The Brain as a Distributed Intelligent Processing System: An EEG Study

Background: Various neuroimaging studies, both structural and functional, have provided support for the proposal that a distributed brain network is likely to be the neural basis of intelligence. The theory of Distributed Intelligent Processing Systems (DIPS), first developed in the field of Artificial Intelligence, was proposed to adequately model distributed neural intelligent processing. In addition, the neural efficiency hypothesis suggests that individuals with higher intelligence display more focused cortical activation during cognitive performance, resulting in lower total brain activation when compared with individuals who have lower intelligence. This may be understood as a property of the DIPS. Methodology and Principal Findings: In our study, a new EEG brain mapping technique, based on the neural efficiency hypothesis and the notion of the brain as a Distributed Intelligence Processing System, was used to investigate the correlations between IQ evaluated with WAIS (Whechsler Adult Intelligence Scale) and WISC (Wechsler Intelligence Scale for Children), and the brain activity associated with visual and verbal processing, in order to test the validity of a distributed neural basis for intelligence. Conclusion: The present results support these claims and the neural efficiency hypothesis.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

EEG-based Brain-Computer Interfaces: An Overview of Basic Concepts and Clinical Applications in Neurorehabilitation

Some patients are no longer able to communicate effectively or even interact with the outside world in ways that most of us take for granted. In the most severe cases, tetraplegic or post-stroke patients are literally `locked in` their bodies, unable to exert any motor control after, for example, a spinal cord injury or a brainstem stroke, requiring alternative methods of communication and control. But we suggest that, in the near future, their brains may offer them a way out. Non-invasive electroencephalogram (EEG)-based brain-computer interfaces (BCD can be characterized by the technique used to measure brain activity and by the way that different brain signals are translated into commands that control an effector (e.g., controlling a computer cursor for word processing and accessing the internet). This review focuses on the basic concepts of EEG-based BC!, the main advances in communication, motor control restoration and the down-regulation of cortical activity, and the mirror neuron system (MNS) in the context of BCI. The latter appears to be relevant for clinical applications in the coming years, particularly for severely limited patients. Hypothetically, MNS could provide a robust way to map neural activity to behavior, representing the high-level information about goals and intentions of these patients. Non-invasive EEG-based BCIs allow brain-derived communication in patients with amyotrophic lateral sclerosis and motor control restoration in patients after spinal cord injury and stroke. Epilepsy and attention deficit and hyperactive disorder patients were able to down-regulate their cortical activity. Given the rapid progression of EEG-based BCI research over the last few years and the swift ascent of computer processing speeds and signal analysis techniques, we suggest that emerging ideas (e.g., MNS in the context of BC!) related to clinical neuro-rehabilitation of severely limited patients will generate viable clinical applications in the near future.

From EEG to BOLD: Brain mapping and estimating transfer functions in simultaneous EEG-fMRI acquisitions

Simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) aims to disentangle the description of brain processes by exploiting the advantages of each technique. Most studies in this field focus on exploring the relationships between fMRI signals and the power spectrum at some specific frequency bands (alpha, beta, etc.). On the other hand, brain mapping of EEG signals (e.g., interictal spikes in epileptic patients) usually assumes an haemodynamic response function for a parametric analysis applying the GLM, as a rough approximation. The integration of the information provided by the high spatial resolution of MR images and the high temporal resolution of EEG may be improved by referencing them by transfer functions, which allows the identification of neural driven areas without strong assumptions about haemodynamic response shapes or brain haemodynamic`s homogeneity. The difference on sampling rate is the first obstacle for a full integration of EEG and fMRI information. Moreover, a parametric specification of a function representing the commonalities of both signals is not established. In this study, we introduce a new data-driven method for estimating the transfer function from EEG signal to fMRI signal at EEG sampling rate. This approach avoids EEG subsampling to fMRI time resolution and naturally provides a test for EEG predictive power over BOLD signal fluctuations, in a well-established statistical framework. We illustrate this concept in resting state (eyes closed) and visual simultaneous fMRI-EEG experiments. The results point out that it is possible to predict the BOLD fluctuations in occipital cortex by using EEG measurements. (C) 2010 Elsevier Inc. All rights reserved.

