The topography of quantified electroencephalography in three syndromes of schizophrenia

Fractal Structure of Brain Electrical Activity of Patients With Mental Disorders

This work was aimed at a comparative analysis of the degree of multifractality of electroencephalographic time series obtained from a group of healthy subjects and from patients with mental disorders. We analyzed long-term records of patients with paranoid schizophrenia and patients with depression. To evaluate the properties of multifractal scaling of various electroencephalographic time series, the method of maximum modulus of the wavelet transform and multifractal analysis of fluctuations without a trend were used. The stability of the width and position of the singularity spectrum for each of the test groups was revealed, and a relationship was established between the correlation and anticorrelation dynamics of successive values of the electroencephalographic time series and the type of mental disorders. It was shown that the main differences between the multifractal properties of brain activity in normal and pathological conditions lie in the different width of the multifractality spectrum and its location associated with the correlated or anticorrelated dynamics of the values of successive time series. It was found that the schizophrenia group is characterized by a greater degree of multifractality compared to the depression group. Thus, the degree of multifractality can be included in a set of tests for differential diagnosis and research of mental disorders.

Dissecting the neurobiology of linguistic disorganisation and impoverishment in schizophrenia

Schizophrenia provides a quintessential disease model of how disturbances in the molecular mechanisms of neurodevelopment lead to disruptions in the emergence of cognition. The central and often persistent feature of this illness is the disorganisation and impoverishment of language and related expressive behaviours. Though clinically more prominent, the periodic perceptual distortions characterised as psychosis are non-specific and often episodic. While several insights into psychosis have been gained based on study of the dopaminergic system, the mechanistic basis of linguistic disorganisation and impoverishment is still elusive. Key findings from cellular to systems-level studies highlight the role of ubiquitous, inhibitory processes in language production. Dysregulation of these processes at critical time periods, in key brain areas, provides a surprisingly parsimonious account of linguistic disorganisation and impoverishment in schizophrenia. This review links the notion of excitatory/inhibitory (E/I) imbalance at cortical microcircuits to the expression of language behaviour characteristic of schizophrenia, through the building blocks of neurochemistry, neurophysiology, and neurocognition.

Separating scale-free and oscillatory components of neural activity in schizophrenia

INTRODUCTION

Alterations in narrow-band spectral power of electroencephalography (EEG) recordings are commonly reported in patients with schizophrenia (SZ). It is well established however that electrophysiological signals comprise a broadband scale-free (or fractal) component generated by mechanisms different from those producing oscillatory neural activity. Despite this known feature, it has not yet been investigated if spectral abnormalities found in SZ could be attributed to scale-free or oscillatory brain function.

METHODS

In this study, we analyzed resting-state EEG recordings of 14 SZ patients and 14 healthy controls. Scale-free and oscillatory components of the power spectral density (PSD) were separated, and band-limited power (BLP) of the original (mixed) PSD, as well as its fractal and oscillatory components, was estimated in five frequency bands. The scaling property of the fractal component was characterized by its spectral exponent in two distinct frequency ranges (1-13 and 13-30 Hz).

RESULTS

Analysis of the mixed PSD revealed a decrease of BLP in the delta band in SZ over the central regions; however, this difference could be attributed almost exclusively to a shift of power toward higher frequencies in the fractal component. Broadband neural activity expressed a true bimodal nature in all except frontal regions. Furthermore, both low- and high-range spectral exponents exhibited a characteristic topology over the cortex in both groups.

CONCLUSION

Our results imply strong functional significance of scale-free neural activity in SZ and suggest that abnormalities in PSD may emerge from alterations of the fractal and not only the oscillatory components of neural activity.

