Distinct and common mechanisms of cross-model semantic conflict and response conflict in an auditory relevant task

The mechanisms of semantic conflict and response conflict in the Stroop task have mainly been investigated in the visual modality. However, the understanding of these mechanisms in cross-modal modalities remains limited. In this electroencephalography (EEG) study, an audiovisual 2-1 mapping Stroop task was utilized to investigate whether distinct and/or common neural mechanisms underlie cross-modal semantic conflict and response conflict. The response time data showed significant effects on both cross-modal semantic and response conflicts. Interestingly, the magnitude of semantic conflict was found to be smaller in the fast response time bins than in the slow response time bins, whereas no such difference was observed for response conflict. The EEG data demonstrated that cross-modal semantic conflict specifically increased the N450 amplitude. However, cross-modal response conflict specifically enhanced theta band power and theta phase synchronization between the medial frontal cortex (MFC) and lateral prefrontal electrodes as well as between the MFC and motor electrodes. In addition, both cross-modal semantic conflict and response conflict led to a decrease in P3 amplitude. Taken together, these findings provide cross-modal evidence for domain-specific mechanism in conflict detection and suggest both domain-specific and domain-general mechanisms exist in conflict resolution.

Functional hierarchies in brain dynamics characterized by signal reversibility in ferret cortex

Brain signal irreversibility has been shown to be a promising approach to study neural dynamics. Nevertheless, the relation with cortical hierarchy and the influence of different electrophysiological features is not completely understood. In this study, we recorded local field potentials (LFPs) during spontaneous behavior, including awake and sleep periods, using custom micro-electrocorticographic (μECoG) arrays implanted in ferrets. In contrast to humans, ferrets remain less time in each state across the sleep-wake cycle. We deployed a diverse set of metrics in order to measure the levels of complexity of the different behavioral states. In particular, brain irreversibility, which is a signature of non-equilibrium dynamics, captured by the arrow of time of the signal, revealed the hierarchical organization of the ferret's cortex. We found different signatures of irreversibility and functional hierarchy of large-scale dynamics in three different brain states (active awake, quiet awake, and deep sleep), showing a lower level of irreversibility in the deep sleep stage, compared to the other. Irreversibility also allowed us to disentangle the influence of different cortical areas and frequency bands in this process, showing a predominance of the parietal cortex and the theta band. Furthermore, when inspecting the embedded dynamic through a Hidden Markov Model, the deep sleep stage was revealed to have a lower switching rate and lower entropy production. These results suggest functional hierarchies in organization that can be revealed through thermodynamic features and information theory metrics.

Leading and following: Noise differently affects semantic and acoustic processing during naturalistic speech comprehension

Despite the distortion of speech signals caused by unavoidable noise in daily life, our ability to comprehend speech in noisy environments is relatively stable. However, the neural mechanisms underlying reliable speech-in-noise comprehension remain to be elucidated. The present study investigated the neural tracking of acoustic and semantic speech information during noisy naturalistic speech comprehension. Participants listened to narrative audio recordings mixed with spectrally matched stationary noise at three signal-to-ratio (SNR) levels (no noise, 3 dB, -3 dB), and 60-channel electroencephalography (EEG) signals were recorded. A temporal response function (TRF) method was employed to derive event-related-like responses to the continuous speech stream at both the acoustic and the semantic levels. Whereas the amplitude envelope of the naturalistic speech was taken as the acoustic feature, word entropy and word surprisal were extracted via the natural language processing method as two semantic features. Theta-band frontocentral TRF responses to the acoustic feature were observed at around 400 ms following speech fluctuation onset over all three SNR levels, and the response latencies were more delayed with increasing noise. Delta-band frontal TRF responses to the semantic feature of word entropy were observed at around 200 to 600 ms leading to speech fluctuation onset over all three SNR levels. The response latencies became more leading with increasing noise and decreasing speech comprehension and intelligibility. While the following responses to speech acoustics were consistent with previous studies, our study revealed the robustness of leading responses to speech semantics, which suggests a possible predictive mechanism at the semantic level for maintaining reliable speech comprehension in noisy environments.

