Power spectral density changes in the EEG during mental arithmetic and eye-opening

EEG alpha and theta time-frequency structure during a written mathematical task

Since the first electroencephalogram (EEG) was obtained, there have been many possibilities to use it as a tool to access brain cognitive dynamics. Mathematical (Math) problem solving is one of the most important cortical processes, but it is still far from being well understood. EEG is an inexpensive and simple indirect measure of brain operation, but only recently has low-cost equipment (mobile EEG) allowed sophisticated analyses in non-clinical settings. The main purpose of this work is to study EEG activation during a Math task in a realistic environment, using mobile EEG. A matching pursuit (MP)-based signal analysis technique was employed, since MP properties render it a priori suitable to study induced EEG activity over long time sequences, when it is not tightly locked to a given stimulus. The study sample comprised sixty healthy volunteers. Unlike the majority of previous studies, subjects were studied in a sitting position with their eyes open. They completed a written Math task outside the EEG lab, wearing a mobile EEG device (EPOC+). Theta [4 Hz-7.5 Hz], alpha (7.5 Hz-13 Hz] and 0.5 Hz micro-bands in the [0.5 Hz-20 Hz] range were studied with a low-density stochastic MP dictionary. Over 1-min windows, ongoing EEG alpha and theta activity was decomposed into numerous MP atoms with median duration around 3 s, similar to the duration of induced, time-locked activity obtained with event-related (des)synchronization (ERS/ERD) studies. Relative to Rest, there was lower right-side and posterior MP alpha atom/min during Math, whereas MP theta atom/min was significantly higher on anteriorly located electrodes, especially on the left side. MP alpha findings were particularly significant on a narrow range around 10 Hz-10.5 Hz, consistent with FFT alpha peak findings from ERS/ERD studies. With a streamlined protocol, these results replicate previous findings of EEG alpha and theta activation obtained during Math tasks with different signal analysis techniques and in different time frames. The efficient application to real-world, noisy EEG data with a low-resolution stochastic MP dictionary shows that this technique is very encouraging. These results provide support for studies of mathematical cognition with mobile EEG and matching pursuit.

Cortical activity associated with the maintenance of balance during unstable stances

Background

Humans continuously maintain and adjust posture during gait, standing, and sitting. The difficulty of postural control is reportedly increased during unstable stances, such as unipedal standing and with closed eyes. Although balance is slightly impaired in healthy young adults in such unstable stances, they rarely fall. The brain recognizes the change in sensory inputs and outputs motor commands to the musculoskeletal system. However, such changes in cortical activity associated with the maintenance of balance following periods of instability require further clarified.

Methods

In this study, a total of 15 male participants performed two postural control tasks and the center of pressure displacement and electroencephalogram were simultaneously measured. In addition, the correlation between amplitude of center of pressure displacement and power spectral density of electroencephalogram was analyzed.

Results

The movement of the center of pressure was larger in unipedal standing than in bipedal standing under both eye open and eye closed conditions. It was also larger under the eye closed condition compared with when the eyes were open in unipedal standing. The amplitude of high-frequency bandwidth (1-3 Hz) of the center of pressure displacement was larger during more difficult postural tasks than during easier ones, suggesting that the continuous maintenance of posture was required. The power spectral densities of the theta activity in the frontal area and the gamma activity in the parietal area were higher during more difficult postural tasks than during easier ones across two postural control tasks, and these correlate with the increase in amplitude of high-frequency bandwidth of the center of pressure displacement.

Conclusions

Taken together, specific activation patterns of the neocortex are suggested to be important for the postural maintenance during unstable stances.

Preoperative electroencephalographic alpha-power changes with eyes opening are associated with postoperative attention impairment and inattention-related delirium severity

BACKGROUND

In the eyes-closed, awake condition, EEG oscillatory power in the alpha band (7-13 Hz) dominates human spectral activity. With eyes open, however, EEG alpha power substantially decreases. Less alpha attenuation with eyes opening has been associated with inattention; thus, we analysed whether reduced preoperative alpha attenuation with eyes opening is associated with postoperative inattention, a delirium-defining feature.

METHODS

Preoperative awake 32-channel EEG was recorded with eyes open and eyes closed in 71 non-neurological, noncardiac surgery patients aged ≥ 60 years. Inattention and other delirium features were assessed before surgery and twice daily after surgery until discharge. Eyes-opening EEG alpha-attenuation magnitude was analysed for associations with postoperative inattention, primarily, and with delirium severity, secondarily, using multivariate age- and Mini-Mental Status Examination (MMSE)-adjusted logistic and proportional-odds regression analyses.

