Cortical and Subcortical Correlates of Electroencephalographic Alpha Rhythm Modulation

Joint Coupling of Awake EEG Frequency Activity and MRI Gray Matter Volumes in the Psychosis Dimension: A BSNIP Study

BACKGROUND

Many studies have examined either electroencephalogram (EEG) frequency activity or gray matter volumes (GMV) in various psychoses [including schizophrenia (SZ), schizoaffective (SZA), and psychotic bipolar disorder (PBP)]. Prior work demonstrated similar EEG and gray matter abnormalities in both SZ and PBP. Integrating EEG and GMV and jointly analyzing the combined data fully elucidates the linkage between the two and may provide better biomarker- or endophenotype-specificity for a particular illness. Joint exploratory investigations of EEG and GMV are scarce in the literature and the relationship between the two in psychosis is even less explored. We investigated a joint multivariate model to test whether the linear relationship or linkage between awake EEG (AEEG) frequency activity and GMV is abnormal across the psychosis dimension and if such effects are also present in first-degree relatives.

METHODS

We assessed 607 subjects comprising 264 probands [105 SZ, 72 SZA, and 87 PBP], 233 of their first degree relatives [82 SZ relatives (SZR), 71 SZA relatives (SZAR), and 80 PBP relatives (PBPR)], and 110 healthy comparison subjects (HC). All subjects underwent structural MRI (sMRI) and EEG scans. Frequency activity and voxel-based morphometric GMV were derived from EEG and sMRI data, respectively. Seven AEEG frequency and gray matter components were extracted using Joint independent component analysis (jICA). The loading coefficients (LC) were examined for group differences using analysis of covariance. Further, the LCs were correlated with psychopathology scores to identify relationship with clinical symptoms.

RESULTS

Joint ICA revealed a single component differentiating SZ from HC (p < 0.006), comprising increased posterior alpha activity associated with decreased volume in inferior parietal lobe, supramarginal, parahippocampal gyrus, middle frontal, inferior temporal gyri, and increased volume of uncus and culmen. No components were aberrant in either PBP or SZA or any relative group. No significant association was identified with clinical symptom measures.

CONCLUSION

Our data suggest that a joint EEG and GMV model yielded a biomarker specific to SZ, not abnormal in PBP or SZA. Alpha activity was related to both increased and decreased volume in different cortical structures. Additionally, the joint model failed to identify endophenotypes across psychotic disorders.

Cerebral and blood correlates of reduced functional connectivity in mild cognitive impairment

Growing evidence suggests that decreased functional connectivity in cortical networks precedes clinical stages of Alzheimer's disease (AD), although our knowledge about cerebral and biological correlates of this phenomenon is limited. To shed light on this issue, we have investigated whether resting-state oscillatory connectivity patterns in healthy older (HO) and amnestic mild cognitive impairment (aMCI) subjects are related to anatomical grey matter (GM) and functional (2-[18F]fluoro-2-deoxy-D-glucose (FDG)-PET) changes of neuroelectric sources of alpha rhythms, and/or to changes in plasma amyloid-beta (Aβ) and serum lipid levels, blood markers tied to AD pathogenesis and aging-related cognitive decline. We found that aMCI subjects showed decreased levels of cortical connectivity, reduced FDG-PET intake of the precuneus, and GM atrophy of the thalamus, together with higher levels of Aβ and apolipoprotein B (ApoB) compared to HO. Interestingly, levels of high-density lipoprotein (HDL) cholesterol were positively correlated with the strength of neural-phase coupling in aMCI subjects, and increased triglycerides accompanied bilateral GM loss in the precuneus of aMCI subjects. Together, these findings provide peripheral blood correlates of reduced resting-state cortical connectivity in aMCI, supported by anatomo-functional changes in cerebral sources of alpha rhythms. This framework constitutes an integrated approach to assess functional changes in cortical networks through neuroimaging and peripheral blood markers during early stages of neurodegeneration.

Cognitive neuroscience in space

Humans are the most adaptable species on this planet, able to live in vastly different environments on Earth. Space represents the ultimate frontier and a true challenge to human adaptive capabilities. As a group, astronauts and cosmonauts are selected for their ability to work in the highly perilous environment of space, giving their best. Terrestrial research has shown that human cognitive and perceptual motor performances deteriorate under stress. We would expect to observe these effects in space, which currently represents an exceptionally stressful environment for humans. Understanding the neurocognitive and neuropsychological parameters influencing space flight is of high relevance to neuroscientists, as well as psychologists. Many of the environmental characteristics specific to space missions, some of which are also present in space flight simulations, may affect neurocognitive performance. Previous work in space has shown that various psychomotor functions degrade during space flight, including central postural functions, the speed and accuracy of aimed movements, internal timekeeping, attentional processes, sensing of limb position and the central management of concurrent tasks. Other factors that might affect neurocognitive performance in space are illness, injury, toxic exposure, decompression accidents, medication side effects and excessive exposure to radiation. Different tools have been developed to assess and counteract these deficits and problems, including computerized tests and physical exercise devices. It is yet unknown how the brain will adapt to long-term space travel to the asteroids, Mars and beyond. This work represents a comprehensive review of the current knowledge and future challenges of cognitive neuroscience in space from simulations and analog missions to low Earth orbit and beyond.

Data-driven analysis of simultaneous EEG/fMRI using an ICA approach

Due to its millisecond-scale temporal resolution, EEG allows to assess neural correlates with precisely defined temporal relationship relative to a given event. This knowledge is generally lacking in data from functional magnetic resonance imaging (fMRI) which has a temporal resolution on the scale of seconds so that possibilities to combine the two modalities are sought. Previous applications combining event-related potentials (ERPs) with simultaneous fMRI BOLD generally aimed at measuring known ERP components in single trials and correlate the resulting time series with the fMRI BOLD signal. While it is a valuable first step, this procedure cannot guarantee that variability of the chosen ERP component is specific for the targeted neurophysiological process on the group and single subject level. Here we introduce a newly developed data-driven analysis procedure that automatically selects task-specific electrophysiological independent components (ICs). We used single-trial simultaneous EEG/fMRI analysis of a visual Go/Nogo task to assess inhibition-related EEG components, their trial-to-trial amplitude variability, and the relationship between this variability and the fMRI. Single-trial EEG/fMRI analysis within a subgroup of 22 participants revealed positive correlations of fMRI BOLD signal with EEG-derived regressors in fronto-striatal regions which were more pronounced in an early compared to a late phase of task execution. In sum, selecting Nogo-related ICs in an automated, single subject procedure reveals fMRI-BOLD responses correlated to different phases of task execution. Furthermore, to illustrate utility and generalizability of the method beyond detecting the presence or absence of reliable inhibitory components in the EEG, we show that the IC selection can be extended to other events in the same dataset, e.g., the visual responses.

