Sex differences, gamma activity and schizophrenia.

This study explores the possibility that the more favourable clinical prognosis in females with schizophrenia may be associated with their greater network interconnectedness, which is possibly reflected in enhanced "Gamma" (40 Hz) electrical brain activity. An auditory "oddball" task was administered to 35 patients with schizophrenia and 35 age and sex matched controls (25 males and 10 females). Peak Gamma amplitude (from a time series of Gamma activity averaged for 40 target stimuli, as well as the immediately preceding 40 background tones) was examined across 19 sites. Peak Gamma activity occurred 250 to 450 ms in targets and 350 to 550 ms in backgrounds. Multiple within and between group MANOVAs were undertaken analysing both Peak Gamma amplitude (microvolts) and latency (milliseconds). Within-group, the control males showed a pattern of earlier Gamma latency in the right compared with the left hemisphere (F(1, 33)=3.70, p<.06), while control females exhibited delayed latency frontally compared with the posterior region (F(1, 33)=6.25, p<.04). This male lateralization finding and the anterior/posterior gradient in females is consistent with Goldberg's model. The patient group however, failed to show this male lateralized and female frontal-posterior pattern of Gamma activity, suggesting suboptimal network integration in the patient group, in both males and females.

Gamma activity in schizophrenia: evidence of impaired network binding?

OBJECTIVES: Gamma ('40 Hz') rhythms may play a role in the integration of sensory processing activity. Impaired temporal integration may be a key feature of the associated disturbances in schizophrenia. This is the first study to examine the time course of Gamma activity induced in response to stimuli in this disorder. METHODS: Gamma activity induced in response to task-relevant and irrelevant auditory oddball stimuli was examined in 35 medicated schizophrenics and 35 age- and gender-matched normal controls. We employed a moving Welch window with short time FFT to examine the time course of Gamma amplitude. The amplitude spectrum for each time point was de-trended to eliminate any contribution of broad spectrum activity (EEG or EMG) to Gamma amplitude. RESULTS: For targets, schizophrenics showed a significant decrease in post-stimulus Gamma response amplitude in left hemisphere and frontal sites and an increase in right hemisphere and parieto-occipital sites (P<0.0009). The abnormalities correlated with PANSS general symptom scores. In the non-targets (at a different latency), schizophrenics showed a widespread Gamma decrease (P<0.0005). CONCLUSIONS: The Gamma findings in non-targets may reflect an abnormality in appropriately processing irrelevant stimuli. This could result in defective processing of the context (integration) of relevant target information.

Synchronous cortical gamma-band activity in task-relevant cognition.

Widespread synchronous oscillatory activity, particularly in the gamma ('40 Hz') band, has been postulated to exist in the brain as a mechanism underlying binding. A new method of examining phase synchronicity across multiple electrode sites in specific EEG frequency bands as a function of time was employed, in a conventional cognitive ERP paradigm in 40 normal subjects. A significant late post-stimulus gamma synchronicity response occurred for task-relevant stimuli, whereas for task-irrelevant stimuli no such response was evident. However, an early response was seen for both task-relevant and irrelevant stimuli. This is the first empirical demonstration that widespread synchronous high frequency oscillations occur in humans in relation to cognition.

Peak gamma latency correlated with reaction time in a conventional oddball paradigm.

OBJECTIVE: To determine whether a relationship existed across trials between evoked gamma and reaction time in a conventional cognitive ERP paradigm. METHODS: Auditory oddball data in 40 normal subjects was examined. A moving Welch window and short time FFT were employed to elucidate the time course of gamma (29 to 45 Hz) activity in each single-trial target ERP. The time point with maximum total gamma amplitude (across all sites) was identified automatically, and the associated amplitude, power and latency of this peak was determined. Spearman's rank correlation was employed to examine the relationship of these measures with reaction time. RESULTS: A highly significant and robust correlation between peak gamma latency and reaction time was found (P = 0.000001). Further frequency analysis revealed that this relationship was primarily confined to the 37 to 41 Hz band. This narrow band finding, coupled with the fact that the finding remained after exclusion of possibly EMG contaminated epochs, indicated that the effect was not due to EMG contamination. No relationship between peak gamma amplitude or power and reaction time was found. CONCLUSIONS: Peak evoked gamma latency was correlated with reaction time and seems likely to have functional significance in relation to stimulus processing.

Prestimulus EEG alpha phase synchronicity influences N100 amplitude and reaction time.

