EEG spectra and glial transformations following seizures induced in rats pretreated with systemic inflammation at two developmental stages

EEG spectra and glial transformations following seizures induced in rats pretreated with systemic inflammation at two developmental stages | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 15 August 2025 V1 Latest version Share on EEG spectra and glial transformations following seizures induced in rats pretreated with systemic inflammation at two developmental stages Authors : Krzysztof Janeczko 0000-0002-9544-918X [email protected] , Emilia Kosonowska , and Zuzanna Setkowicz Authors Info & Affiliations https://doi.org/10.22541/au.175525576.63673895/v1 211 views 136 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract We examined the extent to which reactive glial transformations correspond to the degree of seizure reactivity in adult rats after experiencing inflammation at different developmental stages. In 6- or 30-day-old rats, systemic inflammation was induced with lipopolysaccharide (LPS). At the age of two months, the LPS-treated rats and controls were implanted with EEG teletransmitters and seizures were induced with pilocarpine. Before and during the seizures, EEG recordings were performed and changes in EEG spectra and intensity of behavioral seizure symptoms were analyzed. Brain sections were immunostained for GFAP and Iba1 to visualize astrocytes and microglia, respectively, and ramification degrees of their processes were assessed. No significant effects of the generalized inflammation alone evoked at any developmental stage were observed in EEG recordings in adulthood. Then, seizures were induced with pilocarpine and significant changes appeared in EEG spectra depending on the age of LPS application. In the same respect, significant correlations were detected between the degrees of ramification of astroglial or microglial processes and the power of EEG signal and/or its particular frequency bands. Thus, the initial effects of inflammation remained undetected up till adulthood and became revealed with a “second hit”procedure using pilocarpine as a seizuregenic factor. As revealed by correlation analyses, the effects were strongly reflected by the degree of astrocyte transformations and considerably weaker by microglia. These results indicate a strong, possibly causal involvement of glial reactivity in long-term functional changes in the brain following general inflammation at different developmental stages. Introduction Previous research shows that inflammation may be both a result and a cause of an increase in the brain susceptibility to seizures (Vezzani et al. , 2011; Vezzani and Viviani, 2015). Our previous studies (Kosonowska et al. , 2015; Setkowicz et al. , 2017; Janeczko et al. , 2018) showed that inflammation induced by LPS administration at different developmental stages may lead to various long-term changes in propensity to seizure activities persisting until full adulthood, so it could be considered irreversible. In brains with such altered excitability, even before the seizure induction, changes of microglia and astrocyte morphology were found, but to a relatively small extent (Kosonowska et al. , 2015; Setkowicz et al. , 2017). Such changes, even around the threshold of detectatility, could reflect functional status of glial cells related to neuronal excitation (Baldwin et al. 2024; Reddaway et al., 2023) and, consequently, to susceptibility to seizures. In the present study, the seizures were evoked with pilocarpine administered a long time time after the inflammation had disappeared. Therefore, the inflammatory status did not appear to have a direct causative meaning here, but its long-term effects. Some of these effects might correspond with the transformation of glial cells (Kosonowska et al. , 2015; Setkowicz et al. , 2017). The extent of these transformations varied between experimental groups of animals, so it could be responsible, in part at least, for the differences in seizure excitability depending on LPS administration at different developmental stages. To demonstrate that the level of general seizure susceptibility varied with the degree of glial transformation (a „dose-dependent” relation) we analyzed correlations between these phenomena, where each of them might be the cause or the effect in their interrelationships. Changes in the correlations inform how previous LPS treatment mofify thse relatioships. Much more interesting is confirmation of similar relationships between glial transformations and changes in the intensity of particular bands of EEG spectra. In addition to the relatively small extent of glial cell transformations evoked by administration of LPS alone, the much later seizure induction in the mature brain indicated the possibility of permanent functional changes which, although still undetected, might underlie significant modification in overall brain excitability. Using pilocarpine administration as the „second hit”, significant relations between variabilities in the EEG spectra and in transformations of glial cells were revealed, secondary to those which resulted from administration of LPS alone. Without the seizuregenic stimulus, these relationships would never be observed. 2. Material and methods Animals All experimental procedures were compliant with the European Communities Council Directive (2010/63/EU) and were approved by the Animal Care and Use Committee of the Jagiellonian University (decision no.122/2011). Pregnant Wistar rats were housed in individual cages under conditions of controlled temperature (20 ± 2◦C) and a 12/12 h light/dark cycle. Standard laboratory feed (Labofeed) and water were available ad libitum. The females were allowed to give birth. Within 24 h postpartum, the litters were reduced to 10 with preference to males. On postnatal days 6 or 30, the male rats (P06s and P30s, respectively) were injected intraperitoneally with lipopolysaccharide (LPS, serotype 026:B6; Sigma L3755, 2 mg/kg b.w.) dissolved in 0.9% NaCl solution. This was a moderate dose, compared to those used in similar studies on rats (from 0.002 to 10 mg/kg, Hoogland et al. 2015). Blood samples were obtained from the animals before and 2, 4, 6, and 24 h after the LPS injection. Thereafter, serum levels of TNFα and IL-6 were determined using commercial ELISA kits (Kosonowska et al. , 2015). Remote EEG recordings At the age of 55 days, the male rats were implanted with EEG teletransmitters under anesthesia with 2 to 4% inhaled isoflurane (Aerrane, Baxter) in oxygen. An incision was made in the skin on the side and a portable rodent telemetry transmitter (TA11CTA-F40 Implant, Data Sciences