Disrupted resting-state functional architecture of the brain after 45-day simulated microgravity

Long-term spaceflight induces both physiological and psychological changes in astronauts. To understand the neural mechanisms underlying these physiological and psychological changes, it is critical to investigate the effects of microgravity on the functional architecture of the brain. In this study, we used resting-state functional MRI (rs-fMRI) to study whether the functional architecture of the brain is altered after 45 days of −6° head-down tilt (HDT) bed rest, which is a reliable model for the simulation of microgravity. Sixteen healthy male volunteers underwent rs-fMRI scans before and after 45 days of −6° HDT bed rest. Specifically, we used a commonly employed graph-based measure of network organization, i.e., degree centrality (DC), to perform a full-brain exploration of the regions that were influenced by simulated microgravity. We subsequently examined the functional connectivities of these regions using a seed-based resting-state functional connectivity (RSFC) analysis. We found decreased DC in two regions, the left anterior insula (aINS) and the anterior part of the middle cingulate cortex (MCC; also called the dorsal anterior cingulate cortex in many studies), in the male volunteers after 45 days of −6° HDT bed rest. Furthermore, seed-based RSFC analyses revealed that a functional network anchored in the aINS and MCC was particularly influenced by simulated microgravity. These results provide evidence that simulated microgravity alters the resting-state functional architecture of the brains of males and suggest that the processing of salience information, which is primarily subserved by the aINS–MCC functional network, is particularly influenced by spaceflight. The current findings provide a new perspective for understanding the relationships between microgravity, cognitive function, autonomic neural function, and central neural activity.

Frequencies of inaudible high-frequency sounds differentially affect brain activity: positive and negative hypersonic effects

The hypersonic effect is a phenomenon in which sounds containing significant quantities of non-stationary high-frequency components (HFCs) above the human audible range (max. 20 kHz) activate the midbrain and diencephalon and evoke various physiological, psychological and behavioral responses. Yet important issues remain unverified, especially the relationship existing between the frequency of HFCs and the emergence of the hypersonic effect.

In this study, to investigate the relationship between the hypersonic effect and HFC frequencies, we divided an HFC (above 16 kHz) of recorded gamelan music into 12 band components and applied them to subjects along with an audible component (below 16 kHz) to observe changes in the alpha2 frequency component (10–13 Hz) of spontaneous EEGs measured from centro-parieto-occipital regions (Alpha-2 EEG), which we previously reported as an index of the hypersonic effect.

Our results showed reciprocal directional changes in Alpha-2 EEGs depending on the frequency of the HFCs presented with audible low-frequency component (LFC). When an HFC above approximately 32 kHz was applied, Alpha-2 EEG increased significantly compared to when only audible sound was applied (positive hypersonic effect), while, when an HFC below approximately 32 kHz was applied, the Alpha-2 EEG decreased (negative hypersonic effect). These findings suggest that the emergence of the hypersonic effect depends on the frequencies of inaudible HFC.

Self-enhancement influences medial frontal cortex alpha power to social rejection feedback

Although previous research has demonstrated that individuals are motivated to self-enhance, the neurocognitive mechanisms and temporal dynamics of self-enhancement are poorly understood. The current research examined whether self-enhancing motivations affect the perceptual processing of social feedback. Participants who varied in self-enhancement motivations received accept and reject feedback while EEG was recorded. Following this task, we measured perceptions of feedback by asking participants to estimate the number of times they were rejected. Source localization and time-frequency analyses revealed that alpha power in the medial frontal cortex (MFC) completely mediated the relationship between self-enhancement motivations and rejection estimates. Specifically, greater self-enhancement motivations predicted decreased MFC alpha power to reject compared to accept feedback, which predicted decreased rejection estimates. These findings suggest that self-enhancement motivations decrease perception of social rejection by influencing how the MFC processes social feedback.

Selective changes of resting-state brain oscillations in aMCI: an fMRI study using ALFF

Mild cognitive impairment (MCI) refers to a transitional state between normal aging and dementia and is a syndrome with cognitive decline greater than expected for an individual's age and educational level. As a subtype of MCI, amnestic mild cognitive impairment (aMCI) most often leads to Alzheimer's disease. This study aims to elucidate the altered brain activation in patients with aMCI using resting-state functional magnetic resonance. We observed Frequency-dependent changes in the amplitude of low-frequency fluctuations in aMCI patients (n = 20), and normal subjects (n = 18). At the same time, we took gray matter volume as a covariate. We found that aMCI patients had decreased amplitude of low-frequency fluctuation signal in left superior temporal gyrus, right middle temporal gyrus, right inferior parietal lobe, and right postcentral gyrus compared to the control group. Specially, aMCI patients showed increased signal in left superior and middle frontal gyrus. Our results suggested that increased activation in frontal lobe of aMCI patients may indicate effective recruitment of compensatory brain resources. This finding and interpretation may lead to the better understanding of cognitive changes of aMCI.

The role of alpha-rhythm states in perceptual learning: insights from experiments and computational models

During the past two decades growing evidence indicates that brain oscillations in the alpha band (~10 Hz) not only reflect an "idle" state of cortical activity, but also take a more active role in the generation of complex cognitive functions. A recent study shows that more than 60% of the observed inter-subject variability in perceptual learning can be ascribed to ongoing alpha activity. This evidence indicates a significant role of alpha oscillations for perceptual learning and hence motivates to explore the potential underlying mechanisms. Hence, it is the purpose of this review to highlight existent evidence that ascribes intrinsic alpha oscillations a role in shaping our ability to learn. In the review, we disentangle the alpha rhythm into different neural signatures that control information processing within individual functional building blocks of perceptual learning. We further highlight computational studies that shed light on potential mechanisms regarding how alpha oscillations may modulate information transfer and connectivity changes relevant for learning. To enable testing of those model based hypotheses, we emphasize the need for multidisciplinary approaches combining assessment of behavior and multi-scale neuronal activity, active modulation of ongoing brain states and computational modeling to reveal the mathematical principles of the complex neuronal interactions. In particular we highlight the relevance of multi-scale modeling frameworks such as the one currently being developed by "The Virtual Brain" project.

EEG-informed fMRI analysis during a hand grip task: estimating the relationship between EEG rhythms and the BOLD signal

In the last decade, an increasing interest has arisen in investigating the relationship between the electrophysiological and hemodynamic measurements of brain activity, such as EEG and (BOLD) fMRI. In particular, changes in BOLD have been shown to be associated with changes in the spectral profile of neural activity, rather than with absolute power. Concurrently, recent findings showed that different EEG rhythms are independently related to changes in the BOLD signal: therefore, it would be also important to distinguish between the contributions of the different EEG rhythms to BOLD fluctuations when modeling the relationship between the two signals. Here we propose a method to perform EEG-informed fMRI analysis where the changes in the spectral profile are modeled, and, at the same time, the distinction between rhythms is preserved. We compared our model with two other frequency-dependent regressors modeling using simultaneous EEG-fMRI data from healthy subjects performing a motor task. Our results showed that the proposed method better captures the correlations between BOLD signal and EEG rhythms modulations, identifying task-related, well localized activated volumes. Furthermore, we showed that including among the regressors also EEG rhythms not primarily involved in the task enhances the performance of the analysis, even when only correlations with BOLD signal and specific EEG rhythms are explored.

