After-effects of 10 Hz tACS over the prefrontal cortex on phonological word decisions

Introduction Previous work in the language domain has shown that 10 Hz rTMS of the left or right posterior inferior frontal gyrus (pIFG) in the prefrontal cortex impaired phonological decision-making, arguing for a causal contribution of the bilateral pIFG to phonological processing. However, the neurophysiological correlates of these effects are unclear. The present study addressed the question whether neural activity in the prefrontal cortex could be modulated by 10 Hz tACS and how this would affect phonological decisions. Methods In three sessions, 24 healthy participants received tACS at 10 Hz or 16.18 Hz (control frequency) or sham stimulation over the bilateral prefrontal cortex before task processing. Resting state EEG was recorded before and after tACS. We also recorded EEG during task processing. Results Relative to sham stimulation, 10 Hz tACS significantly facilitated phonological response speed. This effect was task-specific as tACS did not affect a simple control task. Moreover, 10 Hz tACS significantly increased theta power during phonological decisions. The individual increase in theta power was positively correlated with the behavioral facilitation after 10 Hz tACS. Conclusion Our results show a facilitation of phonological decisions after 10 Hz tACS over the bilateral prefrontal cortex. This might indicate that 10 Hz tACS increased task-related activity in the stimulated area to a level that was optimal for phonological performance. The significant correlation with the individual increase in theta power suggests that the behavioral facilitation might be related to increased theta power during language processing

A novel approach to measure brain-to-brain spatial and temporal alignment during positive empathy

: Empathy is defined as the ability to vicariously experience others' suffering (vicarious pain) or feeling their joy (vicarious reward). While most neuroimaging studies have focused on vicarious pain and describe similar neural responses during the observed and the personal negative affective involvement, only initial evidence has been reported for the neural responses to others' rewards and positive empathy. Here, we propose a novel approach, based on the simultaneous recording of multi-subject EEG signals and exploiting the wavelet coherence decomposition to measure the temporal alignment between ERPs in a dyad of interacting subjects. We used the Third-Party Punishment (TPP) paradigm to elicit the personal and vicarious experiences. During a positive experience, we observed the simultaneous presence in both agents of the Late Positive Potential (LPP), an ERP component related to emotion processing, as well as the existence of an inter-subject ERPs synchronization in the related time window. Moreover, the amplitude of the LPP synchronization was modulated by the presence of a human-agent. Finally, the localized brain circuits subtending the ERP-synchronization correspond to key-regions of personal and vicarious reward. Our findings suggest that the temporal and spatial ERPs alignment might be a novel and direct proxy measure of empathy

Multiple-Brain connectivity during third party punishment: an EEG hyperscanning study

Compassion is a particular form of empathic reaction to harm that befalls others and is accompanied by a desire to alleviate their suffering. This altruistic behavior is often manifested through altruistic punishment, wherein individuals penalize a deprecated human's actions, even if they are directed toward strangers. By adopting a dual approach, we provide empirical evidence that compassion is a multifaceted prosocial behavior and can predict altruistic punishment. In particular, in this multiple-brain connectivity study in an EEG hyperscanning setting, compassion was examined during real-time social interactions in a third-party punishment (TPP) experiment. We observed that specific connectivity patterns were linked to behavioral and psychological intra- and interpersonal factors. Thus, our results suggest that an ecological approach based on simultaneous dual-scanning and multiple-brain connectivity is suitable for analyzing complex social phenomena

Online effects of beta-tACS over the left prefrontal cortex on phonological decisions

The left posterior inferior frontal gyrus in the prefrontal cortex is a key region for phonological aspects of language processing. A previous study has shown that alpha-tACS over the prefrontal cortex applied before task processing facilitated phonological decision-making and increased task-related theta power. However, it is unclear how alpha-tACS affects phonological processing when applied directly during the task. Moreover, the frequency specificity of this effect is also unclear since the majority of neurostimulation studies tested a single frequency only. The present study addressed the question whether and how 10 Hz online tACS affects phonological decisions. To this end, 24 healthy participants received tACS at 10 Hz or 16.18 Hz (control frequency) or sham stimulation over the left prefrontal cortex during task processing in three sessions. As an unexpected finding, 16.18 Hz significantly impaired task accuracy relative to sham stimulation, without affecting response speed. There was no significant difference in phonological task performance between 10 Hz and 16.18 Hz tACS or between 10 Hz and sham stimulation. Our results support the functional relevance of the left prefrontal cortex for phonological decisions and suggest that online beta-tACS may modulate language comprehension

Unmet Needs in Children With Attention Deficit Hyperactivity Disorder—Can Transcranial Direct Current Stimulation Fill the Gap? Promises and Ethical Challenges

