Electroencephalographic imaging of higher brain function

Changes of EEG beta band power and functional connectivity during spaceflight: a retrospective study

Spaceflight exposes astronauts to unique conditions like microgravity, which may affect brain function, though it remains underexplored compared to other physiological systems. Astronauts often report temporary neurological symptoms, such as disorientation, visual disturbances, and motor issues, potentially linked to structural and electrophysiological brain changes. To investigate this, electroencephalography (EEG) is a reliable tool to study brain activity in space, measuring oscillatory activity and functional connectivity (FC). This study analyzed EEG data from five male astronauts during three stages: pre-flight, during low Earth orbit (LEO), and post-flight in a 2-min task-free eyes-closed (EC) condition followed by another 2-min of eyes-open (EO) condition. The focus was on beta band (12-30 Hz) activity, which is associated with motor control and proprioception. Results showed increased beta power during spaceflight when compared to pre-flight (EC: p < 0.01) and post-flight (EC: p < 0.01; EO: p < 0.05) conditions. FC strength also increased during spaceflight when compared to pre-flight (EO: p < 0.05) and post-flight (EC: p < 0.01; EO: p < 0.01) conditions. These differences were found primarily in the sensorimotor cortex (SMC) and frontotemporal regions, suggesting the brain's adaptation to altered vestibular and proprioceptive inputs during microgravity. As these results reflect astronaut's movement adaptation to microgravity, this study highlights the importance of understanding central nervous system (CNS) changes during spaceflights to ensure optimal performance and protect astronaut's health during long-duration missions.

The effects of neurofeedback training on behavior and brain functional networks in children with autism spectrum disorder

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with an unclear pathogenesis to date. Neurofeedback (NFB) had shown therapeutic effects in patients with ASD. In this study,we analyzed the brain functional networks of children with ASD and investigated the impact of NFB targeting the beta rhythm training on these networks. The Autism Behavior Checklist (ABC) and Social Response Scale (SRS) were employed to evaluate the effects of NFB training on the behavioral abilities of children with ASD. We compared the differences in static and dynamic brain functional networks between ASD and Typically Developing (TD) children, also explored the changes in these networks in ASD children after 20 sessions of NFB training. The Weighted Phase Lag Index (wPLI) was used to construct static functional networks, and the Fuzzy Entropy (FuzzyEn) algorithm was further employed to measure the complexity of static functional connectivity and construct dynamic functional networks. This allowed the analysis of functional connectivity and fluctuations in the static functional networks of ASD and TD children, as well as the time variability of the dynamic functional networks. Additionally, the study explored the changes in brain functional networks and behavioral scales before and after NFB training. Results from behavioral scales indicated significant improvements in cognitive, communication, language, and social scores in ASD children following NFB intervention. EEG analysis revealed that static functional connectivity was lower, connectivity variability was higher, and temporal variability was greater in ASD children compared to TD children. Following NFB training, increased functional connectivity, reduced connectivity variability in the Delta frequency band, and decreased temporal variability were observed in ASD children. The results revealed abnormalities in both static and dynamic functional networks in children with ASD, with NFB training showed potential to modulate these networks. While our results showed that NFB training can assist participants in regulating connectivity and temporal variability in specific brain regions, robust evidence for its effectiveness in alleviating core symptoms of ASD remained limited.

Differentiating hand gestures from forearm muscle activity using machine learning

This study explored the use of forearm electromyography data to distinguish eight hand gestures. The neural network (NN) and random forest (RF) algorithms were tested on data from 10 participants. As window sizes increase from 200 ms to 1000 ms, the algorithm accuracies increased with RF from 85% to 97% due to the increased temporal resolution. It was also noticed that the RF performed better with an accuracy of 85% than the NN with accuracy 80% when the temporal resolution was smaller, indicating the RF will be efficient when quick-response time is important. As the window size increases, the NN showed higher performance, suggesting that NN will be useful when higher accuracy is required. Future studies should increase the sample size, include more hand gestures, use different feature extraction methods and test different algorithms to improve the accuracy and efficiency of the system.

Neurophysiological evidence for the overview effect: a virtual reality journey into space

The Overview Effect is a complex experience reported by astronauts after viewing Earth from space. Numerous accounts suggest that it leads to increased interconnectedness to other human beings and environmental awareness, comparable to self-transcendence. It can cause fundamental changes in mental models of the world, improved well-being, and stronger appreciation of, and responsibility for Earth. From a cognitive perspective, it is closely linked to the emotion of awe, possibly triggered by the overwhelming perceived vastness of the universe. Given that most research in the domain focuses on self-reports, little is known about potential neurophysiological markers of the Overview Effect. In the experiment reported here, participants viewed an immersive Virtual Reality simulation of a space journey while their brain activity was recorded using electroencephalography (EEG). Post-experimental self-reports confirmed they were able to experience the Overview Effect in the simulated environment. EEG recordings revealed lower spectral power in beta and gamma frequency bands during the defining moments of the Overview Effect. The decrease in spectral power can be associated with reduced mental processing, and a disruption of known mental structures in this context, thereby providing more evidence for the cognitive effects of the experience.

