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Interplay between interictal spikes and behavioral seizures in young, but not aged pilocarpine-treated epileptic rats
Epilepsy & Behavior 57 (2016) 90–94
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Epilepsy & Behavior journal homepage: www.elsevier.com/locate/yebeh
Interplay between interictal spikes and behavioral seizures in young, but not aged pilocarpine-treated epileptic rats Rika Bajorat a,b,1, Doreen Goerss a,1, Linda Brenndörfer a, Lars Schwabe c, Rüdiger Köhling a, Timo Kirschstein a,⁎ a b c
Oscar Langendorff Institute of Physiology, University of Rostock, Germany Dept. of Anesthesiology and Intensive Medicine, University of Rostock, Germany Dept. of Computer Science and Electrical Engineering, University of Rostock, Germany
a r t i c l e
i n f o
Article history: Received 26 November 2015 Revised 11 January 2016 Accepted 12 January 2016 Available online xxxx Keywords: Pilocarpine Interictal spikes Long-term video-EEG
a b s t r a c t Interictal spike activity is commonly observed in the EEG of patients with epilepsy, but the causal interrelationship between interictal spikes and behavioral seizures is poorly understood. We performed long-term video-EEG monitoring of 16 epileptic rats after pilocarpine-induced status epilepticus and five control animals. To quantify the interplay between periods of spikes and seizures, we calculated the time spent with spikes as well as the time spent with seizures for each animal. Within a given subject, we found a significant correlation between these two measures in 7/11 young epileptic rats (b400 days); this correlation was positive in six cases and negative in one. By contrast, none of five aged pilocarpine-treated animals exhibited significant correlation coefficients between spike periods and seizures (N 600 days, P b 0.05). Instead, aged epileptic rats showed a prominent predominance for either spike periods or seizures, which might explain the absence of significant correlation in this population. We found that there is a significant interplay between interictal periods of spikes and behavioral seizures in young epileptic animals, but this association is absent during aging. © 2016 Elsevier Inc. All rights reserved.
1. Introduction Interictal spikes are a common EEG feature in patients with temporal lobe epilepsy (TLE). However, the causal relation between interictal spikes and epileptogenesis or ictal semiology is largely unknown. Since resection of brain areas with high spike rates was predictive for postoperative seizure control in TLE surgery [1,2], spikes are widely considered as proepileptic [3]. In particular, molecular and cellular changes associated with spikes could lead to cell pathology, thereby increasing the risk of seizure occurrence [4]. Moreover, interictal spikes not only were predicative for seizures but also impaired cognitive performance [5,6]. This notion has led to the idea of antispike therapy in order to modify epileptogenesis. By contrast, in vivo and in vitro models suggest that interictal spikes may also impede and interfere with seizures or seizure-like activity [7–10]. The role of spikes is, thus, ambiguous, as they are thought
⁎ Corresponding author at: Oscar Langendorff Institute of Physiology, University of Rostock, Gertrudenstrasse 9, 18057 Rostock, Germany. Tel.: +49 381 494 8037; fax: +49 381 494 8002. E-mail addresses: [email protected] (R. Bajorat), [email protected] (D. Goerss), [email protected] (L. Brenndörfer), [email protected] (L. Schwabe), [email protected] (R. Köhling), [email protected] (T. Kirschstein). 1 Contributed equally to this work.
http://dx.doi.org/10.1016/j.yebeh.2016.01.014 1525-5050/© 2016 Elsevier Inc. All rights reserved.
to either raise or lower epileptogenicity [11]. This ambiguity may be resolved in part as different types of spikes, only one of which is associated with subsequent seizure emergence [12]. As also suggested by the cited paper, the proepileptic versus antiepileptic properties of spikes may be time-dependent, perhaps not only during the relatively brief silent period of epileptogenesis but also beyond during aging and disease progression. It is of utmost interest to disentangle how the passage of time and seizure events influence neuropathology, since – in patients with TLE – hippocampal sclerosis was associated with poorer performance in verbal memory compared with other pathologies [13]. From experimental TLE, we know that seizure rates tend to increase over time [14–16]; hence, it is intriguing to explore how interictal spikes and behavioral seizures develop after the silent period of epileptogenesis. We addressed this issue in the present study by analyzing interictal spikes and behavioral seizures at different time points during the chronically epileptic stage. We hypothesized that if seizures preferentially occurred on days with high incidence of interictal spike activity, this would favor a proepileptic effect of interictal spikes. On the other hand, higher seizure rates on days with less spike activity would point to an antiepileptic effect of interictal spikes. To test this, we recorded and analyzed long-term video-EEG data from 16 epileptic and five control rats and detected periods of spikes and behavioral seizures. Our results show that there is a significant interplay between interictal periods of spikes and behavioral seizures in young epileptic animals, but this association is absent in aged epileptic animals.
R. Bajorat et al. / Epilepsy & Behavior 57 (2016) 90–94
2. Materials and methods
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placed above each cage was used to improve video quality. Recordings from 16 pilocarpine-treated rats (559 days altogether) and five control animals were analyzed (sample rate = 500 Hz, low-pass filter = 30 Hz). For the present analyses, we partly used video-EEG recordings from rats included in a previous study [17].
