Abnormal oscillatory brain dynamics in schizophrenia: a sign of deviant communication in neural network?

Abstract

Background: Slow waves in the delta (0.5-4 Hz) frequency range are indications of normal activity in sleep. In neurological disorders, focal electric and magnetic slow wave activity is generated in the vicinity of structural brain lesions. Initial studies, including our own, suggest that the distribution of the focal concentration of generators of slow waves (dipole density in the delta frequency band) also distinguishes patients with psychiatric disorders such as schizophrenia, affective disorders, and posttraumatic stress disorder.

Methods: The present study examined the distribution of focal slow wave activity (ASWA: abnormal slow wave activity) in 116 healthy subjects, 76 inpatients with schizophrenic or schizoaffective diagnoses and 42 inpatients with affective (ICD-10: F3) or neurotic/reactive (F4) diagnoses using a newly refined measure of dipole density. Based on 5-min resting magnetoencephalogram (MEG), sources of activity in the 1-4 Hz frequency band were determined by equivalent dipole fitting in anatomically defined cortical regions.

Results: Compared to healthy subjects the schizophrenia sample was characterized by significantly more intense slow wave activity, with maxima in frontal and central areas. In contrast, affective disorder patients exhibited less slow wave generators mainly in frontal and central regions when compared to healthy subjects and schizophrenia patients. In both samples, frontal ASWA were related to affective symptoms.

Conclusion: In schizophrenic patients, the regions of ASWA correspond to those identified for gray matter loss. This suggests that ASWA might be evaluated as a measure of altered neuronal network architecture and communication, which may mediate psychopathological signs.

Figure 1

Projection of Z-scores (see method section for description of this measure) for patients with schizophrenia (upper two rows) and with affective or neurotic/reactive diagnoses (lower two rows) onto outer surface (left column) and inner view (second left column) of the brain hemispheres. The letters 'L' and 'R' behind the diagnostic groups indicate the left hemispheric and the right hemispheric views. Z-scores depict ASWA relative to the group of 116 healthy subjects with colors indicating the range of deviation from the healthy subject group; they vary between large deviation (red color = Z-scores > 0.4) to reverse deviation (lower ASWA relative to the healthy subject group; blue color = Z-scores > -0.4); small to negligible deviation from normal is depicted by green color. The segmented brain was calculated using the software package Caret (Van Essen DC, Drury HA, Dickson J, Harwell J, Hanlon D, Anderson CH (2001) An integrated software suite for surface-based analyses of cerebral cortex. J Am Med Inform Assoc, 8: 443–59), overlays of ASWA and the voxel based t-test results are based on AFNI/SUMA (Cox RW (1996) AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res, 29, 162–73).

Figure 2

Mean fronto-central ASWA (Z-scores averaged across the left- and right-frontal and the left- and right central regions, ordinate) are plotted separately for the three groups (filled circles: controls, squares: schizophrenia patients, triangles: patients with affective or neurotic/reactive diagnoses) and for age categories (abscissa: <20 yrs: n = 4 controls, 5 schizophrenics, 0 affective/neurotic patients 17–19 years of age; 20–29: n = 74 controls, 34 schizophrenics, 0 affective/neurotic patients between 20 and 29 years of age; 30–39: n = 26 controls, 28 schizophrenics, 10 affective/neurotic patients between 30 and 39 years; 40–49: n = 4 controls, 8 schizophrenics, 15 affective/neurotic patients between 40 and 49 years; 50–59: n = 3 controls, 1 schizophrenic, 13 affective/neurotic patients between 50 and 59 years; 60+: n = 5 controls, 0 schizophrenic, and 3 affective/neurotic patients 60 years and older). Symbols indicate mean values, bars standard deviation.