EEG-based speaker-listener neural coupling reflects speech-selective attentional mechanisms beyond the speech stimulus

When we pay attention to someone, do we focus only on the sound they make, the word they use, or do we form a mental space shared with the speaker we want to pay attention to? Some would argue that the human language is no other than a simple signal, but others claim that human beings understand each other because they form a shared mental ground between the speaker and the listener. Our study aimed to explore the neural mechanisms of speech-selective attention by investigating the electroencephalogram-based neural coupling between the speaker and the listener in a cocktail party paradigm. The temporal response function method was employed to reveal how the listener was coupled to the speaker at the neural level. The results showed that the neural coupling between the listener and the attended speaker peaked 5 s before speech onset at the delta band over the left frontal region, and was correlated with speech comprehension performance. In contrast, the attentional processing of speech acoustics and semantics occurred primarily at a later stage after speech onset and was not significantly correlated with comprehension performance. These findings suggest a predictive mechanism to achieve speaker-listener neural coupling for successful speech comprehension.

Structural basis of envelope and phase intrinsic coupling modes in the cerebral cortex

Intrinsic coupling modes (ICMs) can be observed in ongoing brain activity at multiple spatial and temporal scales. Two families of ICMs can be distinguished: phase and envelope ICMs. The principles that shape these ICMs remain partly elusive, in particular their relation to the underlying brain structure. Here we explored structure-function relationships in the ferret brain between ICMs quantified from ongoing brain activity recorded with chronically implanted micro-ECoG arrays and structural connectivity (SC) obtained from high-resolution diffusion MRI tractography. Large-scale computational models were used to explore the ability to predict both types of ICMs. Importantly, all investigations were conducted with ICM measures that are sensitive or insensitive to volume conduction effects. The results show that both types of ICMs are significantly related to SC, except for phase ICMs when using measures removing zero-lag coupling. The correlation between SC and ICMs increases with increasing frequency which is accompanied by reduced delays. Computational models produced results that were highly dependent on the specific parameter settings. The most consistent predictions were derived from measures solely based on SC. Overall, the results demonstrate that patterns of cortical functional coupling as reflected in both phase and envelope ICMs are both related, albeit to different degrees, to the underlying structural connectivity in the cerebral cortex.

Personalized alpha-tACS targeting left posterior parietal cortex modulates visuo-spatial attention and posterior evoked EEG activity

BACKGROUND

Covert visuo-spatial attention is marked by the anticipatory lateralization of neuronal alpha activity in the posterior parietal cortex. Previous applications of transcranial alternating current stimulation (tACS) at the alpha frequency, however, were inconclusive regarding the causal contribution of oscillatory activity during visuo-spatial attention.

OBJECTIVE

Attentional shifts of behavior and electroencephalography (EEG) after-effects were assessed in a cued visuo-spatial attention paradigm. We hypothesized that parietal alpha-tACS shifts attention relative to the ipsilateral visual hemifield. Furthermore, we assumed that modulations of behavior and neurophysiology are related to individual electric field simulations.

METHODS

We applied personalized tACS at alpha and gamma frequencies to elucidate the role of oscillatory neuronal activity for visuo-spatial attention. Personalized tACS montages were algorithmically optimized to target individual left and right parietal regions that were defined by an EEG localizer.

RESULTS

Behavioral performance in the left hemifield was specifically increased by alpha-tACS compared to gamma-tACS targeting the left parietal cortex. This hemisphere-specific effect was observed despite the symmetry of simulated electric fields. In addition, visual event-related potential (ERP) amplitudes showed a reduced lateralization over posterior sites induced by left alpha-tACS. Neuronal sources of this effect were localized in the left premotor cortex. Interestingly, accuracy modulations induced by left parietal alpha-tACS were directly related to electric field magnitudes in the left premotor cortex.