Attention deficit hyperactivity disorder (ADHD) is a disorder most frequently diagnosed in children and adolescents. Although ADHD can be effectively treated with psychostimulants, a significant proportion of patients discontinue treatment because of adverse events or insufficient improvement of symptoms. In addition, cognitive abilities that are frequently impaired in ADHD are not directly targeted by medication. Therefore, additional treatment options, especially to improve cognitive abilities, are needed. Because of its relatively easy application, well-established safety, and low cost, transcranial direct current stimulation (tDCS) is a promising additional treatment option. Further research is needed to establish efficacy and to integrate this treatment into the clinical routine. In particular, limited evidence regarding the use of tDCS in children, lack of clear translational guidelines, and general challenges in conducting research with vulnerable populations pose a number of practical and ethical challenges to tDCS intervention studies. In this paper, we identify and discuss ethical issues related to research on tDCS and its potential therapeutic use for ADHD in children and adolescents. Relevant ethical issues in the tDCS research for pediatric ADHD center on safety, risk/benefit ratio, information and consent, labeling problems, and nonmedical use. Following an analysis of these issues, we developed a list of recommendations that can guide clinicians and researchers in conducting ethically sound research on tDCS in pediatric ADHD

Neuronal networks in children with continuous spikes and waves during slow sleep

Epileptic encephalopathy with continuous spikes and waves during slow sleep is an age-related disorder characterized by the presence of interictal epileptiform discharges during at least >85% of sleep and cognitive deficits associated with this electroencephalography pattern. The pathophysiological mechanisms of continuous spikes and waves during slow sleep and neuropsychological deficits associated with this condition are still poorly understood. Here, we investigated the haemodynamic changes associated with epileptic activity using simultaneous acquisitions of electroencephalography and functional magnetic resonance imaging in 12 children with symptomatic and cryptogenic continuous spikes and waves during slow sleep. We compared the results of magnetic resonance to electric source analysis carried out using a distributed linear inverse solution at two time points of the averaged epileptic spike. All patients demonstrated highly significant spike-related positive (activations) and negative (deactivations) blood oxygenation-level-dependent changes (P < 0.05, family-wise error corrected). The activations involved bilateral perisylvian region and cingulate gyrus in all cases, bilateral frontal cortex in five, bilateral parietal cortex in one and thalamus in five cases. Electrical source analysis demonstrated a similar involvement of the perisylvian brain regions in all patients, independent of the area of spike generation. The spike-related deactivations were found in structures of the default mode network (precuneus, parietal cortex and medial frontal cortex) in all patients and in caudate nucleus in four. Group analyses emphasized the described individual differences. Despite aetiological heterogeneity, patients with continuous spikes and waves during slow sleep were characterized by activation of the similar neuronal network: perisylvian region, insula and cingulate gyrus. Comparison with the electrical source analysis results suggests that the activations correspond to both initiation and propagation pathways. The deactivations in structures of the default mode network are consistent with the concept of epileptiform activity impacting on normal brain function by inducing repetitive interruptions of neurophysiological functio

Large-scale signatures of unconsciousness are consistent with a departure from critical dynamics

Loss of cortical integration and changes in the dynamics of electrophysiological brain signals characterize the transition from wakefulness towards unconsciousness. The common mechanism underlying these observations remains unknown. In this study we arrive at a basic model, which explains these empirical observations based on the theory of phase transitions in complex systems. We studied the link between spatial and temporal correlations of large-scale brain activity recorded with functional magnetic resonance imaging during wakefulness, propofol-induced sedation and loss of consciousness, as well as during the subsequent recovery. We observed that during unconsciousness activity in frontal and thalamic regions exhibited a reduction of long-range temporal correlations and a departure of functional connectivity from the underlying anatomical constraints. These changes in dynamics and anatomy-function coupling were correlated across participants, suggesting that temporal complexity and an efficient exploration of anatomical connectivity are inter-related phenomena. A model of a system exhibiting a phase transition reproduced our findings, as well as the diminished sensitivity of the cortex to external perturbations during unconsciousness. This theoretical framework unifies different empirical observations about brain activity during unconsciousness and predicts that the principles we identified are universal and independent of the causes behind loss of awareness.Comment: to appear in Journal of the Royal Society Interfac

With or without spikes: localization of focal epileptic activity by simultaneous electroencephalography and functional magnetic resonance imaging