A Systematic Review over the Effect of Early Infant Diet on Neurodevelopment: Insights from Neuroimaging

The optimization of infant neuronal development through nutrition is an increasingly studied area. While human milk consumption during infancy is thought to give a slight cognitive advantage throughout early childhood in comparison to commercial formula, the biological underpinnings of this process are less well-known and debated in the literature. This systematic review seeks to quantitatively analyze whether early diet affects infant neurodevelopment as measured by various neuroimaging modalities and techniques. Results presented suggest that human milk does have a slight positive impact on the structural development of the infant brain-and that this impact is larger in preterm infants. Other diets with distinct macronutrient compositions were also considered, although these had more conflicting results.

Adiposity and insulin resistance moderate the links between neuroelectrophysiology and working and episodic memory functions in young adult males but not females

INTRODUCTION

Obesity and insulin resistance negatively influence neural activity and cognitive function, but electrophysiological mechanisms underlying these interrelationships remain unclear. This study investigated whether adiposity and insulin resistance moderated neural activity and underlying cognitive functions in young adults.

METHODS

Real-time electroencephalography (EEG) was recorded in 38 lean (n = 12) and obese (n = 26) young adults with (n = 15) and without (n = 23) insulin resistance (18-38 years, 55.3% female) as participants completed three neurocognitive tasks in working memory (Operation Span), inhibitory control (Stroop), and episodic memory (Visual Association Test). Body fat percentage was quantified by a dual-energy X-ray absorptiometry scan (DEXA/DXA). Fasting serum insulin and glucose were quantified to calculate Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) values, for which a higher value indicates more insulin resistance. Hierarchical moderated regression analysis tested these interrelationships.

RESULTS

In males, greater frontal negative slow wave (fNSW) and positive slow wave (PSW) amplitudes were linked to higher working memory accuracy in participants with low, but not high, body fat percentage and HOMA-IR levels. In contrast, body fat percentage and HOMA-IR did not moderate these associations in females. Furthermore, body fat percentage and HOMA-IR values moderated the relationship between greater fNSW amplitudes and better episodic memory accuracy in males, but not females. Finally, body fat percentage and insulin resistance did not moderate the link between neural activity and inhibitory control for either sex.

CONCLUSION

Young adult males, but not females, with higher body adiposity and insulin resistance showed reduced neural activity and worse underlying working and episodic memory functions.

Consumer-Grade Electroencephalogram and Functional Near-Infrared Spectroscopy Neurofeedback Technologies for Mental Health and Wellbeing

Neurofeedback, utilizing an electroencephalogram (EEG) and/or a functional near-infrared spectroscopy (fNIRS) device, is a real-time measurement of brain activity directed toward controlling and optimizing brain function. This treatment has often been attributed to improvements in disorders such as ADHD, anxiety, depression, and epilepsy, among others. While there is evidence suggesting the efficacy of neurofeedback devices, the research is still inconclusive. The applicability of the measurements and parameters of consumer neurofeedback wearable devices has improved, but the literature on measurement techniques lacks rigorously controlled trials. This paper presents a survey and literary review of consumer neurofeedback devices and the direction toward clinical applications and diagnoses. Relevant devices are highlighted and compared for treatment parameters, structural composition, available software, and clinical appeal. Finally, a conclusion on future applications of these systems is discussed through the comparison of their advantages and drawbacks.

Transformers for autonomous recognition of psychiatric dysfunction via raw and imbalanced EEG signals

Early identification of mental disorders, based on subjective interviews, is extremely challenging in the clinical setting. There is a growing interest in developing automated screening tools for potential mental health problems based on biological markers. Here, we demonstrate the feasibility of an AI-powered diagnosis of different mental disorders using EEG data. Specifically, this work aims to classify different mental disorders in the following ecological context accurately: (1) using raw EEG data, (2) collected during rest, (3) during both eye open, and eye closed conditions, (4) at short 2-min duration, (5) on participants with different psychiatric conditions, (6) with some overlapping symptoms, and (7) with strongly imbalanced classes. To tackle this challenge, we designed and optimized a transformer-based architecture, where class imbalance is addressed through focal loss and class weight balancing. Using the recently released TDBRAIN dataset (n= 1274 participants), our method classifies each participant as either a neurotypical or suffering from major depressive disorder (MDD), attention deficit hyperactivity disorder (ADHD), subjective memory complaints (SMC), or obsessive-compulsive disorder (OCD). We evaluate the performance of the proposed architecture on both the window-level and the patient-level. The classification of the 2-min raw EEG data into five classes achieved a window-level accuracy of 63.2% and 65.8% for open and closed eye conditions, respectively. When the classification is limited to three main classes (MDD, ADHD, SMC), window level accuracy improved to 75.1% and 69.9% for eye open and eye closed conditions, respectively. Our work paves the way for developing novel AI-based methods for accurately diagnosing mental disorders using raw resting-state EEG data.