CONCLUSION

Overall, results corroborate the notion that alpha lateralization plays a causal role in covert visuo-spatial attention and indicate an increased susceptibility of parietal and premotor brain regions of the left dorsal attention network to subtle tACS-neuromodulation.

Oscillatory and aperiodic neuronal activity in working memory following anesthesia

OBJECTIVE

Anesthesia and surgery are associated with cognitive impairment, particularly memory deficits. So far, electroencephalography markers of perioperative memory function remain scarce.

METHODS

We included male patients >60 years scheduled for prostatectomy under general anesthesia. We obtained neuropsychological assessments and a visual match-to-sample working memory task with simultaneous 62-channel scalp electroencephalography 1 day before and 2 to 3 days after surgery.

RESULTS

Twenty-six patients completed both pre- and postoperative sessions. Compared with preoperative performance, verbal learning deteriorated after anesthesia (California Verbal Learning Test total recall; t₂₅ = -3.25, p = 0.015, d = -0.902), while visual working memory performance showed a dissociation between match and mismatch accuracy (match*session F_1,25 = 3.866, p = 0.060). Better verbal learning was associated with an increase of aperiodic brain activity (total recall r = 0.66, p = 0.029, learning slope r = 0.66, p = 0.015), whereas visual working memory accuracy was tracked by oscillatory theta/alpha (7 - 9 Hz), low beta (14 - 18 Hz) and high beta/gamma (34 - 38 Hz) activity (matches: p < 0.001, mismatches: p = 0.022).

CONCLUSIONS

Oscillatory and aperiodic brain activity in scalp electroencephalography track distinct features of perioperative memory function.

SIGNIFICANCE

Aperiodic activity provides a potential electroencephalographic biomarker to identify patients at risk for postoperative cognitive impairments.

Subthalamic and nigral neurons are differentially modulated during parkinsonian gait

The parkinsonian gait disorder and freezing of gait are therapeutically demanding symptoms with considerable impact on quality of life. The aim of this study was to assess the role of subthalamic and nigral neurons in the parkinsonian gait control using intraoperative microelectrode recordings of basal ganglia neurons during a supine stepping task. 12 male patients (56±7 years) suffering from moderate idiopathic Parkinson's disease (disease duration 10±3 years, Hoehn & Yahr stage 2) participated in the study. After 10 seconds resting period, stepping at self-paced speed for 35 seconds was followed by short intervals of stepping in response to random "start" and "stop" cues. Single- and multi-unit activity was analysed offline in relation to different aspects of the stepping task (attentional "start" and "stop" cues, heel strikes, stepping irregularities) in terms of firing frequency, firing pattern, and oscillatory activity. Subthalamic nucleus and the substantia nigra neurons responded to different aspects of the stepping task. 24% of the subthalamic nucleus neurons exhibited movement-related activity modulation as an increase of the firing rate, suggesting a predominant role of the subthalamic nucleus in motor aspects of the task, while 8% of subthalamic nucleus neurons showed a modulation in response to the attentional cues. In contrast, responsive substantia nigra neurons showed activity changes exclusively associated with attentional aspects of the stepping task (15%). The firing pattern of subthalamic nucleus neurons revealed gait-related firing regulation and a drop of beta oscillations during regular stepping performance. During freezing episodes instead, there was a rise of beta oscillatory activity. This study shows for the first time specific, task-related, subthalamic nucleus and substantia nigra single unit activity during gait-like movements in humans with differential roles in motor and attentional control of gait. The emergence of perturbed firing patterns in the subthalamic nucleus indicates a disturbed information transfer within the gait network, resulting in freezing of gait.