Oscillatory spatial profile of alcohol's effects on the resting state: anatomically-constrained MEG

It has been firmly established that opening and closing the eyes strongly modulate the electro- and magnetoencephalography (EEG and MEG) signals acquired during wakeful rest. Certain features of the resting EEG are altered in chronic alcoholics and their offspring, and have been proposed as biomarkers for alcoholism. Spontaneous brain oscillations are also affected by pharmacological manipulations, but the spectral and spatial characteristics of these changes are not clear. This study examined effects of the eyes-open (EO) and eyes-closed (EC) resting paradigm and alcohol challenge on the spatial profile of spontaneous MEG and EEG oscillations. Whole-head MEG and scalp EEG signals were acquired simultaneously from healthy social drinkers (n = 17) who participated in both alcohol (0.6 g/kg ethanol for men, 0.55 g/kg for women) and placebo conditions in a counterbalanced design. Power of the signal was calculated with Fast Fourier Transform and was decomposed into its constituent theta (4-7 Hz), alpha (8-12 Hz), and beta (15-20 Hz) frequency bands. High-resolution structural MRI images were additionally obtained from all participants and used to constrain distributed minimum norm inverse source power estimates. The spatial estimates of the main generator nodes were in agreement with studies using a combined fMRI-EEG approach. Alpha band oscillations dominated the spectral profile and their source was estimated to the medial parieto-occipital area. Power in theta and beta bands was weaker overall and their sources were estimated to a more focal medial prefrontal area. EO and EC manipulation most strongly modulated power in the alpha band, but a wide-band power increase was observed during the EC condition. Alcohol intoxication increased alpha power, particularly during the EC condition. Application of this methodology to cohorts of chronic alcoholics or individuals at risk could potentially provide insight into the neural basis of oscillatory differences that may be predictive of the vulnerability to alcoholism.

A phenomenology of meditation-induced light experiences: traditional buddhist and neurobiological perspectives

The scientific study of Buddhist meditation has proceeded without much attention to Buddhist literature that details the range of psychological and physiological changes thought to occur during meditation. This paper presents reports of various meditation-induced light experiences derived from American Buddhist practitioners. The reports of light experiences are classified into two main types: discrete lightforms and patterned or diffuse lights. Similar phenomena are well documented in traditional Buddhist texts but are virtually undocumented in scientific literature on meditation. Within Buddhist traditions, these phenomena are attributed a range of interpretations. However, because it is insufficient and problematic to rely solely upon the textual sources as a means of investigating the cause or significance of these phenomena, these qualitative reports are also considered in relation to scientific research on light-related experiences in the context of sensory deprivation, perceptual isolation, and clinical disorders of the visual system. The typologies derived from these studies also rely upon reports of experiences and closely match typologies derived from the qualitative study of contemporary practitioners and typologies found in Buddhist literary traditions. Taken together, these studies also provide evidence in support of the hypothesis that certain meditative practices – especially those that deliberately decrease social, kinesthetic, and sensory stimulation and emphasize focused attention – have perceptual and cognitive outcomes similar to sensory deprivation. Given that sensory deprivation increases neuroplasticity, meditation may also have an enhanced neuroplastic potential beyond ordinary experience-dependent changes. By providing and contextualizing these reports of meditation-induced light experiences, scientists, clinicians, and meditators gain a more informed view of the range of experiences that can be elicited by contemplative practices.

Altered cingulate and amygdala response towards threat and safe cues in attention deficit hyperactivity disorder

BACKGROUND

Emotional dysregulation is becoming increasingly recognized as an important feature of attention deficit hyperactivity disorder (ADHD). In this study, two experiments were conducted investigating the neural response to either verbally instructed fear (IF) or uninstructed (classically conditioned) fear (UF) using the skin conductance response (SCR) and functional magnetic resonance imaging (fMRI).

METHOD

In the conditioning phase of the UF experiment (17 ADHD and 17 healthy controls), subjects experienced an unconditioned stimulus (UCS, unpleasant electrodermal stimulation) paired with a former neutral conditioned stimulus (CS+), whereas a control stimulus (CS-) was never paired with the UCS. In the subsequent test phase, only the CS+ and the CS- were presented. In the IF experiment (13 ADHD and 17 healthy controls), subjects were only told that an independently experienced UCS might occur together with the CS+ but not the CS- during testing. No UCS was presented.

RESULTS

Groups did not detectably differ in SCR or neural responses to UF. In IF, ADHD patients showed a trend-line decreased SCR and significantly decreased activation of the dorsal anterior cingulate cortex (dACC), a region prominently involved in fear responding, to the CS+. This was accompanied by higher amygdala activation to the CS-.

CONCLUSIONS

During IF, ADHD patients showed deficits in regions centrally involved in fear learning and expression in terms of diminished CS+-related dACC and increased CS--related amygdala signals. This suggests an impaired processing of verbally transmitted aversive information, which is central for conveying fear information in social contexts. This result extends the growing literature on emotional alterations in ADHD.

Dominant frequencies of resting human brain activity as measured by the electrocorticogram

The brain's spontaneous, intrinsic activity is increasingly being shown to reveal brain function, delineate large scale brain networks, and diagnose brain disorders. One of the most studied and clinically utilized types of intrinsic brain activity are oscillations in the electrocorticogram (ECoG), a relatively localized measure of cortical synaptic activity. Here we objectively characterize the types of ECoG oscillations commonly observed over particular cortical areas when an individual is awake and immobile with eyes closed, using a surface-based cortical atlas and cluster analysis. Both methods show that [1] there is generally substantial variability in the dominant frequencies of cortical regions and substantial overlap in dominant frequencies across the areas sampled (primarily lateral central, temporal, and frontal areas), [2] theta (4-8 Hz) is the most dominant type of oscillation in the areas sampled with a mode around 7 Hz, [3] alpha (8-13 Hz) is largely limited to parietal and occipital regions, and [4] beta (13-30 Hz) is prominent peri-Rolandically, over the middle frontal gyrus, and the pars opercularis. In addition, the cluster analysis revealed seven types of ECoG spectral power densities (SPDs). Six of these have peaks at 3, 5, 7 (narrow), 7 (broad), 10, and 17 Hz, while the remaining cluster is broadly distributed with less pronounced peaks at 8, 19, and 42 Hz. These categories largely corroborate conventional sub-gamma frequency band distinctions (delta, theta, alpha, and beta) and suggest multiple sub-types of theta. Finally, we note that gamma/high gamma activity (30+ Hz) was at times prominently observed, but was too infrequent and variable across individuals to be reliably characterized. These results should help identify abnormal patterns of ECoG oscillations, inform the interpretation of EEG/MEG intrinsic activity, and provide insight into the functions of these different oscillations and the networks that produce them. Specifically, our results support theories of the importance of theta oscillations in general cortical function, suggest that alpha activity is primarily related to sensory processing/attention, and demonstrate that beta networks extend far beyond primary sensorimotor regions.

Efficacy of yoga for mental performance in university students

BACKGROUND

With growing scientific evidence, yoga is emerging as an important health behavior-lifestyle modifying module to achieve holistic health at physical, mental, emotional, social and spiritual levels. Brain wave coherence (BWC) recordings from the surface of the skull are associated with different cognitive processes and plays both critical and useful roles in yoga with wide range of functional significance. The psycho-physiological changes that characterize the efficacy of yoga for better mental performance in university students have not been studied adequately.

OBJECTIVE

The study was designed to assess the mental performance through BWC analysis in university students undergoing Integrated Yoga Module (IYM).

MATERIALS AND METHODS

The IYM subjects (n=30) with 25.77±4.85 years of mean age participated in this single group pre-post study. The BWC data was collected before (pre) and after (post) the 21 days IYM using Brain Master (Model: 2E Part # 390-001), Michigan, USA.

STATISTICAL ANALYSIS

Means, standard deviations, Kolmogorov-Smirnov test and Wilcoxon signed rank test were used for analyzing data with the help of SPSS-16.

RESULTS

A complete statistical and spectral analysis showed 43.24% increase (P<0.001) in Delta, 9.13% increase (P=0.289) in Theta, 57.85% increase (P<0.001) in Alpha, 17.65% decrease (P=0.136) in Beta and 9.19% increase (P=0.586) in Gamma BWC between pre and post intervention measurements.

