Behavioral reports have traditionally been the gold standard for evaluating the presence of consciousness. However, it is becoming clear that consciousness can be present even in the absence of overt behavior and in unresponsive subjects. I will present neurophysiological evidence supporting the presence of consciousness in dissociated states from several domains. Measures of cortical integration and differentiation have recently proven to be the most reliable marker of consciousness irrespective of behavior and have been validated in a large number of different conditions. The most common dissociation between consciousness and behavior occurs every night during dreaming sleep. Recent work using both within-state, no-task paradigms and TMS-EEG shows that consciousness can be present during non REM sleep when the front of the brain shows high amplitude slow waves, as long as a posterior cortical hot zone is activated. Studies using different anesthetics have also shown that fully unresponsive subjects anesthetized with ketamine (as compared to propofol or xenon) retrospectively report intense dreams, which are again associated with high complexity responses to TMS, despite the occurrence of slow waves. High complexity responses can also be observed in about 20% of patients in a vegetative state suggesting, in line with previous findings using active paradigms, that a number of completely unresponsive patients may retain consciousness. Finally, a number of studies in healthy awake volunteers have emphasized frequent dissociations between consciousness and task-related cognitive functions. Overall, recent findings show that the anatomical neural correlates of consciousness are primarily localized to a posterior cortical hot zone that includes sensory areas, rather than to a fronto-parietal network involved in task monitoring and reporting. I will end by discussing promising avenues of future research.

Intracranial recordings from patients with epilepsy detect electrical activity at multiple spatial and temporal scales to guide epilepsy surgery. Additionally, patients may participate in cognitive tasks that advance our understanding of high-level cognitive functions. In this symposium, we will first address iEEG oscillations in auditory cortex during the perception of auditory and visual speech (PM). Next, we will characterize the spatial scales of memory networks by simultaneously recording scalp EEG, hippocampal iEEG and single neuron activity (JS, FM). Finally, we show how intraoperative single pulse stimulation elicits perturbations at different temporal scales, which help to tailor the resection of the epileptogenic zone (GH). The symposium elucidates how multi-scale recordings serve to deal with scientific questions in neuroscience and clinical application.

Speech is essentially multisensory: the movements that we make when we speak are visible to our interlocutors. How do visual speech cues influence the processing of speech sounds by auditory cortex? To address this question, we showed short movies containing naturalistic speech to patients undergoing evaluation with intracranial EEG electrodes for epilepsy surgery. Auditory cortex responded to purely visual speech with an alignment of the phase of its low-frequency oscillations. Our results indicate that auditory cortex tracks the temporal dynamics of visual speech and support the role of neuronal oscillations in multisensory integration more generally.

Objective: Verbal working memory elicits workload-dependent theta and alpha oscillations in the frontal and parietal surface EEG (Michels, 2008), but the involvement of subcortical nodes is not known.

Methods: Epilepsy patients with electrodes in the hippocampus and on the scalp performed a modified Sternberg task with setsize 4, 6 and 8 letters. We analyzed the time-frequency profile and the phase locking value (PLV) in theta (4-8 Hz) and alpha (8-12 Hz) and high gamma (> 100 Hz) frequency bands while stimuli were encoded and retained in memory.

Results: In 9 of 10 participants, the theta/alpha PLV was elevated between hippocampus and scalp. In 4 participants, the PLV increased with setsize, predominantly towards the end of the retention period and to frontal and parietal electrodes. Two participants showed strong frontal midline theta and parietal alpha during retention, in agreement with our earlier scalp EEG study. Concurrently, the workload and/or the task conditions modulated the hippocampal theta/alpha and high-gamma power.

Conclusion: While hippocampal activity is known for visuospatial memory tasks, we show here hippocampal involvement also in a cortical network that is activated during verbal working memory and mediated by synchronized theta/alpha EEG oscillations.

Neurons in the human medial temporal lobe are tuned to semantic rather than perceptual features of visual stimuli. These neurons’ activity thus seems to correlate with contents of conscious experience, making them a prime candidate for a content-specific neuronal correlate of consciousness. In this talk, I will first present a study further exploring the nature of these semantic representations, and then present a series of studies aimed at exploring putative single neuron correlates of conscious awareness. One approach is to use adaptive algorithms to continuously estimate perceptual thresholds individually for patients and stimuli. Here, stimuli are presented either very near or clearly above or clearly below this threshold to disentangle effects of stimulus intensity from effects of awareness on spiking activity. These procedures were used to vary noise in visual stimuli when recording from medial temporal lobe neurons, and volume of auditory stimuli in one patient with electrodes in primary auditory areas. Another approach entailed using the attentional blink phenomenon to investigate spiking activity in response to stimuli that are sometimes seen and sometimes not detected at all. Here, we find that neurons fire in response to their preferred stimulus, even when participants reported absence of awareness of that stimulus. Remarkably, neuronal responses to unseen versus seen stimuli were delayed and temporally more dispersed, in addition to being generally attenuated in firing rate. Modulation of neuronal response timing and strength in response to seen versus unseen stimuli was found to increase along an anatomical gradient from posterior to anterior medial temporal lobe areas.