2.1. Video-EEG monitoring of pilocarpine-treated rats Chronic epilepsy was generated by a single pilocarpine-induced status epilepticus (SE) in 30-day-old male Wistar rats as described elsewhere [17,18]. Single-channel epidural electrode implantation was performed as previously described [17]. Animals were housed in individual cages in an isolated room with 12-hour light/dark cycles (lights “on” from 6:00 to 18:00 h). Continuous 24/7 video-EEG data were registered using a telemetric system (DataquestA.R.T.4.2., Data Sciences International, St. Paul, MN, USA) in combination with a light/dark network camera equipped with an infrared filter (Axis 223M; Axis Communications, Lund, Sweden). When the lights were turned off (18:00 to 6:00 h), a small blue lamp (650 mcd imitating moonlight)
2.2. Interictal spike and seizure analysis Both behavioral seizures (generalized and focal) and interictal periods of spikes were detected by manual screening of the EEG for epileptiform potentials and concomitant video analysis to characterize motor symptoms [17]. An interictal spike was defined as a sharp negativegoing EEG transient lasting 20–70 ms with an amplitude exceeding twofold peak-to-peak noise level (see example in Fig. 1A). We only included repetitive spike activity in this study (i.e., periods of spikes),
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Fig. 1. Interictal periods of spikes and behavioral seizures were significantly correlated in half of the young epileptic animals. (A) Sample trace of a 100-s recording frame showing a fragment of a typical period of spikes. Note that the majority of spikes show an amplitude exceeding twofold peak-to-peak noise. (B1) The occurrence of interictal periods of spikes (indicated by x) and behavioral seizures (◊ = generalized, Δ = focal) is displayed for a recording period of 27 days. The time of the day (y-axis) is divided into periods “lights on” (from 6:00 to 18.00) and “lights off” (from 18:00 to 6:00, indicated by a gray box). Day “0” corresponds to the age of 99 days. Note that both interictal periods of spikes and behavioral seizures occur in clusters. (B2) The clusters of interictal spike periods and behavioral seizures, however, were substantially phase-shifted in this animal. Hence, the correlation between the time spent with spikes (black) and the time spent with seizures (red) was significantly negative (indicated by an asterisk). (C) In another animal (240 days at the beginning of the recording), interictal periods of spikes and behavioral seizures also appeared in clusters (C1), but these clusters were positively correlated (C2). (D) In an aged animal (729 days) by contrast, both periods of spikes and seizures occurred in clusters (D1), which were not correlated (D2). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
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and during such an episode of interictal spike activity, no overt behavioral seizure activity was seen in the concomitant video analysis. These definitions helped distinguish real interictal spike activity from nonepileptic EEG transients such as electrode or muscle artifacts. The duration of a period of spikes was, thus, defined as the time from the first to the last spike of this period. In order to collectively determine the interictal spike activity of an animal, we added all such periods on a given day to one value referred to as “time spent with spikes”. Seizures were defined as ictal EEG patterns with a behavioral correlation. In most cases, behavioral correlation in pilocarpine epileptic animals corresponds to motor seizures either in a focal or in a generalized fashion. Individual seizures were, firstly, detected by screening the EEG for ictal patterns and, secondly, confirmed by documenting behavioral convulsions in the video analysis. Moreover, the extent of convulsions was used to define focal and generalized seizures, respectively. The onset and the resolution of the motor seizure, however, were defined on EEG basis. Because of the variability of seizure rate per day and seizure duration, we performed the same calculation for seizures as mentioned above for interictal spike activity and added the total seizure periods on a given day referred to as “time spent with seizures”. All data are expressed as means ± standard error of the mean (SEM). Statistical tests were used as indicated. 3. Results The objective of this study was to investigate the interplay between interictal spikes and behavioral seizures. To this end, we performed 24/7 video-EEG monitoring of 16 pilocarpine-treated epileptic rats and detected interictal periods of spikes and behavioral seizures during the time of the day (from 0:00 to 24:00 h) for roughly one month (recording period = 35 ± 3 days, n = 16). On average, pilocarpine-treated animals had 6.3 ± 7.7 seizures/day, lasting 42 ± 12 s (n = 3589 seizures from 16 animals). The duration of a period of spikes was on average 342 ± 89 s, and epileptic rats showed on average 42 ± 20 periods of spikes per day (n = 26608 periods of spikes from 16 animals, see example of spike activity in Fig. 1A). Importantly, there was no correlation between these measures and animals' age at the onset of recording (r = 0.02 for time spent with seizures; r = −0.04 for time spent with spikes). Fig. 1B1 shows an example of a 99-day-old animal illustrating that both interictal periods of spikes and behavioral seizures appeared in clusters. To quantify the interplay between spikes and seizures, we calculated the time spent with spikes and the time spent with seizures, respectively, for every day of the recording period. On average, the time spent with seizures was 4 ± 1 min/day, while the time spent with spikes was 50 ± 14 min/day (n = 16 animals). As