Neuroimaging of epilepsy: lesions, networks, oscillations

While analysis and interpretation of structural epileptogenic lesion is an essential task for the neuroradiologist in clinical practice, a substantial body of epilepsy research has shown that focal lesions influence brain areas beyond the epileptogenic lesion, across ensembles of functionally and anatomically connected brain areas. In this review article, we aim to provide an overview about altered network compositions in epilepsy, as measured with current advanced neuroimaging techniques to characterize the initiation and spread of epileptic activity in the brain with multimodal noninvasive imaging techniques. We focus on resting-state functional magnetic resonance imaging (MRI) and simultaneous electroencephalography/fMRI, and oppose the findings in idiopathic generalized versus focal epilepsies. These data indicate that circumscribed epileptogenic lesions can have extended effects on many brain systems. Although epileptic seizures may involve various brain areas, seizure activity does not spread diffusely throughout the brain but propagates along specific anatomic pathways that characterize the underlying epilepsy syndrome. Such a functionally oriented approach may help to better understand a range of clinical phenomena such as the type of cognitive impairment, the development of pharmacoresistance, the propagation pathways of seizures, or the success of epilepsy surgery.

Cortical reorganisation of cerebral networks after childhood stroke: impact on outcome.

BACKGROUND Recovery after arterial ischaemic stroke is known to largely depend on the plastic properties of the brain. The present study examines changes in the network topography of the developing brain after stroke. Effects of brain damage are best assessed by examining entire networks rather than single sites of structural lesions. Relating these changes to post-stroke neuropsychological variables and motor abilities will improve understanding of functional plasticity after stroke. Inclusion of healthy controls will provide additional insight into children's normal brain development. Resting state functional magnetic resonance imaging is a valid approach to topographically investigate the reorganisation of functional networks after a brain lesion. Transcranial magnetic stimulation provides complementary output information. This study will investigate functional reorganisation after paediatric arterial ischaemic stroke by means of resting state functional magnetic resonance imaging and transcranial magnetic stimulation in a cross-sectional plus longitudinal study design. The general aim of this study is to better understand neuroplasticity of the developing brain after stroke in order to develop more efficacious therapy and to improve the post-stroke functional outcome. METHODS The cross-sectional part of the study will investigate the functional cerebral networks of 35 children with chronic arterial ischaemic stroke (time of the lesion >2 years). In the longitudinal part, 15 children with acute arterial ischaemic stroke (shortly after the acute phase of the stroke) will be included and investigations will be performed 3 times within the subsequent 9 months. We will also recruit 50 healthy controls, matched for age and sex. The neuroimaging and neurophysiological data will be correlated with neuropsychological and neurological variables. DISCUSSION This study is the first to combine resting state functional magnetic resonance imaging and transcranial magnetic stimulation in a paediatric population diagnosed with arterial ischaemic stroke. Thus, this study has the potential to uniquely contribute to the understanding of neuronal plasticity in the brains of healthy children and those with acute or chronic brain injury. It is expected that the results will lead to the development of optimal interventions after arterial ischaemic stroke.

Epileptic networks are strongly connected with and without the effects of interictal discharges

OBJECTIVE Epilepsy is increasingly considered as the dysfunction of a pathologic neuronal network (epileptic network) rather than a single focal source. We aimed to assess the interactions between the regions that comprise the epileptic network and to investigate their dependence on the occurrence of interictal epileptiform discharges (IEDs). METHODS We analyzed resting state simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) recordings in 10 patients with drug-resistant focal epilepsy with multifocal IED-related blood oxygen level-dependent (BOLD) responses and a maximum t-value in the IED field. We computed functional connectivity (FC) maps of the epileptic network using two types of seed: (1) a 10-mm diameter sphere centered in the global maximum of IED-related BOLD map, and (2) the independent component with highest correlation to the IED-related BOLD map, named epileptic component. For both approaches, we compared FC maps before and after regressing out the effect of IEDs in terms of maximum and mean t-values and percentage of map overlap. RESULTS Maximum and mean FC maps t-values were significantly lower after regressing out IEDs at the group level (p < 0.01). Overlap extent was 85% ± 12% and 87% ± 12% when the seed was the 10-mm diameter sphere and the epileptic component, respectively. SIGNIFICANCE Regions involved in a specific epileptic network show coherent BOLD fluctuations independent of scalp EEG IEDs. FC topography and strength is largely preserved by removing the IED effect. This could represent a signature of a sustained pathologic network with contribution from epileptic activity invisible to the scalp EEG.