International) was inserted under the skin. Two biopotential leads (positive and reference) were guided toward the animal’s head subcutaneously. A hole for the recording lead was drilled 1.0 mm posterior to the Bregma and 3.0 mm left to the midline, over the primary somatosensory cortex for fore- and hindlimbs (Paxinos and Watson, 1986). For the reference lead, a hole was located over the cerebellum, on the midline and 10.5 mm posterior to the Bregma. The leads were placed on the exposed dura, held in place with dental cement (Duracryl Plus, Spofa Dental), and the skin above the cement cap was sutured. The surgeries were carried out in aseptic conditions, and animals were given proper postoperative care. Antibiotics (Sul-Tridin, Norbrook Laboratories Ltd) and nonsteroid anti-inflammatory drug (Tolfedine, Vetaquinol SA) were administered. After surgery, rats were placed in single cages and given 2 weeks recovery before further experimental procedures. At two weeks after the surgery, on the postnatal day 70, 6h-lasting EEG control recordings were performed at 500 Hz sampling rate in all animals using a DSI receiver plates and DSI acquisition software. The 6h recordings were repeated two days later, starting from the moment of pilocarpine injection. Fig. 1 shows the experimental scheme and animal numbers in each EEG-implanted group. Raw EEG data were transferred into the Spike2 program, which was subsequently used for further analysis. Based on initial inspection of the waveforms, an amplitude window was selected and all activity crossing the threshold was marked in a separate event channel. This was followed by a second round of visual inspection, during which any additional artifacts missed by the initial procedure were marked. Our initial observations suggest that the main sources of artefacts were: animal motion (such as chewing, scratching) and momentary loss of wireless signal, resulting in sharp, very high-power spikes with extreme amplitude. All signals in 10-sec time windows from any marked artefact were excluded from further analysis. Excluded were also recordings from animals in which contamination of the signal with electrocardiographic noise, likely due to mechanical damage to the insulation of the biopotential leads, was detected. The resulting signal was processed with fast Fourier transform with a Hanning window of width=256, corresponding to 128 bins of width=1.953 Hz and epochs of 0.5 second. Frequencies from approximately 2 to 65 Hz were used for further analysis. Principal component analysis (PCA) was performed in the frequency domains with relative spectral densities over the entire sampling period (32 total input variables, each corresponding to a single bin obtained from fast Fourier transform). The rationale was that adjacent frequencies that vary together form EEG bands. The first two components obtained from PCA contained 89.2% of the cumulative variance: 72% for the first and 17.2% for the second component, respectively. Component loadings were then examined: concurrent variables (corresponding to adjacent EEG bins) with similar loadings for the first two components were grouped together. Similarity was defined as loadings having the same sign (positive or negative, with values above 0.1) or near-zero (value<0.1). As a result, empirical bands were constructed which corresponded to physiological bands defined in humans: “delta” (approximately 2–4 Hz), “theta” (approximately 6–8 Hz), “alpha” (approximately 10–16 Hz), “beta” (approximately 18-32 Hz) and “gamma” (approximately 34–65 Hz). We then normalized the signal in each band to the sum of all bands. This relative power metric was taken as a measure of the contribution of the specific band to the overall activity. In the text below, acronyms AP and RP placed before the names of particular frequency bands indicate that their absolute or relative power is considered. For example AP Alpha and RP Alpha indicate, respectively, the absolute and relative power of Alpha frequency band. Numbers of animals included in each analysis are shown in appropriate figures. Seizure induction Seventy two-day-old LPS-treated and untreated rats (controls) were injected intraperitoneally with pilocarpine (250 mg/kg b.w., Merck P6503) to evoke status epilepticus. Scopolamine methyl bromide (1 mg/kg, Sigma S8502) was injected i.p. 30 min prior to pilocarpine to reduce its peripheral effects. Pilocarpine was injected between 9 and 10 a.m. to avoid circadian effects of seizure vulnerability. To reduce a relatively high mortality (Curia et al. , 2008) of the animals implanted with EEG transmitters, the pilocarpine dosage used here was lower than that in our previous studies (300 mg/kg, Setkowicz et al. 2003; 2005a; 2006) or, for example, in studies by Covolan and Mello (2000; 350 mg/kg) or Turski et al. , (1983; 400 mg/kg). Thus, all the animals survived the procedure in good condition. Assessment of behavioral seizure symptoms The above model of epilepsy in adult rats has three distinct phases: (i) an acute period of status epilepticus, (ii) a silent period of a progressive normalization of EEG and behavior, and (iii) a chronic period of spontaneous recurrent seizures (Curia et al. 2008). In the present study, we focused on the first 6 h of the acute period of status epilepticus. During that six-hour period following the injection (acute period of status epilepticus), each animal was continuously observed without knowledge of their previous experimental treatments. The intensity of motor manifestations of seizure activity were rated on a previously used six-point scale with respect to characteristic symptoms and their intensity (Setkowicz et al. 2003; 2005a,b; 2020): (a) Light symptoms: 0.5—immobility, piloerection, salivation, narrowing of eyes, face and vibrissae twitching, ear rubbing with forepaws; 1.0—head nodding and chewing movements. (b) Intermediate symptoms: 1.5—clonic movements of forelimbs, and mild whole body convulsions, exophthalmia, aggressive behavior; 2.0—rearing and running with stronger tonic–clonic motions including hindlimbs, tail hypertension, lockjaw; (c) Heavy symptoms: 2.5—rearing and falling, eye congestion; 3.0—loss of postural tone with general body rigidity. The maximal intensity of seizures was rated in each of the successive 10-minute periods within the whole 6 h of the observation time. The recorded scores were summarized separately for each animal and indicated with a symbol 6h SUM SE further in the text. Animal sacrifice and tissue processing Three days after seizure induction, the rats (75 days old) were sacrificed by a lethal dose of pentobarbital and perfused transcardially with 0.9% NaCl followed by 