New perspectives in pharmaco-electroencephalography

Brain space and time in mental disorders: Paradigm shift in biological psychiatry

Contemporary psychiatry faces serious challenges because it has failed to incorporate accumulated knowledge from basic neuroscience, neurophilosophy, and brain-mind relation studies. As a consequence, it has limited explanatory power, and effective treatment options are hard to come by. A new conceptual framework for understanding mental health based on underlying neurobiological spatial-temporal mechanisms of mental disorders (already gained by the experimental studies) is beginning to emerge.

QPEEG analysis of the effects of sodium valproate on adult Chinese patients with generalized tonic-clonic seizures

Objectives EEG effects of the sustained-release form of sodium valproate (SR-VPA) are unknown, although it is widely used in Chinese patients with generalized tonicclonic seizures (GTCS). Methods Fourteen newly diagnosed, untreated GTCS patients were recruited and treated with SR-VPA. Waking EEG was recorded and analyzed by way of quantitative pharmaco-electroencephalogram (QPEEG) analysis during the three-month follow-up. Results There was a statistically significant decrease in the absolute power of the delta band (P < 0.05), theta band (P < 0.03) and partial alpha-1 band (p < 0.05) with treatment compared to before treatment, while there was no significantly different absolute power between one-month and three-months after treatment. There was a strong correlation between the decrease in absolute power and the degree of the initial abnormality in all frequency bands. Two of 14 patients experienced seizures during the second month after initiation of SR-VPA therapy. Conclusions SR-VPA selectively decreased the activity of the abnormal EEG synchronization in a use-dependent manner. The reduced theta, delta, and partial alpha-1 absolute power may reflect or confirm the efficacy of SR-VPA on patients with GTCS.

Usefulness of standard EEG in predicting the outcome of patients with disorders of consciousness after anoxic coma

Although standard EEG is performed routinely in patients with disorders of consciousness after coma, its prognostic value is still debated. The aim of the present study was to evaluate the role of standard EEG in predicting the recovery of cognitive functioning in patients affected by severe disturbances of consciousness after coma caused by cerebral anoxia. A standard EEG was recorded at admission to our Rehabilitation Department in 15 patients experiencing impaired consciousness because of cerebral anoxia. We quantified EEG abnormalities using the Synek scale (1988). Cognitive functioning was measured with the levels of cognitive functioning scale at the time of admission and after 3 months of recovery. EEG scores were significantly correlated with both levels of cognitive functioning scores at admission (P = 0.004) and change in levels of cognitive functioning score after 3 months (P < 0.001). The first correlation confirms the relationship between EEG and cognitive functioning, while the second correlation indicates the prognostic value of EEG in cognitive outcome. In conclusion, standard EEG is a simple and readily available tool with significant prognostic value in patients with disorders of consciousness after coma caused by cerebral anoxia.

PHENOMENOLOGICAL ARCHITECTURE OF A MIND AND OPERATIONAL ARCHITECTONICS OF THE BRAIN: THE UNIFIED METASTABLE CONTINUUM

In our contribution we will observe phenomenal architecture of a mind and operational architectonics of the brain and will show their intimate connectedness within a single integrated metastable continuum. The notion of operation of different complexity is the fundamental and central one in bridging the gap between brain and mind: it is precisely by means of this notion that it is possible to identify what at the same time belongs to the phenomenal conscious level and to the neurophysiological level of brain activity organization, and what mediates between them. Implications for linguistic semantics, self-organized distributed computing algorithms, artificial machine consciousness, and diagnosis of dynamic brain diseases will be discussed briefly.