To be completed

Session chair: Prof. Serge Vulliemoz

Reason for choosing this topic: There is increasing evidence about the usefulness of functional brain connectivity to help diagnose epilepsy, to localize the epileptogenic focus or to unravel brain mechanisms that impact the patient’s life. However, these techniques have limitations and are currently not used in clinical practice. In this session we want to emphasize the methodologies that are used to calculate the functional connectivity pattern, define the added value of functional brain networks derived from EEG signals and discuss important issues in this field to pave the way for their implementation in clinical practice.

Functional MRI has been used increasingly to characterize brain networks in epilepsy and typically shows patterns of decreased connectivity within and increased connectivity between intrinsic cognitive networks (ICN), which in turn has been shown to be associated with cognitive performance. At the same time we know that focal epilepsy is associated with networks that show enhanced connectivity and produce periods of high EEG synchronicity in the form of epileptic discharges which can have a transient impact on cognition and cognitive networks. We have used simultaneous EEG and fMRI to try to tease apart the transient and longer term connectivity differences between focal epilepsy patients and controls. Perhaps surprisingly, ICNs are commonly perturbed by epileptic discharges arising from different brain areas and they explain a large degree of ICN connectivity abnormalities. Functional connectivity measured with fMRI is therefore very sensitivity to transient epileptic activity.

High frequency oscillations (Ripples: 80-250Hz, Fast Ripples (FR): 250-500Hz) are novel biomarkers for epileptogenic tissue. The pathophysiology suggests enhanced functional connectivity within FR-generating tissue. Our aim was to determine the relation between brain areas showing FRs and ‘baseline’ high frequency functional network characteristics. We compared the Eigenvector Centrality between channels that did and did not show events in epilepsy patients. We found functional isolation in the gamma-band and a suggestion of functional integration in the FR-band network of channels covering epileptogenic tissue. ‘Baseline’ high-frequency network parameters might help intra-operative recognition of epileptogenic tissue without the need for waiting for events.

<p>The brain is a complex system of neuronal populations, which establish functional connections during task execution and at rest. BOLD fMRI allows studying the spatial properties of these functional networks; however, it cannot reveal fast interactions which are needed to explain sub-second neural processing. Recent studies have shown that Hidden Markov Modelling (HMM) of MEG data can reveal consistent patterns of brain states fluctuating at small time scales. In this talk we will show that HMM analysis of EEG reveals a rich collection of such fast transient networks. Moreover, we investigate the BOLD correlates of these networks using simultaneously recorded fMRI data. Finally, we extend this methodology to epilepsy patients and characterize fast interactions between resting-state networks during interictal activity.</p>

Directed functional brain connectivity has been shown useful to localize the seizure onset zone in refractory epilepsy patients from intracranial EEG. In this presentation this methodology is extended so it can be applied to scalp EEG. First EEG source imaging is performed and later Granger causality measures such as the partial directed coherence and directed transfer function are calculated to unravel the network at source level. The proposed method is used to successfully localize the seizure onset zone from clinical EEG recordings in 23 patients. Furthermore, we show the capability of the method to classify 20 left from 20 right temporal lobe epilepsy patients based from the networks derived from high density EEG acquired during resting state.

We investigated effects of the presentation of auditory (A), somatorsensory (S), and visual (V) stimuli that were presented separately or in combination. 38 healthy adults (25.7 y, 9 m, 29 f) participated. First, vision and hearing were tested. Sensory thresholds were determined for each modality, and stimuli above threshold were used during EEG recordings. Visual stimuli were checkerboard patterns (250 ms). Auditory stimuli were bursts of white noise (100 ms, 60 dBA SPL). Mechanical stimuli were applied to the left index finger (15 g; 20 ms duration). Stimuli were presented in a randomized as A, S, V, S/A, S/V, A/V, or A/S/V. For each condition a total of 200 stimuli was used. EEG was recorded from 64 electrodes, artifacts were discarded offline, and ERPs were averaged according to experimental condition over 1 s. Global field power analysis revealed various time segments where differences were observed. Components were determined by spatial PCA; five components accounted for more than 85 % of the variance. Llatency was defined by the occurrence of extreme values of component scores. At the respective times experimental conditions were compared by repeated-measures ANOVAs. Various components were affected very early after stimulus presentation: At 30 ms latency an effect was seen for A/V (F(2,74)=5.28, p<0.0072). Auditory and somatosensory processing interacted even earlier (18 ms, F(2,74)=5.25, p<0.0075). Other significant differences support the notion that multisensory processing occurs very early, affecting auditory, somatosensory, and visual processing in the human brain.

Structural and functional connectivity metrics have been shown to be powerful predictors of behavioral and cognitive performance. Furthermore, by tracking across the lifespan, these metrics can provide objective metrics of developmental differences, or of aging, and be used as a clinical diagnostic tool by revealing pathologies.

However, the complexity of these datasets makes it sometimes difficult to understand ; better visualization of the results might be beneficial. Accordingly, we have developed a software-based library, “MultiXplore” which can be used by Neuroscientists, Diagnostic Clinicians, and Neurosurgeons for planning procedural approaches. We demonstrate the utility of this tool for Research in Neuroscience (to contrast with previous presentations showing the utility for surgical planning).

For example with development, as the myelin increases, one sees an increase in structural connectivity; in contrast, with aging, FA values decrease in multiple locations affecting structural connectivity. We also see overall changes in functional connectivity. The integration of both types of differences would otherwise be difficult to visualize.