10% formalin in 0.1 M phosphate buffer, pH 7.4. Brains were removed, postfixed for several days and sectioned into 30-μm-thick coronal slices on a vibratome (Leica). Control rats of the same age but not experiencing seizures were subjected to the same procedure. In free-floating sections, astrocytes and microglia were immunostained for GFAP (DAKO, Z0334, 1:2000, Fig. 2) and Iba1 (Wako, PDN2194, 1:2000, Fig. 3), respectively, combined with Vectastain Elite ABC Universal kit (PK 6200; Vector Lab., 1:50) and mounted on slides. To check specificity of the antibodies, some sections were processed after omitting the primary antibody. No unspecific staining was detected. Glial morphology analyses Images of randomly selected immunopositive astrocytes or microglia, located within the Ammon’s horn CA3 sector (CA3, at the depth from stratum oriens to stratum radiatum) and dentate gyrus (DG, at the depth from molecular layer to polymorphic layer) were collected with a digital camera set on a microscope (Nikon Microphot SA, magnification 400x). Each of the cells was represented by a subset of images taken at different focusing planes. The images were split into three RGB channels and the green channel was thresholded, binarized and processed by a two-step cleaning algorithm including size-based particle exclusion (FIJI/Image J free sofware) and manual pruning of overlapping processes coming from neighboring cells. The obtained binary silhouettes of the cells resulting from combining of image sets were skeletonized for precise counting of cell processes and/or their endings (Young et al., 2018) (Figs 2 and 3). For astroglial or microglial cells, subsets of at least 100 cell profiles were analyzed in the areas for each examined animal group. Astrocytes were morphologically analyzed according to the previously used method (Setkowicz et al. , 2017). The astrocyte processes, due to the relatively large extent, were very frequently interdigitated with processes originating from neighboring astrocytes, especially between their postseizure, reactive forms (Ogata and Kosaka, 2002; Wilhemsson et al. , 2006; Oberheim et al., 2008; Codellupi et al., 2021), and delineation of their complete morphological profiles was not precise and resulted with unreliable assessments of their ramification. Therefore, on the astrocyte images, two circles 25 and 50 μm in diameter were centered on each astrocyte cell body (Fig. 2 B-D and F-H) and intersections between the circles and the astrocyte processes were counted manually. To evaluate their ramification, the branching index (BI) was calculated as the ratio between numbers of intersections with the outer and inner circles (Setkowicz et al. , 2017; Green et al., 2022). When compared to astrocytes, processes of microglial cells occupied significantly smaller areas overlapping each other to a much lower extent (Fig. 3). Therefore, morphological changes of their processes could be assessed as in our previous studies (Oderfeld-Nowak et al. , 2003; Kosonowska et al. , 2015; Sołtys et al. , 2001; 2005) using the ramification factor (RF) which is the ratio between the number of terminal endings and the number primary processes. For each cell profile resulting from the procedure, the ramification factor was calculated. Statistical analysis Most of statistical analyses were performed with STATISTICA software (Statsoft, Inc.) with the exception of exploratory PCA used for informing the choice of EEG bands, which were performed in R. Normality of data and homogeneity of variance were checked with the Shapiro–Wilk and Levene’s tests, respectively. Because of non-normal distribution of the data, Kruskal–Wallis with Mann–Whitney post hoc tests were used. Spearman’s rank coefficients of correlation were calculated for interrelations between parameters of seizure intensity and parameters of cellular processes ramification. The level of statistical significance was set at 0.05. However, p-values within the range 0.05–0.1 were also shown, although in brackets. The sample size of rats necessary to detect a difference of 15% with a power of 80% and alpha 0.05 (Serdar et al. , 2020) was estimated using variance values obtained in previous analyses (Setkowicz et al. 2014; 2020). Behavioral symptoms of seizures Observations of behavioral seizure symptoms within 6 hours after pilocarpine administration to mature animals showed significant intergroup differences (Fig 4). Relative to the control group, the number of 10-minute periods in which seizures were observed, regardless of their intensity, was significantly lower in L06 SEs (p<0.009, Fig. 4A), but much more lower in L30 SEs (p<0.0006). This is expressed by a significant difference between these two groups (p<0.02). Fig. 4B shows that in L30 SEs, the sum of the seizure severity scores that occurred in each of the subsequent 10-minute periods in each hour was lower than in controls, and these differences reached statistical significance at the 1st, 4th, and 6th hours of observation. (p values 0.002, 0.02 and 0.02, respectively). The intensity of seizures in L30 SEs, compared to those observed in L06 SEs, was significantly lower at hours 1, 3, 4, 5 and 6 (p values 0.02, 0.03, 0.006, 0.008 and 0.002, respectively). In L06 SEs, the course of seizures never differed from controls. Fig. 4 C summarizes the data on seizure intensity from the entire observation period and shows its significant reduction in L30 SEs, both in relation to the controls (p<0.03) and L06 SE (p<0.004). Changes in EEG spectra Examples of EEG recordings and power spectra referring to six hour periods before and after pilocarpine injection are presented in Fig 5. Characteristic, clear differences between the EEG recordings of normal and seizure-experiencing rats could easily be seen. However, significant intergroup differences resulting from prior LPS treatments could only be detected using statistical analyzes of the EEG spectra but could not be illustrated by convincing graphs. Before pilocarpine administration (Fig. 6 B-C, gray boxes), groups of mature animals administered LPS at P6 or P30, when related to controls (Fig. 6 A) did not show significant changes in the relative power (RP) of individual bands (contribution of individual bands to the total power of the EEG spectrum). The pilocarpine administration caused increases in the total power of EEG signal in each group but maximal in controls (p<0.02 vs. L06 SEs, Fig. 7A). Also, the controls showed the greatest variations between individual bands. In AP Beta the increases were maximal and higher than in AP Theta (p<0.01) or AP Gamma (p<0.002, Fig. 7 B). L30 SEs also showed an increase in AP Beta, greater than in AP Theta (p<0.02) and AP Gamma (p<0.01, Fig. 7 D). However, in L06 SEs there was no such significant difference between individual bands, although a similar profile of changes was maintained (Fig. 7 C). Consequently, RP Beta also increased in each group (p<0.02 or 0.01, Fig. 6 A-C, black boxes). Additionally, RP Alpha increased (Fig. 6 A, p<0.02) and RP Theta decreased (p<0.03) in the control group and RP Theta decreased in L30 SE (Fig. 6 C, p<0.01). Changes in EEG spectra vs. seizure behavioral symptoms For data from all groups taken together, increases in the total power of EEG signal were significantly correlated with the intensity of behavioral seizure symptoms measured as MAX SE (Fig. 8 A1, r=0.710, p<0.0001) and 6h SUM SE (Fig. 8 B1, r=0.509, p<0.01). For particular EEG bands, these correlations were very similar (Figs. 8 A 2-6 and B 2-6). In the control group (N SEs), analyzed separately, MAX SE was significantly correlated only with increases in AP Gamma band (r=0.777, p<0.04, Fig 9 A6). In L06 SEs, unlike the control group, MAX SE was strongly correlated with increases in the power of total EEG signal (r=0.868, p<0.005, Fig. 9 B1) and of each of EEG bands (Fig. 9 B2-6). In the case of L30 SEs, analogous significant correlations were also detected for the power of total EEG signal (r=0.720, p<0.02, Fig. 9 C1) and only for AP Delta (r=0.720, p<0.02), AP Theta (r=0.775, p<0.009) and AP Alpha (r=0.665, p<0.04, Fig. 9 C2-4). The intensity of seizure symptoms were poorly reflected by changes in relative power of particular EEG bands. No significant correlation occurred in the control group. In L06 SEs, only RP Theta was correlated with both MAX SE and 6h SUM SE (r=0.715, p<0.05 and r=0.731, p<0.04, respectively, Figs. 10 A, B). In L30 SEs, no significant correlation between the phenomena was detected (Fig. 10 C, D). Transformation of astrocytes vs. EEG spectra In L06 SEs, a very high positive correlation was detected between increases in the total power of EEG signal and the branching index of astrocyte processes in CA3 (r=0.886, p<0.02, Fig. 11), but not in DG. For the absolute power of each of the four EEG bands, except Delta, the correlations were very similar. Differently, in L30 SEs, the branching index in CA3 correlated positively with increases in the total power of EEG signal (r=0.661, p<0.04, Fig. 12 A), but also separately with AP Delta, AP Theta and AP Gamma (r=0.709, p<0.02; r=0.721, p<0.02 and r=0.661, p<0.04, respectively, Figs. 12 B, C, F). There were no significant correlations for AP Alpha and AP Beta (Fig. 12 D, E). The control group did not show any significant correlation in this respect. Additionally, in L06 SEs, RP Alpha and RP Beta correlated negatively with the branching index (r=-0.829 and -0.820, respectively, for both p<0.04, Figs. 13 A and B). Transformation of microglia vs. EEG spectra L06 SEs showed significant positive correlations of the microglia Ramification Index with increases in RP Delta (r=0.833, p<0.01 and r=0.929, p<0.0009, respectively for CA3 and DG, Figs. 14 A and B). On the contrary, changes in RP Gamma negatively correlated with values of this index (r=-0.810, p<0.02 and r=-0.762, p<0.03, for CA3 and DG, respectively, Figs. 14 C and D). Discussion In our earliest studies in this field (Setkowicz et al. , 2003), a mechanical brain damage in 30-day-old rats greatly increased their susceptibility to seizures induced with pilocarpine in adulthood. However, a similar injury in 6-day-old rats had no such long-term effects. It was then assumed that this was due to age-dependent differences in reactive inflammatory processes initiating formation of seizuregenic glial scar, which, in turn, interfered with normal neuro-glial interactions and increased neuronal excitability. Later (Kosonowska et al. , 2015, Setkowicz et al. , 2017), we investigated the effects of inflammation alone, without a brain damage, induced by a single 2 mg/kg dose of LPS administered peripherally at the same two developmental stages. Microglial cells in the hippocampal formation showed morphological changes in their solidity, circularity and ramification index depending on the age of LPS administration (Kosonowska et al. , 2015). In the same model, significant changes in the degree of branching of astrocyte processes were demonstrated (Setkowicz et al. , 2017). However, possible correlations of such changes with bioelectrical seizure activity of the brain and corresponding behavioral seizure symptoms have never been investigated. Systemic LPS administration results in generalized activation of the immune system and increased the levels of inflammatory cytokines such as TNFα, IL1β or IL-6 and their mRNAs as well as free oxygen radicals, cell adhesion factors or acute phase proteins (Ho et al. al., 2015; Kosonowska et al. , 2015; Catorce et al. , 2016; Mallard et al. , 2018), and finally in appropriate responses of non-neuronal cells. In the rats at the first postnatal week, as in our study, gliogenesis is of high intensity (Bland et al. , 2010) and then declines up to the end of the first postnatal month, as the age of second animal group examined here. In rodents, at about the first postnatal week, the majority of nerve cells has already been produced. Thus, LPS-induced inflammation could interfere with the ongoing programmed cell death (Pang et al. , 2016) and might also have long-term effects on neurogenesis occurring within the hippocampal formation (Bayer et al. 1993; Quinn, 2005; Bandeira et al. 2009; Smith et al. , 2014; Liang et al. , 2019). It resulted also in aberrant neural connections, modified neuron-glia and brain-blood barrier relationships (Isbrandt et al. , 2017), and activation of microglia in different brain regions, including the hippocampal formation (Bland et al. , 2010; Pang et al. , 2016, Smith et al. , 2014). Maturing astrocytes are also sensitive to inflammatory stimuli (Shen et al. , 2016). While they mediate the formation of GABA inhibitory synapses in the normal, developing hippocampus (Liang, 2019), their reactive forms lose this ability due to changes in morphology, proliferation and molecular expression (Liddelow et al. , 2017). Therefore, the GABAergic system in the hippocampus may be impaired (Lin and Wang, 1014; Liang et al. , 2019). Additionally, neonatal LPS injection may affect axonal myelination (Huang et al, 2020). Because of different experimental designs, contradictory results have been reported (Luo et al. , 2021; Pang et al. , 2016). However, any deviation (either progressive or regressive) in the neuronal development program can be detrimental to neural networks and lead neurobehavioral abnormalities in adulthood (Dinel et al. , 2014). Critical