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Converging evidence from electrophysiological studies suggests that in individuals with schizophrenia EEG fast frontal oscillations are reduced. It is still unclear whether this reduction reflects an intrinsic deficit of underlying cortical/thalamo-cortical circuits, and whether this deficit is specific for frontal regions. Recent electrophysiological studies in healthy individuals have established that, when perturbed, different brain regions oscillate at a specific, intrinsically generated dominant frequency, the natural frequency.
To assess the natural frequency of posterior parietal, motor, premotor, and prefrontal cortices, in schizophrenic and healthy controls.
High-density electroencephalogram (Hd-EEG) recordings during Transcranial Magnetic Stimulation (TMS) of four cortical areas were performed. Several TMS-evoked EEG oscillation parameters, including synchronization, amplitude, and natural frequency were compared across the schizophrenia and healthy control groups.
Wisconsin Psychiatric Institute & Clinic, University of Wisconsin-Madison
Twenty patients with schizophrenia and twenty age-matched healthy controls.
Hd-EEG measurements of TMS-evoked activity in four cortical areas, the positive and negative syndrome scale (PANSS), and performance scores (reaction time, accuracy) in two computerized tasks: the word memory (CPW) and the facial memory (CPF) tests.
Schizophrenia patients showed a slowing in the natural frequency of frontal/prefrontal regions compared to healthy controls (from an average of 2 Hz decrease for the motor area, to almost 10 Hz for the prefrontal cortex). The prefrontal natural frequency of individuals with schizophrenia was slower than in any healthy comparison subject, and correlated with both positive PANSS scores and reaction time in the CPW.
These findings suggest that patients with schizophrenia have an intrinsic slowing in the natural frequency of frontal cortical/thalamo-cortical circuits, that this slowing is not present in parietal areas, and that the prefrontal natural frequency can predict some of the symptoms as well as the cognitive dysfunctions of schizophrenia.
A defect in beta/gamma (β/γ)-range frontal EEG oscillations was recently reported by several electrophysiological studies in schizophrenia1. In a study comparing neural activity immediately preceding self-generated speech and listening schizophrenics failed to show an increase in frontal β-band synchronization (ITC) in the pre-speech vs. listening condition, and this synchronization deficit was inversely related to hallucination severity2. Using a cognitive control task, a study showed that enhanced frontal γ-band oscillations corresponded to better performance in healthy controls, while schizophrenics had reduced frontal γ activity3. Another study employing a similar task found that medication-naive and medicated schizophrenics had lower frontal γ power compared to healthy controls, and this reduction predicted worse performance4, whereas a study investigating face processing reported reduced frontal γ-band activity and synchrony in schizophrenia patients, which was inversely related to their symptoms5. Deficits in EEG frontal fast activity/synchronization was also established employing driving auditory stimuli6, an auditory reaction task7, and oddball paradigms in both schizophrenia patients8–9 and unaffected identical twins10 compared to healthy controls. Furthermore, by combining Transcranial Magnetic Stimulation with high-density EEG (TMS/hd-EEG), we recently found that schizophrenia patients had decreased γ-band frontal amplitude and synchronization after TMS of premotor cortex11.
An important issue is whether these β/γ oscillation deficits are due to an intrinsic defect of the oscillatory properties of cortical/thalamo-cortical circuits in schizophrenia. Furthermore, if there is such an intrinsic defect, is it specific for frontal circuits, or does it extends outside the frontal lobe? TMS/hd-EEG can be used to probe the functioning of cortical/thalamo-cortical circuits, and it was recently employed to characterize the intrinsic oscillatory frequency, or natural frequency, of such circuits in humans12. In a TMS/hd-EEG study in healthy individuals different brain regions showed a specific natural frequency: α-range oscillations in occipital cortex, low-β oscillations in parietal cortex, and high β/γ oscillations in frontal cortex. The study also showed that each brain region maintained its own natural frequency even when activated indirectly after TMS of another cortical area, indicating that the observed oscillations reflected intrinsic, local mechanisms. These findings suggest that the natural frequency is a measure of the intrinsic properties and connections of local cortical/thalamo-cortical circuits (without necessarily being able to disentangle cortico-cortical from thalamo-cortical mechanisms). Importantly, the natural frequency can be assessed without requiring any cognitive engagement and can be measured directly even in frontal brain areas in humans. This is particularly relevant in schizophrenia patients, in which the interpretation of reduced fast frontal oscillations is complicated by the presence of cognitive confounds (i.e., level of attention, motivation), or by not having direct access to frontal areas.