EEG microstate analysis in drug-naive patients with panic disorder

Patients with panic disorder (PD) have a bias to respond to normal stimuli in a fearful way. This may be due to the preactivation of fear-associated networks prior to stimulus perception. Based on EEG, we investigated the difference between patients with PD and normal controls in resting state activity using features of transiently stable brain states (microstates). EEGs from 18 drug-naive patients and 18 healthy controls were analyzed. Microstate analysis showed that one class of microstates (with a right-anterior to left-posterior orientation of the mapped field) displayed longer durations and covered more of the total time in the patients than controls. Another microstate class (with a symmetric, anterior-posterior orientation) was observed less frequently in the patients compared to controls. The observation that selected microstate classes differ between patients with PD and controls suggests that specific brain functions are altered already during resting condition. The altered resting state may be the starting point of the observed dysfunctional processing of phobic stimuli.

Quantification of network perfusion in ASL cerebral blood flow data with seed based and ICA approaches

Independent component analysis (ICA) or seed based approaches (SBA) in functional magnetic resonance imaging blood oxygenation level dependent (BOLD) data became widely applied tools to identify functionally connected, large scale brain networks. Differences between task conditions as well as specific alterations of the networks in patients as compared to healthy controls were reported. However, BOLD lacks the possibility of quantifying absolute network metabolic activity, which is of particular interest in the case of pathological alterations. In contrast, arterial spin labeling (ASL) techniques allow quantifying absolute cerebral blood flow (CBF) in rest and in task-related conditions. In this study, we explored the ability of identifying networks in ASL data using ICA and to quantify network activity in terms of absolute CBF values. Moreover, we compared the results to SBA and performed a test-retest analysis. Twelve healthy young subjects performed a fingertapping block-design experiment. During the task pseudo-continuous ASL was measured. After CBF quantification the individual datasets were concatenated and subjected to the ICA algorithm. ICA proved capable to identify the somato-motor and the default mode network. Moreover, absolute network CBF within the separate networks during either condition could be quantified. We could demonstrate that using ICA and SBA functional connectivity analysis is feasible and robust in ASL-CBF data. CBF functional connectivity is a novel approach that opens a new strategy to evaluate differences of network activity in terms of absolute network CBF and thus allows quantifying inter-individual differences in the resting state and task-related activations and deactivations.

Meditators and non-meditators: EEG source imaging during resting

Many meditation exercises aim at increased awareness of ongoing experiences through sustained attention and at detachment, i.e., non-engaging observation of these ongoing experiences by the intent not to analyze, judge or expect anything. Long-term meditation practice is believed to generalize the ability of increased awareness and greater detachment into everyday life. We hypothesized that neuroplasticity effects of meditation (correlates of increased awareness and detachment) would be detectable in a no-task resting state. EEG recorded during resting was compared between Qigong meditators and controls. Using LORETA (low resolution electromagnetic tomography) to compute the intracerebral source locations, differences in brain activations between groups were found in the inhibitory delta EEG frequency band. In the meditators, appraisal systems were inhibited, while brain areas involved in the detection and integration of internal and external sensory information showed increased activation. This suggests that neuroplasticity effects of long-term meditation practice, subjectively described as increased awareness and greater detachment, are carried over into non-meditating states.

The brain’s default state interacts with working memory processes in a complex and load-dependent manner