CONCLUSION

BWC study showed significant increase in both Delta and Alpha wave coherence suggesting that IYM can result in improvement of coherent and integrated brain functioning among students, thus paving the way for their better mental performance. Although this preliminary research is promising, more well-designed studies are needed before a strong recommendation can be made.

Simultaneous EEG-fMRI reveals a temporal cascade of task-related and default-mode activations during a simple target detection task

Focused attention continuously and inevitably fluctuates, and to completely understand the mechanisms responsible for these modulations it is necessary to localize the brain regions involved. During a simple visual oddball task, neural responses measured by electroencephalography (EEG) modulate primarily with attention, but source localization of the correlates is a challenge. In this study we use single-trial analysis of simultaneously-acquired scalp EEG and functional magnetic resonance image (fMRI) data to investigate the blood oxygen level dependent (BOLD) correlates of modulations in task-related attention, and we unravel the temporal cascade of these transient activations. We hypothesize that activity in brain regions associated with various task-related cognitive processes modulates with attention, and that their involvements occur transiently in a specific order. We analyze the fMRI BOLD signal by first regressing out the variance linked to observed stimulus and behavioral events. We then correlate the residual variance with the trial-to-trial variation of EEG discriminating components for identical stimuli, estimated at a sequence of times during a trial. Post-stimulus and early in the trial, we find activations in right-lateralized frontal regions and lateral occipital cortex, areas that are often linked to task-dependent processes, such as attentional orienting, and decision certainty. After the behavioral response we see correlates in areas often associated with the default-mode network and introspective processing, including precuneus, angular gyri, and posterior cingulate cortex. Our results demonstrate that during simple tasks both task-dependent and default-mode networks are transiently engaged, with a distinct temporal ordering and millisecond timescale.

Phenotypic spectrum of glucose transporter type 1 deficiency syndrome (Glut1 DS)

Glut1 deficiency syndrome (Glut1 DS) was originally described in 1991 as a developmental encephalopathy characterized by infantile onset refractory epilepsy, cognitive impairment, and mixed motor abnormalities including spasticity, ataxia, and dystonia. The clinical condition is caused by impaired glucose transport across the blood brain barrier. The past 5 years have seen a dramatic expansion in the range of clinical syndromes that are recognized to occur with Glut1 DS. In particular, there has been greater recognition of milder phenotypes. Absence epilepsy and other idiopathic generalized epilepsy syndromes may occur with seizure onset in childhood or adulthood. A number of patients present predominantly with movement disorders, sometimes without any accompanying seizures. In particular, paroxysmal exertional dyskinesia is now a well-documented clinical feature that occurs in individuals with Glut1 DS. A clue to the diagnosis in patients with paroxysmal symptoms may be the triggering of episodes during fasting or exercise. Intellectual impairment may range from severe to very mild. Awareness of the broad range of potential clinical phenotypes associated with Glut1 DS will facilitate earlier diagnosis of this treatable neurologic condition. The ketogenic diet is the mainstay of treatment and nourishes the starving symptomatic brain during development.

The change of functional connectivity specificity in rats under various anesthesia levels and its neural origin

Spatiotemporal correlations of spontaneous blood oxygenation level dependent (BOLD) signals measured in the resting brain have been found to imply many resting-state coherent networks under both awake/conscious and anesthetized/unconscious conditions. To understand the resting-state brain networks in the unconscious state, spontaneous BOLD signals from the rat sensorimotor cortex were studied across a wide range of anesthesia levels induced by isoflurane. Distinct resting-state networks covering functionally specific sub-regions of the sensorimotor system were observed under light anesthesia with 1.0% isoflurane; however, they gradually merged into a highly synchronized and spatially less-specific network under deep anesthesia with 1.8% isoflurane. The EEG power correlations recorded using three electrodes from a separate group of rats showed similar dependency on anesthesia depth, suggesting the neural origin of the change in functional connectivity specificity. The specific-to-less-specific transition of resting-state networks may reflect a functional reorganization of the brain at different anesthesia levels or brain states.

The Quest for EEG Power Band Correlation with ICA Derived fMRI Resting State Networks

The neuronal underpinnings of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) resting state networks (RSNs) are still unclear. To investigate the underlying mechanisms, specifically the relation to the electrophysiological signal, we used simultaneous recordings of electroencephalography (EEG) and fMRI during eyes open resting state (RS). Earlier studies using the EEG signal as independent variable show inconclusive results, possibly due to variability in the temporal correlations between RSNs and power in the low EEG frequency bands, as recently reported (Goncalves et al., 2006, 2008; Meyer et al., 2013). In this study we use three different methods including one that uses RSN timelines as independent variable to explore the temporal relationship of RSNs and EEG frequency power in eyes open RS in detail. The results of these three distinct analysis approaches support the hypothesis that the correlation between low EEG frequency power and BOLD RSNs is instable over time, at least in eyes open RS.

EEG-fMRI integration for the study of human brain function

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have proved to be extremely valuable tools for the non-invasive study of human brain function. Moreover, due to a notable degree of complementarity between the two modalities, the combination of EEG and fMRI data has been actively sought in the last two decades. Although initially focused on epilepsy, EEG-fMRI applications were rapidly extended to the study of healthy brain function, yielding new insights into its underlying mechanisms and pathways. Nevertheless, EEG and fMRI have markedly different spatial and temporal resolutions, and probe neuronal activity through distinct biophysical processes, many aspects of which are still poorly understood. The remarkable conceptual and methodological challenges associated with EEG-fMRI integration have motivated the development of a wide range of analysis approaches over the years, each relying on more or less restrictive assumptions, and aiming to shed further light on the mechanisms of brain function along with those of the EEG-fMRI coupling itself. Here, we present a review of the most relevant EEG-fMRI integration approaches yet proposed for the study of brain function, supported by a general overview of our current understanding of the biophysical mechanisms coupling the signals obtained from the two modalities.

Adding dynamics to the Human Connectome Project with MEG

The Human Connectome Project (HCP) seeks to map the structural and functional connections between network elements in the human brain. Magnetoencephalography (MEG) provides a temporally rich source of information on brain network dynamics and represents one source of functional connectivity data to be provided by the HCP. High quality MEG data will be collected from 50 twin pairs both in the resting state and during performance of motor, working memory and language tasks. These data will be available to the general community. Additionally, using the cortical parcellation scheme common to all imaging modalities, the HCP will provide processing pipelines for calculating connection matrices as a function of time and frequency. Together with structural and functional data generated using magnetic resonance imaging methods, these data represent a unique opportunity to investigate brain network connectivity in a large cohort of normal adult human subjects. The analysis pipeline software and the dynamic connectivity matrices that it generates will all be made freely available to the research community.

Medial prefrontal dysfunction and prolonged amygdala response during instructed fear processing in borderline personality disorder

OBJECTIVES

Affective dysregulation is a clinical hallmark of borderline personality disorder (BPD). This study used an instructed fear task combined with functional MRI (fMRI) and skin conductance response (SCR) to test hypotheses about mechanisms of disturbed fronto-limbic neural circuitry underlying dysfunctional emotional processing in BPD.

METHODS

Female BPD patients and matched control subjects were exposed to two visual stimuli during fMRI scanning and SCR recording. Subjects were instructed shortly before scanning that one stimulus (Threat) potentially represents an aversive event whereas another stimulus (Safe) represents safety. The aversive event (electrodermal stimulation) itself was only experienced before this instruction and never occurred during fMRI scanning.