We demonstrate the utility of this tool for Neuroscience with a demonstration using the “Geneva dataset” which is a lifespan study aggregating over 80 subjects, including behavioral, structural, and functional data.

Cognitive system can cause to phase transitions for emergence which is highly nonlinear information dynamics of phase-amplitude information exchange coupling in beta-gamma band. We provide a hypothesis that the emergence of null spikes with single or higher order derivatives as cognitive structures determine the locations of cinematographic events as successive time frames in brain. We will associate an entropy with those null spikes, as key indicators of self-organization. A signal processing approach based on the relationship between phase transitions and power-law behavior in 10-20 channel beta-gamma band provide a strong evidence. We use an information-entropic measure of spatiotemporal complexity derived from two dimensional analytical signal which is a Hilbert Transform of each channel. One dimension depicts beta band while other dimension is being gamma band. Multidimensional representation conveys dynamically modulating different neural populations in both beta and gamma band to enable goal directed behavior.

We quantify both the storage and exchange of information within a Shannon entropy framework. We investigate the behavior of entropy at critical which is linked to null-spikes. This quantitative information shows the relation between information and the emergence of ordered phase transitions over multiple electrodes..

Synchronized brain oscillations are considered a basis for inter-regional neuronal communication. However, the causal role of inter-regional oscillatory phase-synchrony in modulating cortico-cortical signaling efficacy has so far not been directly demonstrated.

To address this relationship, we employed the simultaneous use of transcranial alternating current stimulation (tACS), TMS and EEG. Through tACS we introduced theta oscillatory activity in two regions of the human frontoparietal network; the dorsolateral prefrontal cortex (DLPFC) and posterior parietal cortex (PPC). We applied 6 Hz tACS to the DLPFC and PPC simultaneously in an in-phase or anti-phase manner. For assessing resultant changes in transmission in the frontoparietal network, we simultaneously applied weak single-pulse TMS over the DLPFC at four different phases of tACS (90°, 180°, 270°, 360°) and measured the spread of TMS-evoked EEG potentials (TEPs). The amount of current spread is modulated by the functional status of the neural network, thereby providing a measure of changes in signaling efficacy.

We found that the amplitude of TEPs depended on the phase of the introduced 6 Hz activity during in-phase and anti-phase tACS. These phase-dependent changes of TEPs quickly propagated from the DLPFC to occipital areas in the in-phase condition. However, in the anti-phase condition, phase-dependent changes in TEPs did not reach occipital areas before 100 ms after the TMS, suggesting that the tACS-induced de-synchronization of the frontoparietal network limited communication in the network.

Our results demonstrate the causal role of phase-synchronized endogenous oscillatory activity in modulating inter-regional neuronal communication, in accordance with the proposed communication-through-coherence model.

Background: Transcranial direct current stimulation (tDCS) is a non-invasive approach to modulate cortical excitability. Anodal tDCS is a promising method to enhance working memory (WM) in both healthy people and patients with neurological and psychiatric diseases. However, the underlying mechanisms of anodal tDCS on the enhancement of working memory are yet largely unknown. The purpose of this study was to investigate the effect of anodal tDCS on network connectivity of memory-related circuit in rat brain. Methods: Anodal tDCS was applied over the left prefrontal cortex of rat brain for 20 min at 0.2 mA. Multi-channel local field potentials (LFPs) were obtained from right prefrontal cortex, bilateral cingulate cortex and bilateral hippocampus. The directions of information flow and the strengths of the effective connectivity among these brain regions were calculated using the time-varying Granger causal connectivity approach. Results: The information flow of cingulate cortex input came from both prefrontal cortex and hippocampus. 20 minutes of anodal tDCS at 0.2 mA resulted in a enhancement in the overall strengths of the effective connectivity among right prefrontal cortex, bilateral cingulate cortex and bilateral hippocampus. Especially, the enhancement was more significant from right hippocampus to bilateral cingulate cortex than any other regions. Conclusion: Results indicate that anodal tDCS at 0.2 mA enhances the network connectivity of memory-related circuit in rat brain. Anodal tDCS may improve working memory by enhancing the strengths of the effective connectivity between hippocampus and cingulate cortex.

Voluntary selective attention operates through top-down mechanisms of signal enhancement and suppression, mediated by oscillations in the α-band. But how such top-down influences regulate processing in visual cortex remains poorly understood.

In the present work, we combined dynamic Granger-causality analysis based on EEG source imaging, and phase-amplitude coupling (PAC) measures to characterize the pattern of large-scale directed interactions that orchestrates selective attention, and how these interactions affect stimulus processing in visual areas.

Under changing task demands, twelve subjects either attended to or ignored briefly presented gratings. Time-varying, directed connectivity analysis showed rapid increases of bottom-up γ-band interactions from visual areas in response to attended stimuli. Ignored stimuli, instead, evoked distributed and sustained top-down α-band interactions, originating from parietal cortex. These connectivity changes occurred together with increased α-γ PAC in visual areas for attended stimuli. Furthermore, multi-level modeling revealed that parietal α-band interactions disrupted the α-γ coupling in visual cortex, which in turn reduced the amount of γ-band outflow from visual areas.

Our results are a first demonstration of how directed interactions affect cross-frequency coupling in downstream areas. These findings suggest that parietal cortex realizes selective attention by disrupting cross-frequency coupling at target regions in a way that prevents them from propagating task-irrelevant information.

