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.

Amplitude, Topographie und Latenz von EKP-Komponenten analysiert mit Hilfe von Randomisierungsstatistiken: Ein anwendungsorientierter Ragu-Workshop

Bei EKP-Experimenten ist oft nicht von vornherein klar, in welchen Zeitfenstern Effekte erwartet werden. Daher müssen Analysen die Daten über mehrere Zeitfenster hinweg explorieren. Darüber hinaus sind statistische Analysen, die alle Elektroden berücksichtigen, wünschenswert, aber nicht trivial. Zur Lösung dieser Probleme präsentieren wir hier das Programm Ragu (Randomization Graphical User interface), das spezifisch für die statistische Auswertung von Mehrkanal EEG-Experimenten eingesetzt werden kann. Ragu soll Wissenschaftlern die Möglichkeit geben, die Signifikanzen von EKP-Effekten global zu untersuchen, ohne die Notwendigkeit von A-Priori-Annahmen. Das Programm basiert auf der Messung von Feldstärke-Differenzen unter Berücksichtigung aller Elektroden. Im ersten Teil dieses Workshops werden wir die Notwendigkeit von topografischen ERP-Analysen angesichts des Volumenleitungsproblems herausarbeiten und Vergleiche zu Einzelelektroden-Ansätzen anstellen. Wir werden an Hand unserer frei erhältlichen in-house Software Ragu das Prinzip von Randomisierungsstatistiken erklären und deren unterschiedliche Anwendungsmöglichkeiten für ERP-Analysen. In einem zweiten Teil haben die Teilnehmenden die Gelegenheit, Ragu an einem Beispielsatz auszuprobieren und Möglichkeiten der Anwendung von Ragu in ihrer eigenen Forschungs zu besprechen.

The association between implicit alcohol attitudes and drinking behavior is moderated by baseline activation in the lateral prefrontal cortex

OBJECTIVE Intense alcohol consumption is a risk factor for a number of health problems. Dual-process models assume that self-regulatory behavior such as drinking alcohol is guided by both reflective and impulsive processes. Evidence suggests that (a) impulsive processes such as implicit attitudes are more strongly associated with behavior when executive functioning abilities are low, and (b) higher neural baseline activation in the lateral prefrontal cortex (PFC) is associated with better inhibitory control. The present study integrates these 2 strands of research to investigate how individual differences in neural baseline activation in the lateral PFC moderate the association between implicit alcohol attitudes and drinking behavior. METHOD Baseline cortical activation was measured with resting electroencephalography (EEG) in 89 moderate drinkers. In a subsequent behavioral testing session they completed measures of implicit alcohol attitudes and self-reported drinking behavior. RESULTS Implicit alcohol attitudes were related to self-reported alcohol consumption. Most centrally, implicit alcohol attitudes were more strongly associated with drinking behavior in individuals with low as compared with high baseline activation in the right lateral PFC. CONCLUSIONS These findings are in line with predictions made on the basis of dual-process models. They provide further evidence that individual differences in neural baseline activation in the right lateral PFC may contribute to executive functioning abilities such as inhibitory control. Moreover, individuals with strongly positive implicit alcohol attitudes coupled with a low baseline activation in the right lateral PFC may be at greater risk of developing unhealthy drinking patterns than others.

Baclofen facilitates sleep, neuroplasticity, and recovery after stroke in rats.

OBJECTIVE Sleep disruption in the acute phase after stroke has detrimental effects on recovery in both humans and animals. Conversely, the effect of sleep promotion remains unclear. Baclofen (Bac) is a known non-rapid eye movement (NREM) sleep-promoting drug in both humans and animals. The aim of this study was to investigate the effect of Bac on stroke recovery in a rat model of focal cerebral ischemia (isch). METHODS Rats, assigned to three experimental groups (Bac/isch, saline/isch, or Bac/sham), were injected twice daily for 10 consecutive days with Bac or saline, starting 24 h after induction of stroke. The sleep-wake cycle was assessed by EEG recordings and functional motor recovery by single pellet reaching test (SPR). In order to identify potential neuroplasticity mechanisms, axonal sprouting and neurogenesis were evaluated. Brain damage was assessed by Nissl staining. RESULTS Repeated Bac treatment after ischemia affected sleep, motor function, and neuroplasticity, but not the size of brain damage. NREM sleep amount was increased significantly during the dark phase in Bac/isch compared to the saline/isch group. SPR performance dropped to 0 immediately after stroke and was recovered slowly thereafter in both ischemic groups. However, Bac-treated ischemic rats performed significantly better than saline-treated animals. Axonal sprouting in the ipsilesional motor cortex and striatum, and neurogenesis in the peri-infarct region were significantly increased in Bac/isch group. CONCLUSION Delayed repeated Bac treatment after stroke increased NREM sleep and promoted both neuroplasticity and functional outcome. These data support the hypothesis of the role of sleep as a modulator of poststroke recovery.