Recently, many studies about a network active during rest and deactivated during tasks emerged in the literature: the default mode network (DMN). Spatial and temporal DMN features are important markers for psychiatric diseases. Another prominent indicator of cognitive functioning, yielding information about the mental condition in health and disease, is working memory (WM) processing. In EEG studies, frontal-midline theta power has been shown to increase with load during WM retention in healthy subjects. From these findings, the conclusion can be drawn that an increase in resting state DMN activity may go along with an increase in theta power in high-load WM conditions. We followed this hypothesis in a study on 17 healthy subjects performing a visual Sternberg WM task. The DMN was obtained by a BOLD-ICA approach and its dynamics represented by the percent-strength during pre-stimulus periods. DMN dynamics were temporally correlated with EEG theta spectral power from retention intervals. This so-called covariance mapping yielded the spatial distribution of the theta EEG fluctuations associated with the dynamics of the DMN. In line with previous findings, theta power was increased at frontal-midline electrodes in high- versus low-load conditions during early WM retention. However, load-dependent correlations of DMN with theta power resulted in primarily positive correlations in low-load conditions, while during high-load conditions negative correlations of DMN activity and theta power were observed at frontal-midline electrodes. This DMN-dependent load effect reached significance during later retention. Our results show a complex and load-dependent interaction of pre-stimulus DMN activity and theta power during retention, varying over the course of the retention period. Since both, WM performance and DMN activity, are markers of mental health, our results could be important for further investigations of psychiatric populations.

The brain’s pre-stimulus default state interacts with working memory in a load-dependent manner

Recently, multiple studies showed that spatial and temporal features of a task-negative default mode network (DMN) (Greicius et al., 2003) are important markers for psychiatric diseases (Balsters et al., 2013). Another prominent indicator of cognitive functioning, yielding information about the mental condition in health and disease, is working memory (WM) processing. In EEG and MEG studies, frontal-midline theta power has been shown to increase with load during WM retention in healthy subjects (Brookes et al., 2011). Negative correlations between DMN activity and theta amplitude have been found during resting state (Jann et al., 2010) as well as during WM (Michels et al., 2010). Likewise, WM training resulted in higher resting state theta power as well as increased small-worldness of the resting brain (Langer et al., 2013). Further, increased fMRI connectivity between nodes of the DMN correlated with better WM performance (Hampson et al., 2006). Hence, the brain’s default state might influence it’s functioning during task. We therefore hypothesized correlations between pre-stimulus DMN activity and EEG-theta power during WM maintenance, depending on the WM load. 17 healthy subjects performed a Sternberg WM task while being measured simultaneously with EEG and fMRI. Data was recorded within a multicenter-study: 12 subjects were measured in Zurich with a 64-channels MR-compatible system (Brain Products) in a 3T Philips scanner, 5 subjects with a 96-channel MR-compatible system (Brain Products) in a 3T Siemens Scanner in Bern. The DMN components was obtained by a group BOLD-ICA approach over the full task duration (figure 1). The subject-wise dynamics were obtained by back-reconstructed onto each subject’s fMRI data and normalized to percent signal change values. The single trial pre-stimulus-DMN activation was then temporally correlated with the single trial EEG-theta (3-8 Hz) spectral power during retention intervals. This so-called covariance mapping (Jann et al., 2010) yielded the spatial distribution of the theta EEG fluctuations during retention associated with the dynamics of the pre-stimulus DMN. In line with previous findings, theta power was increased at frontal-midline electrodes in high- versus low-load conditions during early WM retention (figure 2). However, correlations of DMN with theta power resulted in primarily positive correlations in low-load conditions, while during high-load conditions negative correlations of DMN activity and theta power were observed at frontal-midline electrodes. This DMN-dependent load effect reached significance in the middle of the retention period (TANOVA, p<0.05) (figure 3). Our results show a complex and load-dependent interaction of pre-stimulus DMN activity and theta power during retention, varying over time. While at a more global, load-independent view pre-stimulus DMN activity correlated positively with theta power during retention, the correlation was inversed during certain time windows in high-load trials, meaning that in trials with enhanced pre-stimulus DMN activity theta power decreases during retention. Since both WM performance and DMN activity are markers of mental health our results could be important for further investigations of psychiatric populations.