Topological reorganization of brain network might contribute to the resilience of cognitive functioning in mildly disabled relapsing remitting multiple sclerosis

Multiple sclerosis (MS) is an inflammatory and demyelinating disease which leads to impairment in several functional systems including cognition. Alteration of brain networks is linked to disability and its progression. However, results are mostly cross-sectional and yet contradictory as putative adaptive and maladaptive mechanisms were found. Here, we aimed to explore longitudinal reorganization of brain networks over 2-years by combining diffusion tensor imaging (DTI), resting-state functional MRI (fMRI), magnetoencephalography (MEG), and a comprehensive neuropsychological-battery. In 37 relapsing-remitting MS (RRMS) and 39 healthy-controls, cognition remained stable over-time. We reconstructed network models based on the three modalities and analyzed connectivity in relation to the hierarchical topology and functional subnetworks. Network models were compared across modalities and in their association with cognition using linear-mixed-effect-regression models. Loss of hub connectivity and global reduction was observed on a structural level over-years (p < .010), which was similar for functional MEG-networks but not for fMRI-networks. Structural hub connectivity increased in controls (p = .044), suggesting a physiological mechanism of healthy aging. Despite a general loss in structural connectivity in RRMS, hub connectivity was preserved (p = .002) over-time in default-mode-network (DMN). MEG-networks were similar to DTI and weakly correlated with fMRI in MS (p < .050). Lower structural (β between .23-.33) and both lower (β between .40-.59) and higher functional connectivity (β = -.54) in DMN was associated with poorer performance in attention and memory in RRMS (p < .001). MEG-networks involved no association with cognition. Here, cognitive stability despite ongoing neurodegeneration might indicate a resilience mechanism of DMN hubs mimicking a physiological reorganization observed in healthy aging.

Dynamic functional connectivity: causative or epiphenomenal?

Dynamic coupling of neural signals is a hallmark of brain networks, but its potential relevance is still debated. Does coupling play a causal role for network functions, or is it just a by-product of structural connectivity or other physiological processes? With intervention techniques that have become available, experiments seem within reach that may provide answers to this long-standing question.

Coordinating human-robot collaboration by EEG-based human intention prediction and vigilance control

In human-robot collaboration scenarios with shared workspaces, a highly desired performance boost is offset by high requirements for human safety, limiting speed and torque of the robot drives to levels which cannot harm the human body. Especially for complex tasks with flexible human behavior, it becomes vital to maintain safe working distances and coordinate tasks efficiently. An established approach in this regard is reactive servo in response to the current human pose. However, such an approach does not exploit expectations of the human's behavior and can therefore fail to react to fast human motions in time. To adapt the robot's behavior as soon as possible, predicting human intention early becomes a factor which is vital but hard to achieve. Here, we employ a recently developed type of brain-computer interface (BCI) which can detect the focus of the human's overt attention as a predictor for impending action. In contrast to other types of BCI, direct projection of stimuli onto the workspace facilitates a seamless integration in workflows. Moreover, we demonstrate how the signal-to-noise ratio of the brain response can be used to adjust the velocity of the robot movements to the vigilance or alertness level of the human. Analyzing this adaptive system with respect to performance and safety margins in a physical robot experiment, we found the proposed method could improve both collaboration efficiency and safety distance.

ΔFosB accumulation in hippocampal granule cells drives cFos pattern separation during spatial learning

Mice display signs of fear when neurons that express cFos during fear conditioning are artificially reactivated. This finding gave rise to the notion that cFos marks neurons that encode specific memories. Here we show that cFos expression patterns in the mouse dentate gyrus (DG) change dramatically from day to day in a water maze spatial learning paradigm, regardless of training level. Optogenetic inhibition of neurons that expressed cFos on the first training day affected performance days later, suggesting that these neurons continue to be important for spatial memory recall. The mechanism preventing repeated cFos expression in DG granule cells involves accumulation of ΔFosB, a long-lived splice variant of FosB. CA1 neurons, in contrast, repeatedly expressed cFos. Thus, cFos-expressing granule cells may encode new features being added to the internal representation during the last training session. This form of timestamping is thought to be required for the formation of episodic memories.

