Assessing interactions in the brain with exact low-resolution electromagnetic tomography.

Scalp electric potentials (electroencephalogram; EEG) are contingent to the impressed current density unleashed by cortical pyramidal neurons undergoing post-synaptic processes. EEG neuroimaging consists of estimating the cortical current density from scalp recordings. We report a solution to this inverse problem that attains exact localization: exact low-resolution brain electromagnetic tomography (eLORETA). This non-invasive method yields high time-resolution intracranial signals that can be used for assessing functional dynamic connectivity in the brain, quantified by coherence and phase synchronization. However, these measures are non-physiologically high because of volume conduction and low spatial resolution. We present a new method to solve this problem by decomposing them into instantaneous and lagged components, with the lagged part having almost pure physiological origin.

Evaluation of the pain matrix using EEG source localization: a feasibility study.

OBJECTIVES: An extensive neuroimaging literature on chronic pain demonstrates increased cerebral blood flow and metabolism consistent with increased neuronal activity in the structures comprising the "pain matrix"; furthermore, some of these regions have been shown to encode pain intensity. It is the objective of this study to demonstrate the feasibility of using quantitative electroencephalography (EEG) source localization to reflect and to quantify activity in the pain matrix. METHODS: Eyes closed resting EEG was recorded from 19 standardized scalp locations, in a pilot sample of five patients with chronic neuropathic pain, before and after pain reduction. Quantitative electro encephalography (QEEG) source localization was computed estimating the mathematically most probable source generators of EEG surface potentials in each state. Sources identified in this way have been demonstrated to coregister with those identified by neuroimaging methods. RESULTS: QEEG sources demonstrated frequency specific increased neuronal activity in the baseline high pain state in structures including the thalamus, somatosensory cortex, anterior and posterior insula, medial and lateral prefrontal cortex and cingulate. Significant reduction of activation in these regions was seen when pain was reduced (≥50% on subjective ratings). CONCLUSION: The areas that were activated in the high pain state localized to the same regions reported by other neuroimaging methods and with frequency specificity. The frequency and regionally specific activation may indicate distinctive patterns of pathophysiology underlying the pain matrix. Although in a small number of patients, this work suggests that QEEG may be a useful tool in the exploration and quantification of the pain matrix in a clinical setting.

Source imaging of QEEG as a method to detect awareness in a person in vegetative state.

BACKGROUND: Assessment of awareness in patients with severe brain injury remains subjective, although patients with even limited awareness (e.g. minimal conscious state, MCS) have different prognoses and treatment than those in vegetative state (VS). Recently, task appropriate differential regional activation in VS has been reported using fMRI during mental imagery. PRIMARY OBJECTIVE: Demonstration of conscious awareness in reproducible differential EEG source localization images in a VS patient reflecting requested mental imagery was performed. METHODS: A VS patient (with re-test) and a normal control were requested to imagine singing and to mentally perform serial subtraction, while EEG was recorded. QEEG source localization was performed to identify regions of brain activation in response to tasks. RESULTS: Replicable distinctive activation of brain areas appropriate for each task was seen in the VS patient and control. Frequency spectra shifted to beta, with significant source activation in regions including the bilateral anterior cingulate, insula, left caudate and dorsolateral pre-frontal cortex to singing and the putamen, insula, left pre-frontal cortex and right temporal gyrus to subtraction by 7's. CONCLUSIONS: Results from this single case suggests the potential utility of QEEG source localization images to detect awareness in patients clinically diagnosed as being in VS. This indicates the possibility that EEG may serve as an important adjunct to the assessment of awareness in patients with disorders of consciousness in the clinical setting.

The pre-mild cognitive impairment, subjective cognitive impairment stage of Alzheimer's disease.