RESULTS

Both groups showed stronger SCR to Threat compared to Safe indicating differential fear response which habituated over time. BPD compared to control subjects did not show fMRI signal decrease of amygdala activity or relative ventromedial prefrontal cortex (vmPFC) activity increase over time. Moreover, BPD patients showed increased connectivity of the amygdala with vmPFC but decreased connectivity of subgenual ACC with dorsal ACC compared to control subjects.

CONCLUSIONS

Prolonged amygdala response and a functional disconnection between ventral and dorsal mPFC regions may be part of the neural mechanisms underlying emotional dysregulation in BPD patients.

The effect of resting condition on resting-state fMRI reliability and consistency: a comparison between resting with eyes open, closed, and fixated

Resting-state fMRI (rs-fMRI) has been demonstrated to have moderate to high reliability and produces consistent patterns of connectivity across a wide variety of subjects, sites, and scanners. However, there is no one agreed upon method to acquire rs-fMRI data. Some sites instruct their subjects, or patients, to lie still with their eyes closed, while other sites instruct their subjects to keep their eyes open or even fixating on a cross during scanning. Several studies have compared those three resting conditions based on connectivity strength. In our study, we assess differences in metrics of test-retest reliability (using an intraclass correlation coefficient), and consistency of the rank-order of connections within a subject and the ranks of subjects for a particular connection from one session to another (using Kendall's W tests). Twenty-five healthy subjects were scanned at three different time points for each resting condition, twice the same day and another time two to three months later. Resting-state functional connectivity measures were evaluated in motor, visual, auditory, attention, and default-mode networks, and compared between the different resting conditions. Of the networks examined, only the auditory network resulted in significantly higher connectivity in the eyes closed condition compared to the other two conditions. No significant between-condition differences in connectivity strength were found in default mode, attention, visual, and motor networks. Overall, the differences in reliability and consistency between different resting conditions were relatively small in effect size but results were found to be significant. Across all within-network connections, and within default-mode, attention, and auditory networks statistically significant greater reliability was found when the subjects were lying with their eyes fixated on a cross. In contrast, primary visual network connectivity was most reliable when subjects had their eyes open (and not fixating on a cross).

The significance of the senescence pathway in breast cancer progression

Invasive breast cancer develops through prolonged accumulation of multiple genetic changes. The progression to a malignant phenotype requires overriding of growth inhibition. It is evident that some breast cancers have an inherited basis, and both hereditary and sporadic cancers appear to involve molecular mechanisms that are linked to the cell cycle. Frequently, changes in the molecular pathways with gene deletions, point mutations and/or overexpression of growth factors can be seen in these cancers. Recent evidence also implicates the senescence pathway in breast carcinogenesis. It has a barrier effect towards excessive cellular growth, acting as the regulator of tumour initiation and progression. Later in carcinogenesis, acquisition of the senescence associated secretory phenotype may instead promote tumour progression by stimulating growth and transformation in adjacent cells. This two-edge role of senescence in cancer directs more investigations into the effects of the senescence pathway in the development of malignancy. This review presents the current evidence on the roles of senescence molecular pathways in breast cancer and its progression.

The relationship between brain oscillatory activity and therapeutic effectiveness of transcranial magnetic stimulation in the treatment of major depressive disorder

Major depressive disorder (MDD) is marked by disturbances in brain functional connectivity. This connectivity is modulated by rhythmic oscillations of brain electrical activity, which enable coordinated functions across brain regions. Oscillatory activity plays a central role in regulating thinking and memory, mood, cerebral blood flow, and neurotransmitter levels, and restoration of normal oscillatory patterns is associated with effective treatment of MDD. Repetitive transcranial magnetic stimulation (rTMS) is a robust treatment for MDD, but the mechanism of action (MOA) of its benefits for mood disorders remains incompletely understood. Benefits of rTMS have been tied to enhanced neuroplasticity in specific brain pathways. We summarize here the evidence that rTMS entrains and resets thalamocortical oscillators, normalizes regulation and facilitates reemergence of intrinsic cerebral rhythms, and through this mechanism restores normal brain function. This entrainment and resetting may be a critical step in engendering neuroplastic changes and the antidepressant effects of rTMS. It may be possible to modify the method of rTMS administration to enhance this MOA and achieve better antidepressant effectiveness. We propose that rTMS can be administered: (1) synchronized to a patient's individual alpha frequency (IAF), or synchronized rTMS (sTMS); (2) as a low magnetic field strength sinusoidal waveform; and, (3) broadly to multiple brain areas simultaneously. We present here the theory and evidence indicating that these modifications could enhance the therapeutic effectiveness of rTMS for the treatment of MDD.

Objective assessment of the human visual attentional state

PRIMARY OBJECTIVE

The purpose of this study was to develop an objective way to assess human visual attention using the alpha-band component of the visual-evoked potential (VEP).

DESIGN AND METHODS

Six different attentional conditions were tested: eyes-open, eyes-closed, eyes-closed with backwards number counting, and three rapid-serial visual presentation (RSVP) tasks. Eighteen visually normal, young-adult subjects (ages 21-28 years) were tested binocularly at 1 m for each condition on two separate days. The Diopsys™ NOVA-TR system was used to obtain the visual-evoked potential (VEP) and extracted alpha wave and its related power spectrum. Additionally, the Visual Search and Attention Test (VSAT) was administered as a subjective measure of visual attention.

RESULTS

Subjects exhibited significant decreases in power in the alpha band when comparing the eyes-closed with the eyes-open conditions, with power in the eyes-closed condition being, on average, twice as large. The response from the other four conditions did not reflect the differential attentional demands. The ratio of the power in the eyes-closed condition to the eyes-open condition in the lower-alpha frequencies (8-10 Hz) was found to be significantly correlated with the group's performance on the VSAT, especially the 10-Hz component.

CONCLUSIONS

An individual's ability to attenuate their alpha component during visual processing may be a predictor of their visual attentional state. These findings solidify the role of the VEP alpha subcomponent as an objective electrophysiological correlate of visual attention, which may be useful in the diagnosis and treatment of human visual attention disorders in the future.

The spatiospectral characterization of brain networks: fusing concurrent EEG spectra and fMRI maps

Different imaging modalities capture different aspects of brain activity. Functional magnetic resonance imaging (fMRI) reveals intrinsic networks whose BOLD signals have periods from 100 s (0.01 Hz) to about 10s (0.1 Hz). Electroencephalographic (EEG) recordings, in contrast, commonly reflect cortical electrical fluctuations with periods up to 20 ms (50 Hz) or above. We examined the correspondence between intrinsic fMRI and EEG network activity at rest in order to characterize brain networks both spatially (with fMRI) and spectrally (with EEG). Brain networks were separately identified within the concurrently recorded fMRI and EEG at the aggregate group level with group independent component analysis and the association between spatial fMRI and frequency by spatial EEG sources was examined by deconvolving their component time courses. The two modalities are considered linked if the estimated impulse response function (IRF) is significantly non-zero at biologically plausible delays. We found that negative associations were primarily present within two of five alpha components, which highlights the importance of considering multiple alpha sources in EEG-fMRI. Positive associations were primarily present within the lower (e.g. delta and theta) and higher (e.g. upper beta and lower gamma) spectral regions, sometimes within the same fMRI components. Collectively, the results demonstrate a promising approach to characterize brain networks spatially and spectrally, and reveal that positive and negative associations appear within partially distinct regions of the EEG spectrum.