shown in Fig. 1B2, both periods of spikes and seizures occurred in clusters. However, clusters of spike periods and clusters of seizures were substantially phaseshifted, resulting in a significantly negative correlation between the time spent with spikes and the time spent with seizures (r = −0.355, P b 0.05, t-test). In another animal (240 days old at the onset of recording), both periods of spikes and seizures also occurred as clusters but, in contrast to the animal described above, were positively correlated (Fig. 1C). In summary, seven of 11 animals showed a significant within-subject correlation between the time spent with spikes and the time spent with seizures. One of these seven animals showed a negative correlation (Fig. 1B), and the remainder had a positive correlation (exemplified in Fig. 1C). We then investigated EEGs in five aged animals (N600 days) and repeated this analysis (see example in Fig. 1D). Since these animals had also received pilocarpine at 30 days of age, they were suffering from chronic epilepsy more than 18 months when electrodes were implanted. Contrary to the younger animals, none of these aged epileptic rats displayed a significant correlation. This proportion in aged animals (0/5) is significantly smaller than that in the younger population (7/11, P b 0.05, χ2 test). When plotting the within-subject correlation coefficient between the time spent with spikes and the time spent with
seizures against the animal's age at the beginning of the recording, the range of correlation coefficients became markedly smaller with aging (Fig. 2A1). In other words, the age of animals without a significant correlation (│r│ ≤ 0.25, n = 9) was significantly higher than that of animals with such a correlation (│r│ N 0.25, n = 7; P b 0.05, Mann–Whitney test; Fig. 2A2). We conclude that more than half of the young epileptic rats (b400 days) showed a significant correlation between the time spent with spikes and the time spent with seizures, indicating a significant interplay between periods of spikes and seizures. It is important to note that, in most cases, we found a positive correlation. In aged epileptic animals, however, this correlation was absent, and both periods of spikes and seizures became more independent events. We wondered about the reason for the absence of interplay in aged epileptic rats. Therefore, we plotted the time spent with spikes against the time spent with seizures for each day and each animal. As a result, we found a hyperbolic relationship between these two measures pointing to an overall inverse relation (Fig. 2B). When all data points of a given animal were condensed to one value per animal referred to as the mean daily spike time and the mean daily seizure time, respectively, we still observed such a hyperbolic relationship (inset in Fig. 2B). As also shown in the inset of Fig. 2B, there was a significantly negative correlation between the mean daily spike time and the mean daily seizure time in aged animals (r = − 0.872, P b 0.05, t-test) but not in younger rats (r = −0.114). While there was no within-subject correlation between spikes and seizures in aged epileptic animals, there was a significantly negative between-subjects correlation in this population instead. In other words, aged epileptic rats rather showed predominance for either periods of spikes or seizures, and this might explain the absence of interplay between spike periods and seizures. Interictal spikes are most commonly, but perhaps not exclusively, seen in epileptic conditions. We, therefore, recorded and analyzed the video-EEG from five control rats (recording period of 29 ± 7 days). As expected, seizures were never observed (time spent with seizures = 0 ± 0 min/day versus 4.0 ± 1.1 min/day in pilocarpine-treated, P b 0.01, Mann–Whitney test). In addition, three of them (ages = 98, 139, and 239 days) also showed no periods of spikes during the entire recording period. By contrast, spikes were indeed detected in two old control rats (572 and 581 days), demonstrating that spikes may appear in nonepileptic aged rats. Nonetheless, spike periods were significantly less frequent in control rats (2/5) than in epileptic rats (16/16; P b 0.01, χ2 test). On average, the time spent with spikes was 13 ± 11 min/day in controls versus 50 ± 14 min/day in pilocarpine-treated animals (P b 0.05, Mann–Whitney test). Hence, our data clearly demonstrated that spikes not only are regularly seen in epileptic animals but also may be detected in aged nonepileptic rats. 4. Discussion Patients with temporal lobe epilepsy (TLE) often harbor interictal spikes in the EEG. The aim of this study was to analyze the individual interplay between interictal periods of spikes and behavioral seizures in long-term video-EEG data from 16 pilocarpine-treated epileptic rats. In this series, animals developed on average six seizures per day with a mean duration of 42 s, which is consistent with published data [17,19]. In the total of 559 h of video-EEG recording, we found 3589 seizures and 26,608 periods of spikes. It may be argued that seizures and spikes could certainly be generated in different brain areas [20]. Thus, one potential pitfall of our study using one-channel EEG electrodes could be that we might have missed spike activity generated distantly to the recording site. The same could happen with focal seizures involving only minor parts of the brain that might escape detection when generated distantly. However, the time spent with seizures was 4 ± 1 min/day, while the time spent with spikes was 50 ± 14 min/day, and focal seizures are less frequent than generalized ones in the pilocarpine epilepsy model [17]. Thus, the possible error that could arise from insufficient spike detection appears very low.