Neural dynamics underlying the processing of implicit form-meaning connections: The dissociative roles of theta and alpha oscillations

Implicit learning plays an important role in the language acquisition. In addition to helping people acquire the form-level rules (e.g., the word order regularities), implicit learning can also facilitate the acquisition of word meanings (i.e., the establishment of connections between the word form and its meanings). Although some behavioral studies have explored the processing of implicit form-meaning connections, the neural dynamics underlying this processing remains unclear. Through examining whether participants could implicitly acquire the literal and metaphorical meanings of novel words, and applying the time-frequency analysis on the electroencephalogram (EEG) data collected in the testing phase, the neural oscillations corresponding to the processing of implicit form-literal and form-metaphorical meaning connections were explored. The results showed that participants in the experimental group could implicitly acquire the form-literal and form-metaphorical meaning connections after training, while participants in the control group who were not trained did not have access to such form-meaning connections. Meanwhile, during the processing of form-literal meaning connections, the greater suppression of alpha oscillations was induced by the testing items that follow the same rules as the training items (i.e., the regular testing items) in the experimental group, whereas the stronger enhancement of theta oscillations was elicited by the regular testing items in the experimental group during the processing of form-metaphorical meaning connections. Our study provides insights for understanding the processing of implicit form-literal and form-metaphorical meaning connections and the neural dynamics underlying the processing.

Graph approaches for analysis of brain connectivity during dexmedetomidine sedation

Sedation is commonly used to relieve fear and anxiety during procedures. Dexmedetomidine (DEX), approved by the US Food and Drug Administration in 1999 for short-term sedation, is a selective alpha2-adrenoreceptor agonist. The use of DEX is increasing due to minimal respiratory depression and easy and quick awakening from sedation. Its sedative mechanisms are suggested to be related to changes in the interaction between brain regions. In this study, we used graph theory to investigate whether the altered network connection is associated with sedation. Electroencephalogram (EEG) recordings of 32 channels were acquired during awake and DEX-induced sedation for 20 participants. We extracted EEG epochs from the awake and the DEX sedation state. Using the graph theory, we compared the changes in the network connection parameters with the awake state. We observed that the slopes in 1/f dynamics, which indicate overall brain network characteristics, were greater during DEX-induced sedation compared to the awake state, suggesting a transition towards a random network behavior. In addition, network connections from the perspective of information processing were significantly disturbed in the alpha frequency band, unlike other frequency bands augmenting network connections. The alpha frequency band plays a prominent role in the function and interaction of cognitive activities. These results collectively indicate that changes in the brain network critical to cognition during DEX administration may also be related to the mechanism of sedation.

Remotely Powered Two-Wire Cooperative Sensors for Biopotential Imaging Wearables

Biopotential imaging (e.g., ECGi, EEGi, EMGi) processes multiple potential signals, each requiring an electrode applied to the body's skin. Conventional approaches based on individual wiring of each electrode are not suitable for wearable systems. Cooperative sensors solve the wiring problem since they consist of active (dry) electrodes connected by a two-wire parallel bus that can be implemented, for example, as a textile spacer with both sides made conductive. As a result, the cumbersome wiring of the classical star arrangement is replaced by a seamless solution. Previous work has shown that potential reference, current return, synchronization, and data transfer functions can all be implemented on a two-wire parallel bus while keeping the noise of the measured biopotentials within the limits specified by medical standards. We present the addition of the power supply function to the two-wire bus. Two approaches are discussed. One of them has been implemented with commercially available components and the other with an ASIC. Initial experimental results show that both approaches are feasible, but the ASIC approach better addresses medical safety concerns and offers other advantages, such as lower power consumption, more sensors on the two-wire bus, and smaller size.

Cognitive Neuroscience Methods in Enhancing Health Literacy

The aim of the article is to identify the usefulness of cognitive neuroscience methods in assessing the effectiveness of social advertising and constructing messages referring to the generally understood health promotion, which is to contribute to the development of health awareness, and hence to health literacy. The presented research has also proven useful in the field of managing the processes that improve the communication between the organization and its environment. The researchers experimentally applied cognitive neuroscience methods, mainly EEG measurements, including a metric which is one of the most frequently used to measure the reception of advertising messages, i.e., frontal asymmetry. The purpose of the study was to test cognitive responses as expressed by neural indices (memorization, interest) to the reception of an advertisement for the construction of a hospice for adults. For comparative purposes, a questionnaire survey was also conducted. The research findings have confirmed that there are significant differences in remembering the advertisement in question by different groups of recipients (women/men). They also indicate a different level of interest in the advertisement, which may result from different preferences of the recipients concerning the nature of ads. The obtained results contribute to a better understanding of how to design advertising messages concerning health, so that they increase the awareness of the recipients’ responsibility for their own health and induce specific behavior patterns aimed at supporting health-related initiatives, e.g., donating funds for building hospices or performing preventive tests. In this respect, the study findings help improve the organizations’ communication with their environment, thus enhancing their performance. The study has also confirmed the potential and innovativeness of cognitive neuroscience methods as well as their considerable possibilities for application in this field.