periods during the development are important for the magnitude of the effects of LPS-induced inflammation (Luo et al. , 2021; Wasterlain et al. , 2013). At the postnatal day 30, the brain may be called “postmitotic” (Wasterlain, 1973) since neurogenesis had already been completed and quantitative neuron-glia relationships are basically fixed. In this respect it can be compared to the mature brain. Studies of the LPS effects on neurogenesis in the mature brain are usually limited to the hippocampal formation, where neurogenesis still continues. LPS-induced inflammation may also suppress neurogenesis in this region and lead to long-term memory impairments (Perez-Diominingues at al., 2019; Valero et al. , 2014). The glial reactivity becomes much more intense in adulthood (Janeczko, 1988, 1989; 1994) with significant functional impacts on the neuronal system (Alzahrani et al. , 2022; Zhao et al. , 2019). In the mature rat brain, hippocampal microglia can be activated even 3 hours after LPS administration and may return to the resting state in 7 days (Perez-Domingues at al., 2019). The initial microglial response is considered neuroprotective, while its subsequent, enhanced response may impair synaptic transmission (Sheppard et al. , 2019) and trigger neurodegeneration (Ye et al. , 2020), break the mature blood-brain barrier and promote invasion of exogenous cells into the brain (Zhang et al. , 2022). The level of astroglial and microglial involvement in response to the brain inflammation may be reflected by their transformations, indicating changes in their relationships with neurons increasing brain excitability (Baldwin et al., 2024; Reddawy et al., 2023). Functional importance of these long-term initial effects might remain undetected in the adulthood, but could be revealed with a “second hit” such as a seizure-inducing procedure. The seizures may evoke further, but this time detectable changes in glial cell morphology, reflecting their effects on brain excitability, i.e. increased susceptibility to seizures. Significant correlations between these phenomena may suggest casual relations. In the present study, after induction of transient, generalized inflammation by LPS administration on the postnatal day 6, the susceptibility to seizures induced with pilocarpine in adulthood was significantly greater than when LPS was applied at the age of 30 days. Taking into account their possible functional consequences, we initially focused on age-dependent changes in the morphology of microglia (Kosonowska et al. , 2015) and astrocytes (Setkowicz et al. , 2017) which can also be the basis for reactive volumetric changes of the entire brain and its regions (Janeczko et al. , 2018). It should be emphasized that these changes had been detected in the mature brain when the inflammatory reaction had long ended, as indicated by IL-6 and TNFalpha concentrations dropped to normal levels within a week (Kosonowska et al. , 2015). The primary, post-inflammatory cell transformations, in part at least, could determine differently seizure reactivity of the mature brain depending on the developmental stage at which LPS was administered. Consequently, these primary transformations induced by LPS alone were superimposed by the secondary ones, i.e. those evoked with seizures, and made detection of their summarized effects easier. Commonly, the cytoskeletal arrangement is taken as representing the astrocyte morphology, whereas GFAP immunohistochemistry reveals only about 15% of its total volume (Bushong et al., 2002). In the normal brain, the astrocyte processes ramify within largely separate areas overlapping in relatively small zones. In the reacive astrocytes, the thickness, length, number, and extent of GFAP+ processes increase and can penetrate entire domains of neighboring astrocytes. Oberheim et al. (2008) observed that the loss of individual astrocyte domains was accompanied by a reduction of spines in apical dendrites of pyramidal neurons, whereas hypertrophy of astrocytes that retained their individual domains was associated with an increase in the density of dendritic spines. These changes, in concert with dendritic sprouting and new synapse formation, may form the structural basis for recurrent excitation in the epileptic brain. Association of the changes with disturbances in the brain bioelectric activity were also suggested. The precise delineation of overlapping astrocytic domains was possible only by different individual labeling of neighboring astrocytes (Bushong et al., 2002; Ogata and Kosaka, 2002). Thus, GFAP immunohistochemistry not only reveals a part of the true astrocyte processes, but also limits the distinction of the origin of processes in overlap areas. Therefore, the visible profiles are only a sample the true pattern. In pathological conditions the astroglial domains overlap each other at much greater extent. For this reason, our measurements were limited to the relatively closer vicinity of the astrocyte cell body since the process of reactive changes would increase areas of uncertain asessments. With such limitations, the present study managed to detect an association of reactive changes in astrocyte processes with EEG changes and behavioral manifestations of generalized seizures. Oberheimer et al. (2008) draw attention to the frequency of epileptiform activity observed in their study. Pharmacological reduction of seizures simultaneously reduced the zone of interdigitating astrocyte processes. The present study attempted to establish the relationship of astrocytic changes not only with general EEG abnormalities but also with individual EEG bands. Similarly to astrocytes, branching areas of neighboring microglial cells also overlap but at minimal extent (Brawek et al., 2021). Iba1 is the most commonly used marker of microglia cells (Jurga et al., 2020) sufficiently delineating their profiles in resting in reactive states. In pathological conditions microglial processes penetrate astrocytic domains without restrictions (Kettemann et al., 2013) being involved in modeling neuronal connections (Nebeling et al., 2023) and expressing different genes (Dadwal and Heneka, 2023). Neuronal activity increases the level of their branching (Brawek et al., 2021; Nebeling et al., 2023). In response, microglia can change the structure of neuronal connections and thus the excitability of neuronal systems (Guedes et al., 2022). Despite the data on the close astro-microglial cooperation, including mutual influences on morphology (Matejuk and Ransohoff, 2020; Zhang et al., 2020), in this study, no correlation of between morphological responses of the two cell types was demonstrated. Correlation between