T he relationship between epilepsy and schizophrenia has long attracted the attention of clinicians as well as neuroscientists. Approximately 7% of patients with epilepsy develop chronic interictal schizophrenia-like psychosis. 1 The idea that patients with schizophrenia and patients with epilepsy may share some pathogenic process is more than three decades old and continues to stimulate research today. 2 The type of epilepsy that has been most linked to schizophrenia is temporal lobe epilepsy. 3
Buchsbaum used the term “middle evoked response components” to describe three main auditory evoked potentials components: a positive, negative, positive sequence occurring at 40–80 (P50), 75–150 (N100), and 150–250 (P200) msec. 4 Subsequently, Roth and Horvath 5 used the term “mid-latency” to describe evoked potential components occurring between 50 and 200 msec. These components characteristically decrease in amplitude with faster repetitions. 6 The P50 component is hardly affected by attentional factors and therefore may reflect a pre-attentive stage of information processing. 7, 8 The N100 and the P200 have been associated with later (attentive) stages of information processing. 9 Abnormalities of these components have been repeatedly demonstrated in schizophrenia patients. 2, 10 The most consistently reported abnormality of these components is amplitude reduction of the P50 and N100, and less consistently, the P200. 11 Though the P50 has also been reported to decrease in amplitude in epileptic patients, 12, 13 the N100 amplitude was reported not to be affected in this population. 2 To our knowledge, the P200 has not been examined in this population. Examination of these mid-latency auditory evoked responses may thus be helpful in further identifying similar or divergent mechanisms at play in these two disorders.
Sensory gating deficiency has been identified as a possible endophenotype for psychosis. 14 The decrease in response magnitude with repetitive sensory input is an essential function of the central nervous system and has been demonstrated in studies on humans and animals. 6, 15 Deficits of this function could lead to impairments of the brain’s capacity to select, process, and store information, 16 and have been associated with the development of severe behavioral aberration. 17 In humans, the response decrease by repetitive stimulation (also termed sensory gating) has been examined extensively for the P50. A deficient response decrease of the P50 has been reported mainly for patients with schizophrenia, 17 but also for other neuropsychiatric diseases, such as posttraumatic stress disorder (PTSD). 18 Sensory gating is yet to be examined in epileptic populations. While most of the investigations of sensory gating in schizophrenia have focused on the P50 mid-latency auditory-evoked response component, we have recently shown that the abnormality extends to N100 and P200. 10
In the current preliminary study we sought to examine the amplitudes, latencies, and sensory gating indices derived from the three major mid-latency auditory-evoked response components in a group of patients with epilepsy with focal seizures (mostly of temporal lobe origin) in order to ascertain whether sensory gating deficit is observable in this group, and if an observed gating deficit parallels the deficit observed in schizophrenia patients.
METHOD
We included 29 patients (16 men and 13 women, from 19 to 59 years old with a mean of 38.3 years) with focal epilepsy. Of the 29 patients, 17 had temporal lobe epilepsy (11 left, 5 right, and one bilateral). Seven subjects had frontal lobe lesions (three left- and four right-sided). The five remaining subjects were either multifocal or had lesions outside the frontal or temporal lobes (e.g., occipital). The 29 subjects were selected from 39 subjects who had scalp-recorded evoked potentials. Selected records had all three identifiable target components (P50, N100, and P200). The data were collected as part of a larger study to ascertain the anatomical substrates of sensory gating. 19 Patients were being evaluated for resective surgery (on an inpatient basis). The diagnosis of epilepsy was made based on extensive simultaneous EEG/video recordings. All patients were taking antiepileptic medication, and three were taking atypical antipsychotic agents at the time of recording (none was taking clozapin). Other psychiatric problems included history of depression (four), posttraumatic stress disorder (two), a history of panic and depressive disorder (one), and an additional subject with a history of psychotic episodes but who was not psychotic or medicated at the time of recording. No other psychotropic medications were being administered. All mid-latency auditory-evoked response recordings were obtained prior to any invasive procedures.