The structural substrate of brain function: analysis of brain structural networks based on diffusion-weighted imaging

The brain is a complex neural network with a hierarchical organization and the mapping of its elements and connections is an important step towards the understanding of its function. Recent developments in diffusion-weighted imaging have provided the opportunity to reconstruct the whole-brain structural network in-vivo at a large scale level and to study the brain structural substrate in a framework that is close to the current understanding of brain function. However, methods to construct the connectome are still under development and they should be carefully evaluated. To this end, the first two studies included in my thesis aimed at improving the analytical tools specific to the methodology of brain structural networks. The first of these papers assessed the repeatability of the most common global and local network metrics used in literature to characterize the connectome, while in the second paper the validity of further metrics based on the concept of communicability was evaluated. Communicability is a broader measure of connectivity which accounts also for parallel and indirect connections. These additional paths may be important for reorganizational mechanisms in the presence of lesions as well as to enhance integration in the network. These studies showed good to excellent repeatability of global network metrics when the same methodological pipeline was applied, but more variability was detected when considering local network metrics or when using different thresholding strategies. In addition, communicability metrics have been found to add some insight into the integration properties of the network by detecting subsets of nodes that were highly interconnected or vulnerable to lesions. The other two studies used methods based on diffusion-weighted imaging to obtain knowledge concerning the relationship between functional and structural connectivity and about the etiology of schizophrenia. The third study integrated functional oscillations measured using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) as well as diffusion-weighted imaging data. The multimodal approach that was applied revealed a positive relationship between individual fluctuations of the EEG alpha-frequency and diffusion properties of specific connections of two resting-state networks. Finally, in the fourth study diffusion-weighted imaging was used to probe for a relationship between the underlying white matter tissue structure and season of birth in schizophrenia patients. The results are in line with the neurodevelopmental hypothesis of early pathological mechanisms as the origin of schizophrenia. The different analytical approaches selected in these studies also provide arguments for discussion of the current limitations in the analysis of brain structural networks. To sum up, the first studies presented in this thesis illustrated the potential of brain structural network analysis to provide useful information on features of brain functional segregation and integration using reliable network metrics. In the other two studies alternative approaches were presented. The common discussion of the four studies enabled us to highlight the benefits and possibilities for the analysis of the connectome as well as some current limitations.

Compact low-power cortical recording architecture for compressive multichannel data acquisition

This paper introduces an area- and power-efficient approach for compressive recording of cortical signals used in an implantable system prior to transmission. Recent research on compressive sensing has shown promising results for sub-Nyquist sampling of sparse biological signals. Still, any large-scale implementation of this technique faces critical issues caused by the increased hardware intensity. The cost of implementing compressive sensing in a multichannel system in terms of area usage can be significantly higher than a conventional data acquisition system without compression. To tackle this issue, a new multichannel compressive sensing scheme which exploits the spatial sparsity of the signals recorded from the electrodes of the sensor array is proposed. The analysis shows that using this method, the power efficiency is preserved to a great extent while the area overhead is significantly reduced resulting in an improved power-area product. The proposed circuit architecture is implemented in a UMC 0.18 [Formula: see text]m CMOS technology. Extensive performance analysis and design optimization has been done resulting in a low-noise, compact and power-efficient implementation. The results of simulations and subsequent reconstructions show the possibility of recovering fourfold compressed intracranial EEG signals with an SNR as high as 21.8 dB, while consuming 10.5 [Formula: see text]W of power within an effective area of 250 [Formula: see text]m × 250 [Formula: see text]m per channel.

Dynamic directed interictal connectivity in left and right temporal lobe epilepsy.