Multifractal and Entropy-Based Analysis of Delta Band Neural Activity Reveals Altered Functional Connectivity Dynamics in Schizophrenia

Dynamic functional connectivity (DFC) was established in the past decade as a potent approach to reveal non-trivial, time-varying properties of neural interactions – such as their multifractality or information content –, that otherwise remain hidden from conventional static methods. Several neuropsychiatric disorders were shown to be associated with altered DFC, with schizophrenia (SZ) being one of the most intensely studied among such conditions. Here we analyzed resting-state electroencephalography recordings of 14 SZ patients and 14 age- and gender-matched healthy controls (HC). We reconstructed dynamic functional networks from delta band (0.5–4 Hz) neural activity and captured their spatiotemporal dynamics in various global network topological measures. The acquired network measure time series were made subject to dynamic analyses including multifractal analysis and entropy estimation. Besides group-level comparisons, we built a classifier to explore the potential of DFC features in classifying individual cases. We found stronger delta-band connectivity, as well as increased variance of DFC in SZ patients. Surrogate data testing verified the true multifractal nature of DFC in SZ, with patients expressing stronger long-range autocorrelation and degree of multifractality when compared to controls. Entropy analysis indicated reduced temporal complexity of DFC in SZ. When using these indices as features, an overall cross-validation accuracy surpassing 89% could be achieved in classifying individual cases. Our results imply that dynamic features of DFC such as its multifractal properties and entropy are potent markers of altered neural dynamics in SZ and carry significant potential not only in better understanding its pathophysiology but also in improving its diagnosis. The proposed framework is readily applicable for neuropsychiatric disorders other than schizophrenia.

EEG Frequency Bands in Psychiatric Disorders: A Review of Resting State Studies

A significant proportion of the electroencephalography (EEG) literature focuses on differences in historically pre-defined frequency bands in the power spectrum that are typically referred to as alpha, beta, gamma, theta and delta waves. Here, we review 184 EEG studies that report differences in frequency bands in the resting state condition (eyes open and closed) across a spectrum of psychiatric disorders including depression, attention deficit-hyperactivity disorder (ADHD), autism, addiction, bipolar disorder, anxiety, panic disorder, post-traumatic stress disorder (PTSD), obsessive compulsive disorder (OCD) and schizophrenia to determine patterns across disorders. Aggregating across all reported results we demonstrate that characteristic patterns of power change within specific frequency bands are not necessarily unique to any one disorder but show substantial overlap across disorders as well as variability within disorders. In particular, we show that the most dominant pattern of change, across several disorder types including ADHD, schizophrenia and OCD, is power increases across lower frequencies (delta and theta) and decreases across higher frequencies (alpha, beta and gamma). However, a considerable number of disorders, such as PTSD, addiction and autism show no dominant trend for spectral change in any direction. We report consistency and validation scores across the disorders and conditions showing that the dominant result across all disorders is typically only 2.2 times as likely to occur in the literature as alternate results, and typically with less than 250 study participants when summed across all studies reporting this result. Furthermore, the magnitudes of the results were infrequently reported and were typically small at between 20% and 30% and correlated weakly with symptom severity scores. Finally, we discuss the many methodological challenges and limitations relating to such frequency band analysis across the literature. These results caution any interpretation of results from studies that consider only one disorder in isolation, and for the overall potential of this approach for delivering valuable insights in the field of mental health.

Local and Widely Distributed EEG Activity in Schizophrenia With Prevalence of Negative Symptoms

We evaluated EEG frequency abnormalities in resting state (eyes closed and eyes open) EEG in a group of chronic schizophrenia patients as compared with healthy subjects. The study included 3 methods of analysis of deviation of EEG characteristics: genuine EEG, current source density (CSD), and group independent component (gIC). All 3 methods have shown that the EEG in schizophrenia patients is characterized by enhanced low-frequency (delta and theta) and high-frequency (beta) activity in comparison with the control group. However, the spatial pattern of differences was dependent on the type of method used. Comparative analysis has shown that increased EEG power in schizophrenia patients apparently concerns both widely spatially distributed components and local components of signal. Furthermore, the observed differences in the delta and theta range can be described mainly by the local components, and those in the beta range mostly by spatially widely distributed ones. The possible nature of the widely distributed activity is discussed.

