Assessing acute middle cerebral artery ischemic stroke by quantitative electric tomography

Predicting brain edema and outcomes after thrombectomy in stroke: Frontal delta/alpha ratio as an optimal quantitative EEG index

OBJECTIVE

We aimed to determine whether quantitative electroencephalography (QEEG) measures have predictive value for cerebral edema (CED) and clinical outcomes in acute ischemic stroke (AIS) patients with anterior circulation large vessel occlusion who underwent mechanical thrombectomy (MT).

METHODS

A total of 105 patients with AIS in the anterior circulation were enrolled in this prospective study. The occurrence and severity of CED were assessed through computed tomography conducted 24 h after MT. Clinical outcomes were evaluated based on early neurological deterioration (END) and 3-month functional status, as measured by the modified Rankin scale (mRS). Electroencephalography (EEG) recordings were performed 24 h after MT, and QEEG indices were calculated from the standard 16 electrodes and 2 frontal channels (F3-C3, F4-C4). The delta/alpha ratio (DAR), the (delta + theta) / (alpha + beta) ratio (DTABR), and relative delta power were averaged over all electrodes (global) and the F3-C3 and F4-C4 channels (frontal). The predictive effect and value of QEEG indices for CED and clinical outcomes were assessed using ordinal and logistic regression models, as well as receiver operating characteristic (ROC) curves.

RESULTS

Significantly, both global and frontal DAR were found to be associated with the severity of CED, END, and poor functional outcomes at 90 days, while global and frontal DTABR and relative delta power were not associated with outcomes. In ROC analysis, the best predictive effect was observed in frontal DAR, with an area under the curve of approximately 0.80. It exhibited approximately 75% sensitivity and 71% specificity for radiological and clinical outcomes when a threshold of 3.3 was used.

CONCLUSIONS

QEEG techniques may be considered an efficient bedside monitoring method for assessing treatment efficacy, identifying patients at higher risk of severe CED and END, and predicting long-term functional outcomes.

SIGNIFICANCE

QEEG can help identify patients at risk of severe neurological complications that can impact long-term functional recovery in AIS patients who underwent MT.

Effects of anodal transcranial direct current stimulation over motor cortex on resting-state brain activity in the early subacute stroke phase: A power spectral density analysis

INTRODUCTION

Despite promising results, the effects of transcranial direct current stimulation (tDCS) in the early stages of stroke and its impact on brain activity have been poorly studied. Therefore, this study aimed to investigate the effect of tDCS applied over the ipsilesional motor cortex on resting-state brain activity in the early subacute phase of stroke.

METHODS

This is a pilot, randomized, double-blind, proof-of-concept study. The patients with stroke were randomly assigned into two groups: anodal tDCS (A-tDCS) or sham tDCS (S-tDCS). For A-tDCS, the anode was placed over the ipsilesional motor cortex, while the cathode was placed over the left or right supraorbital area (Fp2 for left stroke or Fp1 for right stroke). For the real stimulation, a constant current of 1.0 mA was delivered for 20 min and then ramped down linearly for 30 s, maintaining a resistance below 10 kΩ. For the sham stimulation, the stimulator was turned on, and the current intensity was gradually increased for 30 s, tapered off over 30 s, and maintained for 30 min without stimulation. Each stimulation was performed for three consecutive sessions with an interval of 1 h between them. The primary outcome was spectral electroencephalography (EEG) analysis based on the Power Spectral Density (PSD) determined by EEG records of areas F3, F4, C3, C4, P3, and P4. Brain Vision Analyzer software processed the signals, EEG power spectral density (PSD) was calculated before and after stimulation, and alpha, beta, delta, and theta power were analyzed. The secondary outcomes included hemodynamic variables based on the difference between baseline (D0) and post-intervention session (D1) values of systolic (SBP) and diastolic (DBP) blood pressure, heart rate (HR), respiratory rate (RR) and peripheral oxygen saturation (SPO2). Mann-Whitney test was used to compare position measurements of two independent samples; Fisher's exact test was used to compare two proportions; paired Wilcoxon signed-rank test was used to compare the median differences in the within-group comparison, and Spearman correlations matrix among spectral power analysis between EEG bands was performed to verify consistency of occurrence of oscillations. Statistical significance was set at P < 0.05.

RESULTS

An increase in PSD in the alpha frequency in the P4 region was observed after the intervention in the A-tDCS group, as compared to the placebo group (before = 6.13; after = 10.45; p < 0.05). In the beta frequency, an increase in PSD was observed in P4 (before = 4.40; after = 6.79; p < 0.05) and C4 (before = 4.43; after = 6.94; p < 0.05) after intervention in the A-tDCS group. There was a reduction in PSD at delta frequency in C3 (before = 293.8; after = 58.6; p < 0.05) after intervention in the A-tDCS group. In addition, it was observed a strong relationship between alpha and theta power in the A-tDCS group before and after intervention. However, the sham group showed correlations between more power bands (alpha and theta, alpha and delta, and delta and theta) after intervention. There was no difference in hemodynamic variables between the intra- (before and after stimulation) and inter-groups (mean difference).

CONCLUSION

Anodal tDCS over the ipsilesional motor cortex had significant effects on the brain electrical activity in the early subacute stroke phase, increasing alpha and beta wave activities in sensorimotor regions while reducing slow delta wave activity in motor regions. These findings highlight the potential of anodal tDCS as a therapeutic intervention in the early stroke phase.

Literature review of stroke assessment for upper-extremity physical function via EEG, EMG, kinematic, and kinetic measurements and their reliability

BACKGROUND

Significant clinician training is required to mitigate the subjective nature and achieve useful reliability between measurement occasions and therapists. Previous research supports that robotic instruments can improve quantitative biomechanical assessments of the upper limb, offering reliable and more sensitive measures. Furthermore, combining kinematic and kinetic measurements with electrophysiological measurements offers new insights to unlock targeted impairment-specific therapy. This review presents common methods for analyzing biomechanical and neuromuscular data by describing their validity and reporting their reliability measures.

METHODS

This paper reviews literature (2000-2021) on sensor-based measures and metrics for upper-limb biomechanical and electrophysiological (neurological) assessment, which have been shown to correlate with clinical test outcomes for motor assessment. The search terms targeted robotic and passive devices developed for movement therapy. Journal and conference papers on stroke assessment metrics were selected using PRISMA guidelines. Intra-class correlation values of some of the metrics are recorded, along with model, type of agreement, and confidence intervals, when reported.

RESULTS

A total of 60 articles are identified. The sensor-based metrics assess various aspects of movement performance, such as smoothness, spasticity, efficiency, planning, efficacy, accuracy, coordination, range of motion, and strength. Additional metrics assess abnormal activation patterns of cortical activity and interconnections between brain regions and muscle groups; aiming to characterize differences between the population who had a stroke and the healthy population.

