Quantitative spectral analysis of EEG in psychiatry revisited: drawing signs out of numbers in a clinical setting

Coutin-Churchman, Pedro; Añez, Yelitza; Uzcátegui, Marycelvia; Alvarez, Luis A.; Vergara, F; Méndez, Leopoldo D.; Fleitas, R

doi:10.1016/s1388-2457(03)00228-1

Cited by 77 publications

(48 citation statements)

References 59 publications

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“…Conceivably, such a variety of estimations of EEG coherence in schizophrenia might be caused by the lack of uniform standards for the organization of such studies with respect to test paradigms, EEG frequencies, and stages of the schizophrenic process [7,38].…”

Section: Discussionmentioning

confidence: 99%

Analysis of EEG Structural Synchrony in Adolescents with Schizophrenic Disorders

et al. 2005

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Schizophrenia falls into the small category of diseases that impair the total psychic activity rather than particular brain systems and functions. It is not surprising that researchers have long been interested in the integrative activity of the human brain in schizophrenia. They have reported considerable data on histological and physiological changes in the human brain, providing evidence for disturbance of interrelationships and functional association between different parts of the brain at different stages of schizophrenia [1][2][3]. The most conspicuous data have been obtained for the brain electrical activity [4][5][6][7][8][9][10]. Based on these data, a hypothesis of disintegration of cortical functions (the disconnection hypothesis) has been advanced [11] to explain the schizophrenic disorders [11][12][13].In EEG studies, spectral and correlation analyses are a common method for investigating the integrative activity of the human brain, yielding evidence for the impairment of local and distant synchronies of neuronal networks in schizophrenia [4,5,7,8,14]. However, a number of limitations typical of spectral methods, specifically, of the coherence function [7,[15][16][17], have motivated the development of new techniques to examine the interdependences of EEG paired time series data in schizophrenia, including nonlinear interdependence [9], mutual information transmission measure [18], and phase locking [10], which reflect nonlinear and, in the last case, also in-phase components of the interdependence of cortical electrical processes.The results of the above studies are also in line with Friston's hypothesis of disintegration of neuronal networks in schizophrenia [11].Yet, cortical bioelectrical processes associated with ontological nonstationarity of the EEG signal [19][20][21] are not covered by the traditional or new methods of quantitative analysis of EEG spatiotemporal correlations.EEG nonstationarity implies that the EEG signal consists of quasi-stationary segments that reflect the changes in metastable states of the brain on different time scales [20,21], from microstates, with a duration of no more than several seconds [15,22], to macrostates, with a duration of tens or hundreds of minutes [23]. This concept of EEG nonstationarity provides a means for obtaining new insights into the cooperation of cortical structures. For this purpose, it is possible to estimate the EEG structural synchrony [15], i.e., the temporal synchronization of intersegmentary transitions between different EEG channels. Estimation of the spatiotemporal synchronization of local metastable states of neuronal networks appears to be a new measure of the integrative activity of the human brain.The functional importance of the EEG structural synchrony and segment characteristics has been described in a series of our works performed in several laboratories and with several cognitive and pharmacological paradigms [24][25][26][27]. In our previous work [28], changes in quasi-stationary segments of the EEG α activity were detected i...

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Section: Discussionmentioning

confidence: 99%

Analysis of EEG Structural Synchrony in Adolescents with Schizophrenic Disorders

et al. 2005

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“…An association of increased theta band power in ADHD has been found across the lifespan: both adolescents and adults with ADHD exhibit increased frontocentral theta band power when compared to non-ADHD populations [19]. Elevated theta power, however, may be a nonspecific marker of cortical dysfunction common to other disorders, such as epilepsy, bipolar disorder, and polysubstance abuse [20].…”

Section: Theta Band Eeg and Underarousalmentioning

confidence: 99%

Clinical Utility of EEG in Attention-Deficit/Hyperactivity Disorder: A Research Update

2012

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Summary Psychiatric research applications of electroencephalography (EEG), the earliest approach to imaging human cortical brain activity, are attracting increasing scientific and clinical interest. For more than 40 years, EEG research has attempted to characterize and quantify the neurophysiology of attention-deficit/hyperactivity disorder (ADHD), most consistently associating it with increased frontocentral theta band activity and increased theta to beta (θ/β) power ratio during rest compared to non-ADHD controls. Recent reports suggest that while these EEG measures demonstrate strong discriminant validity for ADHD, significant EEG heterogeneity also exists across ADHD-diagnosed individuals. In particular, additional studies validating the use of the θ/β power ratio measure appear to be needed before it can be used for clinical diagnosis. In recent years, the number and the scientific quality of research reports on EEG-based neurofeedback (NF) for ADHD have grown considerably, although the studies reviewed here do not yet support NF training as a first-line, stand-alone treatment modality. In particular, more research is needed comparing NF to placebo control and other effective treatments for ADHD. Currently, after a long period of relative stasis, the neurophysiological specificity of measures used in EEG research is rapidly increasing. It is likely, therefore, that new EEG studies of ADHD using higher density recordings and new measures drawn from viewing EEG as a 3-dimensional functional imaging modality, as well as intensive re-analyses of existing EEG study data, can better characterize the neurophysiological differences between and within ADHD and non-ADHD subjects, and lead to more precise diagnostic measures and effective NF approaches.

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“…Patients typically show unusually high EEG power in the low frequencies (delta and theta bands, < 8Hz) which is usually interpreted as evidence of neurodevelopmental delay (Galderisi et al, 2009), but this difference is by no means specific to schizophrenia (Coutin-Churchman et al, 2003). Furthermore, although EEG power at single scalp sites reflects localised synchronous neuronal activity, it does not provide a useful index of more long-distance functional connectivity and to do this, some measure of inter-channel covariation is required, such as coherence or phase synchrony.…”

Section: Introductionmentioning

confidence: 99%

Brain connectivity in positive and negative syndrome schizophrenia

et al. 2010

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If, as is widely believed, schizophrenia is characterised 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 * Corresponding author.Tel: (0)20 7594 8524; Fax: (0)20 7594 8517; e-mail: a.walden@imperial.ac.uk Preprint submitted to NeuroscienceJune 8, 2010 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 characterised by widespread changes in functional connectivity with negative syndrome patients showing a more extreme pattern of abnormality than positive syndrome patients.

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Quantitative spectral analysis of EEG in psychiatry revisited: drawing signs out of numbers in a clinical setting

Cited by 77 publications

References 59 publications

Analysis of EEG Structural Synchrony in Adolescents with Schizophrenic Disorders

Analysis of EEG Structural Synchrony in Adolescents with Schizophrenic Disorders

Clinical Utility of EEG in Attention-Deficit/Hyperactivity Disorder: A Research Update

Brain connectivity in positive and negative syndrome schizophrenia

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