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Time spent with seizures (min) Fig. 2. The within-day correlation between spikes and seizures was absent in aged epileptic rats. (A1) The within-day correlation between the time spent with spikes and the time spent with seizures is plotted against animal age at the beginning of the recording. While in young animals more than half of the epileptic rats show a significant within-subject correlation (│r│ N 0.25), this is lost during aging. Nonsignificant correlation coefficients (│r│ ≤ 0.25) are indicated by a gray box. Animal numbers refer to sample rats in Fig. 1. Aged animals (N600 days) are shown with green symbols. (A2) The age of animals without significant correlation (│r│ ≤ 0.25, n = 9) was significantly higher than that of animals with significant correlation (│r│ N 0.25, n = 7). (B) Scatter plot showing the time spent with spikes against the time spent with seizures. Each point represents one day of a given rat (indicated by different colors). Note that there is a hyperbolic relationship (red line) between the time spent with spikes and the time spent with seizures. Inset: scatter plot showing the mean daily spike time against the mean daily seizure time. Each point represents one animal (animal numbers refer to sample rats in Fig. 1). While the hyperbolic relationship is roughly conserved (dotted red line), aged rats (N600 days, green symbols) now show a significantly negative correlation between mean daily spike time and mean daily seizure time (indicated by an asterisk), which is not observed in younger animals (b400 days, black symbols).
As a major finding in the intraindividual analysis, a significant correlation between periods of spikes and seizures in 64% of the younger population (b400 days), but in none of the aged epileptic group (N 600 days), was found. On the other hand, aged epileptic rats tended to have either spikes or seizures, resulting in a significantly negative correlation coefficient between spike periods and seizures in the interindividual analysis. Taken together, there was a significant interplay between periods of spikes and seizures following pilocarpine-induced status epilepticus — that was, however, absent in aged animals. Whether or not a significant correlation between periods of spikes and behavioral seizures had been present earlier in life in these animals is an open
question. Because of electrode displacement problems and battery lifetime issues, it was not possible to record from the same animal covering a longer lifespan. However, we know that seizure rates may vary over time; in roughly half of the pilocarpine-treated rats, they do occur in clusters [17]. Moreover, on a larger time scale, seizure rates tend to increase during the chronic epileptic stage [14–16]. Nonetheless, a significant interplay between interictal spikes and behavioral seizures also appears to exist in patients with TLE. In a large TLE series of 303 patients, higher rates of interictal epileptiform activity were associated with higher seizure frequencies [21]. Moreover, the same study demonstrated that age was positively correlated with a higher frequency of
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interictal patterns. This, however, was not observed in the pilocarpine model. In the present study, both periods of spikes and seizures did not significantly correlate with age. The striking finding of the present study was that aged epileptic rats showed a significantly negative correlation between periods of spikes and seizures. While there is substantial in vitro evidence that interictal activity might reduce seizure-like events [7–9], data on the in vivo situation are scarce but meaningful. For instance, low-frequency stimulation was effective in reducing seizure rates in kindled rats [22], and transcranial magnetic stimulation (TMS) depressed penicillin-induced seizures dependent on the TMS frequency [23]. In humans, on the other hand, a number of clinical trials have been performed using deep brain stimulation (DBS), recently reviewed for the Cochrane Database [24]. While the authors concluded that more and larger randomized clinical trials are needed, they clearly acknowledged significant seizure reduction by DBS applied to the anterior thalamus, the responsive ictal-onset zone, or the hippocampus. Based on our data on experimental epilepsy in aged animals, it will be intriguing to quantify agedependent effects of DBS or TMS on seizure reduction in both animals and humans in further investigations. With respect to potential mechanisms involved in seizure-suppressing effects of such stimulation protocols, there is at least one attractive hypothesis that should be reflected. Chronic seizures in vivo lead to persistent changes in the propensity of synapses to undergo long-term plasticity [18,25], a mechanism that may be involved in TLE-associated memory impairment. On the other hand, seizure-like activity was shown to reverse long-term potentiation in the hippocampal slice preparation [26]. Thus, epileptiform activity appears to interfere with the homeostasis of synaptic function, and it is intriguing to explore whether the interplay between ictal and interictal events involves brain plasticity mechanisms that in turn may be age-dependent or subjected to changes following disease progression. In the present study, periods of spikes were also recorded in two of five control animals. Since these animals did not have behavioral seizures, spikes were obviously not related to epilepsy and should not be considered as “interictal”. Spikes in control animals have been reported previously [5,27], and inpatients without a history of seizures showed spike rates of 12% in nonpredisposed but up to 60% in predisposed cases such as trauma, encephalopathy, coma, dementia, or brain tumors [28]. In summary, we conclude that a significant interplay between interictal periods of spikes and behavioral seizures is present in young epileptic but absent in aged epileptic rats. Rather, spike periods and seizures are negatively correlated in these aged animals, confirming previous in vitro reports and leaving the possibility that spikes or spike-like activity such as therapeutic neurostimulation could lead to seizure reduction. Acknowledgments The authors would like to thank Katrin Porath, Tina Sellmann, Hanka Schmidt, and Bernd Memmener for excellent technical assistance. Disclosure None of the authors has any conflict of interest to disclose. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.