CONCLUSION

Range of motion, mean speed, mean distance, normal path length, spectral arc length, number of peaks, and task time metrics have all demonstrated good to excellent reliability, as well as provide a finer resolution compared to discrete clinical assessment tests. EEG power features for multiple frequency bands of interest, specifically the bands relating to slow and fast frequencies comparing affected and non-affected hemispheres, demonstrate good to excellent reliability for populations at various stages of stroke recovery. Further investigation is needed to evaluate the metrics missing reliability information. In the few studies combining biomechanical measures with neuroelectric signals, the multi-domain approaches demonstrated agreement with clinical assessments and provide further information during the relearning phase. Combining the reliable sensor-based metrics in the clinical assessment process will provide a more objective approach, relying less on therapist expertise. This paper suggests future work on analyzing the reliability of metrics to prevent biasedness and selecting the appropriate analysis.

Spectral slowing in chronic stroke reflects abnormalities in both periodic and aperiodic neural dynamics

Decades of electrophysiological work have demonstrated the presence of "spectral slowing" in stroke patients - a prominent shift in the power spectrum towards lower frequencies, most evident in the vicinity of the lesion itself. Despite the reliability of this slowing as a marker of dysfunctional tissue across patient groups as well as animal models, it has yet to be explained in terms of the pathophysiological processes of stroke. To do so requires clear understanding of the neural dynamics that these differences represent, acknowledging the often overlooked fact that spectral power reflects more than just the amplitude of neural oscillations. To accomplish this, we used a combination of frequency domain and time domain measures to disambiguate and quantify periodic (oscillatory) and aperiodic (non-oscillatory) neural dynamics in resting state magnetoencephalography (MEG) recordings from chronic stroke patients. We found that abnormally elevated low frequency power in these patients was best explained by a steepening of the aperiodic component of the power spectrum, rather than an enhancement of low frequency oscillations, as is often assumed. However, genuine oscillatory activity at higher frequencies was also found to be abnormal, with patients showing alpha slowing and diminished oscillatory activity in the beta band. These aperiodic and periodic abnormalities were found to covary, and could be detected even in the un-lesioned hemisphere, however they were most prominent in perilesional tissue, where their magnitude was predictive of cognitive impairment. This work redefines spectral slowing as a pattern of changes involving both aperiodic and periodic neural dynamics and narrows the gap in understanding between non-invasive markers of dysfunctional tissue and disease processes responsible for altered neural dynamics.

Pathological changes of brain oscillations following ischemic stroke

Brain oscillations recorded in the extracellular space are among the most important aspects of neurophysiology data reflecting the activity and function of neurons in a population or a network. The signal strength and patterns of brain oscillations can be powerful biomarkers used for disease detection and prediction of the recovery of function. Electrophysiological signals can also serve as an index for many cutting-edge technologies aiming to interface between the nervous system and neuroprosthetic devices and to monitor the efficacy of boosting neural activity. In this review, we provided an overview of the basic knowledge regarding local field potential, electro- or magneto- encephalography signals, and their biological relevance, followed by a summary of the findings reported in various clinical and experimental stroke studies. We reviewed evidence of stroke-induced changes in hippocampal oscillations and disruption of communication between brain networks as potential mechanisms underlying post-stroke cognitive dysfunction. We also discussed the promise of brain stimulation in promoting post stroke functional recovery via restoring neural activity and enhancing brain plasticity.

EEG spectral exponent as a synthetic index for the longitudinal assessment of stroke recovery

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The Spectral Exponent (SE) indexes power-law features of the resting EEG in stroke patients.

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SE is consistently steeper in the affected hemisphere of patients after middle cerebral artery stroke.

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SE is linked to clinical status and seems to be a good predictor of clinical outcome.

Objective

Quantitative Electroencephalography (qEEG) can capture changes in brain activity following stroke. qEEG metrics traditionally focus on oscillatory activity, however recent findings highlight the importance of aperiodic (power-law) structure in characterizing pathological brain states. We assessed neurophysiological alterations and recovery after mono-hemispheric stroke by means of the Spectral Exponent (SE), a metric that reflects EEG slowing and quantifies the power-law decay of the EEG Power Spectral Density (PSD).

Methods

Eighteen patients (n = 18) with mild to moderate mono-hemispheric Middle Cerebral Artery (MCA) ischaemic stroke were retrospectively enrolled for this study. Patients underwent EEG recording in the sub-acute phase (T0) and after 2 months of physical rehabilitation (T1). Sixteen healthy controls (HC; n = 16) matched by age and sex were enrolled as a normative group. SE values and narrow-band PSD were estimated for each recording. We compared SE and band-power between patients and HC, and between the affected (AH) and unaffected hemisphere (UH) at T0 and T1 in patients.

Results

At T0, stroke patients showed significantly more negative SE values than HC (p = 0.003), reflecting broad-band EEG slowing. Most important, in patients SE over the AH was consistently more negative compared to the UH and showed a renormalization at T1. This SE renormalization significantly correlated with National Institute of Health Stroke Scale (NIHSS) improvement (R = 0.63, p = 0.005).

Conclusions

SE is a reliable readout of the neurophysiological and clinical alterations occurring after an ischaemic cortical lesion.

Significance

SE promise to be a robust method to monitor and predict patients’ functional outcome.

Surface electroencephalography (EEG) during the acute phase of stroke to assist with diagnosis and prediction of prognosis: a scoping review

BACKGROUND

Stroke is a common medical emergency responsible for significant mortality and disability. Early identification improves outcomes by promoting access to time-critical treatments such as thrombectomy for large vessel occlusion (LVO), whilst accurate prognosis could inform many acute management decisions. Surface electroencephalography (EEG) shows promise for stroke identification and outcome prediction, but evaluations have varied in technology, setting, population and purpose. This scoping review aimed to summarise published literature addressing the following questions: 1. Can EEG during acute clinical assessment identify: a) Stroke versus non-stroke mimic conditions. b) Ischaemic versus haemorrhagic stroke. c) Ischaemic stroke due to LVO. 2. Can these states be identified if EEG is applied < 6 h since onset. 3. Does EEG during acute assessment predict clinical recovery following confirmed stroke.

METHODS

We performed a systematic search of five bibliographic databases ending 19/10/2020. Two reviewers assessed eligibility of articles describing diagnostic and/or prognostic EEG application < 72 h since suspected or confirmed stroke.

RESULTS

From 5892 abstracts, 210 full text articles were screened and 39 retained. Studies were small and heterogeneous. Amongst 21 reports of diagnostic data, consistent associations were reported between stroke, greater delta power, reduced alpha/beta power, corresponding ratios and greater brain asymmetry. When reported, the area under the curve (AUC) was at least good (0.81-1.00). Only one study combined clinical and EEG data (AUC 0.88). There was little data found describing whether EEG could identify ischaemic versus haemorrhagic stroke. Radiological changes suggestive of LVO were also associated with increased slow and decreased fast waves. The only study with angiographic proof of LVO reported AUC 0.86 for detection < 24 h since onset. Amongst 26 reports of prognostic data, increased slow and reduced fast wave EEG changes were associated with future dependency, neurological impairment, mortality and poor cognition, but there was little evidence that EEG enhanced outcome prediction relative to clinical and/or radiological variables. Only one study focussed solely on patients < 6 h since onset for predicting neurological prognosis post-thrombolysis, with more favourable outcomes associated with greater hemispheric symmetry and a greater ratio of fast to slow waves.