Twenty-nine healthy comparison subjects were selected from among a larger sample of already collected evoked potentials of healthy comparison subjects recorded at the electrophysiology laboratory at Yale University. Comparison subjects were selected first based on age and then on gender for matching to subjects in the epilepsy group (16 men and 13 women). All subjects signed a consent form approved by the Institutional Review Board committees of the University of Bonn, Germany (epileptic patients), Yale University for healthy comparison subjects (location of the laboratory at time of data collection).
Epileptic patients were administered the Structured Clinical Interview for DSM-IV (SCID). Additional clinical data were obtained from the medical records. We first screened comparison subjects by phone to assure the absence of any psychiatric or neurological disorders, being on any psychoactive medications, history of head injury (leading to any period of loss of consciousness), and any history of drug abuse. Individuals meeting criteria were invited to the laboratory for a SCID-interview as well as a urine test for drugs of abuse. Urine drug screens are not routinely obtained as part of the initial admission workup for epilepsy patients unless there is a history of drug use. None of the patients included in this sample gave such history.
The inhibitory capacity of the brain was measured using identical pairs of brief tones. For the healthy comparison group, the stimuli were brief tones (1000Hz) of 4 msec duration and 1 msec rise and fall time, and 90 dbSPL as measured at the ear using a measure-and-hold digital sound meter (Tandy Corp). In paired stimulus paradigms, 2 identical stimuli are presented binaurally with a 500 msec interstimulus interval (ISI). 20 The pairs are repeated every 8 seconds. 21 One hundred pairs of stimuli are presented to assure the availability of 60 artifact-free trials. Responses to the first stimulus (S1) and the second stimulus (S2) are averaged separately.
For epileptic patients (recorded in Bonn, Germany), the EEG was recorded with the digital EPAS system (Schwarzer, Munich, Germany) and its implemented Harmonie EEG software (Stellate Systems, Quebec). The EEG was measured against a reference of left and right mastoid electrodes with a sampling rate of 1000 Hz. Patients were seated on a comfortable chair in a quiet room illuminated by bright light. The stimuli used were short tone bursts of a single sine wave with 1500 Hz frequency and a duration of 6.6 msec (including rise and fall times of 1.5 msec) presented by headphones. A set of 100 pairs of stimuli was administered (minimum of 60 artifact-free needed for averaging) with an ISI of 0.5 seconds and an interpair interval of 8 seconds. Tones were presented at 60dbSPL.
Healthy comparison subjects (recorded at West-Haven VA-Medical Center) were allowed to smoke up to arrival at the laboratory. Recordings were made from silver/silver chloride disk electrodes applied at the Fz, Cz, Pz, Oz, F7, F8, T3, T4, P5, and P6 locations and referred to linked ears. For both groups, P50, N100, and P200 measurements were made from the Cz electrode for consistency with the literature. The Oz electrode was used for monitoring levels of alertness (by monitoring alpha/theta activity). Other midline electrodes were used to verify the evoked potential components. One channel was devoted to detecting eye movement artifacts recorded from a supraorbital electrode to the outer canthus. Online EEG artifact rejection allowed for trial rejection when activity in any channel exceeded 75 symbol 109 /f “Symbol” /s 12mV (Neuroscan Software, Herndon, VA). Band-pass filters (0.05 and 300 Hz) were used and data were digitized at 1000 Hz for online averaging. EEG recording started 100 msec prior to stimulation and extended to 400 msec after stimulation.
In order to increase the signal to noise ratio, we refiltered the EEG data between 10 and 50 Hz when examining the P50 component. 7 This procedure is useful as the main frequency content of the P50 component is expected in this frequency range. 22 A 1–30 Hz band-pass was used to examine N100 and P200 components. Only data from midline electrodes are reported in this article. Figures 1 and 2 provide the grand averages resulting from the two sets of filters.
Amplitudes of the three components were measured from peak to the preceding peak of positivity or negativity, 23 as well as from the component’s peak to a 100 msec prestimulus baseline. Criteria for identification of the N100 component were: a) the largest negative peak between 75 and 150 msec post-stimulation (which has to be distinct from ongoing baseline fluctuations), and b) the component was seen clearly in more than one recorded channel. The P50 was identified as the largest positivity within the latency range of 35–85 msec, and the P200 was identified as the largest positivity following the N100 (within the latency range of 150–250 msec).