Brain Networks Communicate Through Theta Oscillations to Encode High Load in a Visuospatial Working Memory Task: An EEG Connectivity Study

The encoding of visuospatial information is the foremost and indispensable step which determines the outcome in a visuospatial working memory (VSWM) task. It is considered to play a crucial role in limiting our ability to attend and process only 3-5 integrated items of information. Despite its importance in determining VSWM performance, the neural mechanisms underlying VSWM encoding have not been clearly differentiated from those involved during VSWM retention, manipulation and/or retrieval. The high temporal resolution of electroencephalography (EEG) and improved spatial resolution with dense array data acquisition makes it an ideal tool to study the dynamics in the functional brain connectivity during a cognitive task. In the present study, the changes in the functional brain connectivity due to memory load during VSWM encoding were studied using 128-channel EEG. Lagged linear coherence (LagR) was computed between 84 regions of interest (ROIs) defined according to the Brodmann areas for seven EEG frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-45 Hz). Interestingly, out of seven EEG frequency bands investigated in the current study, LagR of only theta band varied significantly in 13 brain connections due to memory load during VSWM encoding. LagR of theta band increased significantly at high memory load when compared to low memory load in twelve brain connections with the maximum change observed between right cuneus and right middle temporal gyrus (Cohen's d = 0.836), indicating the integration of brain processes to confront the increase in memory demands. Theta LagR decreased significantly between left postcentral gyrus and right precentral gyrus at high memory load as compared to low memory load, which might have a role for sustaining attention during encoding. Change in the LagR values due to memory load between fusiform gyrus and lingual gyrus in the right hemisphere had a positive correlation (r = 0.464, p = 0.003) with the error rate, signifying the crucial role played by these two regions in predicting the performance. The current study has not only identified the neural connections that are responsible for the formation of working memory traces during VSWM encoding, but also support the notion that encoding is a rate-limiting process underlying our memory capacity limit.

Individual EEG measures of attention, memory, and motivation predict population level TV viewership and Twitter engagement

Television (TV) programming attracts ever-growing audiences and dominates the cultural zeitgeist. Viewership and social media engagement have become standard indices of programming success. However, accurately predicting individual episode success or future show performance using traditional metrics remains a challenge. Here we examine whether TV viewership and Twitter activity can be predicted using electroencephalography (EEG) measures, which are less affected by reporting biases and which are commonly associated with different cognitive processes. 331 participants watched an hour-long episode from one of nine prime-time shows (~36 participants per episode). Three frequency-based measures were extracted: fronto-central alpha/beta asymmetry (indexing approach motivation), fronto-central alpha/theta power (indexing attention), and fronto-central theta/gamma power (indexing memory processing). All three EEG measures and the composite EEG score significantly correlated across episode segments with the two behavioral measures of TV viewership and Twitter volume. EEG measures explained more variance than either of the behavioral metrics and mediated the relationship between the two. Attentional focus was integral for both audience retention and Twitter activity, while emotional motivation was specifically linked with social engagement and program segments with high TV viewership. These findings highlight the viability of using EEG measures to predict success of TV programming and identify cognitive processes that contribute to audience engagement with television shows.

Modeling temporal sequences of cognitive state changes based on a combination of EEG-engagement, EEG-workload, and heart rate metrics

The objective of this study was to investigate the feasibility of physiological metrics such as ECG-derived heart rate and EEG-derived cognitive workload and engagement as potential predictors of performance on different training tasks. An unsupervised approach based on self-organizing neural network (NN) was utilized to model cognitive state changes over time. The feature vector comprised EEG-engagement, EEG-workload, and heart rate metrics, all self-normalized to account for individual differences. During the competitive training process, a linear topology was developed where the feature vectors similar to each other activated the same NN nodes. The NN model was trained and auto-validated on combat marksmanship training data from 51 participants that were required to make "deadly force decisions" in challenging combat scenarios. The trained NN model was cross validated using 10-fold cross-validation. It was also validated on a golf study in which additional 22 participants were asked to complete 10 sessions of 10 putts each. Temporal sequences of the activated nodes for both studies followed the same pattern of changes, demonstrating the generalization capabilities of the approach. Most node transition changes were local, but important events typically caused significant changes in the physiological metrics, as evidenced by larger state changes. This was investigated by calculating a transition score as the sum of subsequent state transitions between the activated NN nodes. Correlation analysis demonstrated statistically significant correlations between the transition scores and subjects' performances in both studies. This paper explored the hypothesis that temporal sequences of physiological changes comprise the discriminative patterns for performance prediction. These physiological markers could be utilized in future training improvement systems (e.g., through neurofeedback), and applied across a variety of training environments.