It is now widely accepted that epilepsy is a disease of brain networks. During presurgical evaluation, a combination of brain mapping modalities can be used such as EEG, MEG, PET, funtional MRI in order to map these networks non-invasively. In a second phase, electrodes can be implanted within the brain, which can record directly within brain structures and confirm/ infirm clinical hypotheses - this is Stereotaxic EEG (SEEG). Each modality has advantages and disadvantages; in order to optimise the use of brain mapping tools, it is therefore crucial to understand how to make best use of these complementary methods. In this context, two questions arise: what are the best markers of epileptogenic tissues, as visible on intracerebral signals, and how can we retrieve them non-invasively. In this talk, I will present recent results on network measures and characterization of high frequency activities. I will also discuss strategies based on simultaneous recordings in for characterizing the links between modalities, in animal models and in patients. In particular, I will show the feasibility of simultaneous EEG-MEG-SEEG recordings thanks to a visual stimulation paradigm and discuss their application to the development of signal processing methods, modelling and diagnosis.

Early clinical detection in psychotic disorders has become a major objective of mental health services, while research on the early phases of the disorder may provide important clues to the pathophysiology underlying psychotic symptoms. Thus, the identification of a clinical syndrome that reflects a predisposition to schizophrenia is fundamental from a clinical and a research perspective. The onset of schizophrenia is usually preceded by a prodromal phase characterized by functional decline and subtle negative symptoms. Structural and functional neuroimaging techniques including brain connectivity analyses have rapidly developed into a powerful tool in psychiatry. In this presentation it will be aimed to show that neuroimaging studies of the prodromal phases of psychosis have the potentials to identify core markers of vulnerability to psychosis and to clarify the onset of psychosis.

Organizer: Matti Stenroos, Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Finland

To understand and treat the human brain, we need to understand its dynamical activity. Brain oscillations, for example, have been associated with perceptive and cognitive functions, but the mechanism of coupling between the oscillations and brain function is not well understood yet. To study this coupling or the interaction between nodes in a functional brain network, we need to be able to modulate the brain in a controlled way and measure the effects of this modulation online. Non-invasive electric or magnetic brain stimulation (NIBS) offers a way for modulating the brain activity directly at electrophysiological level, and the effects of stimulation can be measured using electro- or magnetoencephalography (EEG, MEG).

To reliably measure the effects of electric stimulation during the stimulation and to ensure the repeatability of the experiment, we need dedicated hardware. To plan a stimulation study, to accurately navigate the stimulation coil, and to interpret the measured data, we greatly benefit from modeling of the stimulation and measurement. To optimally manipulate brain dynamics, we need to time the stimulation accurately with brain oscillations that need to be extracted from EEG data in near real time. In this symposium, we discuss these key methodological issues of NIBS and combined NIBS+MEG/EEG and present our latest results. The symposium brings together renowned experts in the field of methodological developments for NIBS & EEG/MEG.

The symposium is complementary to Gregor Thut's keynote lecture, taking a more methodological perspective.

We introduce a bifunctional flexible textile cap for simultaneous TES-EEG applications with novel electrode materials, textile stimulation electrodes and dry EEG electrodes. We verified the functionality of this cap in a study on ten volunteers, analyzing the stimulation effect of TES on visual evoked potentials (VEPs). In accordance to previously reported stimulation effects, the amplitude of the N75 component was modulated post stimulation. Further, we report for the first time a significant reduction of the P100 component in VEPs measured simultaneously during TES. The novel bifunctional cap overcomes limitations of conventional equipment for simultaneous TES-EEG studies.

I will provide evidence that field modeling informed by individual structural MRI combined with electromyographical recordings of peripheral muscle responses to TMS can help to pinpoint the stimulated brain region and reveal the stimulation depth of TMS. I will further show that realistic field modeling can help to determine the origin of interindividual differences in the physiological TMS effects. Finally, I will report on recent advances in Magnetic Resonance Current Density Imaging (MRCDI) to measure the current flow pattern caused by the weak currents injected by electric brain stimulation in the human brain.

To understand and treat the human brain, we need to understand its dynamical activity. Brain oscillations, for example, have been associated with perceptive and cognitive functions, but the mechanism of coupling between the oscillations and brain function is not well understood yet. To study this coupling or the interaction between nodes in a functional brain network, we need to be able to modulate the brain in a controlled way and measure the effects of this modulation online. Non-invasive electric or magnetic brain stimulation (NIBS) offers a way for modulating the brain activity directly at electrophysiological level, and the effects of stimulation can be measured using electro- or magnetoencephalography (EEG, MEG).

To reliably measure the effects of electric stimulation during the stimulation and to ensure the repeatability of the experiment, we need dedicated hardware. To plan a stimulation study, to accurately navigate the stimulation coil, and to interpret the measured data, we greatly benefit from modeling of the stimulation and measurement. To optimally manipulate brain dynamics, we need to time the stimulation accurately with brain oscillations that need to be extracted from EEG data in near real time. In this symposium, we discuss these key methodological issues of NIBS and combined NIBS+MEG/EEG and present our latest results. The symposium brings together renowned experts in the field of methodological developments for NIBS & EEG/MEG.

The symposium is complementary to Gregor Thut's keynote lecture, taking a more methodological perspective.