In patients with medically refractory focal epilepsy who are candidates for epilepsy surgery, concordant non-invasive neuroimaging data are useful to guide invasive electroencephalographic recordings or surgical resection. Simultaneous electroencephalography and functional magnetic resonance imaging recordings can reveal regions of haemodynamic fluctuations related to epileptic activity and help localize its generators. However, many of these studies (40-70%) remain inconclusive, principally due to the absence of interictal epileptiform discharges during simultaneous recordings, or lack of haemodynamic changes correlated to interictal epileptiform discharges. We investigated whether the presence of epilepsy-specific voltage maps on scalp electroencephalography correlated with haemodynamic changes and could help localize the epileptic focus. In 23 patients with focal epilepsy, we built epilepsy-specific electroencephalographic voltage maps using averaged interictal epileptiform discharges recorded during long-term clinical monitoring outside the scanner and computed the correlation of this map with the electroencephalographic recordings in the scanner for each time frame. The time course of this correlation coefficient was used as a regressor for functional magnetic resonance imaging analysis to map haemodynamic changes related to these epilepsy-specific maps (topography-related haemodynamic changes). The method was first validated in five patients with significant haemodynamic changes correlated to interictal epileptiform discharges on conventional analysis. We then applied the method to 18 patients who had inconclusive simultaneous electroencephalography and functional magnetic resonance imaging studies due to the absence of interictal epileptiform discharges or absence of significant correlated haemodynamic changes. The concordance of the results with subsequent intracranial electroencephalography and/or resection area in patients who were seizure free after surgery was assessed. In the validation group, haemodynamic changes correlated to voltage maps were similar to those obtained with conventional analysis in 5/5 patients. In 14/18 patients (78%) with previously inconclusive studies, scalp maps related to epileptic activity had haemodynamic correlates even when no interictal epileptiform discharges were detected during simultaneous recordings. Haemodynamic changes correlated to voltage maps were spatially concordant with intracranial electroencephalography or with the resection area. We found better concordance in patients with lateral temporal and extratemporal neocortical epilepsy compared to medial/polar temporal lobe epilepsy, probably due to the fact that electroencephalographic voltage maps specific to lateral temporal and extratemporal epileptic activity are more dissimilar to maps of physiological activity. Our approach significantly increases the yield of simultaneous electroencephalography and functional magnetic resonance imaging to localize the epileptic focus non-invasively, allowing better targeting for surgical resection or implantation of intracranial electrode array

Multivariate improved weighted multi-scale permutation entropy and its application on EEG data

This paper introduces an entropy based method that measures complexity in non-stationary multivariate signals. This method, called Mutivariate Improved Weighted Multiscale Permutation Entropy (mvIWMPE), has two main advantages: (i) it shows lower variance for the results when applied on a wide range of multivariate signals; (ii) it has good accuracy quantifying complexity of different recorded states in signals and hence discriminating them. mvIWMPE is based on two previously introduced permutation entropy algorithms, Improved Multiscale Permutation Entropy (IMPE) and Multivariate Weighted Mul-tiscale Permutation Entropy (mvWMPE). It combines the concept of coarse graining from IMPE and the introduction of the weight of amplitudes of the signals from mvWMPE. mvIWMPE was validated on both synthetic and human electroencephalographic (EEG) signals. Several synthetic signals were simulated: mixtures of white Gaussian noise (WGN) and pink noise, chaotic and convergent Lorenz system signals, stochastic and deterministic signals. As for real signals, resting-state EEG recorded in healthy and epileptic children during eyes closed and eyes open sessions were analyzed. Our method was compared to multivariate multiscale, multivariate weighted multiscale and multivariate improved multiscale permutation entropy methods. Performance on synthetic as well as on EEG signals showed more undeviating results and higher ability for mvIWMPE discriminating different states of signals (chaotic vs convergent, WGN vs pink noise, stochastic vs deterministic simulated signals, and eyes open vs eyes closed EEG signals). We herein proposed an efficient method to measure the complexity of multivariate non-stationary signals. Experimental results showed the accuracy and the robustness (in terms of variance) of the method

Multivariate improved weighted multi-scale permutation entropy and its application on EEG data

In this paper, we propose a new algorithm to calculate sample entropy of multivariate data. Over the existing method, the one proposed here has the advantage of maintaining good results as the number of channels increases. The new and already-existing algorithms were applied on multivariate white Gaussian noise signals, pink noise signals, and mixtures of both. For high number of channels, the existing method failed to show that white noise is always the most irregular whereas the proposed method always had the entropy of white noise the highest. Application of both algorithms on MIX process signals also confirmed the ability of the proposed method to handle larger number of channels without risking erroneous results. We also applied the proposed algorithm on EEG data from epileptic patients before and after treatments. The results showed an increase in entropy values after treatment in the regions where the focus was localized. This goes in the same way as the medical point of view that indicated a better health state for these patients