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Interplay between interictal spikes and behavioral seizures in young, but not aged pilocarpine-treated epileptic rats Rika Bajorat a,b,1, Doreen Goerss a,1, Linda Brenndörfer a, Lars Schwabe c, Rüdiger Köhling a, Timo Kirschstein a,⁎ a b c
Oscar Langendorff Institute of Physiology, University of Rostock, Germany Dept. of Anesthesiology and Intensive Medicine, University of Rostock, Germany Dept. of Computer Science and Electrical Engineering, University of Rostock, Germany
a r t i c l e
i n f o
Article history: Received 26 November 2015 Revised 11 January 2016 Accepted 12 January 2016 Available online xxxx Keywords: Pilocarpine Interictal spikes Long-term video-EEG
a b s t r a c t Interictal spike activity is commonly observed in the EEG of patients with epilepsy, but the causal interrelationship between interictal spikes and behavioral seizures is poorly understood. We performed long-term video-EEG monitoring of 16 epileptic rats after pilocarpine-induced status epilepticus and five control animals. To quantify the interplay between periods of spikes and seizures, we calculated the time spent with spikes as well as the time spent with seizures for each animal. Within a given subject, we found a significant correlation between these two measures in 7/11 young epileptic rats (b400 days); this correlation was positive in six cases and negative in one. By contrast, none of five aged pilocarpine-treated animals exhibited significant correlation coefficients between spike periods and seizures (N 600 days, P b 0.05). Instead, aged epileptic rats showed a prominent predominance for either spike periods or seizures, which might explain the absence of significant correlation in this population. We found that there is a significant interplay between interictal periods of spikes and behavioral seizures in young epileptic animals, but this association is absent during aging. © 2016 Elsevier Inc. All rights reserved.
1. Introduction Interictal spikes are a common EEG feature in patients with temporal lobe epilepsy (TLE). However, the causal relation between interictal spikes and epileptogenesis or ictal semiology is largely unknown. Since resection of brain areas with high spike rates was predictive for postoperative seizure control in TLE surgery [1,2], spikes are widely considered as proepileptic [3]. In particular, molecular and cellular changes associated with spikes could lead to cell pathology, thereby increasing the risk of seizure occurrence [4]. Moreover, interictal spikes not only were predicative for seizures but also impaired cognitive performance [5,6]. This notion has led to the idea of antispike therapy in order to modify epileptogenesis. By contrast, in vivo and in vitro models suggest that interictal spikes may also impede and interfere with seizures or seizure-like activity [7–10]. The role of spikes is, thus, ambiguous, as they are thought
⁎ Corresponding author at: Oscar Langendorff Institute of Physiology, University of Rostock, Gertrudenstrasse 9, 18057 Rostock, Germany. Tel.: +49 381 494 8037; fax: +49 381 494 8002. E-mail addresses: [email protected] (R. Bajorat), [email protected] (D. Goerss), [email protected] (L. Brenndörfer), [email protected] (L. Schwabe), [email protected] (R. Köhling), [email protected] (T. Kirschstein). 1 Contributed equally to this work.
http://dx.doi.org/10.1016/j.yebeh.2016.01.014 1525-5050/© 2016 Elsevier Inc. All rights reserved.
to either raise or lower epileptogenicity [11]. This ambiguity may be resolved in part as different types of spikes, only one of which is associated with subsequent seizure emergence [12]. As also suggested by the cited paper, the proepileptic versus antiepileptic properties of spikes may be time-dependent, perhaps not only during the relatively brief silent period of epileptogenesis but also beyond during aging and disease progression. It is of utmost interest to disentangle how the passage of time and seizure events influence neuropathology, since – in patients with TLE – hippocampal sclerosis was associated with poorer performance in verbal memory compared with other pathologies [13]. From experimental TLE, we know that seizure rates tend to increase over time [14–16]; hence, it is intriguing to explore how interictal spikes and behavioral seizures develop after the silent period of epileptogenesis. We addressed this issue in the present study by analyzing interictal spikes and behavioral seizures at different time points during the chronically epileptic stage. We hypothesized that if seizures preferentially occurred on days with high incidence of interictal spike activity, this would favor a proepileptic effect of interictal spikes. On the other hand, higher seizure rates on days with less spike activity would point to an antiepileptic effect of interictal spikes. To test this, we recorded and analyzed long-term video-EEG data from 16 epileptic and five control rats and detected periods of spikes and behavioral seizures. Our results show that there is a significant interplay between interictal periods of spikes and behavioral seizures in young epileptic animals, but this association is absent in aged epileptic animals.
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2. Materials and methods
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placed above each cage was used to improve video quality. Recordings from 16 pilocarpine-treated rats (559 days altogether) and five control animals were analyzed (sample rate = 500 Hz, low-pass filter = 30 Hz). For the present analyses, we partly used video-EEG recordings from rats included in a previous study [17].