Using custom-built state-dependent millisecond-accurate electroencephalography-triggered transcranial magnetic stimulation (EEG-TMS) of human motor cortex, we demonstrate that phases of EEG peak negativity versus EEG peak positivity of the endogenous sensorimotor µ-alpha rhythm reflect high- vs. low-excitability states of corticospinal neurons. Moreover, otherwise identical repetitive TMS, triggered consistently at these high-excitability vs. low-excitability states, leads to LTP- vs. LTD-like change in corticospinal excitability. This raises the intriguing possibility that real-time information of instantaneous brain state can be utilized to control direction of plasticity in humans, a prospective with clear potential for therapeutic modulation of brain networks in psychiatric and neurological disease.

The neurological or psychiatric diseases distort the communication in the brain’s connected networks. In a sense, a person with a brain disorder can become unreachable due to dysfunctional integration within and across brain networks as well as impaired processing and integration of incoming sensory signals. The brain’s ability to adapt depends on feedback signaled through the five sensory channels, which produce neuronal synchrony which drives neuronal plasticity. Hence, deficiencies in communication via the senses requires alternative ways to engage adaptation in a diseased brain— one potent way is via transcranial neuromodulation, bypassing the afferents sensory channels, another one is to use the brain activity translated into signals sent as feedback via multimodal sensory channels (brain based neurofeedback).

Even in our personal experience, sometimes the ‘magic’ understanding with a dear person can get sick, we do not understand each other anymore. And, which is the wisest advice in this case? TO LISTEN!

Aiming at developing proper neuromodulation interventions, we propose listening to the brain affected by a disease via proper neuroimaging techniques.

Symposium speakers will present methods and proper strategies to define targets for neuroenhancing brain stimulation. Risto Ilmoniemi will describe the concept of feedback-controlled multi-coil TMS showing initial results. Frank Scharnowski will describe how to define targets for connectivity-based neurofeedback training aiming at normalizing dysfunctional brain networks; Toni Valero-Cabré, how to interact by invasive and non-invasive recordings and stimulations with rhythmic brain activity, with an example against neglect in stroke patients; Hartwig Siebner will describe how modeling can enhance noninvasive transcranial brain stimulation at the biophysical, network, and cognitive level; Franca Tecchio, how to personalize non-invasive neuromodulation anatomically or exploiting the neuronal dynamics of the target area, with a successful example against multiple sclerosis fatigue.

Changing the locus of transcranial magnetic stimulation (TMS) with present mechanically moved TMS coils is too slow for real-time feedback-controlled targeting. To overcome this limitation and to allow algorithmically guided closed-loop stimulation, we have introduced the concept of multi-coil TMS (mTMS) and developed technology to realize it with multiple overlapping coils. We have demonstrated that the new technology allows electronic control of stimulation location with arbitrarily small delays. In addition, with the new electronics, we have shown that TMS pulse shaping can yield information about neuronal ion-channel kinetics. I will discuss possible applications.

<p>Brain training via real-time fMRI-based neurofeedback can improve performance and clinical symptoms in neurological and psychiatric patients. Here, we inform the training by the connectivity between brain areas rather than the activity of a single node. Using this novel connectivity-based neurofeedback, we improved emotion regulation by training participants to voluntarily increase top-down connectivity from cognitive prefrontal areas onto limbic structures. Moreover, neurofeedback can help substance use disorder patients to learn voluntary control over neurotransmitter centers such as the dopaminergic midbrain, thus indirectly modifying their dopaminergic reward system. These novel methodological innovations allow to more specifically target disease-related brain malfunctions.</p>

<p>We are manipulating the brain activity by means of non-invasive and invasive bursts, in dependence on surface and intracerebral EEG recordings. In healthy humans, the rhythmic bursts TMS manipulation of the right Frontal Eye Fields increases the fronto-parietal synchrony and the conscious visual detection in a frequency specific manner. In treatment-resistant epilepsy patients implanted with depth electrodes, stimulated for clinical purposes with electrical bursts, the local neuronal power increases in a manner dependent on stimulation intensity, frequency, phase and position. We will discuss how manipulating brain networks’ synchrony may open new avenues to treat stroke visuo‑spatial neglect.</p>

The human brain can be stimulated with a wide range of non-invasive transcranial brain stimulation (NTBS) techniques. These methods have great potential as neuroscientific and therapeutic tools, but the application is hampered by substantial intra- and inter-subject variability of the acute and outlasting NTBS effects on brain function. In this talk, I will provide an overview over our recent attempts to obtain a mechanistic understanding of NTBS applying a triple-M approach, consisting of brain mapping, modeling and modulation. I will show how anatomically and physiologically informed NTBS can be used to shape human brain function. I will then show how multi-level modelling at the biophysical, local and network level can reveal how NTBS shapes neural activity in the human brain. Finally, I will touch on novel realizations of NTBS such as targeting brain oscillations with TMS or ultra-high frequency repetitive TMS.

I will present a successful example of adapting to fatigue-related brain dysfunction in people with multiple sclerosis a transcranial direct current stimulation (tDCS), which had increased endurance against fatigue in healthy subjects. The adaptation required a personalized electrode designed and positioned based on the patient’s 3D-brain MRI. While this compensation required an anatomical personalization, we are also personalizing a current-modulated transcranial electric stimulation (tES), by mimicking the local dynamics of the ongoing neuronal activity of the target region. We derived the target neurodynamics by Functional Source Separation (FSS)-equipped electroencephalography (EEG) and we obtained an enhancement of the neuromodulation effects, in particular at individual level.