Coupling between visual alpha oscillations and default mode activity

Although, on average, the magnitude of alpha oscillations (8 to 12 Hz) is decreased in task-relevant cortices during externally oriented attention, its fluctuations have significant consequences, with increased level of alpha associated with decreased level of visual processing and poorer behavioral performance. Functional MRI signals exhibit similar fluctuations. The default mode network (DMN) is on average deactivated in cognitive tasks requiring externally oriented attention. Momentarily insufficient deactivation of DMN, however, is often accompanied by decreased efficiency in stimulus processing, leading to attentional lapses. These observations appear to suggest that visual alpha power and DMN activity may be positively correlated. To what extent such correlation is preserved in the resting state is unclear. We addressed this problem by recording simultaneous EEG-fMRI from healthy human participants under two resting-state conditions: eyes-closed and eyes-open. Short-time visual alpha power was extracted as time series, which was then convolved with a canonical hemodynamic response function (HRF), and correlated with blood-oxygen-level-dependent (BOLD) signals. It was found that visual alpha power was positively correlated with DMN BOLD activity only when the eyes were open; no such correlation existed when the eyes were closed. Functionally, this could be interpreted as indicating that (1) under the eyes-open condition, strong DMN activity is associated with reduced visual cortical excitability, which serves to block external visual input from interfering with introspective mental processing mediated by DMN, while weak DMN activity is associated with increased visual cortical excitability, which helps to facilitate stimulus processing, and (2) under the eyes-closed condition, the lack of external visual input renders such a gating mechanism unnecessary.

Resting state in Alzheimer's disease: a concurrent analysis of Flash-Visual Evoked Potentials and quantitative EEG

BACKGROUND

To investigate to what extent Alzheimer's Disease (AD) affects Resting State activity, the possible impairment of independent electrophysiological parameters was determined in Eye-open and Eye-closed Conditions. Specifically, Flash-Visual Evoked Potential (F-VEP) and quantitative EEG (q-EEG) were examined to establish whether abnormalities of the former were systematically associated with changes of the latter.

METHODS

Concurrently recorded F-VEP and q-EEG were comparatively analysed under Eye-open and Eye-closed Conditions in 11 Controls and 19 AD patients presenting a normal Pattern-Visual Evoked Potential (P-VEP). Between Condition differences in latencies of P2 component were matched to variations in spectral components of q-EEG.

RESULTS

P2 latency increased in 10 AD patients with Abnormal Latency (AD-AL) under Eye-closed Condition. In these patients reduction of alpha activity joined an increased delta power so that their spectral profile equated that recorded under Eye-open Condition. On the opposite, in Controls as well as in AD patients with Normal P2 Latency (AD-NL) spectral profiles recorded under Eye-open and Eye-closed Conditions significantly differed from each other. At the baseline, under Eye-open Condition, the spectra overlapped each other in the three Groups.

CONCLUSION

Under Eye-closed Condition AD patients may present a significant change in both F-VEP latency and EEG rhythm modulation. The presence of concurrent changes of independent parameters suggests that the neurodegenerative process can impair a control system active in Eye-closed Condition which the electrophysiological parameters depend upon. F-VEP can be viewed as a reliable marker of such impairment.

Clarifying the role of the rostral dmPFC/dACC in fear/anxiety: learning, appraisal or expression?

Recent studies have begun to carve out a specific role for the rostral part of the dorsal medial prefrontal cortex (dmPFC) and adjacent dorsal anterior cingulate cortex (dACC) in fear/anxiety. Within a novel general framework of dorsal mPFC/ACC areas subserving the appraisal of threat and concomitant expression of fear responses and ventral mPFC/ACC areas subserving fear regulation, the rostral dmPFC/dACC has been proposed to specifically mediate the conscious, negative appraisal of threat situations including, as an extreme variant, catastrophizing. An alternative explanation that has not been conclusively ruled out yet is that the area is involved in fear learning. We tested two different fear expression paradigms in separate fMRI studies (study 1: instructed fear, study 2: testing of Pavlovian conditioned fear) with independent groups of healthy adult subjects. In both paradigms the absence of reinforcement precluded conditioning. We demonstrate significant BOLD activation of an identical rostral dmPFC/dACC area. In the Pavlovian paradigm (study 2), the area only activated robustly once prior conditioning had finished. Thus, our data argue against a role of the area in fear learning. We further replicate a repeated observation of a dissociation between peripheral-physiological fear responding and rostral dmPFC/dACC activation, strongly suggesting the area does not directly generate fear responses but rather contributes to appraisal processes. Although we succeeded in preventing extinction of conditioned responding in either paradigm, the data do not allow us to definitively exclude an involvement of the area in fear extinction learning. We discuss the broader implications of this finding for our understanding of mPFC/ACC function in fear and in negative emotion more generally.

Coupling between resting cerebral perfusion and EEG

While several studies have investigated interactions between the electroencephalography (EEG) and functional magnetic resonance imaging BOLD signal fluctuations, less is known about the associations between EEG oscillations and baseline brain haemodynamics, and few studies have examined the link between EEG power outside the alpha band and baseline perfusion. Here we compare whole-brain arterial spin labelling perfusion MRI and EEG in a group of healthy adults (n = 16, ten females, median age: 27 years, range 21-48) during an eyes closed rest condition. Correlations emerged between perfusion and global average EEG power in low (delta: 2-4 Hz and theta: 4-7 Hz), middle (alpha: 8-13 Hz), and high (beta: 13-30 Hz and gamma: 30-45 Hz) frequency bands in both cortical and sub-cortical regions. The correlations were predominately positive in middle and high-frequency bands, and negative in delta. In addition, central alpha frequency positively correlated with perfusion in a network of brain regions associated with the modulation of attention and preparedness for external input, and central theta frequency correlated negatively with a widespread network of cortical regions. These results indicate that the coupling between average EEG power/frequency and local cerebral blood flow varies in a frequency specific manner. Our results are consistent with longstanding concepts that decreasing EEG frequencies which in general map onto decreasing levels of activation.

Seeing via Miniature Eye Movements: A Dynamic Hypothesis for Vision

During natural viewing, the eyes are never still. Even during fixation, miniature movements of the eyes move the retinal image across tens of foveal photoreceptors. Most theories of vision implicitly assume that the visual system ignores these movements and somehow overcomes the resulting smearing. However, evidence has accumulated to indicate that fixational eye movements cannot be ignored by the visual system if fine spatial details are to be resolved. We argue that the only way the visual system can achieve its high resolution given its fixational movements is by seeing via these movements. Seeing via eye movements also eliminates the instability of the image, which would be induced by them otherwise. Here we present a hypothesis for vision, in which coarse details are spatially encoded in gaze-related coordinates, and fine spatial details are temporally encoded in relative retinal coordinates. The temporal encoding presented here achieves its highest resolution by encoding along the elongated axes of simple-cell receptive fields and not across these axes as suggested by spatial models of vision. According to our hypothesis, fine details of shape are encoded by inter-receptor temporal phases, texture by instantaneous intra-burst rates of individual receptors, and motion by inter-burst temporal frequencies. We further describe the ability of the visual system to readout the encoded information and recode it internally. We show how reading out of retinal signals can be facilitated by neuronal phase-locked loops (NPLLs), which lock to the retinal jitter; this locking enables recoding of motion information and temporal framing of shape and texture processing. A possible implementation of this locking-and-recoding process by specific thalamocortical loops is suggested. Overall it is suggested that high-acuity vision is based primarily on temporal mechanisms of the sort presented here and low-acuity vision is based primarily on spatial mechanisms.