Here we performed TMS/hd-EEG recordings in posterior parietal, motor, premotor, and prefrontal areas in schizophrenia patients and healthy controls. We hypothesized that frontal areas, but not the parietal cortex, would show an intrinsic defect of their cortical/thalamo-cortical circuits, as reflected by a slowing of their natural frequency. We also expected that the natural frequency slowing would be most prominent in prefrontal cortex. Finally, we investigated whether prefrontal natural frequency values would correlate with the Positive and Negative Syndrome Scale (PANSS) scores and with accuracy/reaction time in a word memory and a face memory task in schizophrenics.
Twenty patients with schizophrenia and twenty age-matched healthy comparisons were recruited (Table 1). Each participant gave written informed consent, and the study was approved by the University of Wisconsin-Madison Human Subjects Institutional Review Board. A psychiatrist interviewed all participants and administered the Structured Clinical Interview for DSM-IV-TR13 to confirm/exclude psychiatric diagnoses. Individuals with schizophrenia were diagnosed as paranoid (N=12), undifferentiated (N=3), residual (N=2) or disorganized (N=2) subtypes according to DSMIV-TR criteria Eighteen of the twenty patients were taking second-generation antipsychotics, while two were on first-generation antipsychotics. All were outpatients, with a mean (SD) duration of illness of thirteen years (5).
Superior parietal, precentral, superior frontal, and middle frontal gyrus, corresponding to posterior parietal, motor, premotor, and prefrontal areas, were anatomically identified on T1-weighted individual Magnetic Resonance Imaging (MRIs), acquired using a 3T GE scanner (Talairach coordinates are reported in Table 2). These areas were targeted employing a Navigated Brain Stimulation system (NBS, Nexstim, Finland). The NBS displayed the position of the TMS coil relative to each participant’s brain. It also calculated the distance between the scalp underlying the TMS coil and the cortical surface; this scalp to cortex distance was used to estimate the TMS-evoked electric field, expressed in volts per meter (V/m), on cortical areas. In both healthy and schizophrenia subjects, each cortical area was stimulated at 120 V/m, an intensity effective in eliciting EEG oscillations, as shown in previous TMS/hd-EEG work11–12. This intensity corresponded to 110–115% of resting motor threshold (RMT). RMT was identified in the right first dorsal interosseus, as the TMS intensity required to elicit a ≥50 μV electromyographic response in 5 of 10 consecutive trials.
TMS-evoked EEG responses were recorded using a TMS-compatible 60-channel amplifier (Nexstim, Finland)14. EEG signals were referenced to a forehead electrode, high-pass filtered (0.1Hz), and sampled at 1450 Hz. Two additional sensors were applied to record the electro-oculogram. Because the click associated with the TMS discharge can evoke auditory potentials, a sound masking the TMS click was generated and played via earphones throughout the TMS/hd-EEG sessions (for more details, see11,15).
Each participant was sitting on a reclining chair fitted with a headrest to ensure a stable, comfortable head position throughout the experiment. After preparation for EEG recordings and calibration of the NBS system, TMS sessions were performed. Each session consisted of 200–250 TMS stimuli delivered at 0.4–0.6 Hz, according to international safety guidelines16. To ensure wakefulness during TMS/hd-EEG sessions, subjects had their eyes open and fixated a cross on a computer screen. In each participant we also recorded a session of waking, eyes open spontaneous EEG.
On a different day a subset of schizophrenia patients (N=15) underwent two computer-based cognitive tasks, the Penn Word Recognition (CPW17) and the Penn Facial Memory (CPF17) Tests. The CPW is lateralized to the left hemisphere (the hemisphere here targeted by TMS), and involves particularly prefrontal, language-related cortical areas18. The CPF, which targets right hemisphere areas19 using faces, was performed to control for lateralization and evaluate the specificity of CPW findings.
Data analysis was performed using Matlab (The MathWorks), and the public license toolbox EEGLAB20. Data were from experiments specifically designed for this study, and did not include recordings from our previous TMS/hd-EEG study11. EEG signals were down-sampled (from 1450 to 725 Hz), band-passed (2–80 Hz), and average referenced. Trials containing activity from non-neural sources were automatically rejected if EOG exceeded 70 μV (ocular activity) and/or absolute power of EEG channel F8 in the fast beta range (>25 Hz) exceeded 0.9 μV2, indicating activity of fronto-temporal muscles21.