Resting-state 18F-fallypride positron emission tomography was performed on 25 patients (mean(±sd) age: 31.6±12.2) with schizophrenia (20 medication-naïve and 5 previously medicated for a brief period) and 19 age- and sex-matched healthy volunteers (mean(±sd) age: 29.2±9.3).

Two neuropsychological tasks known to activate frontal and temporal lobe function were chosen, specifically the Wisconsin Card Sorting Test (WCST) and the California Verbal Learning Test (CVLT). Magnetic resonance images in standard Talairach position and segmented into gray and white matter were co-registered to the fallypride images, and the AFNI stereotaxic atlas was applied. Selective AFNI regions of interest (ROIs) were calculated from each subject. We calculated product-moment correlation coefficients between each ROI and the brain areas. Patients with schizophrenia showed negative correlations between binding potential and performance on WCST perseverative errors and CVLT learning slope, while healthy volunteers showed better performance with high binding potential in the frontal cortex and right temporal lobe. The healthy volunteers show positive correlations (red/yellow) indicating that high binding potential is associated with better performance. However patients show the reverse (blue) indicating low binding potential is associated with better performance for WCST.

. The positive correlation may be interpreted as less dopamine is associated with better performance in healthy volunteers. However patients with schizophrenia showed the reverse which suggests a compensatory dopamine system response.These results suggest that partial agonist treatment may assist cognitive performance in schizophrenia.

Background: Motor abnormalities are frequent in schizophrenia. Likewise, schizophrenia is faced with structural and functional dysconnectivity. Here, we tested whether resting state connectivity in the motor system would be aberrant in schizophrenia and linked to motor behavior abnormalities.

Method: In total, 46 patients and 44 controls underwent BOLD resting state scans for 8 mins and performed a comprehensive motor battery. Regions of interest (ROI) were cortical motor areas, basal ganglia, thalamus and motor cerebellum. We computed ROI-to-ROI functional connectivity using CONN. Principal component analyses of motor behavioral data produced four factors (primary motor, catatonia and dyskinesia, coordination, and spontaneous motor activity). We tested group differences in connectivity as well as correlations betwenn motor factor scores and connectivity values.

Results: Schizophrenia was characterized by hyperconnectivity in three main areas: motor cortices to thalamus, motor cortices to cerebellum, and prefrontal cortex to the subthalamic nucleus. In patients, thalamocortical hyperconnectivity was linked to catatonia and dyskinesia, whereas aberrant connectivity between rostral anterior cingulate and caudate was linked to the primary motor factor. Likewise, connectivity between motor cortex and cerebellum correlated with spontaneous motor activity.

Discussion: Altered resting state functional connectivity suggests a specific intrinsic and tonic neural abnormality in the motor system in schizophrenia. Furthermore, altered neural activity at rest was linked to motor abnormalities on the behavioral level. Thus, aberrant resting state connectivity may indicate a system out of balance, which produces characteristic behavioral alterations

Dyscoordination of perceptual sequencing systems is central to many cognitive deficits in schizophrenia. This is well-illustrated by neurophysiological deficits in auditory perceptual grouping and segmentation based on rhythmic sequence structure. Here we examine the N2 and auditory sequence potential (ASP) as they relate to network coordination within sensorimotor sequencing systems in participants at the first psychotic episode (FESz). Twenty-three FESz and 23 matched healthy controls (HC) ignored tone groups while watching a silent cartoon. Stimuli comprised 300 groups of three identical tones (1 kHz; 80 dB; 50 ms duration; 330 ms SOA, 800 ms ITI). Beta entrainment, N2, and ASP were measured to standard groups. ASP sources were localized using minimum-norm estimation for individuals with structural MRI (FESz=14; HC=14). ASP was reduced in FESz compared to HC (p<0.05). N2 responses were not significantly reduced (p>0.1). Source analysis revealed that ASP was generated primarily in bilateral primary auditory cortex (A1) and supplementary motor area (SMA). ASP activity in SMA (p<0.001), but not A1 (p>0.1) was reduced for FESz compared to matched controls. Further, coherent beta-band oscillatory activity was entrained to stimulus onset in HC, but not FESz, and this entrainment correlated with ASP activity in A1 and SMA (r’s>0.3). These results suggest that deficits in auditory pattern processing in schizophrenia occur early in the disease course. Reductions in beta entrainment and SMA activity suggest systems-level dysfunction in sensorimotor sequencing networks in FESz. Further work will assess symptom and functioning concomitants in deficits in this fundamental complex perceptual process.

Psilocybin is a serotonergic psychedelic with an agonist activity at 5-HT2A/C and 5-HT1A receptors. It is used as a research tool to study neurobiology of psychosis as well as it is gaining attention as a possible therapeutic tool to treat depression, anxiety and addiction. It has been already shown that psychedelics including psilocybin acutely induce desynchronization of the alpha activity occipitally and disconnection during the peak of intoxication. However understanding of the dynamics of these changes has not been evaluated yet. Therefore the current study focuses on the behavioural and EEG effects of psilocybin at several time points during the 6 hours of intoxication. Twenty volunteers with a balanced gender ratio (10M/10F) have entered the study. Each participant underwent two sessions with oral psilocybin (0.26 mg/kg) or a placebo in a double blinded crossover design. In most of the subjects, psilocybin induced fully psychedelic effects as measured by psychometric scales, the effects peaked between 1-2 h after administration. Decreased current density of the alpha band in the occipital region which diminished over time was the most robust finding. The connectivity analyses showed biphasic effect on overall connectivity indicating two different connectivity states at the peak of intoxication and 6h after the ingestion. Results will be discussed in relation to the potential therapeutic effects of psilocybin. This study was supported by the projects ED2.1.00/03.0078, LO1611/NPU I, MICR VI20172020056, MH CZ - DRO (NIMH-CZ, 00023752) and PROGRES Q35.