Functional coupling of sensorimotor and associative areas during a catching ball task: a qEEG coherence study

BACKGROUND

Catching an object is a complex movement that involves not only programming but also effective motor coordination. Such behavior is related to the activation and recruitment of cortical regions that participates in the sensorimotor integration process. This study aimed to elucidate the cortical mechanisms involved in anticipatory actions when performing a task of catching an object in free fall.

METHODS

Quantitative electroencephalography (qEEG) was recorded using a 20-channel EEG system in 20 healthy right-handed participants performed the catching ball task. We used the EEG coherence analysis to investigate subdivisions of alpha (8-12 Hz) and beta (12-30 Hz) bands, which are related to cognitive processing and sensory-motor integration.

RESULTS

Notwithstanding, we found the main effects for the factor block; for alpha-1, coherence decreased from the first to sixth block, and the opposite effect occurred for alpha-2 and beta-2, with coherence increasing along the blocks.

CONCLUSION

It was concluded that to perform successfully our task, which involved anticipatory processes (i.e. feedback mechanisms), subjects exhibited a great involvement of sensory-motor and associative areas, possibly due to organization of information to process visuospatial parameters and further catch the falling object.

Theta lingua franca: a common mid-frontal substrate for action monitoring processes

We present evidence that a multitude of mid-frontal event-related potential (ERP) components partially reflect a common theta band oscillatory process. Specifically, mid-frontal ERP components in the N2 time range and error-related negativity time range are parsimoniously characterized as reflections of theta band activities. Forty participants completed three different tasks with varying stimulus-response demands. Permutation tests were used to identify the dominant time-frequency responses of stimulus- and response-locked conditions as well as the enhanced responses to novelty, conflict, punishment, and error. A dominant theta band feature was found in all conditions, and both ERP component amplitudes and theta power measures were similarly modulated by novelty, conflict, punishment, and error. The findings support the hypothesis that generic and reactive medial prefrontal cortex processes are parsimoniously reflected by theta band activities.

EEG in adolescent anorexia nervosa: impact of refeeding and weight gain

OBJECTIVE

To examine resting awake EEG in adolescent AN participants before and after refeeding to determine if EEG abnormalities in Anorexia Nervosa (AN) are reversible.

METHOD

In 37 adolescent first admission AN patients and 45 healthy controls, EEG was recorded during short duration "eyes open" and "eyes closed" awake resting conditions. Repeat testing occurred in 28 AN participants after refeeding and subsequent weight gain.

RESULTS

In "eyes open," underweight AN participants exhibit reduced relative alpha power and increased beta power in frontal brain regions. A significant increase in alpha, and decrease in beta and delta power was observed within participants after refeeding. In "eyes closed", underweight AN participants had elevated theta in parietal-occipital regions which remained after refeeding.

DISCUSSION

EEG abnormalities (reduced alpha/increased beta power) in AN normalizes with refeeding, while increased theta power persists in parietal-occipital regions in an eyes closed context.

Claude Bernard and the heart-brain connection: further elaboration of a model of neurovisceral integration

The intimate connection between the brain and the heart was enunciated by Claude Bernard over 150 years ago. In our neurovisceral integration model we have tried to build on this pioneering work. In the present paper we further elaborate our model. Specifically we review recent neuroanatomical studies that implicate inhibitory GABAergic pathways from the prefrontal cortex to the amygdala and additional inhibitory pathways between the amygdala and the sympathetic and parasympathetic medullary output neurons that modulate heart rate and thus heart rate variability. We propose that the default response to uncertainty is the threat response and may be related to the well known negativity bias. We next review the evidence on the role of vagally mediated heart rate variability (HRV) in the regulation of physiological, affective, and cognitive processes. Low HRV is a risk factor for pathophysiology and psychopathology. Finally we review recent work on the genetics of HRV and suggest that low HRV may be an endophenotype for a broad range of dysfunctions.

Association between BDNF Val66Met polymorphism and trait depression is mediated via resting EEG alpha band activity

A functional polymorphism of the brain-derived neurotrophic factor, BDNF Val66Met, is associated with risk for major depression alongside impairments in memory and selective attention. This study aims to identify the mediating neural mechanisms in links between BDNF and depression using highly heritable electroencephalographic (EEG) recordings. In 305 healthy subjects, BDNF Val66Met genotypes were compared in terms of trait depression, neural function (EEG during a resting state) and cognitive performance. The mediating effects of the EEG brain imaging endophenotypes were also examined using structural equation (path) modeling. A genotype-endophenotype-phenotype path model showed that Met homozygosity predicted elevated working memory commission errors and altered EEG activity; that is elevated relative theta and delta power coupled with reduced alpha power. In turn, reduced EEG alpha activity mediated the relationship between the Met/Met genotype and trait depression. These findings demonstrate the utility of an integrative endophenotype approach. They suggest that the BDNF Met/Met homozygote has a direct impact on memory systems, but impacts trait depression via the secondary effects of neural changes.