OBJECTIVE There is increasing evidence that epileptic activity involves widespread brain networks rather than single sources and that these networks contribute to interictal brain dysfunction. We investigated the fast-varying behavior of epileptic networks during interictal spikes in right and left temporal lobe epilepsy (RTLE and LTLE) at a whole-brain scale using directed connectivity. METHODS In 16 patients, 8 with LTLE and 8 with RTLE, we estimated the electrical source activity in 82 cortical regions of interest (ROIs) using high-density electroencephalography (EEG), individual head models, and a distributed linear inverse solution. A multivariate, time-varying, and frequency-resolved Granger-causal modeling (weighted Partial Directed Coherence) was applied to the source signal of all ROIs. A nonparametric statistical test assessed differences between spike and baseline epochs. Connectivity results between RTLE and LTLE were compared between RTLE and LTLE and with neuropsychological impairments. RESULTS Ipsilateral anterior temporal structures were identified as key drivers for both groups, concordant with the epileptogenic zone estimated invasively. We observed an increase in outflow from the key driver already before the spike. There were also important temporal and extratemporal ipsilateral drivers in both conditions, and contralateral only in RTLE. A different network pattern between LTLE and RTLE was found: in RTLE there was a much more prominent ipsilateral to contralateral pattern than in LTLE. Half of the RTLE patients but none of the LTLE patients had neuropsychological deficits consistent with contralateral temporal lobe dysfunction, suggesting a relationship between connectivity changes and cognitive deficits. SIGNIFICANCE The different patterns of time-varying connectivity in LTLE and RTLE suggest that they are not symmetrical entities, in line with our neuropsychological results. The highest outflow region was concordant with invasive validation of the epileptogenic zone. This enhanced characterization of dynamic connectivity patterns could better explain cognitive deficits and help the management of epilepsy surgery candidates.

Association between intraoperative electroencephalographic suppression and postoperative mortality

BACKGROUND Low bispectral index values frequently reflect EEG suppression and have been associated with postoperative mortality. This study investigated whether intraoperative EEG suppression was an independent predictor of 90 day postoperative mortality and explored risk factors for EEG suppression. METHODS This observational study included 2662 adults enrolled in the B-Unaware or BAG-RECALL trials. A cohort was defined with >5 cumulative minutes of EEG suppression, and 1:2 propensity-matched to a non-suppressed cohort (≤5 min suppression). We evaluated the association between EEG suppression and mortality using multivariable logistic regression, and examined risk factors for EEG suppression using zero-inflated mixed effects analysis. RESULTS Ninety day postoperative mortality was 3.9% overall, 6.3% in the suppressed cohort, and 3.0% in the non-suppressed cohort {odds ratio (OR) [95% confidence interval (CI)]=2.19 (1.48-3.26)}. After matching and multivariable adjustment, EEG suppression was not associated with mortality [OR (95% CI)=0.83 (0.55-1.25)]; however, the interaction between EEG suppression and mean arterial pressure (MAP) <55 mm Hg was [OR (95% CI)=2.96 (1.34-6.52)]. Risk factors for EEG suppression were older age, number of comorbidities, chronic obstructive pulmonary disease, and higher intraoperative doses of benzodiazepines, opioids, or volatile anaesthetics. EEG suppression was less likely in patients with cancer, preoperative alcohol, opioid or benzodiazepine consumption, and intraoperative nitrous oxide exposure. CONCLUSIONS Although EEG suppression was associated with increasing anaesthetic administration and comorbidities, the hypothesis that intraoperative EEG suppression is a predictor of postoperative mortality was only supported if it was coincident with low MAP. CLINICAL TRIAL REGISTRATION NCT00281489 and NCT00682825.

Psychomotor retardation is linked to frontal alpha asymmetry in major depression

BACKGROUND Psychomotor disturbances are a main clinical feature of major depressive disorder (MDD) but little is known about their EEG signature. One of the most replicated EEG findings in MDD is resting frontal asymmetry in the alpha band (FAA), which is thought to be a correlate of withdrawal behavior and reduced approach motivation. The purpose of this study was to assess psychomotor alterations, alpha band power, FAA and investigate the association between them. METHODS 20 MDD patients and 19 healthy subjects were enrolled. Alpha power and FAA scores were calculated from a resting state EEG. Wrist actigraphy was recorded from the non-dominant arm for 24 h and activity level scores (AL) were extrapolated from the wakeful periods. RESULTS MDD patients had a left-lateralized frontal alpha activity and lower AL scores when compared to healthy subjects. A significant correlation was found between mean FAA and AL scores. A negative covariance between power in the lower alpha range and AL scores over the motor cortex bilaterally was detected. LIMITATIONS Relatively small sample size. Patients were pharmacologically treated with antidepressants. CONCLUSIONS This study replicates the finding of left-lateralized FAA and lower AL scores in MDD patients, and establishes the first evidence of significant correlations between alpha power, FAA scores and measures of motor activity, which may be interpreted as an expression of impaired motivational drive in MDD.