Speaker-listener neural coupling reveals a right-lateralized mechanism for non-native speech-in-noise comprehension

While the increasingly globalized world has brought more and more demands for non-native language communication, the prevalence of background noise in everyday life poses a great challenge to non-native speech comprehension. The present study employed an interbrain approach based on functional near-infrared spectroscopy (fNIRS) to explore how people adapt to comprehend non-native speech information in noise. A group of Korean participants who acquired Chinese as their non-native language was invited to listen to Chinese narratives at 4 noise levels (no noise, 2 dB, -6 dB, and - 9 dB). These narratives were real-life stories spoken by native Chinese speakers. Processing of the non-native speech was associated with significant fNIRS-based listener-speaker neural couplings mainly over the right hemisphere at both the listener's and the speaker's sides. More importantly, the neural couplings from the listener's right superior temporal gyrus, the right middle temporal gyrus, as well as the right postcentral gyrus were found to be positively correlated with their individual comprehension performance at the strongest noise level (-9 dB). These results provide interbrain evidence in support of the right-lateralized mechanism for non-native speech processing and suggest that both an auditory-based and a sensorimotor-based mechanism contributed to the non-native speech-in-noise comprehension.

Training the spatially-coded SSVEP BCI on the fly

BACKGROUND

The spatially-coded SSVEP BCI employs the retinotopic map in the human visual pathway to infer the gaze direction of the operator relative to a flicker stimulus inducing steady-state visual evoked potentials (SSVEPs) in the brain. It has been shown that with this method, up to 16 channels can be encoded using only a single flicker stimulus. Another advantage over conventional frequency-coded SSVEP BCIs, in which channels are encoded by different combinations of frequencies and phases, is that the operator does not have to gaze directly at flickering lights. This can reduce visual fatigue and improve user comfort. Whereas the frequency of the SSVEP response is well predictable, which has enabled the development of frequency-coded SSVEP BCIs which do not require training data, the spatial distribution of the SSVEP response over the scalp differs much more between different people. This requires collecting a substantial amount of training data before the spatially-coded BCI could be put into operation.

NEW METHOD

In this study we address this issue by combining the spatially-coded BCI with a feedback channel which the operator uses to flag classification errors, and which allows the system to accumulate valid training data while the BCI is used to solve a spatial navigation task.

RESULTS

Starting from the minimal number of samples required by the classification method, the approach achieved an average accuracy of 69 ± 15 %, corresponding to an ITR of 31 ± 17 bits/min, in solving the task for the first time. This accuracy improved to 87 ± 9 % (ITR: 54 ± 14 bits/min) after completing the task 2 more times. Further we show that participants with a stable SSVEP topography over repeated stimulation enable the BCI to achieve higher accuracies.

COMPARISON WITH EXISTING METHODS

Compared to a similar system with separate training and application phases, the time to achieve the same output is reduced by more than 50 %.

CONCLUSIONS

Evaluating the approach in 17 participants suggests that the performance of the spatially-coded BCI with a minimal set of training samples is sufficient to be operational, and that performance keeps improving in the course of its application.

Instant classification for the spatially-coded BCI

The spatially-coded SSVEP BCI exploits changes in the topography of the steady-state visual evoked response to visual flicker stimulation in the extrafoveal field of view. In contrast to frequency-coded SSVEP BCIs, the operator does not gaze into any flickering lights; therefore, this paradigm can reduce visual fatigue. Other advantages include high classification accuracies and a simplified stimulation setup. Previous studies of the paradigm used stimulation intervals of a fixed duration. For frequency-coded SSVEP BCIs, it has been shown that dynamically adjusting the trial duration can increase the system’s information transfer rate (ITR). We therefore investigated whether a similar increase could be achieved for spatially-coded BCIs by applying dynamic stopping methods. To this end we introduced a new stopping criterion which combines the likelihood of the classification result and its stability across larger data windows. Whereas the BCI achieved an average ITR of 28.4±6.4 bits/min with fixed intervals, dynamic intervals increased the performance to 81.1±44.4 bits/min. Users were able to maintain performance up to 60 minutes of continuous operation. We suggest that the dynamic response time might have worked as a kind of temporal feedback which allowed operators to optimize their brain signals and compensate fatigue.