Several TMS-evoked EEG oscillation parameters were analyzed in the time-frequency domain. Intertrial coherence (ITC) was computed as a measure of synchronization, whereas event-related spectra perturbation (ERSP) was calculated to quantify amplitude modulation independent of phase20. To obtain ERSP for each TMS session we calculated the power spectrum for every trial using wavelet decomposition (3.5 oscillation cycles) and computed the average power across trials. ERSP was then normalized by subtracting mean baseline power. Significant ERSP was detected using a bootstrap method, based on surrogate data distribution randomly extracted from pre-stimulus. Statistical significance was set at p=0.01. Next, for each subject mean ITC and ERSP values, averaged across all trials of a session, were calculated for each channel between 8 and 50 Hz (1 Hz bin resolution). Finally, the main frequency (natural frequency) was computed as the frequency bin with the largest cumulated ERSP. The natural frequency differs from the peak frequency, which is usually calculated as the frequency with the largest activity at any point in time following a stimulus. A 20–300 ms time window was chosen to assess group differences in TMS-evoked EEG parameters, corresponding to the EEG activity significantly evoked by TMS, assessed with the bootstrap analysis. The first 20 ms were excluded to avoid a stereotypical, broad-band, early (0–20 ms) component occurring at each stimulation site. ERSP, ITC, and natural frequency were calculated globally, by averaging their values across all channels, as well as locally, by measuring them in the channel closest to the TMS coil. Because statistical comparisons across groups yielded similar results with global and local EEG oscillation parameters, local data are shown as they more closely reflect the activity of the TMS-targeted cortical areas. For spontaneous EEG analysis, data were band-pass filtered (2–80 Hz), bad channels were visually identified and rejected, and EEG signals were average-referenced. After removal of segments contaminated by eye movements/muscle activity, power spectral density (Welch’s periodogram with 6-second epoch Hamming window) was calculated.
Two-tailed bootstrap statistics were applied to ERSP and ITC values. Two-tailed unpaired t-tests were employed to establish statistical differences for ITC, ERSP, natural frequency, spontaneous EEG analysis, and clinical variables between the two study groups. For the natural frequency, Group × Region repeated measure ANOVAs followed by post-hoc Bonferroni corrected t-tests were computed to establish a progressive natural frequency increase from posterior to anterior areas in healthy, but not schizophrenic subjects. Pearson correlation analysis between medication doses, expressed in Chlorpromazine equivalents22, and the natural frequency of parietal, motor, premotor, and prefrontal areas were performed (see Supp. Table 1). Finally, the prefrontal natural frequency, the most defective EEG parameter in schizophrenics, was correlated with PANSS scores as well as performance and reaction time in the word memory task (CPW) of schizophrenics (see results).
Figure 1 shows EEG responses after TMS of each area superimposed on butterfly plots, with gray traces corresponding to individual channels and black traces indicating the channel closest to the TMS (data are from a representative subject for each group, whose natural frequency closely matched natural frequency group means for each cortical area, see Figure 2). Following an initial broadband response that occurred in each targeted cortical area, TMS evoked several fast (>13 Hz) EEG oscillations in both healthy and schizophrenia subjects. However, whereas in normal controls these oscillations were progressively faster in frequency from the parietal to the prefrontal cortex, in schizophrenics this posterior-anterior frequency increase was much more limited. Furthermore, the amplitude and synchronization of EEG oscillations in frontal/prefrontal locations was increasingly reduced in schizophrenia compared to healthy subjects.