RESULTS

Preoperative alpha attenuation with eyes opening was inversely associated with postoperative inattention (odds ratio [OR] 0.73, 95% confidence interval [CI]: 0.57, 0.94; P=0.038). Sensitivity analyses showed an inverse relationship between alpha-attenuation magnitude and inattention chronicity, defined as 'never', 'newly', or 'chronically' inattentive (OR 0.76, 95% CI: 0.62, 0.93; P=0.019). In addition, preoperative alpha-attenuation magnitude was inversely associated with postoperative delirium severity (OR 0.79, 95% CI: 0.65, 0.95; P=0.040), predominantly as a result of the inattention feature.

CONCLUSIONS

Preoperative awake, resting, EEG alpha attenuation with eyes opening might represent a neural biomarker for risk of postoperative attentional impairment. Further, eyes-opening alpha attenuation could provide insight into the neural mechanisms underlying postoperative inattention risk.

Longitudinal characterization of EEG power spectra during eyes open and eyes closed conditions in children

This study is the first to examine spectrum-wide (1 to 250 Hz) differences in electroencephalogram (EEG) power between eyes open (EO) and eyes closed (EC) resting state conditions in 486 children. The results extend the findings of previous studies by characterizing EEG power differences from 30 to 250 Hz between EO and EC across childhood. Developmental changes in EEG power showed spatial and frequency band differences as a function of age and EO/EC condition. A 64-electrode system was used to record EEG at 4, 5, 7, 9, and 11 years of age. Specific findings were: (1) the alpha peak shifts from 8 Hz at 4 years to 9 Hz at 11 years, (2) EC results in increased EEG power (compared to EO) at lower frequencies but decreased EEG power at higher frequencies for all ages, (3) the EEG power difference between EO and EC changes from positive to negative within a narrow frequency band which shifts toward higher frequencies with age, from 9 to 12 Hz at 4 years to 32 Hz at 11 years, (4) at all ages EC is characterized by an increase in lower frequency EEG power most prominently over posterior regions, (5) at all ages, during EC, decreases in EEG power above 30 Hz are mostly over anterior regions of the scalp. This report demonstrates that the simple challenge of opening and closing the eyes offers the potential to provide quantitative biomarkers of phenotypic variation in brain maturation by employing a brief, minimally invasive protocol throughout childhood.

State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses

Background

A common problem in resting-state neuroimaging studies is that subjects become drowsy or fall asleep. Although this could drastically affect neurophysiological measurements, such as magnetoencephalography (MEG), its specific impact remains understudied. We aimed to systematically investigate how often drowsiness is present during resting-state MEG recordings, and how the state changes alter quantitative estimates of oscillatory activity, functional connectivity, and network topology.

Methods

About 8-min MEG recordings of 19 healthy subjects, split into ~13-s epochs, were scored for the presence of eyes-open (EO), alert eyes-closed (A-EC), or drowsy eyes-closed (D-EC) states. After projection to source-space, results of spectral, functional connectivity, and network analyses in 6 canonical frequency bands were compared between these states on a global and regional levels. Functional connectivity was analyzed using the phase lag index (PLI) and corrected amplitude envelope correlation (AECc), and network topology was analyzed using the minimum spanning tree (MST).

Results

Drowsiness was present in >55% of all epochs that did not fulfill the AASM criteria for sleep. There were clear differences in spectral results between the states (A-EC vs. D-EC) and conditions (EO vs. A-EC). The influence of state and condition was far less pronounced for connectivity analyses, with only minimal differences between D-EC and EO in the AECc in the delta band. There were no effects of drowsiness on any of the MST measures.

Conclusions

Drowsiness during eyes-closed resting-state MEG recordings is present in the majority of epochs, despite the instructions to stay awake. This has considerable influence on spectral properties, but much less so on functional connectivity and network topology. These findings are important for interpreting the results of EEG/MEG studies using spectral analyses in neurological disease, where recordings should be evaluated for the presence of drowsiness. For connectivity analyses or studies on network topology, this seems of far less importance.