[The effects of functional electrical stimulation on cortical interhemispheric asymmetry]

The aim of the present study was to assess the effects of functional electrical stimulation (FES) on cortical interhemispheric asymmetry. Electrostimulation was performed on the right forearm to stimulate the extension of the index finger. EEG activity was recorded simultaneously. The sample included 45 subjects randomly divided into 3 groups of 15 subjects each: control group (submitted to 24 blocks of stimulation at a null intensity current), group 1 (24 blocks) and group 2 (36 blocks). Interhemispheric asymmetry between F3-F4, C3-C4 and P3-P4 was analyzed through an Anova. Results pointed out to a group x electrode interaction and a general tendency of asymmetry decrease after stimulation.

[Changes in cortical interhemispheric coherence produced by functional electrical stimulation (FES)]

The aim of the present study was to observe cortical alterations produced by functional electrical stimulation (FES), through quantitative electroencephalography (qEEG). Electrostimulation was performed on the right forearm to stimulate the extension of the index finger. EEG activity was recorded simultaneously. The sample consisted of 45 subjects randomly divided into 3 groups of 15 subjects each. The control group was submitted to 24 blocks of stimulation at a current intensity of zero. Group 1 was submitted to 24 blocks and group 2 to 36 blocks. Interhemispheric coherence between F3-F4, C3-C4 and P3-P4 was assessed through a statistical analysis. Results pointed out to increased coherence values after stimulation.

Macroscopic brain dynamics during verbal and pictorial processing of affective stimuli

Emotions can be viewed as action dispositions, preparing an individual to act efficiently and successfully in situations of behavioral relevance. To initiate optimized behavior, it is essential to accurately process the perceptual elements indicative of emotional relevance. The present chapter discusses effects of affective content on neural and behavioral parameters of perception, across different information channels. Electrocortical data are presented from studies examining affective perception with pictures and words in different task contexts. As a main result, these data suggest that sensory facilitation has an important role in affective processing. Affective pictures appear to facilitate perception as a function of emotional arousal at multiple levels of visual analysis. If the discrimination between affectively arousing vs. nonarousing content relies on fine-grained differences, amplification of the cortical representation may occur as early as 60-90 ms after stimulus onset. Affectively arousing information as conveyed via visual verbal channels was not subject to such very early enhancement. However, electrocortical indices of lexical access and/or activation of semantic networks showed that affectively arousing content may enhance the formation of semantic representations during word encoding. It can be concluded that affective arousal is associated with activation of widespread networks, which act to optimize sensory processing. On the basis of prioritized sensory analysis for affectively relevant stimuli, subsequent steps such as working memory, motor preparation, and action may be adjusted to meet the adaptive requirements of the situation perceived.

Principal components analysis of Laplacian waveforms as a generic method for identifying ERP generator patterns: II. Adequacy of low-density estimates

OBJECTIVE

To evaluate the comparability of high- and low-density surface Laplacian estimates for determining ERP generator patterns of group data derived from a typical ERP sample size and paradigm.

METHODS

High-density ERP data (129 sites) recorded from 17 adults during tonal and phonetic oddball tasks were converted to a 10-20-system EEG montage (31 sites) using spherical spline interpolations. Current source density (CSD) waveforms were computed from the high- and low-density, but otherwise identical, ERPs, and correlated at corresponding locations. CSD data were submitted to separate covariance-based, unrestricted temporal PCAs (Varimax of covariance loadings) to identify and effectively summarize temporally and spatially overlapping CSD components. Solutions were compared by correlating factor loadings and scores, and by plotting ANOVA F statistics derived from corresponding high- and low-resolution factor scores using representative sites.

RESULTS

High- and low-density CSD waveforms, PCA solutions, and F statistics were remarkably similar, yielding correlations of .9 < or = r < or = .999 between waveforms, loadings, and scores for almost all comparisons at low-density locations except for low-signal CSD waveforms at occipital sites. Each of the first 10 high-density factors corresponded precisely to one factor of the first 10 low-density factors, with each 10-factor set accounting for the meaningful CSD variance (> 91.6%).

CONCLUSIONS

Low-density surface Laplacian estimates were shown to be accurate approximations of high-density CSDs at these locations, which adequately and quite sufficiently summarized group data. Moreover, reasonable approximations of many high-density scalp locations were obtained for group data from interpolations of low-density data. If group findings are the primary objective, as typical for cognitive ERP research, low-resolution CSD topographies may be as efficient, given the effective spatial smoothing when averaging across subjects and/or conditions.

SIGNIFICANCE

Conservative recommendations for restricting surface Laplacians to high-density recordings may not be appropriate for all ERP research applications, and should be re-evaluated considering objective, costs and benefits.