CONCLUSIONS

Although studies report important associations with EEG biomarkers, further technological development and adequately powered real-world studies are required before recommendations can be made regarding application during acute stroke assessment.

Quantitative EEG Correlates with NIHSS and MoCA for Assessing the Initial Stroke Severity in Acute Ischemic Stroke Patients

BACKGROUND: National Institutes of Health Stroke Scale (NIHSS) and Montreal Cognitive Assessment (MoCA) measure stroke severity by assessing the functional and cognitive outcome, respectively. However, they cannot be used to measure subtle evolution in clinical symptoms during the early phase. Quantitative EEG (qEEG) can detect any subtle changes in CBF and brain metabolism thus may also benefit for assessing the severity. AIM: This study aims to identify the correlation between qEEG with NIHSS and MoCA for assessing the initial stroke severity in acute ischemic stroke patients. METHODS: This was a cross-sectional study. We recruited 30 patients with first-ever acute ischemic stroke hospitalized in Dr. Sardjito General Hospital, Yogyakarta, Indonesia. We measured the NIHSS, MoCA score, and qEEG parameter during the acute phase of stroke. Correlation and regression analysis was completed to investigate the relationship between qEEG parameter with NIHSS and MoCA. RESULTS: Four acute qEEG parameter demonstrated moderate-to-high correlations with NIHSS and MoCA. DTABR had positive correlation with NIHSS (r = 0.379, p = 0.04). Meanwhile, delta-absolute power, DTABR, and DAR were negatively correlated with MoCA score (r = −0.654, p = 0.01; r = −0.397, p = 0.03; and r = −0.371, p = 0.04, respectively). After adjusted with the confounding variables, delta-absolute power was independently associated with MoCA score, but not with NIHSS (B = −2.887, 95% CI (−4.304–−1.470), p < 0.001). CONCLUSIONS: Several qEEG parameters had significant correlations with NIHSS and MoCA in acute ischemic stroke patients. The use of qEEG in acute clinical setting may provide a reliable and efficient prediction of initial stroke severity. Further cohort study with larger sample size and wide range of stroke severity is still needed.

Brain Structural and Functional Connectivity: A Review of Combined Works of Diffusion Magnetic Resonance Imaging and Electro-Encephalography

Implications of structural connections within and between brain regions for their functional counterpart are timely points of discussion. White matter microstructural organization and functional activity can be assessed in unison. At first glance, however, the corresponding findings appear variable, both in the healthy brain and in numerous neuro-pathologies. To identify consistent associations between structural and functional connectivity and possible impacts for the clinic, we reviewed the literature of combined recordings of electro-encephalography (EEG) and diffusion-based magnetic resonance imaging (MRI). It appears that the strength of event-related EEG activity increases with increased integrity of structural connectivity, while latency drops. This agrees with a simple mechanistic perspective: the nature of microstructural white matter influences the transfer of activity. The EEG, however, is often assessed for its spectral content. Spectral power shows associations with structural connectivity that can be negative or positive often dependent on the frequencies under study. Functional connectivity shows even more variations, which are difficult to rank. This might be caused by the diversity of paradigms being investigated, from sleep and resting state to cognitive and motor tasks, from healthy participants to patients. More challenging, though, is the potential dependency of findings on the kind of analysis applied. While this does not diminish the principal capacity of EEG and diffusion-based MRI co-registration, it highlights the urgency to standardize especially EEG analysis.

Beneficial Effect of Sodium Nitrite on EEG Ischaemic Markers in Patients with Subarachnoid Haemorrhage

Subarachnoid haemorrhage (SAH) is associated with long-term disability, serious reduction in quality of life and significant mortality. Early brain injury (EBI) refers to the pathological changes in cerebral metabolism and blood flow that happen in the first few days after ictus and may lead on to delayed cerebral ischaemia (DCI). A disruption of the nitric oxide (NO) pathway is hypothesised as a key mechanism underlying EBI. A decrease in the alpha-delta power ratio (ADR) of the electroencephalogram has been related to cerebral ischaemia. In an experimental medicine study, we tested the hypothesis that intravenous sodium nitrite, an NO donor, would lead to increases in ADR. We studied 33 patients with acute aneurysmal SAH in the EBI phase. Participants were randomised to either sodium nitrite or saline infusion for 1 h. EEG measurements were taken before the start of and during the infusion. Twenty-eight patients did not develop DCI and five patients developed DCI. In the patients who did not develop DCI, we found an increase in ADR during sodium nitrite versus saline infusion. In the five patients who developed DCI, we did not observe a consistent pattern of ADR changes. We suggest that ADR power changes in response to nitrite infusion reflect a NO-mediated reduction in cerebral ischaemia and increase in perfusion, adding further evidence to the role of the NO pathway in EBI after SAH. Our findings provide the basis for future clinical trials employing NO donors after SAH.

Electroencephalography-Derived Prognosis of Functional Recovery in Acute Stroke Through Machine Learning Approaches

Stroke, if not lethal, is a primary cause of disability. Early assessment of markers of recovery can allow personalized interventions; however, it is difficult to deliver indexes in the acute phase able to predict recovery. In this perspective, evaluation of electrical brain activity may provide useful information. A machine learning approach was explored here to predict post-stroke recovery relying on multi-channel electroencephalographic (EEG) recordings of few minutes performed at rest. A data-driven model, based on partial least square (PLS) regression, was trained on 19-channel EEG recordings performed within 10 days after mono-hemispheric stroke in 101 patients. The band-wise (delta: 1-4[Formula: see text]Hz, theta: 4-7[Formula: see text]Hz, alpha: 8-14[Formula: see text]Hz and beta: 15-30[Formula: see text]Hz) EEG effective powers were used as features to predict the recovery at 6 months (based on clinical status evaluated through the NIH Stroke Scale, NIHSS) in an optimized and cross-validated framework. In order to exploit the multimodal contribution to prognosis, the EEG-based prediction of recovery was combined with NIHSS scores in the acute phase and both were fed to a nonlinear support vector regressor (SVR). The prediction performance of EEG was at least as good as that of the acute clinical status scores. A posteriori evaluation of the features exploited by the analysis highlighted a lower delta and higher alpha activity in patients showing a positive outcome, independently of the affected hemisphere. The multimodal approach showed better prediction capabilities compared to the acute NIHSS scores alone ([Formula: see text] versus [Formula: see text], AUC = 0.80 versus AUC = 0.70, [Formula: see text]). The multimodal and multivariate model can be used in acute phase to infer recovery relying on standard EEG recordings of few minutes performed at rest together with clinical assessment, to be exploited for early and personalized therapies. The easiness of performing EEG may allow such an approach to become a standard-of-care and, thanks to the increasing number of labeled samples, further improving the model predictive power.