BACKGROUND: Subjective cognitive impairment (SCI) has been a common, but poorly understood condition, frequently occurring in older persons. METHODS: The past and the emerging literature on SCI and synonymously named conditions is reviewed. RESULTS: Findings include: (1) There is support from at least one longitudinal study for a long-standing concept of SCI as a pre-mild cognitive impairment (MCI) condition lasting approximately 15years. (2) There are complex relationships between SCI and depression and anxiety. (3) Differences in SCI subjects from age-matched non-SCI persons are being published in terms of cognitive tests, hippocampal gray matter density, hippocampal volumes, cerebral metabolism, and urinary cortisol levels. Psychometric and dementia test score differences between SCI and MCI subjects have long been evident. (4) Predictive electrophysiologic features of subsequent decline in SCI subjects are being published. CONCLUSIONS: Studies of therapeutic agents in SCI treatment and resultant Alzheimer's disease prevention appear to be feasible. These trials are also necessary from a public health perspective.

Automatic identification of spike-wave events and non-convulsive seizures with a reduced set of electrodes.

Epileptiform activity in the brain, whether localized or generalized, constitutes an important category of abnormal electroencephalogram (EEG). Seizures are episodes of relatively brief disturbances of mental, motor or sensory activity caused by paroxysmal cerebral activity. They are not always accompanied by the characteristic convulsions that we commonly associate with the word epilepsy. In this case, they may be referred to as non-convulsive status epilepticus (NCSE) or as absence seizures (formerly called "petit mal" seizures). They often manifest themselves in scalp-recorded EEG as large-amplitude spike-wave "patterns" (or "events"), usually occurring in bursts. If left undetected and untreated, they can potentially cause significant brain and behavioral dysfunctions, interfere with information processing, or otherwise contribute to altered mental status. In this paper, we describe an algorithm to be implemented in a prototype BrainScope_ED instrument meant to alert to a detected seizure in an emergency department (ED) or other clinical setting. BrainScope_ED uses a reduced electrode set (8 instead of 19). The proposed signal processing algorithm is based on the detection of spike-wave events obtained from a wavelet analysis of the EEG signal, combined with an analysis of the complexity of the EEG using fractal dimension estimates. We show that this algorithm has excellent sensitivity and specificity. In particular, the fractal analysis is a key factor in the removal of falsely detected spike-wave events (false positives) that can be caused by voluntary or involuntary artifacts such as fast eyelid flutter.

The relevance of QEEG to the evaluation of behavioral disorders and pharmacological interventions.

It has become apparent that the electrical signals recorded from the scalp of healthy individuals under standardized conditions are predictable, and that patients with a wide variety of brain disorders display activity with unusual features. It also early became apparent that centrally active medications produced striking changes in this activity. The application of computerized signal analysis to EEG recordings collected using standardized procedures has made it possible to obtain quantitative descriptions of brain electrical activity (QEEG) in normal individuals and patients with disorders of brain function or structure, as well as quantitative description of the ways in which centrally active medications alter this activity (Pharmaco-EEG or "PEEG"). With the emergence of three-dimensional EEG source localization techniques, it has recently become possible to visualize the mathematically most probable generators of QEEG abnormalities within the brain as well as the neuroanatomical regions where abnormal activity is most altered by efficacious medication. As QEEG and PEEG have evolved, a vast body of facts has been accumulated, describing changes in the EEG or event-related potentials (ERPs). observed in a variety of brain disorders or after administration of a variety of medications. With some notable exceptions, these studies have tended to be phenomenological rather than analytic. There has not been a systematic attempt to integrate these phenomena in order to build better understanding of how the abnormal behaviors of a particular psychiatric patient might be related to the specific pattern of the deviant electrical activity, nor just how pharmacological reduction of that deviant activity may have resulted in more normal behavior. This article is an endeavor to provide a more specific theoretical framework for understanding the relationships between the neuroanatomy and neurochemistry of the homeostatic system underlying the regulation of the QEEG, and the mechanisms revealed by Pharmaco-EEG that aid in correcting these illnesses.

Correlation of PET and qEEG in normal subjects.