Differential recruitment of brain networks during visuospatial and color processing: Evidence from ERP microstates

Recent functional magnetic resonance imaging (fMRI) studies consistently revealed contributions of fronto-parietal and related networks to the execution of a visuospatial judgment task, the so-called "Clock Task". However, due to the low temporal resolution of fMRI, the exact cortical dynamics and timing of processing during task performance could not be resolved until now. In order to clarify the detailed cortical activity and temporal dynamics, 14 healthy subjects performed an established version of the "Clock Task", which comprises a visuospatial task (angle discrimination) and a control task (color discrimination) with the same stimulus material, in an electroencephalography (EEG) experiment. Based on the time-resolved analysis of network activations (microstate analysis), differences in timing between the angle compared to the color discrimination task were found after sensory processing in a time window starting around 200ms. Significant differences between the two tasks were observed in an analysis window from 192ms to 776ms. We divided this window in two parts: an early phase - from 192ms to ∼440ms, and a late phase - from ∼440ms to 776ms. For both tasks, the order of network activations and the types of networks were the same, but, in each phase, activations for the two conditions were dominated by differing network states with divergent temporal dynamics. Our results provide an important basis for the assessment of deviations in processing dynamics during visuospatial tasks in clinical populations.

Statistical Learning, Syllable Processing, and Speech Production in Healthy Hearing and Hearing-Impaired Preschool Children: A Mismatch Negativity Study

OBJECTIVES The objectives of the present study were to investigate temporal/spectral sound-feature processing in preschool children (4 to 7 years old) with peripheral hearing loss compared with age-matched controls. The results verified the presence of statistical learning, which was diminished in children with hearing impairments (HIs), and elucidated possible perceptual mediators of speech production. DESIGN Perception and production of the syllables /ba/, /da/, /ta/, and /na/ were recorded in 13 children with normal hearing and 13 children with HI. Perception was assessed physiologically through event-related potentials (ERPs) recorded by EEG in a multifeature mismatch negativity paradigm and behaviorally through a discrimination task. Temporal and spectral features of the ERPs during speech perception were analyzed, and speech production was quantitatively evaluated using speech motor maximum performance tasks. RESULTS Proximal to stimulus onset, children with HI displayed a difference in map topography, indicating diminished statistical learning. In later ERP components, children with HI exhibited reduced amplitudes in the N2 and early parts of the late disciminative negativity components specifically, which are associated with temporal and spectral control mechanisms. Abnormalities of speech perception were only subtly reflected in speech production, as the lone difference found in speech production studies was a mild delay in regulating speech intensity. CONCLUSIONS In addition to previously reported deficits of sound-feature discriminations, the present study results reflect diminished statistical learning in children with HI, which plays an early and important, but so far neglected, role in phonological processing. Furthermore, the lack of corresponding behavioral abnormalities in speech production implies that impaired perceptual capacities do not necessarily translate into productive deficits.

Towards Using Microstate-Neurofeedback for the Treatment of Psychotic Symptoms in Schizophrenia. A Feasibility Study in Healthy Participants

Spontaneous EEG signal can be parsed into sub-second periods of stable functional states (microstates) that assumingly correspond to brief large scale synchronization events. In schizophrenia, a specific class of microstate (class "D") has been found to be shorter than in healthy controls and to be correlated with positive symptoms. To explore potential new treatment options in schizophrenia, we tested in healthy controls if neurofeedback training to self-regulate microstate D presence is feasible and what learning patterns are observed. Twenty subjects underwent EEG-neurofeedback training to up-regulate microstate D presence. The protocol included 20 training sessions, consisting of baseline trials (resting state), regulation trials with auditory feedback contingent on microstate D presence, and a transfer trial. Response to neurofeedback was assessed with mixed effects modelling. All participants increased the percentage of time spent producing microstate D in at least one of the three conditions (p < 0.05). Significant between-subjects across-sessions results showed an increase of 0.42 % of time spent producing microstate D in baseline (reflecting a sustained change in the resting state), 1.93 % of increase during regulation and 1.83 % during transfer. Within-session analysis (performed in baseline and regulation trials only) showed a significant 1.65 % increase in baseline and 0.53 % increase in regulation. These values are in a range that is expected to have an impact upon psychotic experiences. Additionally, we found a negative correlation between alpha power and microstate D contribution during neurofeedback training. Given that microstate D has been related to attentional processes, this result provides further evidence that the training was to some degree specific for the attentional network. We conclude that microstate-neurofeedback training proved feasible in healthy subjects. The implementation of the same protocol in schizophrenia patients may promote skills useful to reduce positive symptoms by means of EEG-neurofeedback.