Longitudinal quantitative electroencephalographic study in mono-hemispheric stroke patients

The identification of individual factors modulating clinical recovery after a stroke is fundamental to personalize the therapeutic intervention to enhance the final clinical outcome. In this framework, electrophysiological factors are promising since are more directly related to neuroplasticity, which supports recovery in stroke patients, than neurovascular factors. In this retrospective observational study, we investigated brain neuronal activity assessed via spectral features and Higuchi’s fractal dimension (HFD) of electroencephalographic signals in acute phase (2–10 days from symptom onset, T0) and sub-acute phase (2.5 months, T1) in 24 patients affected by unilateral middle cerebral artery stroke. Longitudinal assessment of the clinical deficits was performed using the National Institutes of Health Stroke Scale (NIHSS), together with the effective recovery calculated as the ratio between difference of NIHSS at T0 and T1 over the NIHSS value at T0. We observed that delta and alpha band electroencephalographic signal power changed between the two phases in both the hemispheres ipsilateral (ILH) and contralateral (CHL) to the lesion. Moreover, at T0, bilateral higher delta band power correlated with worse clinical conditions (Spearman’s r_s = 0.460, P = 0.027 for ILH and r_s = 0.508, P = 0.013 for CLH), whereas at T1 this occurred only for delta power in ILH (r_s = 0.411, P = 0.046) and not for CHL. Inter-hemispheric difference (ILH vs. CLH) of alpha power in patients was lower at T0 than at T1 (P = 0.020). HFD at T0 was lower than at T1 (P = 0.005), and at both phases, ILH HFD was lower than CLH HFD (P = 0.020). These data suggest that inter-hemispheric low band asymmetry and fractal dimension changes from the acute to the sub-acute phase are sensitive to neuroplasticity processes which subtend clinical recovery. The study protocol was approved by the Bioethical Committee of Ospedale San Giovanni Calibita Fatebenefretelli (No. 40/2011) on July 14, 2011.

Deficits in Behavioral Functions of Intact Barrel Cortex Following Lesions of Homotopic Contralateral Cortex

Focal unilateral injuries to the somatosensory whisker barrel cortex have been shown cause long-lasting deficits in the activity and experience-dependent plasticity of neurons in the intact contralateral barrel cortex. However, the long-term effect of these deficits on behavioral functions of the intact contralesional cortex is not clear. In this study, we used the “Gap-crossing task” a barrel cortex-dependent, whisker-sensitive, tactile behavior to test the hypothesis that unilateral lesions of the somatosensory cortex would affect behavioral functions of the intact somatosensory cortex and degrade the execution of a bilaterally learnt behavior. Adult rats were trained to perform the Gap-crossing task using whiskers on both sides of the face. The barrel cortex was then lesioned unilaterally by subpial aspiration. As observed in other studies, when rats used whiskers that directly projected to the lesioned hemisphere the performance of Gap-crossing was drastically compromised, perhaps due to direct effect of lesion. Significant and persistent deficits were present when the lesioned rats performed Gap-crossing task using whiskers that projected to the intact cortex. The deficits were specific to performance of the task at the highest levels of sensitivity. Comparable deficits were seen when normal, bilaterally trained, rats performed the Gap-crossing task with only the whiskers on one side of the face or when they used only two rows of whiskers (D row and E row) intact on both side of the face. These findings indicate that the prolonged impairment in execution of the learnt task by rats with unilateral lesions of somatosensory cortex could be because sensory inputs from one set of whiskers to the intact cortex is insufficient to provide adequate sensory information at higher thresholds of detection. Our data suggest that optimal performance of somatosensory behavior requires dynamic activity-driven interhemispheric interactions from the entire somatosensory inputs between homotopic areas of the cerebral cortex. These results imply that focal unilateral cortical injuries, including those in humans, are likely to have widespread bilateral effects on information processing including in intact areas of the cortex.

Integrated treatment modality of cathodal-transcranial direct current stimulation with peripheral sensory stimulation affords neuroprotection in a rat stroke model

Cathodal-transcranial direct current stimulation induces therapeutic effects in animal ischemia models by preventing the expansion of ischemic injury during the hyperacute phase of ischemia. However, its efficacy is limited by an accompanying decrease in cerebral blood flow. On the other hand, peripheral sensory stimulation can increase blood flow to specific brain areas resulting in rescue of neurovascular functions from ischemic damage. Therefore, the two modalities appear to complement each other to form an integrated treatment modality. Our results showed that hemodynamics was improved in a photothrombotic ischemia model, as cerebral blood volume and hemoglobin oxygen saturation ([Formula: see text]) recovered to 71% and 76% of the baseline values, respectively. Furthermore, neural activities, including somatosensory-evoked potentials (110% increase), the alpha-to-delta ratio (27% increase), and the [Formula: see text] ratio (27% decrease), were also restored. Infarct volume was reduced by 50% with a 2-fold preservation in the number of neurons and a 6-fold reduction in the number of active microglia in the infarct region compared with the untreated group. Grip strength was also better preserved (28% higher) compared with the untreated group. Overall, this nonpharmacological, nonintrusive approach could be prospectively developed into a clinical treatment modality.

Dynamical Signatures of Structural Connectivity Damage to a Model of the Brain Posed at Criticality

Synchronization of brain activity fluctuations is believed to represent communication between spatially distant neural processes. These interareal functional interactions develop in the background of a complex network of axonal connections linking cortical and subcortical neurons, termed the human "structural connectome." Theoretical considerations and experimental evidence support the view that the human brain can be modeled as a system operating at a critical point between ordered (subcritical) and disordered (supercritical) phases. Here, we explore the hypothesis that pathologies resulting from brain injury of different etiologies are related to this model of a critical brain. For this purpose, we investigate how damage to the integrity of the structural connectome impacts on the signatures of critical dynamics. Adopting a hybrid modeling approach combining an empirical weighted network of human structural connections with a conceptual model of critical dynamics, we show that lesions located at highly transited connections progressively displace the model toward the subcritical regime. The topological properties of the nodes and links are of less importance when considered independently of their weight in the network. We observe that damage to midline hubs such as the middle and posterior cingulate cortex is most crucial for the disruption of criticality in the model. However, a similar effect can be achieved by targeting less transited nodes and links whose connection weights add up to an equivalent amount. This implies that brain pathology does not necessarily arise due to insult targeted at well-connected areas and that intersubject variability could obscure lesions located at nonhub regions. Finally, we discuss the predictions of our model in the context of clinical studies of traumatic brain injury and neurodegenerative disorders.