Positron emission tomography (PET) and quantitative electroencephalography (qEEG) were obtained in 15 normal male subjects with eyes closed at rest. Correlations between qEEG variables and regional metabolism were examined as an approach to investigating the metabolic and neuroanatomical basis of the generation of the EEG. Analogous to the neurometric approach to qEEG, a normative 2-fluoro-deoxyglucose voxel data base was developed for the PET image. The PET image was transformed to an idealized cylindrical set of coordinates to allow registration with the Talairach stereotactic atlas. PET regions of interest for the thalamus, the left and right temporal lobes, the medial frontal cortex and the dorsolateral prefrontal cortex were defined using Talairach coordinates and correlated to the QEEG. Salient findings included a negative correlation of thalamic metabolism to alpha power and a positive correlation of medial frontal cortical metabolism to delta EEG power. The significance of these findings is discussed with reference to the existing literature on the physiology of the generation of the EEG.

The sometimes pernicious role of theory in science.

The role of theory in science is discussed in the context of understanding brain function. Historically, theories of brain functions have oscillated between localization and anti-localization beliefs. In the last 50 years, the important discoveries of the ascending reticular activating system (ARAS), feature extracting neurons and synaptic growth led many to orthodoxy. Research became more and more focused upon the elements comprising the nervous system and their interconnections. The mainstream belief became that many brain functions including consciousness were localized, certain kinds of brain injuries produced irreversible functional deficits. Contrary scientific challenges were discouraged by the omnipresence of such theory. Examples of theoretical "Einstellungen" in the areas of ARAS, coma, treatment of brain injuries and consciousness are given, as well as signs that the pendulum is swinging back to an approach to the system as a whole rather than a focus on its parts.

Electroencephalographic mapping during routine clinical practice: cortical arousal during tracheal intubation?

We used quantitative analysis of the electroencephalogram (EEG) in 42 patients to assess the effect of tracheal intubation after induction of anesthesia with etomidate and sufentanil using standard clinical practice. The EEG was recorded from eight bipolar electrode derivations and Z-transformed relative to age expected normative data for relative power in the delta, theta, alpha, and beta frequency bands. Tracheal intubation resulted in classical cortical arousal, as indicated by acceleration of the EEG frequencies. Significant effects were seen in all frequency bands, most pronounced in the alpha frequency band, with the largest increase bilaterally in the fronto-temporal regions (F-values: Delta - 9.592, P < 0.001; theta - 1.691, P < 0.001; alpha - 18.439, P < 0.001; beta - 4.504, P < 0.001). Changes in alpha and delta power during induction of anesthesia were correlated with the dose of etomidate (P < 0.05). Changes in alpha after tracheal intubation were correlated at the parietooccipital brain regions to the dose of sufentanil (P < 0.05). Individual titration of the dose of etomidate and sufentanil, as during routine clinical practice, is not sufficient to block the strong noxious stimulation of tracheal intubation and results in cortical arousal. The clinical impact of this cortical wake-up phenomenon is undetermined.

Optimal denoising of brainstem Auditory Evoked Response (BAER) for automatic peak identification and brainstem assessment.

Brainstem auditory evoked responses (BAER) are transient signals embedded in the EEG recorded from scalp electrodes, when a subject is presented with a series of acoustic clicks. These signals typically have a signal-to-noise ratio (SNR) well below -10 dB. The extraction of BAER signals from the EEG for the purpose of automatically computing features of interest from the BAER waveform(s) is described in this paper. These features are: 1) Presence of an actual BAER response (at least peak I), 2) Presence of peak V, 3) Inter-peak latency I-V. We propose to combine a signal-adaptive denoising technique based on complex wavelets with a signal quality metric referred to as the FSP variance ratio for quantitative evaluation of signal quality in order to optimally denoise BAER signals and perform reliable waveform analysis.

From synchronous neuronal discharges to subjective awareness?