Detrimental Effects of Irrelevant Speech on Serial Recall of Visual Items are Reflected in Reduced Visual N1 and Reduced Theta Activity

The term irrelevant sound effect (ISE) describes an empirically robust finding in which serial recall performance of visual items is reduced by irrelevant speech. At present little is known about its neurophysiological basis. Although some previous neuroelectric studies have concentrated on responses elicited by irrelevant background sound, whether the processing of visually presented to-be-remembered digits itself is affected by irrelevant speech has yet to be studied. An experiment (n = 20) was conducted in which serial recall performance for visually presented digits was tested during exposure to either irrelevant speech, continuous white noise or silence while measuring EEG activity. White noise was chosen as a control condition, because it constitutes auditory stimulation while leaving serial recall performance unimpaired. In addition to replicating the detrimental behavioural effect of irrelevant speech, an analogous speech-specific early decrease ( approximately 160 ms) in the visual ERP (N1) and subsequently a reduced theta response (4-6 Hz; 400-800 ms) at right prefrontal electrodes were observed. Although irrelevant sound presentation was restricted to the visual presentation phase, power spectra reveal that the weaker theta response for speech persisted in a silent retention phase before serial recall. Based on such data we propose re-evaluating the role attention plays in explaining the ISE.

Correlation between blood flow velocity in the middle cerebral artery and EEG during cognitive effort

Cognitive effort modifies blood flow velocity (BFV) in the middle cerebral artery (MCA) which can be recorded by transcranial Doppler sonography (TCD). EEG parameters can be used as indicators of cortical activation. To find temporal and spatial relation between circulatory and bioelectric phenomena, we used combined EEG and TCD measurements during cognitive experiments. Bilateral BFV in the MCAs and 16-channel scalp EEG were recorded during mental arithmetic (MA) and verbal fluency (VF) tests in 12 healthy volunteers. Temporal profile of BFV, heart rate (HR), EEG central frequency (CF), relative alpha power (ralphap), and laterality index (Li) for BFV and CF were statistically analysed. During mental effort, BFV changes showed a reproducible pattern, which was different in MA and VF tests. The Li(BFV) correlated with handedness in 9/12 subjects (75%) in the VF, and in 6/12 subjects (50%) in the MA test. Significant correlation was found between Li(BFV) and Li(CF) during VF (r(2) = 0.69). Li was more indicative for the hemispheric dominance in the VF than in the MA test. During VF test, correlation between HR and BFV was significant in 7/12 subjects. CF and ralphap provide real time assessment of the functional state of the brain tissue during cognition. The correlation between CF and BFV during mental activity suggests a short latency neurogenic and a long latency, supposedly chemical regulation of regional blood flow. Parallel analysis of EEG and flow parameters increases the confidence of determining hemispheric dominance and provides an alternative to study physiological consequences of cognitive processes.

Dynamics of parietofrontal networks underlying visuospatial short-term memory encoding

Brain imaging studies in TEP, functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) have shown that visuospatial short-term memory tasks depend on dorsal parietofrontal networks. Knowing the spatiotemporal dynamics of this network would provide further understanding of the neural bases of the encoding process. We combined magnetoencephalography (MEG) with EEG and fMRI techniques to study this network in a task, in which participants had to judge the symmetry in position of two dots, presented either simultaneously ("immediate comparison") or successively ("memorization" of a first dot and "delayed comparison", after 3 s, with a second dot). With EEG, larger amplitude was observed in the parietocentral P3b component (350-500 ms) in the immediate and "delayed comparisons" than in "memorization" condition, where topography at this time was more anterior and right lateralized. MEG provided a more accurate localization and temporal variations of sources, revealing a strong M4 component at 450 ms in the "memorization" condition, with two sources localized in parietal and right premotor regions. These localizations are consistent with both fMRI foci and EEG cortical current source densities (CSD), but only MEG revealed the strong increase in premotor region at 450 ms related to "memorization". These combined results suggest that EEG P3B and MEG M4 components reflect two different dynamics in parietofrontal networks: the parietocentral P3b indexes a decision mechanism during the immediate and "delayed comparisons", whereas the MEG M4 component, with a larger right premotor source, reflects the encoding process in visuospatial short-term memory.

Relating fMRI and PET signals to neural activity by means of large-scale neural models

This article reviews the four ways by which large-scale, neurobiologically realistic modeling can be used in conjunction with functional neuroimaging data, especially that obtained by functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), to help investigators understand the neural bases for sensorimotor and cognitive functions. The conceptually distinct purposes served are:(1) formulating and implementing specific hypotheses about how neuronal populations mediate a task, which will be illustrated using models of visual and auditory object processing; (2) determining how well an experimental design paradigm or analysis method works, which will be illustrated by examining event-related fMRI; (3) investigating the meaning in neural terms of macro-level concepts, which will be illustrated using functional connectivity; and (4) combining different types of macroscopic data with one another, which will be illustrated using transcranial magnetic stimulation (TMS) and PET.