Delta Power Is Higher and More Symmetrical in Ischemic Stroke Patients with Cortical Involvement

A brain injury resulting from unilateral stroke critically alters brain functionality and the complex balance within the cortical activity. Such modifications may critically depend on lesion location and cortical involvement. Indeed, recent findings pointed out the necessity of applying a stratification based on lesion location when investigating inter-hemispheric balance in stroke. Here, we tested whether cortical involvement could imply differences in band-specific activity and brain symmetry in post stroke patients with cortico-subcortical and subcortical strokes. We explored brain activity related to lesion location through EEG power analysis and quantitative Electroencephalography (qEEG) measures. Thirty stroke patients in the subacute phase and 10 neurologically intact age-matched right-handed subjects were enrolled. Stroke patients were equally subdivided in two groups based on lesion location: cortico-subcortical (CS, mean age ± SD: 72.21 ± 10.97 years; time since stroke ± SD: 31.14 ± 11.73 days) and subcortical (S, mean age ± SD: 68.92 ± 10.001 years; time since stroke ± SD: 26.93 ± 13.08 days) group. We assessed patients’ neurological status by means of National Institutes of Health Stroke Scale (NIHSS). High density EEG at rest was recorded and power spectral analysis in Delta (1–4 Hz) and Alpha (8–14 Hz) bands was performed. qEEG metrics as pairwise derived Brain Symmetry Index (pdBSI) and Delta/Alpha Ratio (DAR) were computed and correlated with NIHSS score. S showed a lower Delta power in the Unaffected Hemisphere (UH) compared to Affected Hemisphere (AH; z = −1.98, p < 0.05) and a higher Alpha power compared to CS (z = −2.18, p < 0.05). pdBSI was negatively correlated with NIHSS (R = −0.59, p < 0.05). CS showed a higher value and symmetrical distribution of Delta band activity (z = −2.37, p < 0.05), confirmed also by a higher DAR value compared to S (z = −2.48, p < 0.05). Patients with cortico-subcortical and subcortical lesions show different brain symmetry in the subacute phase. Interestingly, in subcortical stroke patient brain activity is related with the clinical function. qEEG measures can be explicative of brain activity related to lesion location and they could allow precise definition of diagnostic-therapeutic algorithms in stroke patients.

MEG Frequency Analysis Depicts the Impaired Neurophysiological Condition of Ischemic Brain

PURPOSE

Quantitative imaging of neuromagnetic fields based on automated region of interest (ROI) setting was analyzed to determine the characteristics of cerebral neural activity in ischemic areas.

METHODS

Magnetoencephalography (MEG) was used to evaluate spontaneous neuromagnetic fields in the ischemic areas of 37 patients with unilateral internal carotid artery (ICA) occlusive disease. Voxel-based time-averaged intensity of slow waves was obtained in two frequency bands (0.3-4 Hz and 4-8 Hz) using standardized low-resolution brain electromagnetic tomography (sLORETA) modified for a quantifiable method (sLORETA-qm). ROIs were automatically applied to the anterior cerebral artery (ACA), anterior middle cerebral artery (MCAa), posterior middle cerebral artery (MCAp), and posterior cerebral artery (PCA) using statistical parametric mapping (SPM). Positron emission tomography with 15O-gas inhalation (15O-PET) was also performed to evaluate cerebral blood flow (CBF) and oxygen extraction fraction (OEF). Statistical analyses were performed using laterality index of MEG and 15O-PET in each ROI with respect to distribution and intensity.

RESULTS

MEG revealed statistically significant laterality in affected MCA regions, including 4-8 Hz waves in MCAa, and 0.3-4 Hz and 4-8 Hz waves in MCAp (95% confidence interval: 0.020-0.190, 0.030-0.207, and 0.034-0.213), respectively. We found that 0.3-4 Hz waves in MCAp were highly correlated with CBF in MCAa and MCAp (r = 0.74, r = 0.68, respectively), whereas 4-8 Hz waves were moderately correlated with CBF in both the MCAa and MCAp (r = 0.60, r = 0.63, respectively). We also found that 4-8 Hz waves in MCAp were statistically significant for misery perfusion identified on 15O-PET (p<0.05).

CONCLUSIONS

Quantitatively imaged spontaneous neuromagnetic fields using the automated ROI setting enabled clear depiction of cerebral ischemic areas. Frequency analysis may reveal unique neural activity that is distributed in the impaired vascular metabolic territory, in which the cerebral infarction has not yet been completed.

Neurophysiologic predictors of motor function in stroke

PURPOSE

Understanding the neural mechanisms of stroke recovery is of paramount importance for neurorehabilitation.

METHODS

For this purpose, we analyzed several TMS and EEG variables and their association with motor recovery. Thirty-five subjects with chronic stroke were recruited. The neurophysiological examination included assessments by transcranial magnetic stimulation (TMS), intra- and inter-hemispheric EEG coherence in different frequency bands (e.g. alpha (8-13 Hz)) as determined by quantitative electroencephalography (qEEG). Motor function was measured by Fugl-Meyer (FM). Multiple univariate and multivariate linear regression analyses were performed to identify the predictors for FM.

RESULTS

Multivariate analyses, showed a significant interaction effect of motor threshold (MT) in the lesioned hemisphere and beta coherence in the unlesioned hemisphere. This interaction suggests that higher beta activity in the unlesioned hemisphere strengthens the negative association between MT and FM scores.

CONCLUSIONS

Our results suggest that MT in the lesioned hemisphere is the strongest predictors of motor recovery after stroke. Moreover, cortical activity in the unlesioned hemisphere measured by qEEG provides additional information, specifying the association between MT and FM scores. Therefore, complementary application of EEG and TMS can help constitute a better model of the lesioned and the unlesioned hemispheres that supports the importance of bihemispheric activity in recovery.

Identifying Dysfunctional Cortex: Dissociable Effects of Stroke and Aging on Resting State Dynamics in MEG and fMRI

Spontaneous signals in neuroimaging data may provide information on cortical health in disease and aging, but the relative sensitivity of different approaches is unknown. In the present study, we compared different but complementary indicators of neural dynamics in resting-state MEG and BOLD fMRI, and their relationship with blood flow. Participants included patients with post-stroke aphasia, age-matched controls, and young adults. The complexity of brain activity at rest was quantified in MEG using spectral analysis and multiscale entropy (MSE) measures, whereas BOLD variability was quantified as the standard deviation (SDBOLD), mean squared successive difference (MSSD), and sample entropy of the BOLD time series. We sought to assess the utility of signal variability and complexity measures as markers of age-related changes in healthy adults and perilesional dysfunction in chronic stroke. The results indicate that reduced BOLD variability is a robust finding in aging, whereas MEG measures are more sensitive to the cortical abnormalities associated with stroke. Furthermore, reduced complexity of MEG signals in perilesional tissue were correlated with hypoperfusion as assessed with arterial spin labeling (ASL), while no such relationship was apparent with BOLD variability. These findings suggest that MEG signal complexity offers a sensitive index of neural dysfunction in perilesional tissue in chronic stroke, and that these effects are clearly distinguishable from those associated with healthy aging.