For practical clinical purposes, as well as because of their deep philosophical implications, it becomes increasingly important to be aware of contemporary studies of the brain mechanisms that generate subjective experiences. Current research has progressed to the point where plausible theoretical proposals can be made about the neurophysiological and neurochemical processes which mediate perception and sustain subjective awareness. An adequate theory of consciousness must describe how information about the environment is encoded by the exogenous system, how memories are stored in the endogenous system and released appropriately for the present circumstances, how the exogenous and endogenous systems interact to produce perception, and explain how consciousness arises from that interaction. Evidence assembled from a variety of neuroscience areas, together with the invariant reversible electrophysiological changes observed with loss and return of consciousness in anesthesia as well as distinctive quantitative electroencephalographic profiles of various psychiatric disorders, provides an empirical foundation for this theory of consciousness. This evidence suggests the need for a paradigm shift to explain how the brain accomplishes the transformation from synchronous and distributed neuronal discharges to seamless global subjective awareness. This chapter undertakes to provide a detailed description and explanation of these complex processes by experimental evidence marshaled from a wide variety of sources.

The neurophysiology of attention-deficit/hyperactivity disorder.

Recent reviews of the neurobiology of Attention-Deficit/Hyperactivity Disorder (AD/HD) have concluded that there is no single pathophysiological profile underlying this disorder. Certainly, dysfunctions in the frontal/subcortical pathways that control attention and motor behavior are implicated. However, no diagnostic criteria or behavioral/neuroimaging techniques allow a clear discrimination among subtypes within this disorder, especially when problems with learning are also considered. Two major Quantitative EEG (QEEG) subtypes have been found to characterize AD/HD. Here we review the major findings in the neurophysiology of AD/HD, focusing on QEEG, and briefly present our previous findings using a source localization technique called Variable Resolution Electromagnetic Tomography (VARETA). These two techniques represent a possible objective method to identify specific patterns corresponding to EEG-defined subtypes of AD/HD. We then propose a model representing the distribution of the neural generators in these two major AD/HD subtypes, localized within basal ganglia and right anterior cortical regions, and hippocampal, para-hippocampal and temporal cortical regions, respectively. A comprehensive review of neurochemical, genetic, neuroimaging, pharmacological and neuropsychological evidence in support of this model is then presented. These results indicate the value of the neurophysiological model of AD/HD and support the involvement of different neuroanatomical systems, particularly the dopaminergic pathways.

Quantitative electroencephalographic studies of cue-induced cocaine craving.

Quantitative electroencephalographic (qEEG) profiles were studied in cocaine dependent patients in response to cocaine cue exposure. Using neurometric analytical methods, the spectral power of each primary bandwidth was computed and topographically mapped. Additional measures of cue-reactivity included cocaine craving, anxiety and related subjective ratings, and physiological measures of skin conductance, skin temperature, heart rate, and plasma cortisol and HVA levels. Twenty-four crack cocaine-dependent subjects were tested for their response to tactile, visual and audio cues related to crack cocaine or neutral items. All measures were analyzed for significant difference by comparing cocaine versus neutral cue conditions. An increase in cocaine craving, anxiety and related subjective ratings, elevated plasma cortisol levels, and a decrease in skin temperature, were induced by cocaine cue exposure. Distinct qEEG profiles were found during the paraphernalia handling and video viewing (eyes-open), and guided imagery (eyes-closed), phases of cocaine cue exposure. During paraphernalia handling and video viewing, there was an increase in beta activity accompanied by a drop in delta power in the frontal cortex, and an increase in beta mean frequency in the occipital cortex. In contrast, during guided imagery there was an increase in theta and delta power in the frontal cortex, and an increase in beta power in the occipital cortex. Correlation analyses revealed that cue-induced anxiety during paraphernalia handling and video viewing was associated with reduced high frequency and enhanced low frequency EEG activity. These findings demonstrated that EEG activation during cue-induced cocaine craving may be topographically mapped and subsequently analyzed for functional relevance.

Quantitative electroencephalography in OCD patients treated with paroxetine.