2.1. Video-EEG monitoring of pilocarpine-treated rats Chronic epilepsy was generated by a single pilocarpine-induced status epilepticus (SE) in 30-day-old male Wistar rats as described elsewhere [17,18]. Single-channel epidural electrode implantation was performed as previously described [17]. Animals were housed in individual cages in an isolated room with 12-hour light/dark cycles (lights “on” from 6:00 to 18:00 h). Continuous 24/7 video-EEG data were registered using a telemetric system (DataquestA.R.T.4.2., Data Sciences International, St. Paul, MN, USA) in combination with a light/dark network camera equipped with an infrared filter (Axis 223M; Axis Communications, Lund, Sweden). When the lights were turned off (18:00 to 6:00 h), a small blue lamp (650 mcd imitating moonlight)
2.2. Interictal spike and seizure analysis Both behavioral seizures (generalized and focal) and interictal periods of spikes were detected by manual screening of the EEG for epileptiform potentials and concomitant video analysis to characterize motor symptoms [17]. An interictal spike was defined as a sharp negativegoing EEG transient lasting 20–70 ms with an amplitude exceeding twofold peak-to-peak noise level (see example in Fig. 1A). We only included repetitive spike activity in this study (i.e., periods of spikes),
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Fig. 1. Interictal periods of spikes and behavioral seizures were significantly correlated in half of the young epileptic animals. (A) Sample trace of a 100-s recording frame showing a fragment of a typical period of spikes. Note that the majority of spikes show an amplitude exceeding twofold peak-to-peak noise. (B1) The occurrence of interictal periods of spikes (indicated by x) and behavioral seizures (◊ = generalized, Δ = focal) is displayed for a recording period of 27 days. The time of the day (y-axis) is divided into periods “lights on” (from 6:00 to 18.00) and “lights off” (from 18:00 to 6:00, indicated by a gray box). Day “0” corresponds to the age of 99 days. Note that both interictal periods of spikes and behavioral seizures occur in clusters. (B2) The clusters of interictal spike periods and behavioral seizures, however, were substantially phase-shifted in this animal. Hence, the correlation between the time spent with spikes (black) and the time spent with seizures (red) was significantly negative (indicated by an asterisk). (C) In another animal (240 days at the beginning of the recording), interictal periods of spikes and behavioral seizures also appeared in clusters (C1), but these clusters were positively correlated (C2). (D) In an aged animal (729 days) by contrast, both periods of spikes and seizures occurred in clusters (D1), which were not correlated (D2). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
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and during such an episode of interictal spike activity, no overt behavioral seizure activity was seen in the concomitant video analysis. These definitions helped distinguish real interictal spike activity from nonepileptic EEG transients such as electrode or muscle artifacts. The duration of a period of spikes was, thus, defined as the time from the first to the last spike of this period. In order to collectively determine the interictal spike activity of an animal, we added all such periods on a given day to one value referred to as “time spent with spikes”. Seizures were defined as ictal EEG patterns with a behavioral correlation. In most cases, behavioral correlation in pilocarpine epileptic animals corresponds to motor seizures either in a focal or in a generalized fashion. Individual seizures were, firstly, detected by screening the EEG for ictal patterns and, secondly, confirmed by documenting behavioral convulsions in the video analysis. Moreover, the extent of convulsions was used to define focal and generalized seizures, respectively. The onset and the resolution of the motor seizure, however, were defined on EEG basis. Because of the variability of seizure rate per day and seizure duration, we performed the same calculation for seizures as mentioned above for interictal spike activity and added the total seizure periods on a given day referred to as “time spent with seizures”. All data are expressed as means ± standard error of the mean (SEM). Statistical tests were used as indicated. 3. Results The objective of this study was to investigate the interplay between interictal spikes and behavioral seizures. To this end, we performed 24/7 video-EEG monitoring of 16 pilocarpine-treated epileptic rats and detected interictal periods of spikes and behavioral seizures during the time of the day (from 0:00 to 24:00 h) for roughly one month (recording period = 35 ± 3 days, n = 16). On average, pilocarpine-treated animals had 6.3 ± 7.7 seizures/day, lasting 42 ± 12 s (n = 3589 seizures from 16 animals). The duration of a period of spikes was on average 342 ± 89 s, and epileptic rats showed on average 42 ± 20 periods of spikes per day (n = 26608 periods of spikes from 16 animals, see example of spike activity in Fig. 1A). Importantly, there was no correlation between these measures and animals' age at the onset of recording (r = 0.02 for time spent with seizures; r = −0.04 for time spent with spikes). Fig. 1B1 shows an example of a 99-day-old animal illustrating that both interictal periods of spikes and behavioral seizures appeared in clusters. To quantify the interplay between spikes and seizures, we calculated the time spent with spikes and the time spent with seizures, respectively, for every day of the recording period. On average, the time spent with seizures was 4 ± 1 min/day, while the time spent with spikes was 50 ± 14 min/day (n = 16 animals). As