Distinguishing Voluntarily Upregulation of Localized Central Alpha from Widespread Posterior Alpha

Neurofeedback (NF) training based on alpha upregulation has been widely used on patient and healthy populations. However, active voluntary modulation of central or widespread posterior alpha in response to central alpha feedback is still ambiguous. The objective of this study is to confirm whether patients learn to truly increase alpha power and to determine if patients modulate central or widespread alpha power when alpha feedback is provided from central brain region. This EEG-based NF study was conducted on seven paraplegic patients with same injury type, pain location, and sensitization to ensure homogeneity. In addition to routine NF training sessions, various experiments were performed to compare alpha NF modulation received from C4 with alpha shift during cognitive tasks, occipital or parieto-occipital cortex, and Laplacian montage which is expected to separate localized alpha from widespread alpha, to attain objectives. Moreover, imaginary coherence analysis in alpha band was also performed to check whether C4 training site is coupled with other brain regions and to confirm whether activity at training site leads/lags the activity of other brain regions. The results indicate widespread alpha modulation in patients during regular NF sessions (p < 0.05) with large effect size (> 0.8), sufficiently high statistical power (> 80%), and a narrower confidence interval (CI) in response to NF provided from the central brain region reflecting less uncertainty and higher precision. However, small effect size obtained with Laplacian montage require patients to be trained with Laplacian feedback to achieve a reliable conclusion regarding localized alpha modulation. The outcomes of this study are not only limited to validate true alpha modulation in response to central alpha feedback but also to explore the mechanism of central alpha NF training.

An Analysis of the External Validity of EEG Spectral Power in an Uncontrolled Outdoor Environment during Default and Complex Neurocognitive States

Traditionally, quantitative electroencephalography (QEEG) studies collect data within controlled laboratory environments that limit the external validity of scientific conclusions. To probe these validity limits, we used a mobile EEG system to record electrophysiological signals from human participants while they were located within a controlled laboratory environment and an uncontrolled outdoor environment exhibiting several moderate background influences. Participants performed two tasks during these recordings, one engaging brain activity related to several complex cognitive functions (number sense, attention, memory, executive function) and the other engaging two default brain states. We computed EEG spectral power over three frequency bands (theta: 4-7 Hz, alpha: 8-13 Hz, low beta: 14-20 Hz) where EEG oscillatory activity is known to correlate with the neurocognitive states engaged by these tasks. Null hypothesis significance testing yielded significant EEG power effects typical of the neurocognitive states engaged by each task, but only a beta-band power difference between the two background recording environments during the default brain state. Bayesian analysis showed that the remaining environment null effects were unlikely to reflect measurement insensitivities. This overall pattern of results supports the external validity of laboratory EEG power findings for complex and default neurocognitive states engaged within moderately uncontrolled environments.

Normative values for SedLine-based processed electroencephalography parameters in awake volunteers: a prospective observational study

Processed electroencephalography (pEEG) is used to monitor depth of anaesthesia and/or sedation. A novel device (SedLine®) has been recently introduced into clinical practice. However, there are no published data on baseline SedLine values for awake adult subjects. We aimed to determine baseline values for SedLine-derived parameters in eyes-open and eyes-closed states. We performed a prospective observational study in healthy volunteers. SedLine EEG-derived parameters were recorded for 2 min with eyes closed and 8 min with eyes open. We determined the overall reference range for each value, as well as the reference range in each phase. We investigated changes in recorded parameters between the two phases, and the interaction between EMG, baseline characteristics, and Patient State Index (PSI). We collected data from 50 healthy volunteers, aged 23-63 years. Median PSI was 94 (92-95) with eyes open and 88 (87-91) with eyes closed (p < 0.001 for open versus close). EMG activity decreased from 47.2% (46.6-47.9) with eyes open to 28.6% (28.0-29.3) with eyes closing (p < 0.001). There was a significant positive correlation between EMG and PSI with eyes closed (p = 0.01) but not with eyes open, which was confirmed with linear regression analysis (p = 0.01). In awake volunteers, keeping eyes open induces significant changes to SedLine-derived parameters, most likely due to increased EMG activity (e.g. eye blinking). These findings have implications for the clinical interpretation of PSI parameters and for the planning of future research.

Continuous decoding of cognitive load from electroencephalography reveals task-general and task-specific correlates

OBJECTIVE

Algorithms to detect changes in cognitive load using non-invasive biosensors (e.g. electroencephalography (EEG)) have the potential to improve human-computer interactions by adapting systems to an individual's current information processing capacity, which may enhance performance and mitigate costly errors. However, for algorithms to provide maximal utility, they must be able to detect load across a variety of tasks and contexts. The current study aimed to build models that capture task-general EEG correlates of cognitive load, which would allow for load detection across variable task contexts.