The influence of the level of prestimulus alpha phase synchronicity on the N100 component and reaction time (RT) was examined, in target auditory oddball data from 25 normal subjects. Alpha phase synchronicity is a new measure consisting (for a given stimulus presentation) of the angular or circular variance of the alpha phase at stimulus onset across the parieto-occipital sites. The lower the angular variance, the higher the phase synchronicity (the more closely in phase the alpha activity across these sites) and vice versa. Subaveraged event-related potentials (ERPs) were formed for high and low prestimulus alpha phase synchronicity stimulus presentations. N100 amplitude was significantly greater in the high than the low phase synchronicity subaverages. In addition, RT was significantly reduced in the high prestimulus alpha phase synchronicity cases. Alpha phase synchronicity reflects an aspect of brain state that influences subsequent stimulus processing.

EEG alpha phase at stimulus onset significantly affects the amplitude of the P3 ERP component.

Analysis of the relationship between prestimulus EEG alpha phase and the subsequent ERP has proved difficult because of the non-Euclidean nature of phase measurements. In this study, we employed a conventional P3 templating method of single-trial analysis to identify the P3 component in target auditory oddball data from 25 normals. As in previous studies, the absence or near absence of P3 from a subset of single-trials was clearly demonstrated. We investigated this phenomenon to determine whether those single-trials with a large P3 had a different prestimulus alpha phase from those with a small or no P3. Statistical analysis of phase required the use of circular statistical analysis and the development of a new form of topographic mapping, circular topography. The alpha phase at stimulus onset in single-trials with a large P3 was significantly different from that in single-trials with a small or no P3 (p = .02).

To scale or not to scale: McCarthy and Wood revisited.

We dispute McCarthy and Wood's (1985) claim that some form of scaling should be applied routinely to ERP data before determining differences in scalp distributions between conditions (or groups). Their simulation study involved assumptions about the nature of the variability within each condition, most significantly that the standard deviations are identical at all electrodes, irrespective of the means. Alternative plausible assumptions may be proposed for which scaling is unnecessary. Furthermore, we show that the two main forms of scaling they proposed may distort or even completely eliminate real differences in scalp topography reflecting genuinely different underlying sources.

Classification of single-trial ERP sub-types: application of globally optimal vector quantization using simulated annealing.

Examination of the single trials which are traditionally averaged to form late-component ERPs reveals a number of different sub-types of response. This study introduces an automated and robust approach to objectively classify these ERP sub-types. Auditory oddball ERP (target tones) data were examined in 25 normal subjects. Globally optimal vector quantization using simulated annealing (the "Metropolis algorithm") was employed to determine the natural groupings of the single-trial responses that constitute the average ERP. No prior assumptions about the ERP patterns were imposed. This is the first study to employ a cluster analysis technique with globally optimal properties in ERP research. We demonstrate that, due to the presence of many different undesirable local minima, a globally optimal solution is crucial if the classification of the single-trial ERPs is to reflect their real structure. The results of this study showed that only around 40% of single trials had a morphology which resembled the averaged ERP wave form. The remaining single trials had a response morphology which was different from the average, in terms of the amplitude and latency of the components. Single-trial ERP response sub-types may provide fundamental complementary functional information to the ERP average.

Projection onto centroids difference vectors: a new approach to determine between group topographical differences, applied to P3 amplitude in schizophrenia.

A common problem in electrophysiological research concerns between group analysis of EEG and ERP topography. This paper proposes a new technique for determining whether or not a significant difference exists between multiple scalp site measurements from two groups. The method requires no a priori assumptions about the data and is thus ideal for exploratory data analysis, and it also requires that only one statistical test need be performed (significantly reducing the possibility of type I errors). The Projection onto Centroids Difference Vectors (PCDV) method involves deriving a measure from each individual of whether their measurements across sites are closer overall to the mean measurements of the rest of their experimental group, or to the other group. These measures from each individual are then compared between groups using a Student's t test, which indicates whether one group's data is significantly spatially different from the other. In this study we describe the method in detail and apply it to both stimulated data and to real auditory P3 data in unmedicated, medicated schizophrenics and matched normal controls. The PCDV method was also compared with statistical probability mapping (SPM). The PCDV method revealed the differences between the normal and patient groups more unambiguously than SPM, and the simulated data revealed that it was not liable to type I errors. PCDV provides an appropriate method for testing any between group EEG and ERP topographical differences.