shown in Fig. 1B2, both periods of spikes and seizures occurred in clusters. However, clusters of spike periods and clusters of seizures were substantially phaseshifted, resulting in a significantly negative correlation between the time spent with spikes and the time spent with seizures (r = −0.355, P b 0.05, t-test). In another animal (240 days old at the onset of recording), both periods of spikes and seizures also occurred as clusters but, in contrast to the animal described above, were positively correlated (Fig. 1C). In summary, seven of 11 animals showed a significant within-subject correlation between the time spent with spikes and the time spent with seizures. One of these seven animals showed a negative correlation (Fig. 1B), and the remainder had a positive correlation (exemplified in Fig. 1C). We then investigated EEGs in five aged animals (N600 days) and repeated this analysis (see example in Fig. 1D). Since these animals had also received pilocarpine at 30 days of age, they were suffering from chronic epilepsy more than 18 months when electrodes were implanted. Contrary to the younger animals, none of these aged epileptic rats displayed a significant correlation. This proportion in aged animals (0/5) is significantly smaller than that in the younger population (7/11, P b 0.05, χ2 test). When plotting the within-subject correlation coefficient between the time spent with spikes and the time spent with
seizures against the animal's age at the beginning of the recording, the range of correlation coefficients became markedly smaller with aging (Fig. 2A1). In other words, the age of animals without a significant correlation (│r│ ≤ 0.25, n = 9) was significantly higher than that of animals with such a correlation (│r│ N 0.25, n = 7; P b 0.05, Mann–Whitney test; Fig. 2A2). We conclude that more than half of the young epileptic rats (b400 days) showed a significant correlation between the time spent with spikes and the time spent with seizures, indicating a significant interplay between periods of spikes and seizures. It is important to note that, in most cases, we found a positive correlation. In aged epileptic animals, however, this correlation was absent, and both periods of spikes and seizures became more independent events. We wondered about the reason for the absence of interplay in aged epileptic rats. Therefore, we plotted the time spent with spikes against the time spent with seizures for each day and each animal. As a result, we found a hyperbolic relationship between these two measures pointing to an overall inverse relation (Fig. 2B). When all data points of a given animal were condensed to one value per animal referred to as the mean daily spike time and the mean daily seizure time, respectively, we still observed such a hyperbolic relationship (inset in Fig. 2B). As also shown in the inset of Fig. 2B, there was a significantly negative correlation between the mean daily spike time and the mean daily seizure time in aged animals (r = − 0.872, P b 0.05, t-test) but not in younger rats (r = −0.114). While there was no within-subject correlation between spikes and seizures in aged epileptic animals, there was a significantly negative between-subjects correlation in this population instead. In other words, aged epileptic rats rather showed predominance for either periods of spikes or seizures, and this might explain the absence of interplay between spike periods and seizures. Interictal spikes are most commonly, but perhaps not exclusively, seen in epileptic conditions. We, therefore, recorded and analyzed the video-EEG from five control rats (recording period of 29 ± 7 days). As expected, seizures were never observed (time spent with seizures = 0 ± 0 min/day versus 4.0 ± 1.1 min/day in pilocarpine-treated, P b 0.01, Mann–Whitney test). In addition, three of them (ages = 98, 139, and 239 days) also showed no periods of spikes during the entire recording period. By contrast, spikes were indeed detected in two old control rats (572 and 581 days), demonstrating that spikes may appear in nonepileptic aged rats. Nonetheless, spike periods were significantly less frequent in control rats (2/5) than in epileptic rats (16/16; P b 0.01, χ2 test). On average, the time spent with spikes was 13 ± 11 min/day in controls versus 50 ± 14 min/day in pilocarpine-treated animals (P b 0.05, Mann–Whitney test). Hence, our data clearly demonstrated that spikes not only are regularly seen in epileptic animals but also may be detected in aged nonepileptic rats. 4. Discussion Patients with temporal lobe epilepsy (TLE) often harbor interictal spikes in the EEG. The aim of this study was to analyze the individual interplay between interictal periods of spikes and behavioral seizures in long-term video-EEG data from 16 pilocarpine-treated epileptic rats. In this series, animals developed on average six seizures per day with a mean duration of 42 s, which is consistent with published data [17,19]. In the total of 559 h of video-EEG recording, we found 3589 seizures and 26,608 periods of spikes. It may be argued that seizures and spikes could certainly be generated in different brain areas [20]. Thus, one potential pitfall of our study using one-channel EEG electrodes could be that we might have missed spike activity generated distantly to the recording site. The same could happen with focal seizures involving only minor parts of the brain that might escape detection when generated distantly. However, the time spent with seizures was 4 ± 1 min/day, while the time spent with spikes was 50 ± 14 min/day, and focal seizures are less frequent than generalized ones in the pilocarpine epilepsy model [17]. Thus, the possible error that could arise from insufficient spike detection appears very low.
