Research ReportThe dependence of P300 amplitude on gamma synchrony breaks down in schizophrenia
Introduction
Communication and coordination failures between different brain regions may account for a wide range of problems in schizophrenia, from psychosis to cognitive dysfunction (Phillips and Silverstein, 2003). The phenomenology of schizophrenia suggests a disturbance in integration of brain activity through loss of “inner unity” (Kraepelin, 1919) or “cognitive coordination”(Phillips and Silverstein, 2003). It has been hypothesized that many of the deficits in schizophrenia can be attributed to core abnormalities in the timing, synchronization, and efficiency of neural processes that bind and integrate information from different brain regions, as measured by EEG (Green and Nuechterlein 1999; Spencer et al., 2004b).
EEG-based averaged event-related potentials (ERPs) recorded at the scalp are evidence of underlying synchronous activity among large assemblies of neurons firing at the same frequency (Makeig et al., 2002) The finding that the P300 component in the average ERP is reduced in amplitude in schizophrenia (Jeon and Polich, 2003) suggests that there is a deficit in the power and/or trial-to-trial synchrony of the neural activity generating the average P300. In a single trial analysis of the P300, we used a 2Hz half-sine wave as a “P300 template” and fitted it to the EEG following a target tone. We found that patients with schizophrenia have greater latency variability from trial to trial and have smaller amplitudes on each trial (Ford et al., 1994). In that analysis, we reported that even when the single trials were aligned on the peak latency, the average of these latency-adjusted trials still produced a smaller amplitude in the patients. This suggested that both the consistency of the latency of the peak across trials and power on each trial were diminished in this group.
With the advent of sophisticated EEG time–frequency analysis algorithms, we are in a position to address whether (1) P300 amplitude depends on single trial estimates of power across a wide range of frequencies (2) whether P300 amplitude depends on trial to trial phase synchrony of that activity with respect to stimulus onset across trials, and (3) whether the reduction of P300 in schizophrenia can be entirely accounted for by deficits in power or synchrony at specific frequencies. Trial-to-trial phase coherence, termed phase-locking factor (Tallon-Baudry et al., 1997) or inter-trial coherence (Makeig et al., 2004) reflects the consistency across trials of the phase of the EEG at a particular frequency, or in a particular frequency band, with respect to the onset of a stimulus. When power is extracted from the average ERP, it is called “evoked power”, whereas power extracted from the single trials that go into the average ERP is called “total power”. Evoked power reflects the amplitude of oscillations that are phase locked to a stimulus event, since averaging across trials tends to cancel out non-phase locked oscillatory activity. When evoked power is removed from total power, it is referred to as “induced power” (Tallon-Baudry et al., 1997), but this practice has been questioned (Truccolo et al., 2002). Here, we report phase-locking factor and total power extracted by wavelet-based spectral decomposition of single trial EEG epochs time-locked to target stimuli presented during an “oddball” target detection task.
In this paper, we conducted two sets of analyses. In the group analyses, we compared patients to controls in the traditional time-voltage domain (P300 amplitude) and in the time-frequency domain (phase-locking factor and total power). We tested these primary hypotheses: patients will have smaller auditory target P300s than controls, the canonical finding in the literature (Jeon and Polich, 2003); patients will have reduced phase-locking factor in the frequency range of the P300 component (∼ 3Hz), consistent with single trial analyses of P300 indicating increased cross-trial latency variability in patients (Ford et al., 1994, Roschke et al., 1996, Roth et al., 2007); patients will have reduced power at the lower frequencies, consistent with our earlier report of smaller amplitude P300s regardless of the latency variability (Ford et al., 1994). In addition, we asked whether these different measures make unique or overlapping contributions to the discrimination between patients and controls.
In the correlational analyses, we asked whether people who have large P300s have higher power and greater cross-trial phase synchrony of neural activity, and if the relationships are different in patients and healthy controls. In addition, we asked whether P300 amplitude is reflective of synchrony and power at slow frequencies (3Hz) characteristic of slow P300 itself, or whether it is reflective of synchrony and power of faster neural activity, such as gamma band activity, invoked during complex cognitive and perceptual tasks (Miltner et al., 1999, Tallon-Baudry and Bertrand, 1999) or in the binding of sensory with executive cortical areas (Basar et al., 2001), which might be required in an auditory target detection task.
Section snippets
Group analyses
The results of the Group × Site analyses of variance can be seen in Table 1.
Group analyses
As predicted, patients with schizophrenia have smaller auditory target P300s than healthy comparison subjects. This confirms a large literature showing P300 amplitude reductions to auditory targets in patients with schizophrenia (for reviews, see Bramon et al., 2004, Ford, 1999, Jeon and Polich, 2003). We have also extended this literature to include power and synchrony of neural activity associated with auditory targets, at the latency of P300. We found reductions in both single trial power
Participants
EEG data were acquired from patients with schizophrenia (n = 21) and age-matched healthy comparison subjects (n = 22). All gave written informed consent after procedures had been fully described. Demographic and clinical data are summarized in Table 4. Informed consent was obtained from all subjects. This study was approved by the Human Subjects Committees at the Connecticut VA Healthcare System and Yale University.
Patients were recruited from community mental health centers, outpatient services of
Acknowledgments
This work was supported by the VA Schizophrenia Biological Research Center and grants from National Institute of Mental Health (MH40052, MH 58262, MH067967), and the National Alliance for Research in Schizophrenia and Affective Disorders (NARSAD).
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