Perturbation of Brain Oscillations after Ischemic Stroke: A Potential Biomarker for Post-Stroke Function and Therapy

Brain waves resonate from the generators of electrical current and propagate across brain regions with oscillation frequencies ranging from 0.05 to 500 Hz. The commonly observed oscillatory waves recorded by an electroencephalogram (EEG) in normal adult humans can be grouped into five main categories according to the frequency and amplitude, namely δ (1-4 Hz, 20-200 μV), θ (4-8 Hz, 10 μV), α (8-12 Hz, 20-200 μV), β (12-30 Hz, 5-10 μV), and γ (30-80 Hz, low amplitude). Emerging evidence from experimental and human studies suggests that groups of function and behavior seem to be specifically associated with the presence of each oscillation band, although the complex relationship between oscillation frequency and function, as well as the interaction between brain oscillations, are far from clear. Changes of brain oscillation patterns have long been implicated in the diseases of the central nervous system including ischemic stroke, in which the reduction of cerebral blood flow as well as the progression of tissue damage have direct spatiotemporal effects on the power of several oscillatory bands and their interactions. This review summarizes the current knowledge in behavior and function associated with each brain oscillation, and also in the specific changes in brain electrical activities that correspond to the molecular events and functional alterations observed after experimental and human stroke. We provide the basis of the generations of brain oscillations and potential cellular and molecular mechanisms underlying stroke-induced perturbation. We will also discuss the implications of using brain oscillation patterns as biomarkers for the prediction of stroke outcome and therapeutic efficacy.

QEEG spectral and coherence assessment of autistic children in three different experimental conditions

We studied autistics by quantitative EEG spectral and coherence analysis during three experimental conditions: basal, watching a cartoon with audio (V–A), and with muted audio band (VwA). Significant reductions were found for the absolute power spectral density (PSD) in the central region for delta and theta, and in the posterior region for sigma and beta bands, lateralized to the right hemisphere. When comparing VwA versus the V–A in the midline regions, we found significant decrements of absolute PSD for delta, theta and alpha, and increments for the beta and gamma bands. In autistics, VwA versus V–A tended to show lower coherence values in the right hemisphere. An impairment of visual and auditory sensory integration in autistics might explain our results.

MEG-based detection and localization of perilesional dysfunction in chronic stroke

Post-stroke impairment is associated not only with structural lesions, but also with dysfunction in surviving perilesional tissue. Previous studies using equivalent current dipole source localization of MEG/EEG signals have demonstrated a preponderance of slow-wave activity localized to perilesional areas. Recent studies have also demonstrated the utility of nonlinear analyses such as multiscale entropy (MSE) for quantifying neuronal dysfunction in a wide range of pathologies. The current study utilized beamformer-based reconstruction of signals in source space to compare spectral and nonlinear measures of electrical activity in perilesional and healthy cortices. Data were collected from chronic stroke patients and healthy controls, both young and elderly. We assessed relative power in the delta (1–4 Hz), theta (4–7 Hz), alpha (8–12 Hz) and beta (15–30 Hz) frequency bands, and also measured the nonlinear complexity of electrical activity using MSE. Perilesional tissue exhibited a general slowing of the power spectrum (increased delta/theta, decreased beta) as well as a reduction in MSE. All measures tested were similarly sensitive to changes in the posterior perilesional regions, but anterior perilesional dysfunction was detected better by MSE and beta power. The findings also suggest that MSE is specifically sensitive to electrophysiological dysfunction in perilesional tissue, while spectral measures were additionally affected by an increase in rolandic beta power with advanced age. Furthermore, perilesional electrophysiological abnormalities in the left hemisphere were correlated with the degree of language task-induced activation in the right hemisphere. Finally, we demonstrate that single subject spectral and nonlinear analyses can identify dysfunctional perilesional regions within individual patients that may be ideal targets for interventions with noninvasive brain stimulation.

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We assessed the spontaneous MEG activity of perilesional tissue in stroke.

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We observed perilesional spectral slowing and reduced signal complexity.

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We demonstrate a method to identify dysfunctional tissue within a single subject.

Identification of acute stroke using quantified brain electrical activity

OBJECTIVES

Acute stroke is a leading cause of brain injury and death and requires rapid and accurate diagnosis. Noncontrast head computed tomography (CT) is the first line for diagnosis in the emergency department (ED). Complicating rapid triage are presenting conditions that clinically mimic stroke. There is an extensive literature reporting clinical utility of brain electrical activity in early diagnosis and management of acute stroke. However, existing technologies do not lend themselves to easily acquired rapid evaluation. This investigation used an independently derived classifier algorithm for the identification of traumatic structural brain injury based on brain electrical activity recorded from a reduced frontal montage to explore the potential clinical utility of such an approach in acute stroke assessment.

METHODS

Adult patients (age 18 to 95 years) presenting with stroke-like and/or altered mental status symptoms were recruited from urban academic EDs as part of a large research study evaluating the clinical utility of quantitative brain electrical activity in acutely brain-injured patients. All patients from the parent study who had confirmed strokes, and a control group of stroke mimics (those with final ED diagnoses of migraine or syncope), were selected for this study. All stroke patients underwent head CT scans. Some patients with negative CTs had further imaging with magnetic resonance imaging (MRI). Ten minutes of electroencephalographic data were acquired on a hand-held device in development, from five frontal electrodes. Data analyses were done offline. A Structural Brain Injury Index (SBII) was derived using an independently developed binary discriminant classification algorithm whose input was specified features of brain electrical activity. The SBII was previously found to have high accuracy in the identification of traumatic brain-injured patients who were found to have brain injury on CT (CT+). This algorithm was applied to patients in this study and used to classify patients as CT+ or not CT+. Performance was assessed using sensitivity, specificity, and negative and positive predictive values (NPV, PPV).

RESULTS

Forty-eight stroke patients (31 ischemic and 17 hemorrhagic) and 135 stroke mimic controls were included. Within the ischemic population, approximately half were CT- but later confirmed for stroke with MRI (CT-/MRI+). Sensitivity to stroke was 91.7%, specificity 50.4% (to stroke mimic), NPV 94.4%, and PPV 39.6%. Eighty percent of the CT-/MRI+ ischemic strokes were correctly identified at the time of the CT- scan.

CONCLUSIONS

Despite a small population and the use of a classifier without the benefit of training on a stroke population, these data suggest that a rapidly acquired, easy-to-use system to assess brain electrical activity at the time of evaluation of acute stroke could be a valuable adjunct to current clinical practice.