Aim: Mood disorders patients present difficulties to switch away from negative and self-focused automatic thoughts, which might represent the basis for incapacitating symptoms such as rumination. We aimed to investigate the activity in neural networks when patients have to switch between internally and externally focused attention and correlations with rumination scale.

Method: We compared a group of 20 euthymic bipolar patients and a group of 20 matched heathy controls during a fMRI task where they either rate how they are feeling, or how many letters are in the stimulus, using positive and negative adjectives.

Results: The “externally focused” condition elicited activity in a classical attentional network, and the “internally focused” condition in a network with central activations in medial prefrontal and cingulate regions, validating our paradigm. Bipolar patients showed significantly higher activity than controls in the vmPFC, PCC and parietal cortex, and in particular increased activity in pregenual ACC during the internal trials, which correlated with the tendency to ruminate. Switching from an internal to an external trial revealed higher activity in the entorhinal cortex for patients, especially after a negative trial. Repetition of negative internal trials also showed increased and correlated activity in medial areas.

Conclusion: Patients showed higher activity in medial cortical areas during the internally-focused condition, supporting the notion of an enhancement of self-processing in those patients. Negative valence might additionally trigger more activity in network associated with autobiographic memory and rumination.

Simultaneous MR-PET-EEG (magnetic resonance imaging - positron emission tomography – electroencephalography), a new tool for the investigation of neuronal networks in the human brain, is presented here for the first time. It enables the assessment of molecular metabolic information with high spatial and temporal resolution in a given brain simultaneously. Here, we characterize the brain’s default mode network (DMN) in healthy male subjects using multimodal fingerprinting by quantifying energy metabolism via 2- [18F]fluoro-2-desoxy-D-glucose PET (FDG-PET), the inhibition – excitation balance of neuronal activation via magnetic resonance spectroscopy (MRS), its functional connectivity via fMRI and its electrophysiological signature via EEG. The trimodal approach reveals a complementary fingerprint. Neuronal activation within the DMN as assessed with fMRI is positively correlated with the mean standard uptake value of FDG. Electrical source localization of EEG signals shows a significant difference between the dorsal DMN and sensorimotor network in the frequency range of δ, θ, α and β–1, but not with β–2 and β–3. In addition to basic neuroscience questions addressing neurovascular-metabolic coupling, this new methodology lays the foundation for individual physiological and pathological fingerprints for a wide research field addressing healthy aging, gender effects, plasticity and different psychiatric and neurological diseases.

Brain oscillations reflect interactions between neuronal elements which functionally assemble into networks through synchronization in specific frequency bands, and which can be measured by encephalography (EEG/MEG). NTBS on the other hand can be used to stimulate cortical areas rhythmically at frequencies that characterize EEG/MEG-signals. This raises a series of intriguing questions: Could frequency-tuned NTBS be used to transiently entrain oscillatory network activity? Could this enhance the specificity of established NTBS interventions by adding a temporal to the customary spatial dimension of targeting? And may this promote associated functions?

This talk will outline the opportunities of timing NTBS to ongoing brain activity for enhancing its efficacy. Emerging findings emphasize brain oscillations as promising targets for interventions. This offers a principled framework for influencing the brain-behavior relationship by NTBS. The talk will cover research on frequency-tuned rhythmic TMS or tACS, combined with EEG/MEG recordings, to guide and document the effects of transcranial stimulation, with an emphasis on the visual/attention system. This has been used to address whether brain oscillations merely reflect correlates of the neuronal processes implementing brain functions (are inevitable side-products) or may also have explanatory power as to how the brain operates, and by extension may serve as targets for experimental and clinical interventions. Applications that have helped to shed new light on the neural substrates of sensory sampling and attentional selection are highlighted.

EEG for personalized treatment in psychiatry

Despite the call for new treatment options in psychiatry, the biomarker-informed choice of already available therapy approaches might yield important improvements in the management of several disorders such as major depression or obsessive compulsive disorder. With the outstanding ability of assessing neuronal activity with a high temporal resolution at relatively low costs, the EEG seems a perfect tool for personalized treatment. Source localization algorithms such as low resolution brain electromagnetic tomography (LORETA) in combination with hypothesis driven frameworks such as the vigilance framework (VIGALL) that links electrophysiological arousal patterns with clinical syndromes, might help to guide treatment decisions in the future.