15 Years of Microstate Research in Schizophrenia - Where Are We? A Meta-Analysis

Schizophrenia patients show abnormalities in a broad range of task demands. Therefore, an explanation common to all these abnormalities has to be sought independently of any particular task, ideally in the brain dynamics before a task takes place or during resting state. For the neurobiological investigation of such baseline states, EEG microstate analysis is particularly well suited, because it identifies subsecond global states of stable connectivity patterns directly related to the recruitment of different types of information processing modes (e.g., integration of top-down and bottom-up information). Meanwhile, there is an accumulation of evidence that particular microstate networks are selectively affected in schizophrenia. To obtain an overall estimate of the effect size of these microstate abnormalities, we present a systematic meta-analysis over all studies available to date relating EEG microstates to schizophrenia. Results showed medium size effects for two classes of microstates, namely, a class labeled C that was found to be more frequent in schizophrenia and a class labeled D that was found to be shortened. These abnormalities may correspond to core symptoms of schizophrenia, e.g., insufficient reality testing and self-monitoring as during auditory verbal hallucinations. As interventional studies have shown that these microstate features may be systematically affected using antipsychotic drugs or neurofeedback interventions, these findings may help introducing novel diagnostic and treatment options.

Altered directed functional connectivity in temporal lobe epilepsy in the absence of interictal spikes: A high density EEG study.

OBJECTIVE In patients with epilepsy, seizure relapse and behavioral impairments can be observed despite the absence of interictal epileptiform discharges (IEDs). Therefore, the characterization of pathologic networks when IEDs are not present could have an important clinical value. Using Granger-causal modeling, we investigated whether directed functional connectivity was altered in electroencephalography (EEG) epochs free of IED in left and right temporal lobe epilepsy (LTLE and RTLE) compared to healthy controls. METHODS Twenty LTLE, 20 RTLE, and 20 healthy controls underwent a resting-state high-density EEG recording. Source activity was obtained for 82 regions of interest (ROIs) using an individual head model and a distributed linear inverse solution. Granger-causal modeling was applied to the source signals of all ROIs. The directed functional connectivity results were compared between groups and correlated with clinical parameters (duration of the disease, age of onset, age, and learning and mood impairments). RESULTS We found that: (1) patients had significantly reduced connectivity from regions concordant with the default-mode network; (2) there was a different network pattern in patients versus controls: the strongest connections arose from the ipsilateral hippocampus in patients and from the posterior cingulate cortex in controls; (3) longer disease duration was associated with lower driving from contralateral and ipsilateral mediolimbic regions in RTLE; (4) aging was associated with a lower driving from regions in or close to the piriform cortex only in patients; and (5) outflow from the anterior cingulate cortex was lower in patients with learning deficits or depression compared to patients without impairments and to controls. SIGNIFICANCE Resting-state network reorganization in the absence of IEDs strengthens the view of chronic and progressive network changes in TLE. These resting-state connectivity alterations could constitute an important biomarker of TLE, and hold promise for using EEG recordings without IEDs for diagnosis or prognosis of this disorder.

Uniform approach to linear and nonlinear interrelation patterns in multivariate time series

Currently, a variety of linear and nonlinear measures is in use to investigate spatiotemporal interrelation patterns of multivariate time series. Whereas the former are by definition insensitive to nonlinear effects, the latter detect both nonlinear and linear interrelation. In the present contribution we employ a uniform surrogate-based approach, which is capable of disentangling interrelations that significantly exceed random effects and interrelations that significantly exceed linear correlation. The bivariate version of the proposed framework is explored using a simple model allowing for separate tuning of coupling and nonlinearity of interrelation. To demonstrate applicability of the approach to multivariate real-world time series we investigate resting state functional magnetic resonance imaging (rsfMRI) data of two healthy subjects as well as intracranial electroencephalograms (iEEG) of two epilepsy patients with focal onset seizures. The main findings are that for our rsfMRI data interrelations can be described by linear cross-correlation. Rejection of the null hypothesis of linear iEEG interrelation occurs predominantly for epileptogenic tissue as well as during epileptic seizures.