All averages were printed without identifying information. Three copies of all averages were then evaluated blindly by three investigators (Dr. Boutros, Dr. Burroughs, and Dr. Korzyukov). Each evaluator marked the P50, N100, and P200 peaks. Following the independent evaluations, a consensus session was held and all three evaluators were able to reach 100% agreement on the detected components.
Statistical Analysis
Peak latencies were measured from stimulus onset to peak of component. Amplitudes were measured from peak to preceding peak (for consistency with sensory gating literature), as well as from peak to baseline. The patients and healthy comparison subjects were compared on P50, N100, and P200 components for amplitudes, latencies, and sensory gating measures derived from each component. Two sensory gating measures were computed for each component. The ratio measure was calculated by dividing the amplitude of the S2 response by the amplitude of the S1 response (i.e., S2/S1). Smaller ratios indicate better gating . The difference measure was calculated by subtracting the amplitude of the S2 response from that of the S1 response (i.e., S1-S2). Larger differences indicate better gating . Analyses were performed based on both peak-to-peak as well as baseline-to-peak measurements. The first series of analyses performed were 2 (patients versus healthy comparison subjects) x 2 (gender: men versus women) between-subjects ANOVAs on amplitudes, latencies, and gating measures. The next set of analyses of variance (ANOVAs) was performed to examine differences related to sensory gating measures.
RESULTS
Eleven patients had some psychiatric history. ANOVA did not reveal any significant differences (or trends) on any of the electrophysiological measures between these 11 subjects and rest of the epilepsy group. The small sample size and heterogeneity of psychiatric syndromes did not allow the examination of correlations with lesion location. There was no effect of gender on any of the electrophysiological measures.
Amplitude and Latency Measurements:
Table 1 shows the means and standard deviations of the amplitudes of the S1 and S2 responses (all values measured peak-to-peak) as well as the latencies of the S1 responses of the three measured mid-latency auditory-evoked responses in the two groups.
TABLE 1. Means and Standard Deviations for S1, S2, Gating Ratios, Gating Differences and Latencies of the P50, N100, and P200 Components (All Values Measured Peak to Peak) for the Two Groups
Among the three mid-latency auditory-evoked responses, only the P200 was significantly smaller (with peak-to-peak amplitude measurements) in epileptic patients ( F (1, 54)=9.0, p<0.004). Similar results were obtained when comparing amplitudes based on baseline-to-peak measurements ( Table 2 ). No significant effects were found for latency measurements. The grand averages from epilepsy patients and healthy comparison subjects are shown by two grand averages in Figure 1 .
TABLE 2. Means and Standard Deviations for S1, S2, Gating Ratios, Gating Differences and Latencies of the P50, N100, and P200 Components (All Values Measured Baseline to Peak) for the Two Groups
FIGURE 1. Grand Averages of S1 Responses at Cz from the Two Groups
a) average filtered to highlight the P50 component. Arrows indicate peaks and troughs of the P50 in healthy subjects and arrowheads indicate the P50 in epileptic patients. b) averages filtered to highlight the N100 and P200 components. Short arrows indicate N100 peaks and troughs in healthy subjects, arrowheads indicate N100 peak and trough in epilepsy patients. Arrows with circles indicate P200 peak and trough in healthy subjects and long arrows indicate P200 peak and trough in epileptic patients.
Note in Figure 1 that the amplitude of the P50 (particularly in epilepsy patients) does not match the mathematical mean (smaller in the grand average). This discrepancy likely reflects the variability in latencies (small component in a large time window).