Gamma band oscillations under influence of bromazepam during a sensorimotor integration task: An EEG coherence study

The goal of the present study was to explore the dynamics of the gamma band using the coherence of the quantitative electroencephalography (qEEG) in a sensorimotor integration task and the influence of the neuromodulator bromazepam on the band behavior. Our hypothesis is that the needs of the typewriting task will demand the coupling of different brain areas, and that the gamma band will promote the binding of information. It is also expected that the neuromodulator will modify this coupling. The sample was composed of 39 healthy subjects. We used a randomized double-blind design and divided subjects into three groups: placebo (n = 13), bromazepam 3 mg (n = 13) and bromazepam 6 mg (n = 13). The two-way ANOVA analysis demonstrated a main effect for the factors condition (i.e., C4-CZ electrode pair) and moment (i.e., C3-CZ, C3-C4 and C4-CZ pairs of electrodes). We propose that the gamma band plays an important role in the binding among several brain areas in complex motor tasks and that each hemisphere is influenced in a different manner by the neuromodulator. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Good surgical outcome in discordant ictal EEG-MRI unilateral mesial temporal sclerosis patients

Purpose:Video electroencephalography (vEEG) monitoring of patients with unilateral mesial temporal sclerosis (uMTS) may show concordant or discordant seizure onset in relation to magnetic resonance imaging (MRI) evidence of MTS. Contralateral seizure usually leads to an indication of invasive monitoring. Contralateral seizure onset on invasive monitoring may contraindicate surgery. We evaluated long-term outcome after anteromesial temporal lobectomy (AMTL) in a consecutive series of uMTS patients with concordant and discordant vEEG findings, uniformly submitted to AMTL on the MRI evidence of MTS side without invasive monitoring. Methods:We compared surgical outcome of all uMTS patients undergoing vEEG monitoring between January 1999 and April 2005 in our service. Discordant cases were defined by at least one seizure onset contralateral to the MRI evidence of MTS. Good surgical outcome was considered as Engel`s class I. We also evaluated ictal SPECT concordance to ictal EEG and surgical outcome. Results:Fifty-four patients had concordant (C) and 22 had discordant (D) scalp EEG and MRI. Surgical outcome was similar in both groups (C = 74% versus D = 86%). Duration of follow-up was comparable in both groups: C = 56.1 +/- 20.7 months versus D = 59.8 +/- 21.2 months (p = 0.83, nonsignificant). Discordant single-photon emission computed tomography (SPECT) results did not influence surgical outcome. Discussion:Surgical outcome was not influenced by contralateral vEEG seizure onset or contralateral increased flow on ictal SPECT. Although vEEG monitoring should still be performed in these patients, to rule out psychogenic seizures and extratemporal seizure onset, a potentially risky procedure such as invasive monitoring may not only not be indicated in this patient population, but may also lead to patients erroneously being denied surgery.

Multiple Pathways Analysis of Brain Functional Networks from EEG Signals: An Application to Real Data

In the present study, we propose a theoretical graph procedure to investigate multiple pathways in brain functional networks. By taking into account all the possible paths consisting of h links between the nodes pairs of the network, we measured the global network redundancy R (h) as the number of parallel paths and the global network permeability P (h) as the probability to get connected. We used this procedure to investigate the structural and dynamical changes in the cortical networks estimated from a dataset of high-resolution EEG signals in a group of spinal cord injured (SCI) patients during the attempt of foot movement. In the light of a statistical contrast with a healthy population, the permeability index P (h) of the SCI networks increased significantly (P < 0.01) in the Theta frequency band (3-6 Hz) for distances h ranging from 2 to 4. On the contrary, no significant differences were found between the two populations for the redundancy index R (h) . The most significant changes in the brain functional network of SCI patients occurred mainly in the lower spectral contents. These changes were related to an improved propagation of communication between the closest cortical areas rather than to a different level of redundancy. This evidence strengthens the hypothesis of the need for a higher functional interaction among the closest ROIs as a mechanism to compensate the lack of feedback from the peripheral nerves to the sensomotor areas.