What do brain network interactions tell about cognitive processes? How to seek causality?

Optimal adjustment of brain networks allows the biased processing of information in response to the demand of environments and is therefore prerequisite for adaptive behaviour. It is widely shown that a biased state of networks is associated with a particular cognitive process. However, those associations were identified by backward categorization of trials and cannot provide a causal association with cognitive processes. This problem still remains a big obstacle to advance the state of our field in particular human cognitive neuroscience. In my talk, I will present two approaches to address the causal relationships between brain network interactions and behaviour. Firstly, we combined connectivity analysis of fMRI data and a machine leaning method to predict inter-individual differences of behaviour and responsiveness to environmental demands. The connectivity-based classification approach outperforms local activation-based classification analysis, suggesting that interactions in brain networks carry information of instantaneous cognitive processes. Secondly, we have recently established a brand new method combining transcranial alternating current stimulation (tACS), transcranial magnetic stimulation (TMS), and EEG. We use the method to measure signal transmission between brain areas while introducing extrinsic oscillatory brain activity and to study causal association between oscillatory activity and behaviour. We show that phase-matched oscillatory activity creates the phase-dependent modulation of signal transmission between brain areas, while phase-shifted oscillatory activity blunts the phase-dependent modulation. The results suggest that phase coherence between brain areas plays a cardinal role in signal transmission in the brain networks. In sum, I argue that causal approaches will provide more concreate backbones to cognitive neuroscience.

Minimized Extracorporeal Circulation does not impair cognitive brain function after coronary artery bypass grafting

Gebiet: Chirurgie Abstract: Minimized Extracorporeal Circulation does not impair cognitive brain function after coronary artery bypass grafting – – Objectives – Objective evaluation of the impact of minimized extracorporeal circulation (MECC) on perioperative cognitive brain function in coronary bypass grafting (CABG) by Electroencephalogram (EEG) P 300 wave event related potentials (ERP) and number connection test ( NCT) as metrics of cognitive function. – – Methods – Cognitive brain function was assessed in 31 patients with a mean age of 65y (Standard Deviation/SD 10) undergoing coronary artery bypass grafting (CABG) by the use of MECC with P300 auditory evoked potentials (peak latencies in milliseconds [ms]) directly prior to intervention, 7 days after and 3 month later. Number connection test (NCT), serving as method of control, was performed simultaneously in all patients. – – Results – Seven days following CABG, cognitive P300 evoked potentials were comparable to preoperative baseline values (vertex [Cz] 376 (SD 11) ms vs. 378 (18) ms, p=0.39, frontal [Fz] 377 (11) vs. 379 (21) ms, p=0.53). Cognitive brain function showed at 3 months compared to baseline values ([Cz] 376 (11) ms vs. 371 (14 ms) p=0.09, [Fz] 377 (11) ms vs. 371 (15) ms, p=0.04. Between the first postoperative measurement and 3 months later, significant improvement was observed ([Cz] 378 (18) ms vs. 371 (14) ms, p=0.03, [Fz] 379 (21) vs. 371 (15) ms, p=0.02). Similar clearly corresponding patterns could be obtained via number connection test. Results could be confirmed in repeated measures analysis of variance for Cz (p = 0.05) and (Fz) results (p = 0.04). – – Conclusions

The spectrum of the non-rapid eye movement sleep electroencephalogram following total sleep deprivation is trait-like

The sleep electroencephalogram (EEG) spectrum is unique to an individual and stable across multiple baseline recordings. The aim of this study was to examine whether the sleep EEG spectrum exhibits the same stable characteristics after acute total sleep deprivation. Polysomnography (PSG) was recorded in 20 healthy adults across consecutive sleep periods. Three nights of baseline sleep [12 h time in bed (TIB)] following 12 h of wakefulness were interleaved with three nights of recovery sleep (12 h TIB) following 36 h of sustained wakefulness. Spectral analysis of the non-rapid eye movement (NREM) sleep EEG (C3LM derivation) was used to calculate power in 0.25 Hz frequency bins between 0.75 and 16.0 Hz. Intraclass correlation coefficients (ICCs) were calculated to assess stable individual differences for baseline and recovery night spectra separately and combined. ICCs were high across all frequencies for baseline and recovery and for baseline and recovery combined. These results show that the spectrum of the NREM sleep EEG is substantially different among individuals, highly stable within individuals and robust to an experimental challenge (i.e. sleep deprivation) known to have considerable impact on the NREM sleep EEG. These findings indicate that the NREM sleep EEG represents a trait.