Sensory Gating Measurements:
Means and standard deviations of the ratio and difference gating measures of the three components in the two groups are shown below in Table 1 . The gating ratios and differences reported in Tables 1 and 2 are the means of the individual data and ratios or differences of the means of the data. Neither the P50 ratio or difference measures of gating differed between the groups (whether measured peak-to-peak or baseline-to-peak). When utilizing peak-to-peak data, the N100 ratio or difference measures also did not differ between the groups. On the other hand, when utilizing baseline-to-peak data, the N100 ratio measure of the epileptic group was noted to be lower (stronger gating effect) than those of the healthy comparison subjects (41 [SD=27] and 69 [SD=63], respectively) (t=−2.09, p<0.04 two-tailed). The difference measure remained nonsignificant. In a further exploratory analysis the ratios were compared between patients with temporal (N=18) versus extratemporal lobe (N=10) epileptic foci. No significant differences were found between the ratios of temporal lobe and extra temporal lobe patients (45% [SD=41], and 61% [SD=66], respectively).
Utilizing peak-to-peak data, the P200 ratio measure did not significantly differ between groups, but the S1-S2 difference measure was significantly smaller in epileptic subjects (indicating less effective gating of the P200 component) ( F (1, 55)=5.7, p<0.02). When utilizing baseline-to-peak data, both measures were significantly statistically different between the groups ( F (1, 56)=5.3, p<0.005 for ratio and F (1, 56)=17.2, p<0.0001 for the difference) ( Table 2 ). In order to examine further the relative contribution of the amplitude of the S1 response and the degree of attenuation of the S2 response to the ratio and difference measures, we matched subsamples based on the amplitudes of S1 alone (from peak-to-peak measurements, N=21, from base-to-peak measurements, N=18). We then used t tests to compare the ratio measures in the two subsamples. In both conditions, sensory gating measures became nonsignificant. There was no effect of gender or age with any of the gating measures. Figure 2 shows the S1 and S2 responses for each group.
FIGURE 2. Grand Averages of the S1 and S2 Responses at Cz from the Two Groups
a) healthy subjects filtered for P50, b) epilepsy patients filtered for P50, c) healthy subjects filtered for N100/P200, and d) epilepsy patients filtered for the N100/P200 responses.
DISCUSSION
A Number of Significant Findings Emerge from the Above Data
Though no differences in the amplitudes of the P50 and N100 were noted between patients with focal epilepsy and healthy comparison subjects, the P200 amplitude was significantly smaller in epileptic patients. This is an important finding as it points to a significant difference in the pathology between epilepsy and schizophrenia where the N100 and P50 are rather consistently decreased in amplitude. 22, 24 – 26 This finding suggests that the epileptic process may not be adversely affecting information processing at an early stage, compared to schizophrenia, and perhaps may provide some explanation of the less severe behavioral and cognitive disturbances seen in this population. Our finding of decreased P200 amplitude agrees with prior investigations in this population. 27 Our data regarding an intact N100 also agree with one prior report where N100 was found not to be affected even in epileptics exhibiting schizophrenia-like symptoms 2 and contradicts another report where N100 amplitudes and latency were found to be affected in a similar population. 27
Sensory gating measures derived from the P50 component did not significantly differ between the two groups. This is a significant difference from the pattern associated with schizophrenia where a sensory gating deficit has repeatedly been reported. 28 The N100-derived gating measures mostly did not differ between the groups, with the exception of the ratio measure when amplitude data measured base-to-peak were used. The difference was barely significant, however, and thus we feel that it is too early to speculate on any significance it may have. On the other hand, three of the four gating measures (the S1-S2 difference with peak-to-peak amplitude measurements and both the difference and gating measures when using baseline-to-peak measures) of P200 gating were significantly different in epileptic patients suggesting less gating of the P200 component in this group. This finding suggests that the sensory gating deviation in epilepsy is either less severe, affecting only the P200 as compared to P50, N100, and P200 in schizophrenia, 10 or that it is a more specific abnormality affecting only the neural processes underlying the generation of the P200 component. Furthermore, the data presented above argue against the P200 gating deficit being a floor effect secondary to the smaller amplitudes of S1 responses (i.e., no further room for attenuation of S2 responses). As seen in Table 1, the N100 amplitude was attenuated from a mean of 9.8 μV to a mean of 3.8 μV and even the smaller amplitude P50 component was attenuated from a mean of 2.8 μV to a mean of 1.3 μV. Larger sample sizes will be necessary to further examine the possible contribution of an attenuated S1 response to the observed gating deficit. Moreover, this finding highlights the usefulness of obtaining both peak-to-peak and baseline-to-peak amplitude measures when assessing sensory gating.