Reorganization of the composition of brain oscillations and their temporal characteristics during opioid withdrawal

Majority of the opioid-dependence and withdrawal studies are dominated with many inconsistencies and contradictions. One of the reasons for such inconsistencies may be methodological while performing EEG analysis. To overcome methodological limitations, in the present study we examined the composition of electroencephalographic (EEG) brain oscillations in broad frequency band (0.5-30 Hz) in 13 withdrawal opioid-dependent patients and 14 healthy subjects during resting condition (closed eyes). The exact compositions of brain oscillations and their temporal behaviour were assessed by the probability-classification analysis of short-term EEG spectral patterns (SPs). It was reported that early withdrawal had a generalized effect: the activity in all EEG channels was affected nearly equally. EEG of withdrawal patients was characterized by (a) different dominant SP types (had unique SP types which describe beta-frequency band), (b) increased number of SP types observed in each EEG channel, (c) a larger percentage of alpha(2)-, beta- and poly-rhythmic activity, and by a smaller percentage of delta-, - and alpha(1)-rhythmic activity, (d) predominantly right-sided asymmetry and (e) longer periods of temporal stabilization for alpha- and beta-brain oscillations and by shorter periods of temporal stabilization for -activity when compared with control subjects. When taken together, these findings suggest a considerable reorganization of composition of brain oscillations, which reflects a disorganization process and an allostatic state with neuronal activation in EEG of opioid withdrawal patients.

Effects of levetiracetam vs topiramate and placebo on visually evoked phase synchronization changes of alpha rhythm in migraine

OBJECTIVE

Recent theories about migraine pathogenesis have outlined an abnormal central processing of sensory signals, also suggested by an abnormal pattern of EEG hyper-synchronization under visual stimulation. The aim of the present study was to test the efficacy of topiramate and levetiracetam vs placebo in a double blind project observing the effects of the three treatments on the EEG synchronization in the alpha band under sustained flash stimulation.

METHODS

Forty-five migraine without aura outpatients (MO) were selected and randomly assigned to 100mg topiramate, 1000 mg levetiracetam or placebo treatment. In addition, 24 non-migraine healthy controls were submitted to EEG analysis. The EEG was recorded by 19 channels: flash stimuli with a luminosity of 0.2J were delivered, in a frequency range from 3 to 30 Hz. We evaluated the phase synchronization index, that we previously applied in migraine, after EEG signals filtering in the alpha band. Our approach was based on the Hilbert transform.

RESULTS

Both levetiracetam and topiramate significantly decreased migraine frequency, compared with placebo. MO patients displayed increased alpha-band phase synchronization as an effect of stimulus frequency; on the other hand the stimuli had an overall desynchronizing effect on control subjects. The phase synchronization index separates the two stages, before and after the treatment, only for levetiracetam, at stimulus frequencies of 9, 18, 24 and 27 Hz.

CONCLUSIONS

An abnormal alpha band synchronization under visual stimuli was confirmed in migraine; this phenomenon was reversed by levetiracetam preventive treatment.

SIGNIFICANCE

These results confirmed in humans the inhibiting action of levetiracetam on neuronal hyper-synchronization.

Opioid withdrawal results in an increased local and remote functional connectivity at EEG alpha and beta frequency bands

Withdrawal may be a natural model to study craving and compulsive drug seeking, since craving can be viewed as a conditioned dysphoric state. It has been suggested that functional connectivity between brain areas may be of major value in explaining excessive craving and compulsive drug seeking by providing essential link between psychological and biological processes. Considering that withdrawal initiates a widespread activation of cortical regions responsible for compulsive drug seeking and desire for the drug, we predict that withdrawal would result in a significant increase in functional cortical connectivity. We applied the novel operational architectonics approach that enables us to estimate both local and remote functional cortical connectivity by means of EEG structural synchrony measure. In 13 withdrawal opioid-dependent patients we found the evidence that local and remote cortical functional connectivity was indeed significantly enhanced (for both alpha and beta frequency oscillations). Additionally, statistical relationship between functional connectivity and the severity of opioid withdrawal has been found.