microglial transformations and EEG was also very weak. The relationships between the type of astro-microglial interactions and neuronal function, remain unclear (Vidal-Itriago et al., 2022; Handy et al., 2023). Numerous functional consequences of post-inflammatory changes have already been reported (Mallard et al. , 2011; Zhao et al. , 2019; Beyer et al. , 2020; Kealy et al. , 2020; Alzahrani et al. , 2022). Inflammation, even if eripherally induced, increases the brain seizure susceptibility (Ho et al. , 2015), which in turn intensifies inflammation and leads to further changes in microglia and astrocytes, also of an epileptogenic nature (Vezzani and Viviani, 2015). If insufficient to trigger seizures themselves, they can be detected indirectly as an increased sensitivity to seizuregenic stimuli. In the present study, LPS administration alone at either P6 or P30 did not change the absolute or relative power of any of EEG bands analyzed in adulthood (Fig. 6, gray boxes). Thus, in this respect, long-time LPS effects would remain undetected. However, after seizure induction, the total power of EEG signal increased differently as well as the intensity of seizure behavior. In controls (Fig. 6A), the increase in AP Beta clearly dominated over those in the remaining four bands (Fig. 7B). In L30 SEs this profile was much less pronounced (Fig. 7D) but in L06 SEs was statistically insignificant (Fig. 7C). Consequently, pilocarpine-induced seizures evoked changes in relative power of particular EEG bands (Fig. 6, differences between gray and black boxes). The controls showed a decrease in RP Theta, and increases in RP Alpha and RP Beta (Fig. 6A). In L30 SEs, a similar reduction in RP Theta was accompanied by an increase in RP Beta (Fig. 6C) but RP Alpha and RP Beta underwent further reduction when related to the controls. L06 SEs showed an increase only in RP Beta (Fig. 6B). Concerning the data taken together from all the examined animals, there were obvious positive correlations between the intensity of behavioral seizure symptoms (MAX SE and 6h SUM SE) and the total power, and particular bands of EEG signal (Fig. 8). Intergroup differences were additionally revealed. In N SEs (Fig. 9A), significant correlation occurred only for AP Gamma without a similar trend in the remaining bands. Conversely, in L30 SEs (Fig. 9C), significant correlations were missing for AP Gamma and AP Beta but not for lower EEG frequencies. L06 SEs (Fig. 9B) showed very high correlations between the intensity of maximal seizures (MAX SE) and the power of total EEG signal including the absolute power of each EEG band. When changes in RP of individual bands were related to the intensity of seizure behavior (Fig. 10), high positive correlations were detected only for RP Theta, typical of hippocampal activity, but exclusively in L06 SEs. Thus, it could generally be concluded that the correlations characterize the scale of animal seizure behavior as a useful tool in this study. Since glial cell transformations are closely related with epileptic seizures, we examined if they were correlated with the brain seizure activity and how this correlation depended on the developmental age at which generalized inflammation was induced. Concerning the astrocyte reactive transformation, increases of their Branching Index in L06 SEs, but exclusively in CA3, were very strongly positively correlated with increases in the total power of EEG signal (r=0.886, Fig. 11) but negatively with RP Alpha and RP Beta (r=-0.829 and -0.820, respectively Fig. 13). Thus, the astrocyte reactivity to particular EEG frequencies in the seizure-experiencing brain activity may display diverse and supposedly specific patterns. In L30 SEs, also exclusively in CA3, the results were different. High positive correlations were detected between the Branching Index and the total power of EEG signal and with AP Delta, AP Theta and AP Gamma, but not with AP Alpha and AP Beta (Fig. 12). With respect of microglial response in L06 SEs, increases of the Ramification Index, both in CA3 and DG, were accompanied by increases in RP Delta and decreases in RP Gamma (opposite correlations with different EEG frequencies, Fig. 14). Again, the relationships seem to be rather specific, as they did not occur with respect to changes in the power of total EEG signal. It should, however, be noted that the typical morphological reactivity of astrocytes differs significantly from that of microglia. Under pathological conditions, astrocytes develop branching of their processes, while microglial transformations tend to reduce their processes towards macrophage-like forms. In fact, in the case of microglia, increases in RP Gamma were accompanied by decreases in the Ramification Index. However, at the same time, increases in RP Delta corresponded to opposite, rather unexpected increases of the Index. It can, therefore, be assumed that RP Gamma had a typical pathogenic influence on the microglia reactivity. Iaccarino et al. (2016) and Bobola et al. , (2020) reported reactive transformation and phagocytosis of microglia stimulated with gamma frequency in the mouse brain. Although the changes in the EEG spectral profile were the greatest in N SEs, they were not reflected by changes in seizure behavior or by transformations of astrocytes or microglia. In contrast, these associations were most clearly marked in L06 SEs although the seizure patterns did not differ from those in the controls. Bilateral relations between glia transformations and EEG spectra, especially in respect of particular frequency bands are still poorly explored and hypothetical (Guan et al. , 2022; Andrade-Talavera et al. , 2023). Thus, the detected intergroup differences in seizure reactivity (behavioral and electrophysiological) are not easy to explain. LPS-induced astroglial and microglial transformations and changes in neuronal and brain (Auvin et al. , 2010; Isbrandt, 2017) chacterize feedback loops between inflammation and epileptogenesis (Hernandez-Baltazar et al. , 2020; Pintado et al. , 2011; Vezzani and Viviani, 2015). Yamanashi et al. (2021) detected an LPS-induced five-day-lasting increase in the power of the low-frequency delta band (3 Hz) compared to the higher frequency (10 Hz), as an indicator of electrophysiological brain dysfunction, and postulated further studies of relationships between microglial activation and EEG changes. Similarly, Mamad et al. (2018) detected an increase in Delta frequency power relative to Theta and epileptiform discharges in the hippocampus, but not in the cortex. Sayyah et al. (2003 a, b) found an LPS dose-dependent short-term reduction in the myoclonus threshold but also an increase in