To quantify such differences, several TMS-evoked EEG oscillation parameters, amplitude modulation (ERSP), synchronization (ITC), and main frequency were calculated for each participant and compared between groups (Table 2, data for ERSP and ITC were cumulated between 8–50 Hz and 20–300 ms post TMS). TMS-evoked EEG parameters were cumulated for two reasons: to establish whether the total amplitude (ERSP) and synchronization (ITC) evoked by TMS was reduced in schizophrenia patients compared to healthy controls in any of the four targeted cortical areas; and to characterize the natural oscillatory frequency of these brain regions. The natural frequency is the main frequency at which a system oscillates, and is best computed by cumulating the oscillatory activity after TMS and selecting the frequency showing the largest activity. Following TMS of parietal cortex no difference in EEG oscillation parameters was found across groups. By contrast, ERSP and main frequency of EEG oscillations evoked by TMS of motor cortex were significantly reduced in schizophrenics compared to healthy comparisons (Table 2). For the motor cortex, we also found that motor threshold was not different between schizophrenics, with a mean (SD) of 61.7 (6.2) %, and healthy subjects, with a mean (SD) of 60.4 (5.7) %. TMS-evoked EEG oscillations of the premotor cortex showed clear deficits in all parameters measured, including synchronization (ITC), in schizophrenia patients (Table 2). Differences between schizophrenia and healthy subjects were even more prominent after TMS of prefrontal cortex, with EEG oscillations markedly smaller, less synchronous, and slower in frequency in schizophrenics (Table 2).
Because the natural frequency was the most altered TMS-evoked EEG oscillation parameters at group level, we compared the individual natural frequency of schizophrenia and healthy subjects for each cortical regions stimulated. Whereas frequency values at parietal cortex were largely overlapping between groups, schizophrenics showed a progressive slowing in the natural frequency of frontal cortical areas, which permitted an increasing separation from healthy controls. Group × Region ANOVAs showed significant effects for Group (F=84.892, p=3*10−11), Region (F=38.7, p=4*10−10), and Group × Region interaction (F=23.871, p=4*10−9). Post-hoc Bonferroni corrected t-tests established that in healthy controls the premotor natural frequency was faster than the motor frequency (p=6*10−6), and the prefrontal natural frequency was significantly faster than the frequency of the other cortical areas (p≤2*10−8). By contrast, in schizophrenics there was no difference between the natural frequency of the four areas, suggesting a failure to show the parietal-prefrontal frequency increase of healthy comparisons (Figure 2, bottom). Furthermore, the prefrontal natural frequency could distinguish each patient with schizophrenia from healthy subjects, since the highest prefrontal natural frequency in schizophrenics was 24 Hz, while the lowest value in control subjects was 25 Hz (Figure 2, top). To assess gender effects, a factorial ANOVA with natural frequency as dependent variable and group and gender as categorical predictors was performed. This analysis showed that group (F=80.04, p=1.1*10−9) was highly significant, whereas gender failed to reach significance (F=0.42, p=0.52), and showed no interaction with group (F=2.48, p=0.12). Within subject reproducibility of the prefrontal natural frequency was assessed in a subset of schizophrenia patients (n=7) and healthy controls (n=11), and was found to be highly stable (±2 Hz, Supp. Figure 2). To confirm that no outliers were driving group effects/correlations, and to establish that individual prefrontal natural frequency values were within expected group level ranges, we performed the Grubbs’ test23. No outliers in either the healthy (highest Z value=1.74, critical Z value=2.7, p>0.05) or schizophrenia (highest Z value=1.91, critical Z value=2.7, p>0.05) group were found.
We also performed correlation analysis between prefrontal natural frequency and PANSS scores, and found that it was inversely related to positive symptoms (r=−0.55, p=0.01, Figure 3, left). Prefrontal natural frequency values showed the strongest, inverse correlation with two sub-scores of PANSS positive symptoms, feeling of grandiosity (P5, r=−0.51, p=0.02) and delusions (P1, r=−0.62, p=0.003). By contrast, the prefrontal natural frequency did not correlate with medication doses in schizophrenia patients (Supp. Table 1).
Topographic analysis of γ-range (30–50 Hz) spontaneous EEG showed similar activity across groups throughout the scalp, including the prefrontal region (Supp. Fig. 1). Statistical comparison found no difference between schizophrenia patients and healthy controls (F1,38=1.27; p=0.3). To investigate spontaneous γ immediately preceding TMS, we averaged γ activity in the 300 ms before TMS of the prefrontal cortex in each subject and performed an unpaired t-test between schizophrenic and healthy individuals. No significant difference in γ between groups was found (healthy subjects mean=0.2 μV2, schizophrenia patients mean=0.13 μV2, F1,38=3.3, p=0.08).