Benign focal seizures of adolescence and neuropsychological findings in patients from community

RATIONALE: Benign focal seizures of adolescence (BFSA) described by Loiseau et al in 1972, is considered a rare entity, but maybe underdiagnosed. Although mild neuropsychological deficits have been reported in patients with benign epilepsies of childhood, these evaluations have not so far been described in BFSA. The aim of this study is to evaluate neuropsychological functions in BFSA with new onset seizures (<12 months). METHODS: Eight patients with BFSA (according to Loiseau et al, 1972, focal or secondarily tonic clonic generalized seizures between the ages of 10-18 yrs., normal neurologic examination, normal EEG or with mild focal abnormalities) initiated in the last 12 months were studied between July 2008 to May 2009. They were referred from the Pediatric Emergency Section of the Hospital Universitário of the University of Sao Paulo, a secondary care regionalized facility located in a district of middle-low income in Sao Paulo city, Brazil. The study was approved by the Ethics Committee of the Institution. All patients performed neurological, EEG, brain CT and neuropsychological evaluation which consisted of Raven's Special Progressive Matrices - General and Special Scale (according to different ages), Wechsler Children Intelligence Scale-WISC III with ACID Profile, Trail Making Test A/B, Stroop Test, Bender Visuo-Motor Test, Rey Complex Figure, Rey Auditory Verbal Learning Test-RAVLT, Boston Naming Test, Fluency Verbal for phonological and also conceptual patterns - FAS/Animals and Hooper Visual Organization Test. For academic achievement, we used a Brazilian test for named "Teste do Desempenho Escolar", which evaluates abilities to read, write and calculate according to school grade. RESULTS: There were 2 boys and 6 girls, with ages ranging from 10 yrs. 9 m to 14 yrs. 3 m. Most (7/8) of the patients presented one to two seizures and only three of them received antiepileptic drugs (AEDs). Six had mild EEG focal abnormalities and all had normal brain CT. All were literate, attended regular public schools and scored in a median range for IQ, and seven showed discrete higher scores for the verbal subtests. There were low scores for attention in different modalities in six patients, mainly in alternated attention as well as inhibitory subtests (Stroop test and Trail Making Test part B). Four of the latter cases who showed impairment both in alternated and inhibitory attention were not taking AEDs. Visual memory was impaired in five patients (Rey Complex Figure). Executive functions analysis showed deficits in working memory in five, mostly observed in Digits Indirect Order and Arithmetic tests (WISC III). Reading and writing skills were below the expected average for school grade in six patients according to the achievement scholar performance test utilized. One patient of this series who had the best scores in all tests was taking phenobarbital. CONCLUSIONS: Neuropsychological imbalance between normal IQ and mild dysfunctions such as in attention domain and in some executive abilities like working memory and planning, as well as difficulties in visual memory and in reading and writing, were described in this group of patients with BFSA from community. This may reflect mild higher level neurological dysfunctions in adolescence idiopathic focal seizures probably caused by an underlying dysmaturative epileptogenic process. Although academic problems often have multiple causes, a specific educational approach may be necessary in these adolescents, in order to improve their scholastic achievements, helping in this way, to decrease the stigma associated to epileptic seizures in the community.

Antinociceptive effect of stimulating the occipital or retrosplenial cortex in rats