Electroencephalographic characteristics of Iranian schizophrenia patients

Schizophrenia is a prevalent psychiatric disease with heterogeneous causes that is diagnosed based on history and mental status examination. Applied electrophysiology is a non-invasive method to investigate the function of the involved brain areas. In a previously understudied population, we examined acute phase electroencephalography (EEG) records along with pertinent Positive and Negative Syndrome Scale (PANSS) and Mini Mental State Examination (MMSE) scores for each patient. Sixty-four hospitalized patients diagnosed to have schizophrenia in Ebn-e-Sina Hospital were included in this study. PANSS and MMSE were completed and EEG tracings for every patient were recorded. Also, EEG tracings were recorded for 64 matched individuals of the control group. Although the predominant wave pattern in both patients and controls was alpha, theta waves were almost exclusively found in eight (12.5 %) patients with schizophrenia. Pathological waves in schizophrenia patients were exclusively found in the frontal brain region, while identified pathological waves in controls were limited to the temporal region. No specific EEG finding supported laterality in schizophrenia patients. PANSS and MMSE scores were significantly correlated with specific EEG parameters (all P values <0.04). Patients with schizophrenia demonstrate specific EEG patterns and show a clear correlation between EEG parameters and PANSS and MMSE scores. These characteristics are not observed in all patients, which imply that despite an acceptable specificity, they are not applicable for the majority of schizophrenia patients. Any deduction drawn based on EEG and scoring systems is in need of larger studies incorporating more patients and using better functional imaging techniques for the brain.

Brain connectivity in positive and negative syndrome schizophrenia

If, as is widely believed, schizophrenia is characterized by abnormalities of brain functional connectivity, then it seems reasonable to expect that different subtypes of schizophrenia could be discriminated in the same way. However, evidence for differences in functional connectivity between the subtypes of schizophrenia is largely lacking and, where it exists, it could be accounted for by clinical differences between the patients (e.g. medication) or by the limitations of the measures used. In this study, we measured EEG functional connectivity in unmedicated male patients diagnosed with either positive or negative syndrome schizophrenia and compared them with age and sex matched healthy controls. Using new methodology (Medkour et al., 2009) based on partial coherence, brain connectivity plots were constructed for positive and negative syndrome patients and controls. Reliable differences in the pattern of functional connectivity were found with both syndromes showing not only an absence of some of the connections that were seen in controls but also the presence of connections that the controls did not show. Comparing connectivity graphs using the Hamming distance, the negative-syndrome patients were found to be more distant from the controls than were the positive syndrome patients. Bootstrap distributions of these distances were created which showed a significant difference in the mean distances that was consistent with the observation that negative-syndrome diagnosis is associated with a more severe form of schizophrenia. We conclude that schizophrenia is characterized by widespread changes in functional connectivity with negative syndrome patients showing a more extreme pattern of abnormality than positive syndrome patients.

Spatio-temporal EEG waves in first episode schizophrenia

OBJECTIVE

Schizophrenia is characterized by a deficit in context processing, with physiological correlates of hypofrontality and reduced amplitude P3b event-related potentials. We hypothesized an additional physiological correlate: differences in the spatio-temporal dynamics of cortical activity along the anterior-posterior axis of the scalp.

METHODS

This study assessed latency topographies of spatio-temporal waves under task conditions that elicit the P3b. EEG was recorded during separate auditory and visual tasks. Event-related spatio-temporal waves were quantified from scalp EEG of subjects with first episode schizophrenia (FES) and matched controls.

RESULTS

The P3b-related task conditions elicited a peak in spatio-temporal waves in the delta band at a similar latency to the P3b event-related potential. Subjects with FES had fewer episodes of anterior to posterior waves in the 2-4 Hz band compared to controls. Within the FES group, a tendency for fewer episodes of anterior to posterior waves was associated with high Psychomotor Poverty symptom factor scores.