Composition of EEG oscillations and their temporal characteristics: Methadone treatment

In this study, we examine the composition of electroencephalographic (EEG) oscillations within a broad frequency band (0.5-30 Hz) for opioid abuse (22 patients), during withdrawal (13 patients), and after 6 months of methadone treatment (6 patients) and in 14 healthy subjects during a resting condition (closed eyes). The exact compositions of EEG oscillations and their temporal behaviour were assessed using the probability-classification analysis of short-term EEG spectral patterns. The study reveals the dynamics of particular EEG oscillations throughout the conditions of opioid dependency, withdrawal and methadone-based treatment. It was shown that methadone maintenance treatment normalized considerably the composition of EEG oscillations and their percentage ratio and restored the temporal structure of patients' EEG comparable with healthy subjects. The importance of the methadone's ability to restore a normal temporal structure of the brain's activity is discussed.

Impaired functional connectivity at EEG alpha and theta frequency bands in major depression

Recent reports on functional brain imaging in major depression have lead to an assumption that observed psychopathology might be related to an altered brain functional connectivity. Our hypothesis was that an increase in brain functional connectivity occurs in major depression. As a measure of functional connectivity, the electroencephalogram (EEG) structural synchrony approach was used in 12 medication-free depressive outpatients and 10 control subjects. Differences in the number and strength of structurally synchronized EEG patterns were compared between groups. In depressive patients the number and strength of short cortex functional connections were significantly larger for the left than for the right hemisphere, while the number and strength of long functional connections were significantly larger for the right than for the left hemisphere. Some of the functional connections were positively correlated with the severity of depression, thus being predictive. These were short-range anterior, posterior, and left hemisphere functional connections for the alpha frequency band and short-range anterior functional connections for the theta frequency band. The topology of the most representative functional connections among all patients with major depression indicated that the right anterior and left posterior brain parts may discriminate depressive patients from healthy controls. The obtained data support our hypothesis that there is an increase in brain functional connectivity in major depression. This finding was interpreted within the semantic framework, where different specialization of left (monosemantic context) and right (polysemantic context) hemispheres is functionally insufficient in patients with depression.

Increased local and decreased remote functional connectivity at EEG alpha and beta frequency bands in opioid-dependent patients

RATIONALE

Although researchers now have a working knowledge of key brain structures involved in realization of actions of substance abuse and addiction, deeper understanding will require examination of network interactions between cortical neuronal assemblies and their subcortical tails in the effects of opioid dependence.

OBJECTIVES

Given that repeated exposure to opiates initiates a widespread reorganization of cortical regions, we predict that opioid dependence would result in a considerable reorganization of local and remote functional connectivity in the neocortex.

METHODS

We applied the novel operational architectonics approach that enables us to estimate two local and remote functional cortex connectivities by means of electroencephalogram structural synchrony measure.

RESULTS

In 22 opioid-dependent patients, we found the evidence that brain functional connectivity was indeed disrupted by chronic opioid abuse (i.e., the local functional connectivity increased and remote functional connectivity decreased in opioid abusers). This significant difference between "opioid" and "control" populations was the same for alpha and beta frequency bands. Additionally, significant negative relations between duration (years) of daily opioid abuse and the number/strength of functional connections in the posterior section of the cortex were found.

Disordered connectivity in the autistic brain: challenges for the "new psychophysiology"

In 2002, we published a paper [Brock, J., Brown, C., Boucher, J., Rippon, G., 2002. The temporal binding deficit hypothesis of autism. Development and Psychopathology 142, 209-224] highlighting the parallels between the psychological model of 'central coherence' in information processing [Frith, U., 1989. Autism: Explaining the Enigma. Blackwell, Oxford] and the neuroscience model of neural integration or 'temporal binding'. We proposed that autism is associated with abnormalities of information integration that is caused by a reduction in the connectivity between specialised local neural networks in the brain and possible overconnectivity within the isolated individual neural assemblies. The current paper updates this model, providing a summary of theoretical and empirical advances in research implicating disordered connectivity in autism. This is in the context of changes in the approach to the core psychological deficits in autism, of greater emphasis on 'interactive specialisation' and the resultant stress on early and/or low-level deficits and their cascading effects on the developing brain [Johnson, M.H., Halit, H., Grice, S.J., Karmiloff-Smith, A., 2002. Neuroimaging of typical and atypical development: a perspective from multiple levels of analysis. Development and Psychopathology 14, 521-536]. We also highlight recent developments in the measurement and modelling of connectivity, particularly in the emerging ability to track the temporal dynamics of the brain using electroencephalography (EEG) and magnetoencephalography (MEG) and to investigate the signal characteristics of this activity. This advance could be particularly pertinent in testing an emerging model of effective connectivity based on the balance between excitatory and inhibitory cortical activity [Rubenstein, J.L., Merzenich M.M., 2003. Model of autism: increased ratio of excitation/inhibition in key neural systems. Genes, Brain and Behavior 2, 255-267; Brown, C., Gruber, T., Rippon, G., Brock, J., Boucher, J., 2005. Gamma abnormalities during perception of illusory figures in autism. Cortex 41, 364-376]. Finally, we note that the consequence of this convergence of research developments not only enables a greater understanding of autism but also has implications for prevention and remediation.