A role for the occipital or retrosplenial cortex in nociceptive processing has not been demonstrated yet, but connections from these cortices to brain structures involved in descending pain-inhibitory mechanisms were already demonstrated. This study demonstrated that the electrical stimulation of the occipital or retrosplenial cortex produces antinociception in the rat tail-flick and formalin tests. Bilateral lesions of the dorsolateral funiculus abolished the effect of cortical stimulation in the tail-flick test. Injection of glutamate into the same targets was also antinociceptive in the tail-flick test. No rats stimulated in the occipital or retrosplenial cortex showed any change in motor performance on the Rota-rod test, or had epileptiform changes in the EEG recording during or up to 3 hours after stimulation. The antinociception induced by occipital cortex stimulation persisted after neural block of the retrosplenial cortex. The effect of retrosplenial cortex stimulation also persisted after neural block of the occipital cortex. We conclude that stimulation of the occipital or retrosplenial cortex in rats leads to antinociception activating distinct descending pain-inhibitory mechanisms, and this is unlikely to result from a reduced motor performance or a postictal phenomenon. Perspective: This study presents evidence that stimulation of the retrosplenial or occipital cortex produces antinociception in rat models of acute pain. These findings enhance our understanding of the role of the cerebral cortex in control of pain. (C) 2010 by the American Pain Society

Frequency Domain Connectivity Identification: An Application of Partial Directed Coherence in fMRI

Functional magnetic resonance imaging (fMRI) has become an important tool in Neuroscience due to its noninvasive and high spatial resolution properties compared to other methods like PET or EEG. Characterization of the neural connectivity has been the aim of several cognitive researches, as the interactions among cortical areas lie at the heart of many brain dysfunctions and mental disorders. Several methods like correlation analysis, structural equation modeling, and dynamic causal models have been proposed to quantify connectivity strength. An important concept related to connectivity modeling is Granger causality, which is one of the most popular definitions for the measure of directional dependence between time series. In this article, we propose the application of the partial directed coherence (PDC) for the connectivity analysis of multisubject fMRI data using multivariate bootstrap. PDC is a frequency domain counterpart of Granger causality and has become a very prominent tool in EEG studies. The achieved frequency decomposition of connectivity is useful in separating interactions from neural modules from those originating in scanner noise, breath, and heart beating. Real fMRI dataset of six subjects executing a language processing protocol was used for the analysis of connectivity. Hum Brain Mapp 30:452-461, 2009. (C) 2007 Wiley-Liss, Inc.

Hemispheric Lateralization in Benign Focal Epilepsy in Childhood With Centrotemporal Spikes (BECTS)

Benign focal epilepsy in childhood with centrotemporal spikes (BECTS) is one of the most common forms of epilepsy. In adults there is a higher percentage of lateralized epileptic discharges in the left cerebral hemisphere; however, in children this pattern does not seem to have the same distribution. The objective of this study was to evaluate the lateralization of interictal spikes in children with BECTS in relation to the sex of the child and the age of onset of epilepsy. We studied the electroencephalograms (EEGs) of 114 children with a clinical diagnosis of BECTS according to ILAE. The results obtained from two EEGs, performed at intervals of 6 and 12 months, were correlated with the age of onset of the epileptic seizures and the sex of the child. There was no association between the onset of epileptic seizures and the age of the child (p=0.461). When we analyzed the relationship between laterality and sex we did not observe any difference in the first EEG (p = 0.767) results; however, in the results of the second EEG there was a difference (p = 0.002). In males, left and bilateral interictal spikes were predominant, and in females the right hemisphere showed predominant spikes and there were continuous spike-and-wave discharges during slow sleep (CSWSS). The analysis between laterality and a child`s age did not show predominant interictal spikes in the hemispheres, except in males where there were predominant multifocal and generalized spikes, but not lateralization (p=0.011). The conclusion was that in BECTS the lateralization of interictal spikes was not consistent as described in adult patients, but there was a slight left hemispheric predominance in boys and right hemispheric predominance in girls.

Improving Alzheimer`s Disease Diagnosis with Machine Learning Techniques

There is not a specific test to diagnose Alzheimer`s disease (AD). Its diagnosis should be based upon clinical history, neuropsychological and laboratory tests, neuroimaging and electroencephalography (EEG). Therefore, new approaches are necessary to enable earlier and more accurate diagnosis and to follow treatment results. In this study we used a Machine Learning (ML) technique, named Support Vector Machine (SVM), to search patterns in EEG epochs to differentiate AD patients from controls. As a result, we developed a quantitative EEG (qEEG) processing method for automatic differentiation of patients with AD from normal individuals, as a complement to the diagnosis of probable dementia. We studied EEGs from 19 normal subjects (14 females/5 males, mean age 71.6 years) and 16 probable mild to moderate symptoms AD patients (14 females/2 males, mean age 73.4 years. The results obtained from analysis of EEG epochs were accuracy 79.9% and sensitivity 83.2%. The analysis considering the diagnosis of each individual patient reached 87.0% accuracy and 91.7% sensitivity.