CONCLUSIONS

Subjects with FES had altered global EEG dynamics along the anterior-posterior axis during task conditions involving context update.

SIGNIFICANCE

The directional nature of this finding and its association with Psychomotor Poverty suggest this result is related to findings of hypofrontality in schizophrenia.

Evidence-based medicine and electrophysiology in schizophrenia

In research on schizophrenia electrophysiological measures have been investigated to identify biomarkers of the disorder, indices enabling differential diagnosis among psychotic disorders, prognostic indicators or endophenotypes. The present systematic review will focus on the most largely studied electrophysiological indices, i.e., qualitative or quantitative (limited to spectral analysis) EEG and the P300 event-related potential. The PubMed clinical query was used with research methodology filters for each of the following categories: diagnosis/prognosis/ aetiology and a broad sensitive search strategy. The key-words: SCHIZOPHRENIA AND EEG/P3/P300 were used. The search results were then narrowed by including the terms "human" and "English language", and cross-referenced. Systematic reviews and meta-analyses, when available, were also used for cross-referencing. Case reports and studies irrelevant to the topics and methodologies under examination were excluded. The remaining papers were screened to verify the eligibility for this systematic review. Inclusion criteria were: a) a diagnosis of schizophrenia confirmed by DSM-III/ICD-9 criteria (or later editions of the same classification systems); b) the inclusion of both a schizophrenia study group and an healthy control group (when appropriate, i.e., for P300 and quantitative EEG); c) qualitative or spectral EEG findings and amplitude measures for P300. The included studies were then reviewed to verify homogeneity of the results, as well as the presence of the information needed for the present systematic review and meta-analysis. Previous reviews and studies meeting the above requirements (n = 22 for qualitative EEG; n = 45 for spectral EEG and n = 132 for P300) were classified according to the Oxford Centre for Evidence-based Medicine (EBM) levels of evidence criteria. For qualitative EEG as a diagnostic test, the majority of studies predated the introduction of DSM-III and were excluded from the review. Few post DSM-III studies investigated the usefulness of qualitative EEG in the differential diagnosis between schizophrenia and psychosis due to general medical condition. None of them was Oxford CEBM level 3b (non-consecutive-study or cohort-study without consistently-applied reference standard) or better (exploratory or validating cohort-study). No meta-analysis could be conducted due to the lack of reliable quantification methods in the reviewed studies. For spectral EEG as a diagnostic test, most studies qualified as level 4 (case-control study with poor reference standard), and only 24% as level 3b or better. An increase of slow activity in patients is reported by most of these studies. As to meta-analyses examining 29 studies, with 32 independent samples for the delta band and 35 for the theta band, a moderate effect size was found and only 1 study yielded findings in the opposite direction for both measures. There was no identified source for the discrepancy. The analysis of moderator factors included medication, band frequency limits, spectral parameters and disease stage. The medication status was significant for the theta band but the effect was unclear as findings for drug-naïve and drug-free patients were in a different direction. Chronicity had a significant effect on both delta and theta bands, with slow activity increase larger in chronic than in first episode patients. For P3 amplitude reduction as a diagnostic index, 63% of the studies qualified as level 3b or better. Meta-analysis (52 studies, 60 independent samples) results demonstrated a large effect size. None of the studies reported opposite findings. The analysis of moderator factors, including medication status and disease stage, revealed no significant effect on data heterogeneity. In conclusion, the examined indices are good candidates but are not ready yet for clinical applications aimed to improve present diagnostic standards for schizophrenia. Further research carried out according to adequate methodological standards and based on large scale multi-center studies is mandatory.