Dissociated mean and functional connectivity BOLD signals in visual cortex during eyes closed and fixation

We investigated the effects of resting state type on blood oxygen level-dependent (BOLD) signal and functional connectivity in two paradigms: participants either alternated between fixation and eyes closed or maintained fixation or eyes closed throughout each scan. The BOLD signal and functional connectivity of lower and higher tiers of the visual cortical hierarchy were found to be differentially modulated during eyes closed versus fixation. Fixation was associated with greater mean BOLD signals in primary visual cortex and lower mean BOLD signals in extrastriate visual areas than periods of eyes closed. In addition, analysis of thalamocortical functional connectivity during scans in which participants maintained fixation showed synchronized BOLD fluctuations between those thalamic nuclei whose mean BOLD signal was systematically modulated during alternating epochs of eyes closed and fixation, primary visual cortex and the attention network, while during eyes closed negatively correlated fluctuations were seen between the same thalamic nuclei and extrastriate visual areas. Finally, in all visual areas the amplitude of spontaneous BOLD fluctuations was greater during eyes closed than during fixation. The dissociation between early and late tiers of visual cortex, which characterizes both mean and functionally connected components of the BOLD signal, may depend on the reorganization of thalamocortical networks. Since dissociated changes in local blood flow also characterize transitions between different stages of sleep and wakefulness (Braun AR, Balkin TJ, Wesenten NJ, Gwadry F, Carson RE, Varga M, Baldwin P, Belenky G, Herscovitch P. Science 279: 91-95, 1998), our results suggest that dissociated endogenous neural activity in primary and extrastriate cortex may represent a general aspect of brain function.

The impact of acamprosate on cue reactivity in alcohol dependent individuals: a functional magnetic resonance imaging study

Alcohol cue-induced brain activation has been studied extensively in alcoholics. However, little is known about the impact of standard treatment protocols on this phenomenon. The current study aimed at investigating the impact of the anticraving substance acamprosate on alcohol cue-related brain activity. Patients underwent a functional magnetic resonance imaging investigation before the beginning of medication with acamprosate or placebo (T0) and 2 weeks later (T1). All patients also received psychiatric inpatient treatment including psychotherapeutic interventions. Twenty-nine patients were included in the T0 analysis and 22 patients in the T1 analysis. At T0, a cluster in the left and right posterior cingulate cortex, covering parts of the retrosplenial cortex, was significantly associated with alcohol versus neutral cue exposure. At T1, no significant cluster was found for the alcohol-versus-neutral contrast. The analysis of the impact of acamprosate on cue-related activity in the posterior cingulate cortex cluster revealed no significant difference to placebo. These results provide further evidence for the involvement of the posterior cingulate cortex in alcohol cue exposure. However, in comparison with psychiatric inpatient treatment alone, there was no additional effect of acamprosate on cue-related brain activity.

Dissociation between neuronal activity in sensorimotor cortex and hand movement revealed as a function of movement rate

It is often assumed that similar behavior is generated by the same brain activity. However, this does not take into account the brain state or recent behavioral history and movement initiation or continuation may not be similarly generated in the brain. To study whether similar movements are generated by the same brain activity, we measured neuronal population activity during repeated movements. Three human subjects performed a motor repetition task in which they moved their hand at four different rates (0.3, 0.5, 1, and 2 Hz). From high-resolution electrocorticography arrays implanted on motor and sensory cortex, high-frequency power (65-95 Hz) was extracted as a measure of neuronal population activity. During the two faster movement rates, high-frequency power was significantly suppressed, whereas movement parameters remained highly similar. This suppression was nonlinear: after the initial movement, neuronal population activity was reduced most strongly, and the data fit a model in which a fast decline rapidly converged to saturation. The amplitude of the beta-band suppression did not change with different rates. However, at the faster rates, beta power did not return to baseline between movements but remained suppressed. We take these findings to indicate that the extended beta suppression at the faster rates, which may suggest a release of inhibition in motor cortex, facilitates movement initiation. These results show that the relationship between behavior and neuronal activity is not consistent: recent movement influences the state of motor cortex and facilitates next movements by reducing the required level of neuronal activity.

Finding thalamic BOLD correlates to posterior alpha EEG

Oscillatory electrical brain activity in the alpha (8-13 Hz) band is a prominent feature of human electroencephalography (EEG) during alert wakefulness, and is commonly thought to arise primarily from the occipital and parietal parts of the cortex. While the thalamus is considered to play a supportive role in the generation and modulation of cortical alpha rhythms, its precise function remains controversial and incompletely understood. To address this, we evaluated the correlation between the blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) signals in the thalamus and the spontaneous modulation of posterior alpha rhythms based on EEG-fMRI data acquired concurrently during an eyes-closed task-free condition. We observed both negative and positive correlations in the thalamus. The negative correlations were mostly seen within the visual thalamus, with a preference for the pulvinar over lateral geniculate nuclei. The positive correlations were found at the anterior and medial dorsal nuclei. Through functional connectivity analysis of the fMRI data, the pulvinar was found to be functionally associated with the same widespread cortical visual areas where the fMRI signals were negatively correlated with the posterior alpha modulation. In contrast, the dorsal nuclei were part of a distinct functional network that included brain stem, cingulate cortex and cerebellum. These observations are consistent with previous animal electrophysiology studies and the notion that the visual thalamus, and the pulvinar in particular, is intimately involved in the generation and spontaneous modulation of posterior alpha rhythms, facilitated by its reciprocal and widespread interaction with the cortical visual areas. We further postulate that the anterior and medial dorsal nuclei, being part of the ascending neuromodulatory system, may indirectly modulate cortical alpha rhythms by affecting vigilance and arousal levels.

Electrophysiological correlation patterns of resting state networks in single subjects: a combined EEG-fMRI study

With combined EEG-fMRI a powerful combination of methods was developed in the last decade that seems promising for answering fundamental neuroscientific questions by measuring functional processes of the human brain simultaneously with two complementary modalities. Recently, resting state networks (RSNs), representing brain regions of coherent BOLD fluctuations, raised major interest in the neuroscience community. Since RSNs are reliably found across subjects and reflect task related networks, changes in their characteristics might give insight to neuronal changes or damage, promising a broad range of scientific and clinical applications. The question of how RSNs are linked to electrophysiological signal characteristics becomes relevant in this context. In this combined EEG-fMRI study we investigated the relationship of RSNs and their correlated electrophysiological signals [electrophysiological correlation patterns (ECPs)] using a long (34 min) resting state scan per subject. This allowed us to study ECPs on group as well as on single subject level, and to examine the temporal stability of ECPs within each subject. We found that the correlation patterns obtained on group level show a large inter-subject variability. During the long scan the ECPs within a subject show temporal fluctuations, which we interpret as a result of the complex temporal dynamic of the RSNs.