Interictal EEG as a physiological adaptation. Part II. Topographic variability of composition of brain oscillations in interictal EEG

OBJECTIVE

In the present experimental study, we examined topographic variability of composition of brain oscillations and their temporal behavior in frequencies from 0.5 to 30 Hz of interictal EEG without epileptiform abnormalities and healthy EEG.

METHODS

Spatio-temporal variability of brain oscillations (indexed by short-term EEG spectral patterns (SPs)) was assessed by the probability-classification analysis of SPs. As a result, multi-dimensional SP-vector for each analysis EEG epoch was obtained.

RESULTS

It was demonstrated that interictal EEG was characterized (a) by a significant decrease of spatio-temporal variability of brain oscillations, (b) by longer periods of temporal stabilization for operational modules which comprise larger number of cortical areas, and (c) by significantly more intermittent recurrence when compared with EEG of control subjects. Generally it was shown that EEG channels display different states of coordination independently on their correlation and coherence using brain oscillations at multiple frequencies.

CONCLUSIONS

Results of this study suggested that EEG correlate of chronic epileptogenesis in the brain is a particular metastable state of biopotential field, which can be estimated by SP-vector. The fact that all results were significantly different from surrogate EEGs reflects a nonoccasional and thus, most likely, an adaptive nature of spatio-temporal reorganization in interictal EEG.

SIGNIFICANCE

Parameters of spatio-temporal organization of interictal EEG without the signs of epileptiform activity can be considered as additional information in premorbid diagnostics of status epilepticus, and may also provide insights into basic laws that govern brain oscillations in general.

Pharmaco-EEG in psychiatry

In spite of its origins deeply rooted in the discipline, pharmaco-EEG applications in psychiatry remain limited to its achievements in the field of psychotropic drugs classification and, in few instances, discovery. In the present paper two attempts to transfer pharmaco-EEG methods to psychiatric clinical routine will be described: 1) monitoring of psychotropic drug toxicity at the central nervous system level, and 2) prediction of clinical response to treatment with psychotropic drugs. Both applications have been the object of several investigations providing promising and sometimes consistent findings which, however, had no impact on clinical practice. For the first topic, the review is limited to antipsychotics, lithium and recreational drugs, as for other psychotropic drugs mostly case studies are available, while for the response prediction it will include antipsychotics, antidepressants, anxiolytics, psychostimulants and nootropics. In spite of several methodological limitations, pharmaco-EEG studies dealing with monitoring of antipsychotic- and lithium-induced EEG abnormalities went close to, but never became, a clinical routine. EEG studies of recreational drugs are flawed by several limitations, and failed, so far, to identify reliable indices of CNS toxicity to be used in clinical settings. Several QEEG studies on early predictors of treatment response to first generation antipsychotics have produced consistent findings, but had no clinical impact. For other psychotropic drug classes few and inconsistent reports have appeared. Pharmaco-EEG had the potential for important clinical applications, but so far none of them entered clinical routine. The ability to upgrade theories and methods and promote large scale studies represent the future challenge.