The effectiveness of drugs that have a specific effect on the activity of the serotonergic neurotransmitter systemhas changed the outlook for patients suffering from obsessive-compulsive disorder (OCD). With a response rate of about 70% to such compounds and the great amount of brain imaging studies conducted over the past decades, an understanding of the biochemical nature and origins of OCD is beginning to unfold. Convergent data including ethological and experimental observations, clinico-pathological findings and different imaging methods have implicated the basal ganglia along with the cortical and related thalamic structures to be involved in the pathophysiology of OCD. In a previous study using the quantitative electroencephalographic (QEEG) method known as neurometrics, in which QEEG data from OCD patients were compared statistically with those from an age-appropriate normative population, two subtypes within a clinically homogeneous patient group were classified. Patients with relative excess theta activity, especially in the frontal regions, were nonresponders to treatment with serotonin reuptake inhibitors (SSRI), while those with increased relative power in alpha activity were responders to pharmacological treatment. These findings suggested at least two subgroups in a patient population with similar symptoms but differential responses to treatment. In the present study we used neurometric QEEG to subtype a group of 20 non-depressed OCD patients, fulfilling DSM-R-III criteria, treated with paroxetine, of whom 18 were responders to treatment. Of the treatment responders, 94.4% were predicted by subtype membership to be SSRI responsers. In these subjects there was a strong relative alpha baseline activity; after successful treatment through at least 3 months this activity decreased, looking more normal. The group average topographic maps showed none of the characteristics seen in the nonresponder cluster (no excess relative power in theta). As in the previous investigation, baseline QEEG profile membership points to a predictive value with regard to therapeutic response.

The neurophysics of consciousness.

Consciousness combines information about attributes of the present multimodal sensory environment with relevant elements of the past. Information from each modality is continuously fractionated into distinct features, processed locally by different brain regions relatively specialized for extracting these disparate components and globally by interactions among these regions. Information is represented by levels of synchronization within neuronal populations and of coherence among multiple brain regions that deviate from random fluctuations. Significant deviations constitute local and global negative entropy, or information. Local field potentials reflect the degree of synchronization among the neurons of the local ensembles. Large-scale integration, or 'binding', is proposed to involve oscillations of local field potentials that play an important role in facilitating synchronization and coherence, assessed by neuronal coincidence detectors, and parsed into perceptual frames by cortico-thalamo-cortical loops. The most probable baseline levels of local synchrony, coherent interactions among brain regions, and frame durations have been quantitatively described in large studies of their age-appropriate normative distributions and are considered as an approximation to a conscious 'ground state'. The level of consciousness during anesthesia can be accurately predicted by the magnitude and direction of reversible multivariate deviations from this ground state. An invariant set of changes takes place during anesthesia, independent of the particular anesthetic agent. Evidence from a variety of neuroscience areas supporting these propositions, together with the invariant reversible electrophysiological changes observed with loss and return of consciousness, are used to provide a foundation for this theory of consciousness. This paper illustrates the increasingly recognized need to consider global as well as local processes in the search for better explanations of how the brain accomplishes the transformation from synchronous and distributed neuronal discharges to seamless global subjective awareness.

Millisecond by millisecond, year by year: normative EEG microstates and developmental stages.

Most studies of continuous EEG data have used frequency transformation, which allows the quantification of brain states that vary over seconds. For the analysis of shorter, transient EEG events, it is possible to identify and quantify brain electric microstates as subsecond time epochs with stable field topography. These microstates may correspond to basic building blocks of human information processing. Microstate analysis yields a compact and comprehensive repertoire of short lasting classes of brain topographic maps, which may be considered to reflect global functional states. Each microstate class is described by topography, mean duration, frequency of occurrence and percentage analysis time occupied. This paper presents normative microstate data for resting EEG obtained from a database of 496 subjects between the age of 6 and 80 years. The extracted microstate variables showed a lawful, complex evolution with age. The pattern of changes with age is compatible with the existence of developmental stages as claimed by developmental psychologists. The results are discussed in the framework of state dependent information processing and suggest the existence of biologically predetermined top-down processes that bias brain electric activity to functional states appropriate for age-specific learning and behavior.