To assess whether the slowing of prefrontal natural frequency affected some aspects of cognitive performance in schizophrenia, a subset of schizophrenia patients completed two computer-based cognitive tasks, the Penn Word Recognition (CPW) and the Penn Facial Memory (CPF) Tests. Overall performance and median reaction time were correlated with prefrontal natural frequency values in these patients. We found that, while schizophrenics did not significantly differ in total number of correctly recognized words when compared to PENN normative data from healthy comparisons (Z score=−0.14, t-ratio=0.91, p=0.4), their reaction time for correctly identified words (CRT) was significantly slower (Z score=−1.1, t-ratio= 87.6, p<0.0001). The slowing of prefrontal natural frequency in schizophrenics, which did not correlate with their overall performance (r=−0.11, p=0.8), was inversely related to their CRT (r=−0.63, p=0.02, Figure 3 right). By contrast, no significant correlation between prefrontal natural frequency and reaction time in CPF was found (r=−0.29, p=0.3).
We employed TMS to directly perturb posterior parietal, motor, premotor, and prefrontal regions, and hd-EEG to measure their oscillatory activity. We found a reduction in TMS-related amplitude (ERSP) and synchronization (ITC) of β/γ-band EEG oscillations recorded at frontal/prefrontal sites in schizophrenia patients compared to healthy controls. Schizophrenics also showed a slowing in the main oscillatory frequency, the natural frequency, of frontal/prefrontal oscillations. Each schizophrenia patient had a slower prefrontal natural frequency than any healthy comparison, and this prefrontal slowing predicted level of positive symptoms and reaction time in a word memory task.
Frontal β/γ-band deficits were recently reported in schizophrenia. Schizophrenia patients had decreased β synchrony and perceptual impairments in a study of long-range synchronization during face perception24 and a reduction of β-band power associated with auditory gating deficits25. Deficits in frontal fast synchrony/amplitude were shown by event-related studies, including oddball9,26–28 and illusory square discrimination visual paradigms29, as well as by studies using cognitive probes3,30 in schizophrenics. A recent EEG study showed that during an N-back task increased prefrontal γ oscillations correlated with greater cognitive demand, and repetitive TMS could potentiate γ oscillations in healthy, but not schizophrenia subjects31, while another EEG study employing TMS to directly perturb a frontal area (premotor cortex) found that schizophrenics had decreased frontal γ amplitude (ERSP) and synchronization (ITC) compared to healthy comparisons11.
One aim of this study was to establish whether TMS-evoked EEG fast oscillation deficits were specific for frontal thalamo-cortical circuits in schizophrenia. Whereas no difference was found between evoked EEG oscillations after TMS of the parietal cortex between schizophrenics and healthy subjects, following TMS of the motor area schizophrenia patients had smaller evoked EEG oscillations. Since there were no motor threshold differences across groups, these findings argue against differences in neuronal excitability between schizophrenia and healthy subjects, and likely reflect impairments in local cortical and thalamo-cortical circuits in schizophrenia32–33. Although in parietal and motor regions some fast, γ-range oscillations were observed right after TMS, the main oscillatory activity (i.e., natural frequency) of these areas was in the low β-band. TMS-evoked β-range motor oscillation reduction in schizophrenics is consistent with decreased β-band sensorimotor synchronization during a self-paced button press paradigm34 as well as reduced contra-lateral sensorimotor β oscillations during proprioceptive evoked potentials35 found in schizophrenics compared to healthy controls.
An important goal of this study was to establish if deficits in prefrontal high β/γ oscillations, which were much smaller and less synchronous in schizophrenia patients, were due to an intrinsic defect of underlying thalamo-cortical circuits. To achieve this goal, we capitalized on recent TMS/hd-EEG work showing the possibility to characterize the intrinsic oscillatory frequency, or natural frequency, of human thalamo-cortical circuits. In this study, TMS consistently evoked α-band oscillations in the occipital cortex, low-β-range oscillations in the parietal cortex, and high-β/γ oscillations in the premotor area in healthy controls12. Here we found that the prefrontal natural frequency was markedly defective in schizophrenia patients, to the extent that there was no overlap between prefrontal frequency values across groups. A limitation of the present study was that the two groups were not gender-matched (Table 1); however, gender differences are unlikely to account for these findings. Indeed, a factorial ANOVAs showed no gender effects on the prefrontal natural frequency differences between schizophrenic and healthy subjects. Furthermore, the absence of overlap between schizophrenia and healthy subjects suggests that regardless of the gender these patients were unable to generate prefrontal oscillations at the same frequency of healthy controls.