The symposium will give insights into the latest developments of EEG based analysis in major depression and obsessive compulsive disorder. The talks will focus on markers that not only differentiate between pathological conditions and healthy controls but also enable prediction of treatment outcome or the relapse after discontinuation of treatment (Quentin Huys, TNU Zurich). Besides markers that reflect brain arousal (EEG-vigilance framework as presented by Ulrich Hegerl, Leipzig), also findings on EEG-based connectivity analysis (Sebastian Olbrich, PUK Zurich) and emotional reactivity measures will be presented. Since the clinical value of a set of predictive markers increases with the number of alternatives for treatment, several treatment approaches will be covered, ranging from psychopharmacological treatment over electroconvulsive therapy to psychotherapeutic interventions and novel treatment approaches such as ketamine (Martin Brunovsky, Prague).

The human brain takes on different arousal levels which can be separated based on the temporal-spatial pattern of scalp recorded EEG activity. The regulation of brain arousal has been found to be intraindividually stable with considerable interindividual differences. The arousal regulation model of affective disorders describes the pathogenetic impact of disturbed brain arousal regulation in psychiatric disorders.

The Vigilance Algorithm Leipzig (VIGALL), an EEG-based algorithm for the classification of vigilance stages, will be introduced. VIGALL takes into account different frequency bands and the cortical distribution of EEG activity using EEG source localization approaches (Low Resolution Electromagnetic Tomography, LORETA) and has adaptive features concerning individual alpha peaks and amplitude levels. Furthermore, an overview on recent findings on arousal regulation as a diagnostic and predictive biomarker in affective disorders will be given.

Not only the topographic or temporal changes of neuronal activity yield important information on the functional principles of the human brain. A main part of the mode of operation is reflected in the interaction of distinct cortical areas. Thus EEG-based connectivity profiles might serve as biomarkers with a clinical prognostic value.

The talk will give an overview on connectivity measures before presenting recent findings of altered connectivity patterns in disorders like obsessive compulsive disorder and major depression and their association with treatment outcome. The presentation will include results from the large randomized clinical trial “International Study to Predict Optimized Treatment for Depression (iSPOT-D)”.

Novel glutamatergic antidepressant, ketamine, does not improve symptoms in all depressive patients, and it is therefore important to identify neurobiological predictors of treatment response. We pooled data from two double-blind, cross-over, placebo-controlled studies, assessing the effect of single infusion of ketamine (0.54 mg/kg within 30min) in 50 depressive patients to evaluate potential QEEG predictors of treatment response. EEG data were analyzed at baseline, during the infusion and 24hours after ketamine administration using spectral and exact low-resolution electromagnetic tomography (eLORETA) analyses. Responders to ketamine were characterized by higher baseline absolute and relative alpha power and lower relative theta power. At baseline, the responders showed also an increase of alpha-2 current density sources in medial parieto-occipital areas and a decrease of theta sources in subgenual and anterior cingulate as well as in left mediofrontal region. There was no baseline difference between the responders and non-responders in eLORETA-assessed cortical connectivity.

<p>Supported by the grant AZV MZCR 15-33250A and by the project Progres Q35.</p>

Relapses are a major determinant of the long-term outcomes of depression. The relapse risk should therefore feature prominently in decisions about treatment and treatment discontinuation. Although it is known that antidepressant continuation reduced the risk of relapse, there are no known biomarkers to guide individual choices about when to discontinue. AIDA (“Antidepressiva Absetzstudie”) is an ongoing observational study that examines the predictive potential of EEG biomarkers after antidepressant discontinuation. Patients who had a clear response to antidepressants and wish to discontinue their medication are being included. EEG data is acquired during a standardized vigilance paradigm (VIGALL) and a paradigm of emotional reactivity to sad movies. Recruitment is ongoing at both study sites in Berlin and Zurich and we will present the first preliminary results focusing on emotional reactivity measures.

The methodological and modeling challenges offered by the new field of hyperscanning are among the most interesting opportunities of development for brain connectivity methods. The analysis of multiple-subjects connectivity aims to build models of social cognitive functions describing the complex relationship between the brain activities of interacting subjects. Such new approach promises to reach a deeper understanding of the neurophysiological mechanisms involved in social interactions. In this lecture, the theoretical framework explaining the need for simultaneous recording and multivariate modeling of multiple subjects data will be discussed, and I will show some examples of multi-subject models related to collaboration, joint action and empathic pro-social behavior, obtained by high density EEG and source reconstruction techniques.

Optically pumped atomic magnetometers (OPAMs) using alkali metal vapors contained in glass cells are capable of measuring extremely small magnetic fields. In recent years, OPAMs operating under spin-exchange relaxation-free (SERF) conditions have reached sensitivities comparable to and even surpassing those of superconducting quantum interference devices (SQUIDs). The most sensitive OPAM has sensitivity in the sub-femto tesla range. In addition, OPAMs have the intrinsic advantage of not requiring cryogenic cooling. Therefore, OPAMs are currently expected to overtake SQUIDs, and the possibilities for magnetoencephalography (MEG) and ultra-low field MRI have been demonstrated.

We have been developing super-sensitive OPAMs since 2006. After describing principles of the OPAM, we introduce our recent results of MEG and NMR/MRI measurements using a portable OPAM module to demonstrate its feasibility as a magnetic sensor towards innovative neuroimaging systems.

Finally, we describe some future research directions of the optical neuroimaging systems. For instance, we plan to detect neural magnetic field dependent (NMFD) changes in MR signals towards a new fMRI. To demonstrate the feasibility of the NMFD-fMRI, we present our results of both simulation and phantom studies using a spin-lock sequence, which is sensitive to oscillating magnetic fields.