The utility of amplitude-integrated EEG and NIRS measurements as indices of hypoxic ischaemia in the newborn pig

OBJECTIVE

The early detection and stratification of potential hypoxic ischaemia (HI) injury in neonates are crucial for reducing the risk of neural disability. This study investigates early changes in brain function caused by acute HI of varying severities in the neonatal pig.

METHODS

Two non-invasive techniques, amplitude-integrated electroencephalogram (aEEG) and near-infrared spectroscopy (NIRS), were used to monitor electrocortical and cerebral haemodynamic function, respectively. The fraction of inspired oxygen (FiO(2)) was varied to produce different HI severities. The sensitivity and HI correlation of these methods were systematically analysed to assess their abilities to both detect injury early and assess HI severity accurately.

RESULTS

The tissue oxygen index measured via NIRS detected acute changes in cerebral oxygenation and was highly sensitive to HI (sensitivity=0.97), whereas aEEG was comparatively insensitive to HI. On the other hand, aEEG measurements correlated well with FiO(2) during the entire HI event as well as the 3-h recovery period (R=0.43-0.61). NIRS measurements did not correlate well with FiO(2).

CONCLUSIONS

Parameters measured via aEEG and NIRS displayed different time profiles during and following the HI event.

SIGNIFICANCE

These results highlight the potential advantage of using aEEG and NIRS in conjunction to monitor neonatal brain function, and provide an objective and rigorous method for the characterisation of cerebral function both during and following HI insults.

Using continuous electroencephalography in the management of delayed cerebral ischemia following subarachnoid hemorrhage

BACKGROUND

Using clinical parameters to identify and monitor treatment response in patients with delayed cerebral ischemia (DCI) following subarachnoid hemorrhage is challenging. We sought to determine whether continuous electroencephalography (CEEG) aids the prediction of the clinical course and response to treatment of DCI.

METHODS

Patients deemed high-risk for DCI based on the modified Fisher scale were prospectively monitored. A novel CEEG parameter measuring relative alpha power and variability in the anterior brain quadrants termed composite alpha index (CAI) was graphically displayed. Predictions of the status of patients for the ensuing day were made by an independent reviewer, first using clinical data then repeated following the addition of CAI trends. These were compared to the actual clinical state. The reviewer was blinded to the presence and treatment of DCI. Patients with DCI were further studied by trending the daily mean alpha power against the modulation of treatment and clinical evolution.

RESULTS

Fifty-nine predictions were made in 12 patients (mean age 54.3 years, range 35-70; nine females) with Hunt-Hess grades ranging I-V. Sensitivity of predicting clinical deterioration with CEEG improved from 40 to 67% and clinical improvement from 8 to 50%. In three patients, CEEG was predictive greater than 24 h prior to clinical change. Tracking the daily mean alpha power accurately identified DCI recurrence and poor responders to first-line therapy at pre-clinical stages.

CONCLUSION

CEEG is a useful non-invasive tool to supplement routine clinical parameters in the prediction of DCI. It can dynamically monitor the response to treatment and might aid pre-clinical management decisions.

Quantitative EEG in ischemic stroke: correlation with functional status after 6 months

OBJECTIVE

Stroke is a major cause of adult-onset disability and dependency. We investigated whether EEG parameters are of prognostic value for functional outcome 6 months after ischemic stroke.

METHODS

One-hundred and ten patients presenting with acute ischemic stroke and persistent neurological deficits at EEG recording were incrementally included. Clinical characteristics, volume of ischemia and EEG parameters were correlated with functional outcome assessed with the modified Rankin Scale (mRS) score. Predictive values for disability, dependency and death were calculated using receiver operating characteristic (ROC) curves and logistic regression modeling.

RESULTS

The EEG pairwise derived Brain Symmetry Index (pdBSI) and (delta+theta)/(alpha+beta) ratio (DTABR) were significantly correlated with the modified Rankin Scale (mRS) score at month 6 (Spearman ρ=0.46 and ρ=0.47, respectively, p<0.0005 for both). NIHSS (OR 1.15, 95% CI 1.04-1.27, p=0.005) and pdBSI (OR 4.07, 95% CI 1.32-12.58, p=0.015) were independently associated with disability 6 months after stroke. Dependency was independently indicated by NIHSS (OR 1.22, 95% CI 1.09-1.37, p<0.0005) and DTABR (OR 2.25, 95% CI 1.16-4.37, p=0.016). Six month mortality was independently indicated by age at stroke onset (OR 1.18, 95% CI 1.05-1.32, p=0.007), NIHSS (OR 1.11, 95% CI 1.03-1.21, p=0.009) and DTABR (OR 2.04, 95% CI 1.08-3.85, p=0.028).

CONCLUSIONS

EEG in the subacute setting of ischemic stroke may be of prognostic value for disability, dependency and death after 6 months.

SIGNIFICANCE

Early prognostication of functional outcome after stroke is relevant to efficient rehabilitation management to enhance recovery and minimize long-term disability.

Persistent vegetative and minimally conscious states

The diagnosis and management of patients with persistent vegetative (PVS) and minimally conscious (MCS) states entail powerful medical, ethical and legal debates. The recent description of the MCS highlights the crucial role of unexpected and well-documented recoveries of cognitive functions. Functional neuroimaging has provided new insights for assessing neuropathology and cerebral activity in these patients, providing information on the presence, degree, and location of any residual brain function in patients with PVS or MCS. We present a review on this topic, emphasizing the clinical and neuroimaging assessment of these states, with some of our recent results in this area. We conclude that the development of rehabilitation techniques for patients with PVS and others suffering long-lasting effects of brain injury is a crucial challenge for actual and future generations of neuroscientists.

Additional value of quantitative EEG in acute anterior circulation syndrome of presumed ischemic origin

OBJECTIVE

The clinical course of acute stroke can be highly variable and for effective management outcome prediction needs to be refined. We investigated whether EEG parameters are of additional diagnostic and prognostic value in the early phase of acute ischemic anterior circulation stroke.

METHODS

Ninety-four patients presenting with acute anterior circulation syndrome (ACS) of presumed ischemic origin were incrementally included. Clinical characteristics were correlated with volume of ischemia and EEG parameters. Predictive values for definite stroke, early neurological deterioration, spontaneous early neurological improvement and death within 1 week after ACS were calculated using ROC curves and logistic regression modelling.

RESULTS

In patients with normal or near normal NIHSS score of 0 or 1, the pairwise derived brain symmetry index (pdBSI) was an independent predictor for definite stroke displaying an overall accuracy of 80%. Early neurological deterioration was independently predicted by pdBSI with a correct classification rate of 95%. In ROC analysis, death was predicted by pdBSI with overall accuracy of 97%. Spontaneous neurological improvement was independently predicted by the delta+theta/alpha+beta - ratio with overall accuracy of 75%. Small-vessel stroke was independently predicted by pdBSI with a correct classification rate of 92%.

