4.** Functional subnetwork that presented a significant decrease in electroencephalogram connectivity strength during the late postictal period in the theta band in patients with left mTLE.</figcaption></figure>

Network-based statistics were employed to assess the independence between the functional networks and periods. The subnetwork was thresholded to display only the most significant edges within this network (corresponding to a *p*-value < 0.01). Abbreviations: mTLE, mesial temporal lobe epilepsy.

<figure><img src="image_8.png" /><figcaption>**Fig. 5.** Functional subnetwork that presented a significant decrease in electroencephalogram connectivity strength during the late postictal period in the alpha band in patients with left mTLE.</figcaption></figure>

Network-based statistics were employed to assess the independence between the functional networks and periods. The subnetwork was thresholded to display only the most significant edges within this network (corresponding to a *p*-value < 0.01). Abbreviations: mTLE, mesial temporal lobe epilepsy.
high stability across different states, with macroscale networks persisting over various conditions, while experiencing only modest changes related to task-state variability (Gratton et al., 2018).

## 4.4. Conclusion

In summary, we found that left temporal lobe seizures are associated with prolonged and widespread consequences on cortical activity. We propose a model in which the postictal state is associated with alterations in cortical activity that could promote the progression of functional network disorganization. Further studies are needed to fully understand these consequences and their cognitive repercussions.

## Funding sources

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

## CRediT authorship contribution statement

**Mathieu Dhoisne:** Writing – review & editing, Writing – original draft, Methodology, Formal analysis, Data curation, Conceptualization. **Nacim Betrouni:** Writing – review & editing, Methodology, Formal analysis, Conceptualization. **Sophie Hennion:** Writing – review & editing, Methodology, Conceptualization. **Lucie Plomhause:** Writing – review & editing, Methodology, Conceptualization. **Arnaud Delval:** Writing – review & editing, Methodology, Conceptualization. **Philippe Derambure:** Writing – review & editing, Methodology, Conceptualization.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.neuroimage.2024.120975.

## Data availability

Data will be made available on request.

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