Stereotactic disconnection of hypothalamic hamartoma to control seizure and behavior disturbance: case report and literature review

An 18-year-old boy with refractory epilepsy and aggressiveness associated to a hypothalamic hamartoma was submitted to a stereotactically guided lesion by thermocoagulation. The target was based on magnetic resonance (MR) images merged with computed tomography scan images taken on the day of surgery while patient was on a stereotactic frame. In order to reveal structures not discernible in MR images, the Schaltenbrand digital brain atlas was merged onto the patient`s images. Target and trajectory of the depth electrode were chosen based on three-dimensional imaging reconstructions. A surgical plan was devised to disconnect the hypothalamic hamartoma from the hypothalamus, medial forebrain bundle, fasciculus princeps, and dorsal longitudinal fasciculus. Our target was placed at the inferior portion of the posterolateral component of the hamartoma, bordering the normal hypothalamus. The patient evolved with marked lessening of aggressiveness. Seizure frequency was reduced from several seizures per day to less than one tonic-clonic seizure during sleep per month and only two episodes suggestive of partial complex seizures during daytime. These results have remained consistent over a 24-month postoperative follow-up. Functional neuroanatomy of hypothalamic connections involved in seizure propagation and aggressive behavior was reviewed.

Emotional trauma and abuse in patients with psychogenic nonepileptic seizures

A history of childhood trauma and the presence of dissociative phenomena are considered to be the most important risk factors for psychogenic nonepileptic seizure disorder (PNESD). This case-control study investigated 20 patients with PNESD and 20 with temporal lobe epilepsy (TLE) diagnosed by video/EEG monitoring who were matched for gender and age. Patients with both conditions were not included in the study. Groups were evaluated for age at onset and at diagnosis, worst lifetime weekly seizure frequency, trauma history, and presence of dissociative phenomena. Age at onset (P = 0.007) and age at diagnosis (P < 0.001) were significantly higher in the PNESD group than the control group, as were the scores on the Dissociative Experiences Scale (P < 0.001) and Childhood Trauma Questionnaire (P = 0.014). Only the differences in scores on the Childhood Trauma Questionnaire subscales Emotional Neglect (P = 0.013) and Emotional Abuse (P = 0.014) reached statistical significance. Dissociative phenomena and a reported history of childhood trauma are more common in patients with PNESD than in those with TLE. However, only emotional neglect and abuse were associated with PNESD in this study. (C) 2010 Elsevier Inc. All rights reserved.

Gamma-band oscillations in fronto-central areas during performance of a sensorimotor integration task: A qEEG coherence study

This study aimed to elucidate electrophysiological and cortical mechanisms involved in anticipatory actions when 23 healthy right-handed subjects had to catch a free falling object by qEEG gamma-band (30-100 Hz). It is involved in cognitive processes, memory, spatial/temporal and proprioceptive factors. Our hypothesis is that an increase in gamma coherence in frontal areas will be observed during moment preceding ball drop, due to their involvement in attention, planning, selection of movements, preparation and voluntary control of action and in central areas during moment after ball drop, due to their involvement in motor preparation, perception and execution of movement. However, through a paired t-test, we found an increase in gamma coherence for F3-F4 electrode pair during moment preceding ball drop and confirmed our hypothesis for C3-C4 electrode pair. We conclude that gamma plays an important role in reflecting binding of several brain areas in a complex motor task as observed in our results. Moreover, for selection of movements, preparation and voluntary control of action, motor preparation, perception and execution of movement, the integration of somatosensory and visual information is mandatory. (C) 2010 Elsevier Ireland Ltd. All rights reserved.