APPROACH

Sliding-window support vector machines (SVM) were trained to predict periods of high versus low cognitive load across three cognitively and perceptually distinct tasks: n-back, mental arithmetic, and multi-object tracking. To determine how well these SVMs could generalize to novel tasks, they were trained on data from two of the three tasks and evaluated on the held-out task. Additionally, to better understand task-general and task-specific correlates of cognitive load, a set of models were trained on subsets of EEG frequency features.

MAIN RESULTS

Models achieved reliable performance in classifying periods of high versus low cognitive load both within and across tasks, demonstrating their generalizability. Furthermore, continuous model outputs correlated with subtle differences in self-reported mental effort and they captured predicted changes in load within individual trials of each task. Additionally, alpha or beta frequency features achieved reliable within- and cross-task performance, suggesting that activity in these frequency bands capture task-general signatures of cognitive load. In contrast, delta and theta frequency features performed considerably worse than the full cross-task models, suggesting that delta and theta activity may be reflective of task-specific differences across cognitive load conditions.

SIGNIFICANCE

EEG data contains task-general signatures of cognitive load. Sliding-window SVMs can capture these signatures and continuously detect load across multiple task contexts.

From eyes-closed to eyes-open: Role of cholinergic projections in EC-to-EO alpha reactivity revealed by combining EEG and MRI

Alpha rhythm (8 to 12 Hz) observed in EEG over human posterior cortex is prominent during eyes-closed (EC) resting and attenuates during eyes-open (EO) resting. Research shows that the degree of EC-to-EO alpha blocking or alpha desynchronization, termed alpha reactivity here, is a neural marker of cognitive health. We tested the role of acetylcholine in EC-to-EO alpha reactivity by applying a multimodal neuroimaging approach to a cohort of young adults and a cohort of older adults. In the young cohort, simultaneous EEG-fMRI was recorded from twenty-one young adults during both EO and EC resting. In the older cohort, functional MRI was recorded from forty older adults during EO and EC resting, along with FLAIR and diffusion MRI. For a subset of twenty older adults, EEG was recorded during EO and EC resting in a separate session. In both young and older adults, functional connectivity between the basal nucleus of Meynert (BNM), the major source of cortical acetylcholine, and the visual cortex increased from EC to EO, and this connectivity increase was positively associated with alpha reactivity; namely, the stronger the BNM-visual cortex functional connectivity increase from EC to EO, the larger the EC-to-EO alpha desynchronization. In older adults, lesions of the fiber tracts linking BNM and visual cortex quantified by leukoaraiosis volume, associated with reduced alpha reactivity. These findings support a role of acetylcholine and particularly cholinergic pathways in mediating EC-to-EO alpha reactivity and suggest that impaired alpha reactivity could serve as a marker of the integrity of the cholinergic system.

Electrophysiological activity is associated with vulnerability of Internet addiction in non-clinical population

This study investigated the electrophysiological activity associated with vulnerability of problematic Internet use in non-clinical population. The resting EEG spectrum of alpha (8-13 Hz) rhythm was measured in 22 healthy subjects who have used the Internet for recreational purpose. The vulnerability of Internet addiction was assessed using Young's Internet Addiction Test (IAT) and Assessment for Computer and Internet Addiction-Screener (AICA-S) respectively. Depression and impulsivity were also measured with Beck Depression Inventory (BDI) and Barratt Impulsiveness Scale 11(BIS-11) respectively. The IAT was positively correlated with alpha power obtained during eyes closed (EC, r = 0.50, p = 0.02) but not during eyes open (EO). This was further supported by a negative correlation (r = -0.48, p = 0.02) between IAT scores and alpha desynchronization (EO-EC). These relationships remained significant following correction for multiple comparisons. Furthermore, The BDI score showed positive correlation with alpha asymmetry at mid-lateral (r = 0.54, p = 0.01) and mid-frontal (r = 0.46, p = 0.03) regions during EC, and at mid-frontal (r = 0.53, p = 0.01) region during EO. The current findings suggest that there are associations between neural activity and the vulnerability of problematic Internet use. Understanding of the neurobiological mechanisms underlying problematic Internet use would contribute to improved early intervention and treatment.