CONCLUSIONS

EEG may be of prognostic value for spontaneous neurological improvement, early neurological deterioration and death in the acute setting of acute anterior circulation syndrome of presumed ischemic origin.

SIGNIFICANCE

These findings may have an impact on stroke care.

Quantitative imaging of spontaneous neuromagnetic activity for assessing cerebral ischemia using sLORETA-qm

To image cerebral neural activity in ischemic areas, we proposed a novel technique to analyze spontaneous neuromagnetic fields based on standardized low-resolution brain electromagnetic tomography modified for a quantifiable method (sLORETA-qm). Using a 160-channel whole-head-type magnetoencephalographic system, cerebral magnetic fields were obtained pre- and postoperatively from 5 patients with unilateral internal carotid artery occlusive disease and 16 age-matched healthy volunteers. For quantitative imaging, voxel-based time-averaged intensities of slow waves in 4 frequency bands (0.3-2 Hz, 2-4 Hz, 4-6 Hz and 6-8 Hz) were obtained by the proposed technique based on sLORETA-qm. Positron emission tomography with (15)O gas inhalation ((15)O-PET) was also performed in these patients to evaluate cerebral blood flow and metabolism. In all 5 patients, slow waves in every frequency band were distributed in the area of cerebrovascular insufficiency, as confirmed by (15)O-PET preoperatively. In 4 patients, slow-wave intensities in theta bands (4-6 Hz, 6-8 Hz) decreased postoperatively along with improvements in cerebral blood flow and metabolism, whereas delta bands (0.3-2 Hz, 2-4 Hz) showed no significant differences between pre- and postoperatively. One patient with deterioration of cerebral infarction after surgery showed marked increases in slow-wave intensities in delta bands (0.3-2 Hz, 2-4 Hz) postoperatively, with distribution close to the infarct region. The proposed quantitative imaging of spontaneous neuromagnetic fields enabled clear visualization and alternations of cerebral neural conditions in the ischemic area. This technique may offer a novel, non-invasive method for identifying cerebral ischemia, although further studies in a larger number of patients are warranted.

Recognizing a mother's voice in the persistent vegetative state

We studied an 8-year-old boy after a near-drowning left him in a vegetative state (VS) for 4 years before the study. Findings fulfilled all clinical criteria for the diagnosis of VS. The purpose of this study was to investigate whether there was significant differential activation of the brain in response to hearing his mother's voice compared with the voices of unknown women. The data were assessed using quantitative electric tomography (QEEGt), a technique that combines anatomical information of the brain by MRI with EEG patterns to estimate the sources of the EEG within the brain. We found significant differences for EEG frequencies from 14-58 Hz, with a peak at 33.2 Hz (gamma band). The 3D reconstruction showed that these statistical differences were localized in the lateral and posterior regions of the left hemisphere. No significant differences were found between unknown women vs. basal conditions. These results demonstrate recognition of the mother's voice and indicate high-level residual linguistic processing in a patient meeting clinical criteria for VS. These findings launch new ethical and practical implications for the management of VS patients.

Evaluation and validity of a LORETA normative EEG database

To evaluate the reliability and validity of a Z-score normative EEG database for Low Resolution Electromagnetic Tomography (LORETA), EEG digital samples (2 second intervals sampled 128 Hz, 1 to 2 minutes eyes closed) were acquired from 106 normal subjects, and the cross-spectrum was computed and multiplied by the Key Institute's LORETA 2,394 gray matter pixel T Matrix. After a log10 transform or a Box-Cox transform the mean and standard deviation of the *.lor files were computed for each of the 2394 gray matter pixels, from 1 to 30 Hz, for each of the subjects. Tests of Gaussianity were computed in order to best approximate a normal distribution for each frequency and gray matter pixel. The relative sensitivity of a Z-score database was computed by measuring the approximation to a Gaussian distribution. The validity of the LORETA normative database was evaluated by the degree to which confirmed brain pathologies were localized using the LORETA normative database. Log10 and Box-Cox transforms approximated Gaussian distribution in the range of 95.64% to 99.75% accuracy. The percentage of normative Z-score values at 2 standard deviations ranged from 1.21% to 3.54%, and the percentage of Z-scores at 3 standard deviations ranged from 0% to 0.83%. Left temporal lobe epilepsy, right sensory motor hematoma and a right hemisphere stroke exhibited maximum Z-score deviations in the same locations as the pathologies. We conclude: (1) Adequate approximation to a Gaussian distribution can be achieved using LORETA by using a log10 transform or a Box-Cox transform and parametric statistics, (2) a Z-Score normative database is valid with adequate sensitivity when using LORETA, and (3) the Z-score LORETA normative database also consistently localized known pathologies to the expected Brodmann areas as an hypothesis test based on the surface EEG before computing LORETA.

Parametric vs. non-parametric statistics of low resolution electromagnetic tomography (LORETA)

This study compared the relative statistical sensitivity of non-parametric and parametric statistics of 3-dimensional current sources as estimated by the EEG inverse solution Low Resolution Electromagnetic Tomography (LORETA). One would expect approximately 5% false positives (classification of a normal as abnormal) at the P < .025 level of probability (two tailed test) and approximately 1% false positives at the P < .005 level. EEG digital samples (2 second intervals sampled 128 Hz, 1 to 2 minutes eyes closed) from 43 normal adult subjects were imported into the Key Institute's LORETA program. We then used the Key Institute's cross-spectrum and the Key Institute's LORETA output files (*.lor) as the 2,394 gray matter pixel representation of 3-dimensional currents at different frequencies. The mean and standard deviation *.lor files were computed for each of the 2,394 gray matter pixels for each of the 43 subjects. Tests of Gaussianity and different transforms were computed in order to best approximate a normal distribution for each frequency and gray matter pixel. The relative sensitivity of parametric vs. non-parametric statistics were compared using a "leave-one-out" cross validation method in which individual normal subjects were withdrawn and then statistically classified as being either normal or abnormal based on the remaining subjects. Log10 transforms approximated Gaussian distribution in the range of 95% to 99% accuracy. Parametric Z score tests at P < .05 cross-validation demonstrated an average misclassification rate of approximately 4.25%, and range over the 2,394 gray matter pixels was 27.66% to 0.11%. At P < .01 parametric Z score cross-validation false positives were 0.26% and ranged from 6.65% to 0% false positives. The non-parametric Key Institute's t-max statistic at P < .05 had an average misclassification error rate of 7.64% and ranged from 43.37% to 0.04% false positives. The nonparametric t-max at P < .01 had an average misclassification rate of 6.67% and ranged from 41.34% to 0% false positives of the 2,394 gray matter pixels for any cross-validated normal subject. In conclusion, adequate approximation to Gaussian distribution and high cross-validation can be achieved by the Key Institute's LORETA programs by using a log10 transform and parametric statistics, and parametric normative comparisons had lower false positive rates than the non-parametric tests.