Different molecular and structural adaptations with eccentric and conventional strength training in elderly men and women

Reprogramming of gene expression contributes to structural and functional adaptation of muscle tissue in response to altered use. The aim of this study was to investigate mechanisms for observed improvements in leg extension strength, gain in relative thigh muscle mass and loss of body and thigh fat content in response to eccentric and conventional strength training in elderly men (n = 14) and women (n = 14; average age of the men and women: 80.1 ± 3.7 years) by means of structural and molecular analyses. Biopsies were collected from m. vastus lateralis in the resting state before and after 12 weeks of training with two weekly resistance exercise sessions (RET) or eccentric ergometer sessions (EET). Gene expression was analyzed using custom-designed low-density PCR arrays. Muscle ultrastructure was evaluated using EM morphometry. Gain in thigh muscle mass was paralleled by an increase in muscle fiber cross-sectional area (hypertrophy) with RET but not with EET, where muscle growth is likely occurring by the addition of sarcomeres in series or by hyperplasia. The expression of transcripts encoding factors involved in muscle growth, repair and remodeling (e.g., IGF-1, HGF, MYOG, MYH3) was increased to a larger extent after EET than RET. MicroRNA 1 expression was decreased independent of the training modality, and was paralleled by an increased expression of IGF-1 representing a potential target. IGF-1 is a potent promoter of muscle growth, and its regulation by microRNA 1 may have contributed to the gain of muscle mass observed in our subjects. EET depressed genes encoding mitochondrial and metabolic transcripts. The changes of several metabolic and mitochondrial transcripts correlated significantly with changes in mitochondrial volume density. Intramyocellular lipid content was decreased after EET concomitantly with total body fat. Changes in intramyocellular lipid content correlated with changes in body fat content with both RET and EET. In the elderly, RET and EET lead to distinct molecular and structural adaptations which might contribute to the observed small quantitative differences in functional tests and body composition parameters. EET seems to be particularly convenient for the elderly with regard to improvements in body composition and strength but at the expense of reducing muscular oxidative capacity.

Neural correlates of disbalanced motor control in major depression

Motor retardation is a common symptom of major depressive disorder (MDD). Despite the existence of various assessment methods, little is known on the pathobiology of motor retardation. We aimed to elucidate aspects of motor control investigating the association of objective motor activity and resting state cerebral blood flow (CBF).

Effects of transcranial direct current stimulation (tDCS) on behaviour and electrophysiology of language production

Excitatory anodal transcranial direct current stimulation (A-tDCS) over the left dorsal prefrontal cortex (DPFC) has been shown to improve language production. The present study examined neurophysiological underpinnings of this effect. In a single-blinded within-subject design, we traced effects of A-tDCS compared to sham stimulation over the left DPFC using electrophysiological and behavioural correlates during overt picture naming. Online effects were examined during A-tDCS by employing the semantic interference (SI-)Effect – a marker that denotes the functional integrity of the language system. The behavioural SI-Effect was found to be reduced, whereas the electrophysiological SI-Effect was enhanced over left compared to right temporal scalp-electrode sites. This modulation is suggested to reflect a superior tuning of neural responses within language-related generators. After -(offline) effects of A-tDCS were detected in the delta frequency band, a marker of neural inhibition. After A-tDCS there was a reduction in delta activity during picture naming and the resting state, interpreted to indicate neural disinhibition. Together, these findings demonstrate electrophysiological modulations induced by A-tDCS of the left DPFC. They suggest that A-tDCS is capable of enhancing neural processes during and after application. The present functional and oscillatory neural markers could detect positive effects of prefrontal A-tDCS, which could be of use in the neuro-rehabilitation of frontal language functions.

Discovering imaging endophenotypes for major depression

Psychiatry research lacks an in-depth understanding of mood disorders phenotypes, leading to limited success of genetics studies of major depressive disorder (MDD). The dramatic progress in safe and affordable magnetic resonance-based imaging methods has the potential to identify subtle abnormalities of neural structures, connectivity and function in mood disordered subjects. This review paper presents strategies to improve the phenotypic definition of MDD by proposing imaging endophenotypes derived from magnetic resonance spectroscopy measures, such as cortical gamma-amino butyric acid (GABA) and glutamate/glutamine concentrations, and from measures of resting-state activity and functional connectivity. The proposed endophenotypes are discussed regarding specificity, mood state-independence, heritability, familiarity, clinical relevance and possible associations with candidate genes. By improving phenotypic definitions, the discovery of new imaging endophenotypes will increase the power of candidate gene and genome-wide associations studies. It will also help to develop and evaluate novel therapeutic treatments and enable clinicians to apply individually tailored therapeutic approaches. Finally, improvements of the phenotypic definition of MDD based on neuroimaging measures will contribute to a new classification system of mood disorders based on etiology and pathophysiology.