REM sleep EEG spectral analysis in patients with first-episode schizophrenia

The pathophysiology of schizophrenia includes abnormalities in subcortical-cortical transfer of information that can be studied using REM sleep EEG spectral analysis, a measure that reflects spontaneous and endogenous thalamocortical activity. We recorded 10 patients with first-episode schizophrenia and 30 healthy controls for two consecutive nights in a sleep laboratory, using a 10-electrode EEG montage. Sixty seconds of REM sleep EEG without artifact were analyzed using FFT spectral analysis. Absolute and relative spectral amplitudes of five frequency bands (delta, theta, alpha, beta1 and beta2) were extracted and compared between the two groups. Frequency bands with significant differences were correlated with BPRS positive and negative symptoms scores. Patients with schizophrenia showed lower relative alpha and higher relative beta2 spectral amplitudes compared to healthy controls over the averaged total scalp. Analysis using cortical regions showed lower relative alpha over frontal, central and temporal regions and higher relative beta2 over the occipital region. Absolute spectral amplitude was not different between groups for any given EEG band. However, absolute alpha activity correlated negatively with BPRS positive symptoms scores and correlated positively with negative symptoms scores. Since similar results have been reported following EEG spectral analysis during the waking state, we conclude that abnormalities of subcortical-cortical transfer of information in schizophrenia could be generated by mechanisms common to REM sleep and waking.

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

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.

Correlation of symptom clusters of schizophrenia with absolute powers of main frequency bands in quantitative EEG

Background

Research of QEEG activity power spectra has shown intriguing results in patients with schizophrenia. Different symptom clusters have been correlated to QEEG frequency bands. The findings have been to some extent inconsistent. Replication of the findings of previous research is thus an important task. In the current study we investigated the correlations between the absolute powers of delta, theta, alpha, and beta frequency bands over the fronto-central scalp area (FC) with the PANSS subscales and the Liddle's factors in 16 patients with schizophrenia.

The authors hypothesised a priori the correlations reported by Harris et al (1999) of PANSS negative subscale with delta power, Liddle's psychomotor poverty with delta and beta powers, disorganisation with delta power and reality distortion with alpha power on the midline FC.

Methods

The sample consisted of 16 patients with chronic schizophrenia considered as having insufficient clinical response to conventional antipsychotic treatment and evidencing a relapse. The correlations between quantitative electroencephalography (QEEG) absolute powers of delta (1.5–3.0 Hz), theta (3.0–7.5 Hz), alpha (7.5–12.5 Hz), and beta (12.5–20.0 Hz) frequency bands over the fronto-central scalp area (FC) with PANSS subscales and Liddle's factors (reality distortion, disorganisation, psychomotor poverty) were investigated.

Results

Significant positive correlations were found between the beta and psychomotor poverty (p < 0.05). Trends towards positive correlations (p < 0.1) were observed between delta and PANSS negative subscale and psychomotor poverty. Alpha did not correlate with reality distortion and delta did not correlate with disorganisation.

Post hoc analysis revealed correlations of the same magnitude between beta and psychopathology generally over FC.

Conclusion

The a priori hypothesis was partly supported by the correlation of the beta and psychomotor poverty. Liddle's factors showed correlations of the same magnitude with PANSS subscales. Supplementary analysis showed beta frequency correlating non-specifically over FC with a wide range of psychiatric symptomatology in patients with schizophrenia having a relapse.

Differentiating autistic children with quantitative encephalography: a 3-month longitudinal study

The present study used a single-channel quantitative electroencephalographic (EEG) assessment to differentiate autistic children from normal control subjects. One hundred five normal and 17 autistic children participated in the study. In addition to amplitude measures of the frequency bands of delta, theta, alpha, sensorimotor rhythm, and beta and the theta to beta ratio, intra- (6 minutes) and intersessional (3 months) consistencies were also examined. The results indicated that autistic children showed significantly higher quantitative EEG amplitudes in many of the frequency bands than normal children; furthermore, their quantitative EEG activities were found to be relatively unstable within a 6-minute session compared with normal children. Discriminant function analyses revealed that absolute sensorimotor rhythm and beta amplitudes were the best predictors that correctly differentiated autistic children from normal children in the present sample, with a high accuracy rate of 95.2%. In addition, quantitative EEG measurements of normal and autistic children were found to be generally consistent across the 3-month period.