Resting-state quantitative electroencephalography reveals increased neurophysiologic connectivity in depression

Symptoms of Major Depressive Disorder (MDD) are hypothesized to arise from dysfunction in brain networks linking the limbic system and cortical regions. Alterations in brain functional cortical connectivity in resting-state networks have been detected with functional imaging techniques, but neurophysiologic connectivity measures have not been systematically examined. We used weighted network analysis to examine resting state functional connectivity as measured by quantitative electroencephalographic (qEEG) coherence in 121 unmedicated subjects with MDD and 37 healthy controls. Subjects with MDD had significantly higher overall coherence as compared to controls in the delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), and beta (12-20 Hz) frequency bands. The frontopolar region contained the greatest number of "hub nodes" (surface recording locations) with high connectivity. MDD subjects expressed higher theta and alpha coherence primarily in longer distance connections between frontopolar and temporal or parietooccipital regions, and higher beta coherence primarily in connections within and between electrodes overlying the dorsolateral prefrontal cortical (DLPFC) or temporal regions. Nearest centroid analysis indicated that MDD subjects were best characterized by six alpha band connections primarily involving the prefrontal region. The present findings indicate a loss of selectivity in resting functional connectivity in MDD. The overall greater coherence observed in depressed subjects establishes a new context for the interpretation of previous studies showing differences in frontal alpha power and synchrony between subjects with MDD and normal controls. These results can inform the development of qEEG state and trait biomarkers for MDD.

Brain state regulation during normal development: Intrinsic activity fluctuations in simultaneous EEG-fMRI

Brain maturation in adolescence is mirrored by the EEG as a pronounced decrease in low frequency activity. This EEG power attenuation parallels reductions of structural and metabolic markers of neuronal maturation (i.e., gray matter loss and decrease of absolute cerebral glucose utilization). However, it is largely unknown what causes these electrophysiological changes, and how this functional reorganization relates to other functional measures such as the fMRI BOLD signal. In this study, we used simultaneously recorded EEG and fMRI to localize hemodynamic correlates of fluctuating EEG oscillations and to study the development of this EEG-BOLD coupling. Furthermore, the maturational EEG power attenuation was directly compared to BOLD signal power maturation. Both analyses were novel in their developmental perspective and aimed at providing a functional lead to EEG maturation. Data from 19 children, 18 adolescents and 18 young adults were acquired in 10 min eyes-open/eyes-closed resting states. Our results revealed that both EEG and BOLD amplitudes strongly decrease between childhood and adulthood, but their functional coupling remains largely unchanged. The global reduction of absolute amplitude of spontaneous slow BOLD signal fluctuation is a novel marker for brain maturation, and parallels the globally decreasing trajectories of EEG amplitudes, gray matter and glucose metabolism during adolescence. Further, the absence of thalamocortical EEG-BOLD coupling in children together with age-related normalized thalamic BOLD power increase indicated maturational changes in brain state regulation.

Neuromagnetic oscillations and hemodynamic correlates of P50 suppression in schizophrenia

Behavioral and electrophysiological data indicate compromised stimulus suppression in schizophrenia. The physiological basis of this effect and its contributions to the etiology of the disease are poorly understood. We examined neural and metabolic measures of P50 suppression in 12 patients with schizophrenia and controls. First, whole-head magnetoencephalography (MEG) assessed amplitudes of left- and right-hemispheric evoked responses and induced oscillations. Secondly, functional magnetic resonance imaging (fMRI) measured the hemodynamic responses to pairs of beeps with a short interval (500ms) as compared with those with a long interval (1500ms). The suppression of alpha power (8-13Hz) time-locked to the stimuli was negatively correlated with the suppression of evoked components and the hemodynamic measures. Remarkably, the suppression of alpha power was reduced in the patients already prior to stimulus onset. Conceivably, alpha oscillations play a central role in stimulus adaptation of neuronal networks and reflect an active mechanism for sensory suppression. The reduced stimulus suppression in schizophrenia seems to be in part due to impaired generation of alpha oscillations in the auditory cortex, resulting in higher metabolic demand as detected by fMRI. Delayed recovery of alpha rhythm may reflect an impaired gating function and contribute to sensory and cognitive deficits in schizophrenia.

How ongoing neuronal oscillations account for evoked fMRI variability

Variability of evoked single-trial responses despite constant input or task is a feature of large-scale brain signals recorded by fMRI. Initial evidence signified relevance of fMRI signal variability for perception and behavior. Yet the underlying intrinsic neuronal sources have not been previously substantiated. Here, we address this issue using simultaneous EEG-fMRI and real-time classification of ongoing alpha-rhythm states triggering visual stimulation in human subjects. We investigated whether spontaneous neuronal oscillations-as reflected in the posterior alpha rhythm-account for variability of evoked fMRI responses. Based on previous work, we specifically hypothesized linear superposition of fMRI activity related to fluctuations of ongoing alpha rhythm and a visually evoked fMRI response. We observed that spontaneous alpha-rhythm power fluctuations largely explain evoked fMRI response variance in extrastriate, thalamic, and cerebellar areas. For extrastriate areas, we confirmed the linear superposition hypothesis. We hence linked evoked fMRI response variability to an intrinsic rhythm's power fluctuations. These findings contribute to our conceptual understanding of how brain rhythms can account for trial-by-trial variability in stimulus processing.

Modeling the contribution of neuron-astrocyte cross talk to slow blood oxygenation level-dependent signal oscillations

A consistent and prominent feature of brain functional magnetic resonance imaging (fMRI) data is the presence of low-frequency (<0.1 Hz) fluctuations of the blood oxygenation level-dependent (BOLD) signal that are thought to reflect spontaneous neuronal activity. In this report we provide modeling evidence that cyclic physiological activation of astroglial cells produces similar BOLD oscillations through a mechanism mediated by intracellular Ca(2+) signaling. Specifically, neurotransmission induces pulses of Ca(2+) concentration in astrocytes, resulting in increased cerebral perfusion and neuroactive transmitter release by these cells (i.e., gliotransmission), which in turn stimulates neuronal activity. Noticeably, the level of neuron-astrocyte cross talk regulates the periodic behavior of the Ca(2+) wave-induced BOLD fluctuations. Our results suggest that the spontaneous ongoing activity of neuroglial networks is a potential source of the observed slow fMRI signal oscillations.

Current source density measures of electroencephalographic alpha predict antidepressant treatment response

BACKGROUND

Despite recent success in pharmacologic treatment of depression, the inability to predict individual treatment response remains a liability. This study replicates and extends findings relating pretreatment electroencephalographic (EEG) alpha to treatment outcomes for serotonergic medications.

METHODS

Resting EEG (eyes-open and eyes-closed) was recorded from a 67-electrode montage in 41 unmedicated depressed patients and 41 healthy control subjects. Patients were tested before receiving antidepressants including a serotonergic mode of action (selective serotonin reuptake inhibitor [SSRI], serotonin and norepinephrine reuptake inhibitor, or SSRI plus norepinephrine and dopamine reuptake inhibitor). EEG was quantified by frequency principal components analysis of spectra derived from reference-free current source density (CSD) waveforms, which sharpens and simplifies EEG topographies, disentangles them from artifact, and yields measures that more closely represent underlying neuronal current generators.

RESULTS

Patients who did not respond to treatment had significantly less alpha CSD compared with responders or healthy control subjects, localizable to well-defined posterior generators. The alpha difference between responders and nonresponders was greater for eyes-closed than eyes-open conditions and was present across alpha subbands. A classification criterion based on the median alpha for healthy control subjects showed good positive predictive value (93.3) and specificity (92.3). There was no evidence of differential value for predicting response to an SSRI alone or dual treatment targeting serotonergic plus other monoamine neurotransmitters.

CONCLUSIONS

Findings confirm the value of EEG alpha amplitude as a viable predictor of antidepressant response and suggest that personalized treatments for depression may be identified using simple electrophysiologic CSD measures.