seizure latency. In similar experiments, EEG disturbances were indicated by Albrecht et al. (2018) and Sultan et al. , (2021). All the above cited data concern functional effects of direct, short-term LPS influences which, however, may have much longer-lasting consequences in neuronal circuits. In the present study only its long-term indirect effects of LPS were examined, i.e. changes persisting up till full maturity. Moreover, these effects were age-dependent. The revealed significant correlations strongly suggest the existence relationships between the LPS-induced transformations of glial cells and their long-term effects on the brain seizure reactivity. Conclusions It is commonly known that peripheral inflammation has a negative impact on both the developing and mature brain, not only temporary but also long-lasting or permanent, structural and functional. Since in the normal brain glial cells provide optimal conditions for the functioning of neurons, any change in the neuron-glia relationships modifies the activity of neurons and may also increase excitability of the entire brain. The changes, when evoked at a developmental stage, may remain unrevealed by general observations of animal behavior in adulthood, but may be detected by additional procedures, such as stimulation with seizuregenic agents (”second hit”). The primary glial response to inflammation underlys changes the brain reactivity to future stimuli, in our case to seizuregenic stimulation with pilocarpine in adulthood. This is accompanied by the secondary glial response which may also be of importance to the brain activity and accelerate epileptogenesis. To the best of our knowledge, such a wide range of general relationships, including their age-dependent aspects, has never been investigated. It is seems obvious that the qualitative and quantitative scope of the changes, including the diversity of cell types their interrelationships, do not allow to directly indicate the mechanisms responsible for the changes in seizure susceptibility. However, the significant correlations characterize the relationships between the observed phenomena as „dose-dependent”, suggest the existence of cause-and-effect relationships between them, depending on previous LPS treatments, justifying further investigations. Acknowledgements This work was supported by the Polish National Science Centre, Grant no. 2012/05/B/NZ4/02406 awarded to Z.S. Conflict of interest None of the authors has any conflict of interest to disclose. Author contributions Conceived and designed the experiments: Z.S. Performed the experiments: Z.S. EK. Analysed the data K.J., Z.S., E.K. Data interpretation, manuscript preparation K.J. Data availability statement The data that support the findings of this study are available from the corresponding author upon reasonable request. REFERENCES Albrecht MA, Vaughn CN, Erickson MA, Clark SM, Tonelli, LH. (2018). 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Cell biology international 46:1510–1518. https://doi.org/10.1002/cbin.11832. Zhao J, Bi W, Xiao S, Lan X, Cheng X, Zhang J, Lu D, Wei W, Wang Y, Li H, Fu Y & Zhu L. (2019). Neuroinflammation induced by lipopolysaccharide causes cognitive impairment in mice. Sci Rep 9:5790. https://doi.org/10.1038/s41598-019-42286-8. FIGURES Fig. 1 A general scheme of the present study. Male rats were injected with LPS (blue arrows) on postnatal days 6 (L06) or 30 (L30) and normal rats (N) remained untreated. On postnatal day 55 (P55), EEG teletransmitters were implanted and, after two weeks recovery, six hour-lasting EEG control recordings (Con EEG) were performed on P70. On P72, after seizure induction with pilocarpine (red arrows), the 6 h EEG recordings were repeated (SE EEG). On P75, perfusion-fixation of the rats was performed. The symbol SE added to the group names indicates seizure experience of the animals. Fig. 2 Branching of astrocyte processes in the CA3 region of Ammon’s horn (A) and dentate gyrus (B) areas. Examples of GFAP-immunopositive astrocyte profiles are encircled in red. Scale bar - 500 μm. Below, there are enlarged images of the same cells with their binary silhouettes and skeletonized profiles. Two circles of 25 μm and 50 μm in diameter were centered on the astrocyte cell body and intersections between the astrocyte processes and the circles were counted. The ratio between numbers of intersections with the outer and inner circles was calculated and termed the Branching Index (BI). Fig. 3 Ramification of microglial processes in the CA3 region of Ammon’s horn (A) and dentate gyrus (B) areas. Examples of Iba1-immunopositive microglial profiles, are encircled in red. Scale bar - 500 μm. Below, there are enlarged images of the same cells with their binary silhouettes and skeletonized profiles. The ratio between the number of terminal endings and the number primary processes was calculated and termed the Ramification factor (RF). Fig. 4 The course of seizures after pilocarpine injection in 72-day-old rats. The graphs show results of quantitative assessments of behavioral seizure symptoms (Y axis) induced in previously untreated, control rats (N SE, white boxes) and in rats treated with LPS on postnatal day 6 (L06 SE, grey boxes) or 30 (L30 SE, black boxes). (A) Total numbers of 10-minute periods within the whole 6h observation time when seizures of any intensity (0.5-3.0) occurred. (B) Scores of maximal seizure intensity representing each of the successive 10-minute periods summarized separately for each of six subsequent hours of the whole observation time. (C) Scores of maximal seizure intensity representing each of the successive 10-minute periods summarized for the whole observation time. Colored circles, boxes or whiskers present, respectively, medians, 25–75% variability ranges and maximal or minimal values. Decimal indexes located over whiskers show statistical significance of differences (Mann–Whitney U-test) in relation to the control group. The indexes located between boxes show statistical significance of differences between rats injected with LPS on postnatal days 6 or 30. Fig. 5 Examples of EEG recordings and power spectra referring to 6-h periods before (black bars and lower tracing) and after (blue bars and upper tracing) seizure induction. Fig. 6 Relative power of particular EEG bands (Y axes) during 6h-lasting periods before (grey boxes) and after (black boxes) pilocarpine injections. Symbols N, L06 and L30 refer to EEG recordings in untreated, normal rats and in rats treated with LPS on postnatal day 6 or 30, respectively. SE added to the symbols refer to EEG recordings during seizure occurrence in each of the animal groups. Small squares, boxes and