The nonlinear theory of schizophrenia

OBJECTIVE

Nonlinear properties exist within the brain across a hierarchy of scales and within a variety of critical neural processes. Only a few studies of brain activity in schizophrenia, however, have used nonlinear methods. This review paper evaluates the contribution of the nonlinear sciences towards understanding schizophrenia.

METHOD

Applications of nonlinear methods to the study of schizophrenia symptoms and to healthy and schizophrenia functional neuroscience data are reviewed. The main flaws of nonlinear algorithms and recent methods to correct these are also appraised.

RESULTS

Initial research methods utilized in the study of nonlinearity in schizophrenia have fundamental methodological limitations. In the last decade, many of these problems have been addressed, facilitating future progress. Research incorporating these improvements has been applied to normal electroencephalogram (EEG) data and to the symptoms of schizophrenia, but not systematically to brain imaging data collected from patients with schizophrenia.

CONCLUSION

There is strong statistical evidence for weak nonlinearity in normal EEG and in the fluctuations of the symptoms of schizophrenia. However, the contribution of nonlinear processes to brain dysfunction in schizophrenia is yet to be properly established or accurately quantified. Despite this, recent methodological advances suggest that a 'nonlinear theory' of schizophrenia may be helpful in understanding this disorder.

NEUROPHYSIOLOGICALLY-BASED MEAN-FIELD MODELLING OF TONIC CORTICAL ACTIVITY IN POST-TRAUMATIC STRESS DISORDER (PTSD), SCHIZOPHRENIA, FIRST EPISODE SCHIZOPHRENIA AND ATTENTION DEFICIT HYPERACTIVITY DISORDER (ADHD)

A recently developed quantitative model of cortical activity is used that permits data comparison with experiment using a quantitative and standardized means. The model incorporates properties of neurophysiology including axonal transmission delays, synaptodendritic rates, range-dependent connectivities, excitatory and inhibitory neural populations, and intrathalamic, intracortical, corticocortical and corticothalamic pathways. This study tests the ability of the model to determine unique physiological properties in a number of different data sets varying in mean age and pathology. The model is used to fit individual electroencephalographic (EEG) spectra from post-traumatic stress disorder (PTSD), schizophrenia, first episode schizophrenia (FESz), attention deficit hyperactivity disorder (ADHD), and their age/sex matched controls. The results demonstrate that the model is able to distinguish each group in terms of a unique cluster of abnormal parameter deviations. The abnormal physiology inferred from these parameters is also consistent with known theoretical and experimental findings from each disorder. The model is also found to be sensitive to the effects of medication in the schizophrenia and FESz group, further supporting the validity of the model.

A source-imaging (low-resolution electromagnetic tomography) study of the EEGs from unmedicated men with schizophrenia

Imaging studies and quantitative electroencephalography (EEG) have often, but not consistently, implicated the left hemisphere and the prefrontal cortex in schizophrenia. To help clarify this picture, a spatial filter shown to be effective for enhancing differences between EEG populations was combined with low-resolution electromagnetic tomography and used to compare the source-current densities from a group of 57 male subjects with schizophrenia and a group of 65 matched controls. To elicit differences, comparisons were made during resting conditions and during verbal and spatial cognitive challenges to the subjects. Estimates of the source-current density were derived from 43-electrode recordings of the EEG reduced to the delta, alpha and beta frequency bands. The patients were unmedicated and were selected according to DSM-IV criteria. As a group, they were severe, chronic states with both deficit negative and superimposed florid psychotic symptomatology. The results confirm that schizophrenia is a left-hemispheric disorder centered in the temporal and frontal lobes. They also suggest that, in schizophrenia, functions normally performed by these regions in controls are assumed by homologous regions in the opposite hemispheres.