Recent imaging data suggested an implication of prefrontal cortex in positive symptoms, and especially delusions. An fMRI study showed that reduced prefrontal-hippocampal connectivity correlated with higher PANSS positive symptoms in schizophrenia patients36, while another fMRI study reported that increased delusion severity in schizophrenics was associated with decreased prefrontal activation during a reward task37. Here we found that the prefrontal natural frequency was inversely related to positive symptoms, and the strongest correlation was with delusion PANSS sub-scores in schizophrenics. Recent modeling work demonstrated that reduced GABA-ergic inhibition within prefrontal circuits increases vulnerability to psychosis38, whereas another modeling study showed that reductions in GABA-ergic activity resulted in reduced cortical fast oscillations39. Thus, a common mechanism underlying both the slowing of prefrontal natural frequency and the increased severity of psychosis may be a decreased (GABA-ergic) inhibitory control on cortical excitatory neurons.
A defect of prefrontal circuits may also cause performance impairments in perceptual/cognitive tasks in schizophrenia40. For example, during an auditory odd-ball paradigm schizophrenia patients showed enhanced nonstimulus-related frontal EEG activity, which negatively correlated with performance in an N-back WM task. Another study employing a cognitive control task found that schizophrenics had reduced frontal γ power compared to healthy controls, and γ reduction was inversely correlated to task performance4. In a recent fMRI study employing a word memory task (CPW), schizophrenics had reduced activation in the left prefrontal cortex, as well as in the thalamus, during the recognition phase, even when restricting BOLD analysis to correct responses18. Here the same task was employed, and the left prefrontal natural frequency slowing predicted an increased reaction time. Notably, no correlation was found with the performance on CPW, a word memory task implicating primarily right hemisphere areas, suggesting that the prefrontal natural frequency slowing provides a sensitive measure for deficits in lateralized cognitive functions. While the link between natural frequency and memory needs to be established in future studies, a reduced ability to generate fast oscillations, reflected by the prefrontal natural frequency slowing, may be implicated in memory impairments, as suggested by recent rat electrophysiological data showing that decreased prefrontal γ-band oscillations, combined with reduced theta hippocampal activity and disrupted hippocampal-prefrontal coherence, was associated with worse performance in memory tasks41.
No difference in spontaneous prefrontal EEG activity between healthy and schizophrenic subjects was found. This is likely related to the variability of spontaneous EEG oscillations. Resting state oscillations in a given area may reflect local activity, may be driven by the activity of other regions, or by sudden changes in cognitive state. Thus, the intrinsic activity of a given area is best assessed by directly and selectively activating it (i.e., with TMS) and by measuring its output (i.e., prefrontal natural frequency).
Two possible mechanisms could be responsible for the prefrontal natural frequency slowing: 1) an intrinsic deficit of prefrontal cortical neurons, and 2) a defect in prefrontal thalamo-cortical circuitry. GABA-ergic cortical interneurons can initiate and maintain fast oscillations generating inhibitory postsynaptic potentials (IPSPs) in excitatory pyramidal neurons. IPSPs enable the synchronization of large populations of pyramidal neurons, and IPSPs duration determine the main oscillatory frequency of these neurons42. Among GABA-ergic interneurons, fast-spiking cells expressing Ca+ binding protein parvoalbumin are particularly important, since recent in vivo experiments in mice demonstrated that inhibiting fast-spiking parvoalbumin interneurons suppressed γ oscillations, whereas driving these interneurons was sufficient to generate γ-band rhythmicity43. Similarly, decreasing fast-spiking interneurons output in a computational model of a cortical area reduced power and synchronization of γ oscillations44. Deficits in GABA-ergic activity have been consistently reported in schizophrenia45, and genetic studies found that schizophrenics had a reduction in the mRNA of GAD67, an enzyme involved in GABA synthesis, and in the density of GABA membrane transporter 1 (GAT-1)46, which was most prominent in parvalbumin-positive interneurons47. The presence of GABA deficits in schizophrenia is also supported by the observation that Clozapine, regarded as the most effective antipsychotic, is associated with potentiation of cortical GABA activity48, and by the improvement of psychosis with BL-1020, a GABA agonist, in schizophrenics49. A GABA deficiency is also suggested by the beneficial effects in schizophrenia patients of cortical stimulation techniques (e.g., ECT and rTMS), which enhance GABA-mediated control on pyramidal neurons via cortical interneurons50.