Though gating of the P50 response has received significant attention and gating of the N100 is currently being examined by a number of groups, gating of the P200 remains largely unexamined. We previously reported a P200 gating deficiency as the sole gating problem in a group of healthy older individuals between the ages of 70 and 80. 29 It should be noted that both groups, the elderly and epilepsy patients, are believed to have an increased susceptibility to developing psychotic symptomatology. 2, 30 The functional implications of P200 as well as N100 sensory gating deficits are yet to be elucidated.
We would also like to point out that the P200 component of the mid-latency auditory-evoked responses has not been extensively examined in any neuro- or psychopathological populations. The P200 is dissociable experimentally, 31 developmentally, 32 and topographically. 33 A review of available evidence suggests that the P200 component is an independent component a with different determinant than the preceding, and much more extensively examined N100 or the subsequent endogenous components like the P300. 34 Data reported in this article strongly argue for greater attention to this mid-latency auditory-evoked response component.
Our finding of stronger N100 gating effect in epileptic patients must be viewed as tentative at this stage. Nonetheless, a supernormal gating of the N100 could be seen as leading to increased salience of perceived information. The observation that the mean ratio of patients with temporal lobe foci was smaller than the mean of ratios of patients with extratemporal foci, while nonsignificant, points to the same idea. We propose that if this finding is replicated in a larger sample, it may possibly lend some support to the theory of sensory hyperconnectivity for the pathogenesis of the temporal lobe epilepsy personality syndrome. 35
It should be acknowledged that the fact that the two groups were not recorded in the same laboratory may have contributed to some of the noted differences. This situation resulted from the fact that the original design was focused on collection of invasive data (reported elsewhere). 19 It is unlikely, on the other hand, that methodological differences (most importantly the difference in the frequency of the auditory stimulus being 1000Hz for healthy comparison subjects and 1500Hz for patients) could have contributed to the main finding of the study which is the significant attenuation of the amplitude of the P200 component in treatment-resistant individuals with focal epilepsy. Further reassurance is obtained from the fact that the N100 amplitudes were almost identical between the two groups and the P50 amplitudes did not significantly differ. Moreover, epileptic subjects were on antiepileptic medications. This could be a confounding factor. To the best of our knowledge, there is no evidence that any medication could selectively affect the P200 without influencing the N100 as well. Finally, the group of patients included was heterogeneous regarding the focal origin of the seizures. Whether the observed effects are secondary to the fact that all subjects had seizures or related to chronicity and severity of epilepsy in this sample cannot be determined based on current data. It is also possible that the selection of patients based on the quality of the recordings may have biased the data against finding P50 or N100 gating deficits. Such selection would not, on the other hand, explain the P200 findings.
Further speculation on the above findings should await replications with a larger sample and with more closely matched healthy comparison groups. Having demonstrated a gating problem in the included medication-resistant patients, further studies of more representative samples of epilepsy patients and in direct comparison to schizophrenia patients seems justified.
Acknowledgments
This work was supported by grant #RO1 MH063476. The authors would also like to acknowledge the valuable comments provided by Dr. Marianna Spannaki of Henry Ford Hospital Epilepsy program.
Footnote
Received November 10, 2005; revised April 21, 2006; accepted April 24, 2006. Drs. Boutros, Korzyukov, and Burroughs are affiliated with Wayne State University, School of Medicine, Department of Psychiatry and Behavioral Neurosciences, Detroit, Michigan. Drs. Trautner, Elger, and Rosburg are affiliated with the Department of Epilepsy, University of Bonn, Germany. Dr. Grunwald is affiliated with Zurich Epilepsy Center, Zurich, Switzerland. Dr. Kurthen is affiliated with the Department of Epilepsy, University of Bonn, Germany, and Zurich Epilepsy Center, Zurich, Switzerland. Address correspondence to Dr. Boutros, Wayne State University School of Medicine, UPC-Jefferson. 2751 E. Jefferson, Suite 305, Detroit, MI 48207; [email protected] (E-mail).
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