Source distribution of neuromagnetic slow wave activity in schizophrenic and depressive patients

OBJECTIVE

Focal slow waves in the delta and theta frequency range frequently appear in psychopathological conditions. Due to their focal nature they can be localized by dipole modeling. We previously reported regional clustering of slow waves in temporal and parietal cortex of schizophrenic patients whereas such activity is largely absent in normals. Here we examine, to what extent distribution of slow wave generators differentiates schizophrenic from depressive syndromes.

METHODS

The regional densities of generators of focal slow waves were determined during resting conditions in patients with DSM-IV diagnoses of schizophrenia (N=25) and depression (N=27) and in 18 healthy controls.

RESULTS

Schizophrenic patients demonstrated accentuated temporal and parietal delta and theta dipole clustering, when compared to both the control and the depressive sample. In contrast, depressive patients had reduced frontal and prefrontal delta and theta dipole density relative to both schizophrenics and controls. This pattern was not related to age. Men generally displayed somewhat higher slow wave activity than women. For the areas of most pronounced slow wave deviances activity within each group was related to symptom scores: higher left-temporal slow wave activity was associated with hallucinations in schizophrenics, suppression of left-prefrontal slow wave activity correlated with depression scores.

CONCLUSIONS

Results suggest that slow wave distribution may assist in differentially diagnosing psychopathological conditions.

A disturbance of nonlinear interdependence in scalp EEG of subjects with first episode schizophrenia

It has been proposed that schizophrenia arises through a disturbance of coupling between large-scale cortical systems. This "disconnection hypothesis" is tested by applying a measure of dynamical interdependence to scalp EEG data. EEG data were collected from 40 subjects with a first episode of schizophrenia and 40 matched healthy controls. An algorithm for the detection of dynamical interdependence was applied to six pairs of bipolar electrodes in each subject. The topographic organization of the interdependence was calculated and served as the principle measure of cortical integration. The rate of occurrence of dynamical interdependence did not statistically differ between subject groups at any of the sites. However, the topography across the scalp was significantly different between the two groups. Specifically, nonlinear interdependence tended to occur in larger concurrent "clusters" across the scalp in schizophrenia than in the healthy subjects. This disturbance was reflected most strongly in left intrahemispheric coupling and did not differ significantly according to symptomatology. Medication dose and subject arousal were not observed to be confounding factors. The study of dynamical interdependence in scalp EEG data does not support a straightforward interpretation of the disconnection hypothesis-that there is a decrease in the strength of functional coupling between adjacent cortical regions. Rather, it suggests a dysregulation in the organization of dynamical interactions across supraregional brain systems.

Induced oscillations and the distributed cortical sources during the Wisconsin card sorting test performance in schizophrenic patients: new clues to neural connectivity

Prefrontal dysfunction has been associated with schizophrenia. Activation during Wisconsin card sorting test (WCST) is a common approach used in functional neuroimaging to address this failure. Equally, current knowledge states that oscillations are basic forms of cells-assembly communications during mental activity. Promising results were revealed in a previous study assessing healthy subjects, WCST and oscillations. However, those previous studies failed to meet the functional integration of the network during the WCST in schizophrenics, based on the induced oscillations and their distributed cortical sources. In this research, we utilized the brain electrical tomography (variable-resolution brain electromagnetic tomography) technique to accomplish this goal. Task specific delta, theta, alpha and beta-2 oscillations were induced and simultaneously synchronized over large extensions of cortex, encompassing prefrontal, temporal and posterior regions as in healthy subjects. Every frequency had a well-defined network involving a variable number of areas and sharing some of them. Oscillations at 11.5, 5.0 and 30 Hz seem to reflect an abnormal increase or decrease, being located at supplementary motor area (SMA), left occipitotemporal region (OT), and right frontotemporal subregions (RFT), respectively. Three cortical areas appeared to be critical, that may lead to difficulties either in coordinating/sequencing the input/output of the prefrontal networks-SMA, and retention of information in memory-RFT, both preceded or paralleled by a deficient visual information processing-OT.