whiskers present medians, 25–75% variability ranges and maximal or minimal values. Decimal indexes located over whiskers with grey arrows show statistical significance of decreases (Mann–Whitney U-test) in relation to the control group. The indexes located between boxes show statistical significance of changes between EEG recordings performed before and after seizure induction (Mann–Whitney U-test). Up- or down-oriented arrows, red and blue, respectively, indicate increases or decreases. Fig. 7 Changes in the absolute power of EEG signal after seizure induction with pilocarpine in previously untreated, normal rats (N SE) and in rats treated with LPS on postnatal day 6 (L06 SE) or 30 (L30 SE). (A) Increases in the absolute power of the total EEG signal in each animal group. (B) Increases in the absolute power of particular EEG bands in previously untreated rats and (C) in rats treated with LPS on postnatal day 6 or (D) on day 30. The graphs present ratios between the absolute power recorded during 6h-lasting periods after and before seizure induction. Small squares, boxes and whiskers show medians, 25–75% variability ranges and maximal or minimal values. Decimal indexes located at double-headed arrows show statistical significance of differences (Mann–Whitney U-test) between two respective EEG bands. Fig. 8 Correlations between increases in the absolute power of EEG signal (X-axes) after pilocarpine injections and the intensity of behavioral seizure symptoms (Y-axes) in all animal groups taken together, and represented by two parameters: (A) maximal seizure intensity (MAX SE) and (B) the sum of maximal seizure scores recorded in each of subsequent 10 min periods (6h SUM SE) during the whole observation period. Scatterplots in sets A or B represent the total EEG signal (1) or particular EEG bands (2-6), respectively. A red solid diagonal line in each diagram shows a linear fit for Spearman’s rank coefficient of correlation (r) with its index of statistical significance (decimal indexes in upper or lower positions, respectively). Fig. 9 Correlations between increases in the absolute power of EEG signal (X-axes) after pilocarpine injections and the maximal seizure intensity recorded during the whole observation period (MAX SE). Scatterplot sets represent control, previously untreated rats (A) and rats treated with LPS on postnatal day 6 (B) or 30 (C). Within each of the three sets, the graphs refer to the total EEG signal (1) or to particular EEG bands (graphs 2-6), respectively. A solid thick diagonal line in each diagram shows a linear fit for Spearman’s rank coefficient of correlation (r) with its index of statistical significance (decimal indexes in upper and lower positions, respectively. Fig. 10 Correlations between increases in the relative power of Theta EEG signal (RP Theta, Y-axes) after pilocarpine injections and the intensity of seizure symptoms (X-axes) in rat groups treated with LPS on postnatal days 6 (A, B) or 30 (C, D). For each of the groups two parameters of the seizure symptoms were used: MAX SE - maximal seizure intensity (MAX SE) and 6h SUM SE - the sum of maximal seizure scores recorded in each of subsequent 10 min periods during the whole observation time. A solid thick diagonal line in each diagram shows a linear fit for Spearman’s rank coefficient of correlation (r) with its index of statistical significance (decimal indexes in upper or lower positions, respectively. Statistical insignificance is indicated with black indexes. Fig. 11 Correlations between increases in the absolute power of EEG signal (X-axes) after pilocarpine injections and the astrocyte Branching Index (Y-axes) in the CA3 region (A) and dental gyrus (DG, B) of hippocampal formation in rats treated with LPS on postnatal day 6. A solid thick diagonal line in each diagram shows a linear fit for Spearman’s rank coefficient of correlation (r) and its index of statistical significance in upper or lower position, respectively. Statistical insignificance is indicated as n.s. Fig. 12 Correlations between increases in the absolute power (AP, X-axes) of EEG signal after pilocarpine injections and the astrocyte Branching Index (Y-axes). The scatterplots refer to the total EEG signal (A) or to particular EEG bands, (B-F) respectively, in the CA3 region of hippocampal formation in rats treated with LPS on postnatal day 30. A solid thick diagonal line in each diagram shows a linear fit for Spearman’s rank coefficient of correlation (r) with its index of statistical significance in upper or lower position, respectively. Statistical insignificance is indicated as n.s. Fig. 13 Correlations between increases in the relative power (X-axes) of Alpha (A) and Beta (B) EEG bands (RP Alpha and RP Beta, respectively) after pilocarpine injections and the astrocyte Branching Index (Y-axes) in the CA3 region of hippocampal formation in rats treated with LPS on postnatal day 6. A solid thick diagonal line in each scatterplot shows a linear fit for Spearman’s rank coefficient of correlation (r) with its index of statistical significance in upper or lower position, respectively. Fig. 14 Correlations between increases in the relative power (RP, X-axis) of Delta (A, B) and Gamma (C, D) EEG bands after pilocarpine injections and the microglia Ramification Index (Y-axis) in the CA3 region (A, C) and dental gyrus (DG) (B, D) of the hippocampal formation in rats treated with LPS on postnatal day 6. A solid thick diagonal line in each scatterplot shows a linear fit for Spearman’s rank coefficient of correlation (r) with its index of statistical significance in upper or lower position, respectively. Information & Authors Information Version history V1 Version 1 15 August 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords astrocytes cell morphology lipopolysaccharide microglia Authors Affiliations Krzysztof Janeczko 0000-0002-9544-918X [email protected] Jagiellonian University in Kraków Faculty of Biology View all articles by this author Emilia Kosonowska Jagiellonian University in Kraków Faculty of Biology View all articles by this author Zuzanna Setkowicz Jagiellonian University in Kraków Faculty of Biology View all articles by this author Metrics & Citations Metrics Article Usage 211 views 136 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Krzysztof Janeczko, Emilia Kosonowska, Zuzanna Setkowicz. EEG spectra and glial transformations following seizures induced in rats pretreated with systemic inflammation at two developmental stages. Authorea . 15 August 2025. DOI: https://doi.org/10.22541/au.175525576.63673895/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. 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