High-resolution electroencephalogram (EEG) mapping: scalp charge layer

The neural electrical signal related to the human brain function is one of the tracks to understanding ourselves. Various electroencephalogram imaging techniques have been developed to reveal spatial information on neural activities in the brain from scalp recordings, such as Laplacian, equivalent source layer and potential. Physically, these methods may be classified into two categories: scalp surface or cortical surface based techniques. In this work, the focus is on the scalp surface based equivalent charge layer (ECL), with a comparison to the scalp potential with different references and scalp Laplacian (SL). The contents include theoretical analysis and numeric evaluation of simulated data and real alpha (8-12 Hz) data. The results confirm the fact that SL and ECL are of higher spatial resolution than various scalp potential maps, and for SL and ECL, SL is of higher resolution but more sensitive to noise.

Neurocortical electrical activity tomography in chronic schizophrenics

Functional imaging of brain electrical activity was performed in 25 chronic medicated schizophrenics and 40 controls, analyzing the classical frequency bands (delta, theta, alpha, and beta) of 19-channel EEG during resting state to identify brain regions with deviant activity of different functional significances, using LORETA (Low Resolution Tomography) and SPM99 (Statistical Parametric Mapping). Patients differed from controls due to an excess of slow activity comprising delta + theta frequency bands (inhibitory pattern) located at the right middle frontal gyrus, right inferior frontal gyrus, and right insula, as well as at the bilateral anterior cingulum with a left preponderance. The high temporal resolution of EEG enables the specification of the deviations not only as an excess or a deficit of brain electrical activity, but also as inhibitory (delta, theta), normal (alpha), and excitatory (beta) activities. These deviations point out to an impaired functional brain state consisting of inhibited frontal and prefrontal areas that may result in inadequate treatment of externally or internally generated information.

Response error correction--a demonstration of improved human-machine performance using real-time EEG monitoring

We describe a brain-computer interface (BCI) system, which uses a set of adaptive linear preprocessing and classification algorithms for single-trial detection of error related negativity (ERN). We use the detected ERN as an estimate of a subject's perceived error during an alternative forced choice visual discrimination task. The detected ERN is used to correct subject errors. Our initial results show average improvement in subject performance of 21% when errors are automatically corrected via the BCI. We are currently investigating the generalization of the overall approach to other tasks and stimulus paradigms.

The novelty P3: an event-related brain potential (ERP) sign of the brain's evaluation of novelty

A review of the literature that examines event-related brain potentials (ERPs) and novelty processing reveals that the orienting response engendered by deviant or unexpected events consists of a characteristic ERP pattern, comprised sequentially of the mismatch negativity (MMN) and the novelty P3 or P3a. A wide variety of evidence suggests that the MMN reflects the detection of deviant events, whereas the P3a is associated more with the evaluation of those events for subsequent behavioral action. On the scalp, the novelty P3a is comprised of at least two aspects, one frontal the other posterior, each with different cognitive (and presumably neurologic) correlates. Intracranial ERP investigations and studies of patients with localized brain lesions (and, to some extent, fMRI data) converge with the scalp-recorded data in suggesting a widespread neural network, the different aspects of which respond differentially to stimulus and task characteristics.

Maturation of white matter in the human brain: a review of magnetic resonance studies

This review focuses on the maturation of brain white-matter, as revealed by magnetic resonance (MR) imaging carried out in healthy subjects. The review begins with a brief description of the nature of the MR signal and its possible biological underpinnings, and proceeds with a description of MR findings obtained in newborns, infants, children and adolescents. On MR images, a significant decrease in water content leads to a decrease of longitudinal relaxation times (T1) and transverse relaxation times (T2) and consequent "adult-like" appearance of T1-weighted and T2-weighted images becomes evident towards the end of the first year of life. Owing to the onset of myelination and the related increase of lipid content, MR images gradually acquire an exquisite grey-white matter contrast in a temporal sequence reflecting the time course of myelination. Albeit less pronounced, age-related changes in white matter continue during childhood and adolescence; white matter increases its overall volume and becomes more myelinated in a region-specific fashion. Detection of more subtle changes during this "late" phase of brain development is greatly aided by computational analyses of MR images. The review also briefly outlines future directions, including the use of novel MR techniques such as diffusion tensor imaging and magnetization transfer, as well as the suggestion for the concurrent use of experimental behavioral test-batteries, with structural MR imaging, to study developmental changes in structure-function relationships.

Event-related potential (ERP) studies of memory encoding and retrieval: a selective review

As event-related brain potential (ERP) researchers have increased the number of recording sites, they have gained further insights into the electrical activity in the neural networks underlying explicit memory. A review of the results of such ERP mapping studies suggests that there is good correspondence between ERP results and those from brain imaging studies that map hemodynamic changes. This concordance is important because the combination of the high temporal resolution of ERPs with the high spatial resolution of hemodynamic imaging methods will provide a greatly increased understanding of the spatio-temporal dynamics of the brain networks that encode and retrieve explicit memories.

Neural modeling and functional brain imaging: an overview

This article gives an overview of the different functional brain imaging methods, the kinds of questions these methods try to address and some of the questions associated with functional neuroimaging data for which neural modeling must be employed to provide reasonable answers.