Combined Subthalamic and Nigral Stimulation Modulates Temporal Gait Coordination and Cortical Gait-Network Activity in Parkinson’s Disease

Background

Freezing of gait (FoG) is a disabling burden for Parkinson’s disease (PD) patients with poor response to conventional therapies. Combined deep brain stimulation of the subthalamic nucleus and substantia nigra (STN+SN DBS) moved into focus as a potential therapeutic option to treat the parkinsonian gait disorder and refractory FoG. The mechanisms of action of DBS within the cortical-subcortical-basal ganglia network on gait, particularly at the cortical level, remain unclear.

Methods

Twelve patients with idiopathic PD and chronically-implanted DBS electrodes were assessed on their regular dopaminergic medication in a standardized stepping in place paradigm. Patients executed the task with DBS switched off (STIM OFF), conventional STN DBS and combined STN+SN DBS and were compared to healthy matched controls. Simultaneous high-density EEG and kinematic measurements were recorded during resting-state, effective stepping, and freezing episodes.

Results

Clinically, STN+SN DBS was superior to conventional STN DBS in improving temporal stepping variability of the more affected leg. During resting-state and effective stepping, the cortical activity of PD patients in STIM OFF was characterized by excessive over-synchronization in the theta (4–8 Hz), alpha (9–13 Hz), and high-beta (21–30 Hz) band compared to healthy controls. Both active DBS settings similarly decreased resting-state alpha power and reduced pathologically enhanced high-beta activity during resting-state and effective stepping compared to STIM OFF. Freezing episodes during STN DBS and STN+SN DBS showed spectrally and spatially distinct cortical activity patterns when compared to effective stepping. During STN DBS, FoG was associated with an increase in cortical alpha and low-beta activity over central cortical areas, while with STN+SN DBS, an increase in high-beta was prominent over more frontal areas.

Conclusions

STN+SN DBS improved temporal aspects of parkinsonian gait impairment compared to conventional STN DBS and differentially affected cortical oscillatory patterns during regular locomotion and freezing suggesting a potential modulatory effect on dysfunctional cortical-subcortical communication in PD.

tACS phase-specifically biases brightness perception of flickering light

BACKGROUND

Visual phenomena like brightness illusions impressively demonstrate the highly constructive nature of perception. In addition to physical illumination, the subjective experience of brightness is related to temporal neural dynamics in visual cortex.

OBJECTIVE

Here, we asked whether biasing the temporal pattern of neural excitability in visual cortex by transcranial alternating current stimulation (tACS) modulates brightness perception of concurrent rhythmic visual stimuli.

METHODS

Participants performed a brightness discrimination task of two flickering lights, one of which was targeted by same-frequency electrical stimulation at varying phase shifts. tACS was applied with an occipital and a periorbital active control montage, based on simulations of electrical currents using finite element head models.

RESULTS

Experimental results reveal that flicker brightness perception is modulated dependent on the phase shift between sensory and electrical stimulation, solely under occipital tACS. Phase-specific modulatory effects by tACS were dependent on flicker-evoked neural phase stability at the tACS-targeted frequency, recorded prior to electrical stimulation. Further, the optimal timing of tACS application leading to enhanced brightness perception was correlated with the neural phase delay of the cortical flicker response.

CONCLUSIONS

Our results corroborate the role of temporally coordinated neural activity in visual cortex for brightness perception of rhythmic visual input in humans. Phase-specific behavioral modulations by tACS emphasize its efficacy to transfer perceptually relevant temporal information to the cortex. These findings provide an important step towards understanding the basis of visual perception and further confirm electrical stimulation as a tool for advancing controlled modulations of neural activity and related behavior.