Symbolic time series analysis of electroencephalographic (EEG) epileptic seizure and brain dynamics with eye-open and eye-closed subjects during resting states

Objective

Epilepsy is a neuronal disorder for which the electrical discharge in the brain is synchronized, abnormal and excessive. To detect the epileptic seizures and to analyse brain activities during different mental states, various methods in non-linear dynamics have been proposed. This study is an attempt to quantify the complexity of control and epileptic subject with and without seizure as well as to distinguish eye-open (EO) and eye-closed (EC) conditions using threshold-based symbolic entropy.

Methods

The threshold-dependent symbolic entropy was applied to distinguish the healthy and epileptic subjects with seizure and seizure-free intervals (i.e. interictal and ictal) as well as to distinguish EO and EC conditions. The original time series data was converted into symbol sequences using quantization level, and word series of symbol sequences was generated using a word length of three or more. Then, normalized corrected Shannon entropy (NCSE) was computed to quantify the complexity. The NCSE values were not following the normal distribution, and the non-parametric Mann–Whitney–Wilcoxon (MWW) test was used to find significant differences among various groups at 0.05 significance level. The values of NCSE were presented in a form of topographic maps to show significant brain regions during EC and EO conditions. The results of the study were compared to those of the multiscale entropy (MSE).

Results

The results indicated that the dynamics of healthy subjects are more complex compared to epileptic subjects (during seizure and seizure-free intervals) in both EO and EC conditions. The comparison of the dynamics of epileptic subjects revealed that seizure-free intervals are more complex than seizure intervals. The dynamics of healthy subjects during EO conditions are more complex compared to those during EC conditions. Further, the results clearly demonstrated that threshold-dependent symbolic entropy outperform MSE in distinguishing different physiological and pathological conditions.

Conclusion

The threshold symbolic entropy has provided improved accuracy in quantifying the dynamics of healthy and epileptic subjects during EC an EO conditions for each electrode compared to the MSE.

Eye closure causes widespread low-frequency power increase and focal gamma attenuation in the human electrocorticogram

OBJECTIVE

We sought to characterize the effects of eye closure on EEG power using electrocorticography (ECoG). Specifically, we sought to elucidate the anatomical areas demonstrating an eye closure effect, and at which frequencies this effect occurs.

METHODS

ECoG was recorded from 32 patients undergoing invasive monitoring for seizure focus localization. Patients were instructed to close and open their eyes repeatedly. ECoG power was compared in the epochs following eye closure and opening, for various frequency bands and brain regions.

RESULTS

We found that at low frequencies, eye closure causes widespread power increases involving all lobes of the brain. This effect was significant not only in the α (8-12 Hz) band but in the δ (2-4 Hz), θ (4-8 Hz), and β (15-30 Hz) bands as well. At high frequencies, eye closure causes comparatively focal power decreases over occipital cortex and frontal Brodmann areas 8 and 9.

CONCLUSIONS

Eye closure (1) affects a broad range of frequencies outside the α band and (2) involves a distributed network of neural activity in anatomical areas outside visual cortex.

SIGNIFICANCE

This study constitutes the first large-scale, systematic application of ECoG to study eye closure, which is shown to influence a broad range of frequencies and brain regions.

Reactivity of alpha rhythms to eyes opening is lower in athletes than non-athletes: a high-resolution EEG study

In the present study, we tested the hypothesis that compared with non-athletes, elite athletes are characterized by a reduction of reactivity of electroencephalographic (EEG) alpha rhythms (about 8-12 Hz) to eyes opening in the condition of resting state, as a possible index of spatially selective cortical activation (i.e. "neural efficiency"). EEG data (56 channels; Eb-Neuro©) were recorded in 18 elite karate athletes and 28 non-athletes during resting state eyes-closed and eyes-open conditions. The EEG data were spatially enhanced by surface Laplacian estimation. Cortical activity was indexed by task-related power decrease (TRPD), namely the alpha power during the eyes-open referenced to the eyes-closed resting condition. Low-frequency alpha TRPD (about 8-10 Hz) was lower in the elite karate athletes than in the non-athletes in frontal (p<0.00002), central (p<0.008) and right occipital (p<0.02) areas. Similarly, high-frequency alpha TRPD (about 10-12 Hz) was lower in the elite karate athletes than in the non-athletes in frontal (p<0.00009) and central (p<0.01) areas. These results suggest that athletes' brain is characterized by reduced cortical reactivity to eyes opening in the condition of resting state, in line with the "neural efficiency" hypothesis. The present study motivates future research evaluating the extent to which this general functional brain feature is related to heritable trait or intensive visuo-motor training of elite athletes.