Furthermore, a recent TMS/hd-EEG study showed a decrease in GABA-mediated cortical inhibition in the dorsolateral prefrontal cortex of schizophrenics compared to healthy controls51. A reduction in GABAergic interneurons was recently demonstrated beyond the prefrontal cortex in schizophrenia52. Additionally, γ-band deficits were reported in sensory cortices, using steady-state auditory53 and visual54 stimulation as well as visual probes evoking fast oscillations55 in schizophrenia patients. These findings are consistent with the idea that GABAergic deficits become functionally apparent whenever cortical areas oscillate at fast frequencies. Here we found that, of the regions tested, the prefrontal cortex, which intrinsically oscillates at high β/γrange, was the most defective in schizophrenics.
Beside cortical neurons, thalamic and thalamo-cortical neurons have been implicated in generating fast oscillations. Recent simultaneous EEG-fMRI recordings in humans during a WM task showed load-dependent effects on BOLD as well as EEG γ-band activity in both the prefrontal cortex and the thalamus56. Furthermore, intracellular thalamic recordings combined with cortical local field potentials demonstrated that EEG γ oscillations are associated with γ-band oscillatory activity in both thalamic and cortical neurons57. In the thalamus most inhibitory neurons are located within the thalamic reticular nucleus (TRN). The TRN consists entirely of GABA-ergic neurons, receives projections from cortico-thalamic and thalamo-cortical neurons and sends efferents to all dorsal thalamus nuclei58. Intra- and extra-cellular rat recordings showed that TRN neurons can intrinsically oscillate at 30–60 Hz, and can be the γ-band oscillation pacemakers during wakefulness59. The TRN is also the pacemaker of sleep spindles, NREM sleep fast oscillations, and two recent studies found marked deficits in the spindle activity of schizophrenics compared to healthy and psychiatric controls60–61. Thus, the TRN, which is strategically placed between the cortex and the thalamus may be part of a defective cortico-TRN-thalamus circuitry underlying thalamo-cortical oscillation abnormalities in schizophrenia62.
Future studies are needed to address some of the questions left unanswered in this study. Schizophrenia patients were medicated, which raises the question whether the prefrontal natural frequency slowing was simply a medication effect. If so, one would expect a generalized, aspecific effect of antipsychotic medications on TMS-evoked EEG oscillations, which is inconsistent with the finding that the natural frequency of other cortical areas was unaffected (parietal cortex) or only partially reduced (motor cortex). Additionally, there was no correlation between medication doses and the prefrontal natural frequency of schizophrenics, even after removing the patients on first-generation antipsychotics. Furthermore, a recent study showed that both unmedicated first-episode and medicated schizophrenics had reduced task-related frontal γ oscillations compared to healthy subjects, suggesting deficits in generating frontal fast oscillations in schizophrenia independent of medication status4.
Here we found that the prefrontal natural frequency slowing in schizophrenia was such that there was no overlap between schizophrenia and healthy subjects. Future studies are needed to confirm this finding in larger groups of patients, including first-break individuals, as well as in first-degree relatives of schizophrenia probands. This would help to establish the potential of such measures as biological markers63 as well as endophenotypes64 for schizophrenia. Furthermore, collecting and comparing EEG parameters (e.g., TMS-evoked EEG oscillations, NREM sleep spindles) with several clinical/cognitive measures in the same patient population may contribute to revealing which brain activity measures predict impaired cognitive performances and clinical symptoms in schizophrenia65. As a first step in that direction, the findings reported here of a correlation between reduced prefrontal natural frequency, increased reaction time in a work memory task, and higher positive symptoms in schizophrenics point to a common deficit of the underlying prefrontal cortical/thalamo-cortical circuitry.
We thank Drs. Ron Diamond and Fred Langheim for their help in recruiting/screening study participants, Dr. Daniela Dentico for her help in performing some TMS/hd-EEG experiments, and Dr. Adenauer Casali for data analysis assistance.
This work was funded by the schizophrenia program of the HealthEmotions Research Institute; a National Institutes of Health/National Institute of Mental Health Conte Center grant, 1P20MH-077967-01A1 (Dr. Tononi); and a European Union Marie Curie grant, FP7-PEOPLE-2007-5-4-3-IRG-No208779 (Dr. Ferrarelli).