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Time spent with seizures (min) Fig. 2. The within-day correlation between spikes and seizures was absent in aged epileptic rats. (A1) The within-day correlation between the time spent with spikes and the time spent with seizures is plotted against animal age at the beginning of the recording. While in young animals more than half of the epileptic rats show a significant within-subject correlation (│r│ N 0.25), this is lost during aging. Nonsignificant correlation coefficients (│r│ ≤ 0.25) are indicated by a gray box. Animal numbers refer to sample rats in Fig. 1. Aged animals (N600 days) are shown with green symbols. (A2) The age of animals without significant correlation (│r│ ≤ 0.25, n = 9) was significantly higher than that of animals with significant correlation (│r│ N 0.25, n = 7). (B) Scatter plot showing the time spent with spikes against the time spent with seizures. Each point represents one day of a given rat (indicated by different colors). Note that there is a hyperbolic relationship (red line) between the time spent with spikes and the time spent with seizures. Inset: scatter plot showing the mean daily spike time against the mean daily seizure time. Each point represents one animal (animal numbers refer to sample rats in Fig. 1). While the hyperbolic relationship is roughly conserved (dotted red line), aged rats (N600 days, green symbols) now show a significantly negative correlation between mean daily spike time and mean daily seizure time (indicated by an asterisk), which is not observed in younger animals (b400 days, black symbols).
As a major finding in the intraindividual analysis, a significant correlation between periods of spikes and seizures in 64% of the younger population (b400 days), but in none of the aged epileptic group (N 600 days), was found. On the other hand, aged epileptic rats tended to have either spikes or seizures, resulting in a significantly negative correlation coefficient between spike periods and seizures in the interindividual analysis. Taken together, there was a significant interplay between periods of spikes and seizures following pilocarpine-induced status epilepticus — that was, however, absent in aged animals. Whether or not a significant correlation between periods of spikes and behavioral seizures had been present earlier in life in these animals is an open
question. Because of electrode displacement problems and battery lifetime issues, it was not possible to record from the same animal covering a longer lifespan. However, we know that seizure rates may vary over time; in roughly half of the pilocarpine-treated rats, they do occur in clusters [17]. Moreover, on a larger time scale, seizure rates tend to increase during the chronic epileptic stage [14–16]. Nonetheless, a significant interplay between interictal spikes and behavioral seizures also appears to exist in patients with TLE. In a large TLE series of 303 patients, higher rates of interictal epileptiform activity were associated with higher seizure frequencies [21]. Moreover, the same study demonstrated that age was positively correlated with a higher frequency of
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interictal patterns. This, however, was not observed in the pilocarpine model. In the present study, both periods of spikes and seizures did not significantly correlate with age. The striking finding of the present study was that aged epileptic rats showed a significantly negative correlation between periods of spikes and seizures. While there is substantial in vitro evidence that interictal activity might reduce seizure-like events [7–9], data on the in vivo situation are scarce but meaningful. For instance, low-frequency stimulation was effective in reducing seizure rates in kindled rats [22], and transcranial magnetic stimulation (TMS) depressed penicillin-induced seizures dependent on the TMS frequency [23]. In humans, on the other hand, a number of clinical trials have been performed using deep brain stimulation (DBS), recently reviewed for the Cochrane Database [24]. While the authors concluded that more and larger randomized clinical trials are needed, they clearly acknowledged significant seizure reduction by DBS applied to the anterior thalamus, the responsive ictal-onset zone, or the hippocampus. Based on our data on experimental epilepsy in aged animals, it will be intriguing to quantify agedependent effects of DBS or TMS on seizure reduction in both animals and humans in further investigations. With respect to potential mechanisms involved in seizure-suppressing effects of such stimulation protocols, there is at least one attractive hypothesis that should be reflected. Chronic seizures in vivo lead to persistent changes in the propensity of synapses to undergo long-term plasticity [18,25], a mechanism that may be involved in TLE-associated memory impairment. On the other hand, seizure-like activity was shown to reverse long-term potentiation in the hippocampal slice preparation [26]. Thus, epileptiform activity appears to interfere with the homeostasis of synaptic function, and it is intriguing to explore whether the interplay between ictal and interictal events involves brain plasticity mechanisms that in turn may be age-dependent or subjected to changes following disease progression. In the present study, periods of spikes were also recorded in two of five control animals. Since these animals did not have behavioral seizures, spikes were obviously not related to epilepsy and should not be considered as “interictal”. Spikes in control animals have been reported previously [5,27], and inpatients without a history of seizures showed spike rates of 12% in nonpredisposed but up to 60% in predisposed cases such as trauma, encephalopathy, coma, dementia, or brain tumors [28]. In summary, we conclude that a significant interplay between interictal periods of spikes and behavioral seizures is present in young epileptic but absent in aged epileptic rats. Rather, spike periods and seizures are negatively correlated in these aged animals, confirming previous in vitro reports and leaving the possibility that spikes or spike-like activity such as therapeutic neurostimulation could lead to seizure reduction. Acknowledgments The authors would like to thank Katrin Porath, Tina Sellmann, Hanka Schmidt, and Bernd Memmener for excellent technical assistance. Disclosure None of the authors has any conflict of interest to disclose. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.
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