EEG differences in children between eyes-closed and eyes-open resting conditions

OBJECTIVE

Recent work on arousal vs. activation in adults showed that skin conductance levels (SCLs) increased, and global alpha levels decreased, from eyes-closed to eyes-open resting baseline conditions. This study explored whether similar effects occur in children.

METHODS

EEG activity was recorded from 30 children aged 8-12 years during counterbalanced eyes-closed and eyes-open resting conditions; SCL was measured as an index of arousal.

RESULTS

SCLs were negatively correlated with mean alpha levels in the eyes-closed condition, and increased significantly from eyes-closed to eyes-open. Reductions were found in across-scalp mean absolute delta, theta, alpha, and beta from eyes-closed to eyes-open. Topographic changes were evident in all bands except alpha.

CONCLUSIONS

Results confirm the use of mean alpha level as a measure of resting-state arousal under eyes-closed and eyes-open conditions. Focal changes in the other bands suggest that these reflect differences in activation, rather than the simple increase in arousal shown in alpha.

SIGNIFICANCE

This child study confirms the generality of eyes-closed vs. eyes-open non-alpha EEG measures differing in mean power levels and topography, the latter indicating brain activity related to visual processing. Such differences should be considered when evaluating EEG research, and in choosing baseline conditions for different paradigms.

EEG differences between eyes-closed and eyes-open resting conditions

OBJECTIVE

Recent work has attempted to clarify the energetics of physiological responding and behaviour by refining and separating the operational definitions of "arousal" and "activation", which have different effects on physiological responding and behaviour. At the EEG level, we relate the former to widespread activity, and the latter to task-specific topographically-focussed activity reflecting regional processing. This study aimed to investigate this further in terms of differences in EEG activity between eyes-closed and eyes-open resting conditions.

METHODS

EEG activity was recorded from 28 university students during both eyes-closed and eyes-open resting conditions, Fourier transformed to provide estimates for absolute power in the delta, theta, alpha and beta bands, and analysed in 9 regions across the scalp. Skin conductance level was also measured as an indicator of arousal level.

RESULTS

Across the eyes-closed conditions, skin conductance levels were negatively correlated with mean alpha levels. Skin conductance levels increased significantly from eyes-closed to eyes-open conditions. Reductions were found in across-scalp mean absolute delta, theta, alpha and beta from the eyes-closed to eyes-open condition. Topographic changes were also evident in all bands except for alpha, with reduced lateral frontal delta and posterior theta, and decreased posterior/increased frontal beta in the eyes-open condition. In particular, the topographic beta effects indicate that the across-scalp reduction arose from focal reductions rather than global changes.

CONCLUSIONS

The obtained results confirm the use of mean alpha level as a measure of resting-state arousal under eyes-closed and eyes-open conditions. The focal nature of EEG effects in the other bands suggests that these reflect cortical processing of visual input, producing differences in activation between eyes-closed and eyes-open resting conditions, rather than just the simple increase in arousal level shown in alpha.

SIGNIFICANCE

This study demonstrates that the eyes-closed and eyes-open conditions provide EEG measures differing in topography as well as power levels. These differences should be recognised when evaluating EEG research, and considered when choosing eyes-open or eyes-closed baseline conditions for different paradigms.

Defective alpha reactivity with mental concentration

We have studied 120 patients with EEGs that show defective reactivity of alpha activity in which one side fails to attenuate during the performance of mental arithmetic. The side of defective reactivity was the right side in 74 patients and the left in 46. A similar asymmetric reactivity of alpha activity to eye opening (Bancaud phenomenon) was seen in 32 patients. Also, 113 patients had lateralized EEG abnormalities on the side of defective reactivity and on the side in which cerebral lesions or disorders of cerebral function were present. The unilateral failure of alpha attenuation with mental concentration represents a subtle lateralized electrographic manifestation of cerebral dysfunction on the side of defective reactivity.

Motor and cognitive interactions during lateralized cerebral functions in children: an EEG study

Power spectra of hemispheric EEG asymmetries were recorded in children performing cognitive tasks requiring motor output. Verbal and spatial cognitive tasks were administered and subjects performed tasks with either right or left hand. The average power in the alpha band was computed. Significant changes in right/left ratios were obtained when the task changed from verbal to spatial. A major predictor of which hemisphere was most activated, however, was the hand involved in solving the task. It appears that attention must be directed to both the cognitive and motor components when investigating asymmetries of cerebral hemisphere function.