Neuronal Oscillatory Signatures of Joint Attention and Intersubjectivity in Arrhythmic Coaction

Hyper-brain studies analyze the brain activity of two or more individuals during some form of interaction. Several studies found signs of inter-subject brain activity coordination, such as power and phase synchronization or information flow. This hyper-brain coordination is frequently studied in paradigms which induce rhythms or even synchronization, e.g., by mirroring movements, turn-based activity in card or economic games, or joint music making. It is therefore interesting to figure out in how far coordinated brain activity may be induced by a rhythmicity in the task and/or the sensory feedback that the partners receive. We therefore studied the EEG brain activity of dyads in a task that required the smooth pursuit of a target and did not involve any extrinsic rhythms. Partners controlled orthogonal axes of the two-dimensional motion of an object that had to be kept on the target. Using several methods for analyzing hyper-brain coupling, we could not detect signs of coordinated brain activity. However, we found several brain regions in which the frequency-specific activity significantly correlated with the objective task performance, the subjective experience thereof, and of the collaboration. Activity in these regions has been linked to motor control, sensorimotor integration, executive control and emotional processing. Our results suggest that neural correlates of intersubjectivity encompass large parts of brain areas that are considered to be involved in sensorimotor control without necessarily coordinating their activity across agents.

Socializing Sensorimotor Contingencies

The aim of this review is to highlight the idea of grounding social cognition in sensorimotor interactions shared across agents. We discuss an action-oriented account that emerges from a broader interpretation of the concept of sensorimotor contingencies. We suggest that dynamic informational and sensorimotor coupling across agents can mediate the deployment of action-effect contingencies in social contexts. We propose this concept of socializing sensorimotor contingencies (socSMCs) as a shared framework of analysis for processes within and across brains and bodies, and their physical and social environments. In doing so, we integrate insights from different fields, including neuroscience, psychology, and research on human-robot interaction. We review studies on dynamic embodied interaction and highlight empirical findings that suggest an important role of sensorimotor and informational entrainment in social contexts. Furthermore, we discuss links to closely related concepts, such as enactivism, models of coordination dynamics and others, and clarify differences to approaches that focus on mentalizing and high-level cognitive representations. Moreover, we consider conceptual implications of rethinking cognition as social sensorimotor coupling. The insight that social cognitive phenomena like joint attention, mutual trust or empathy rely heavily on the informational and sensorimotor coupling between agents may provide novel remedies for people with disturbed social cognition and for situations of disturbed social interaction. Furthermore, our proposal has potential applications in the field of human-robot interaction where socSMCs principles might lead to more natural and intuitive interfaces for human users.

Stress enhances emotional memory-related theta oscillations in the medial temporal lobe

Stressful events impact memory formation, in particular for emotionally arousing stimuli. Although these stress effects on emotional memory formation have potentially far-reaching implications, the underlying neural mechanisms are not fully understood. Specifically, the temporal processing dimension of the mechanisms involved in emotional memory formation under stress remains elusive. Here, we used magnetoencephalography (MEG) to examine the neural processes underlying stress effects on emotional memory formation with high temporal and spatial resolution and a particular focus on theta oscillations previously implicated in mnemonic binding. Healthy participants (n = 53) underwent a stress or control procedure before encoding emotionally neutral and negative pictures, while MEG was recorded. Memory for the pictures was probed in a recognition test 24 h after encoding. In this recognition test, stress did not modulate the emotional memory enhancement but led to significantly higher confidence in memory for negative compared to neutral stimuli. Our neural data revealed that stress increased memory-related theta oscillations specifically in medial temporal and occipito-parietal regions. Further, this stress-related increase in theta power emerged during memory formation for emotionally negative but not for neutral stimuli. These findings indicate that acute stress can enhance, in the medial temporal lobe, oscillations at a frequency that is ideally suited to bind the elements of an ongoing emotional episode, which may represent a mechanism to facilitate the storage of emotionally salient events that occurred in the context of a stressful encounter.

Preparatory delta phase response is correlated with naturalistic speech comprehension performance

While human speech comprehension is thought to be an active process that involves top-down predictions, it remains unclear how predictive information is used to prepare for the processing of upcoming speech information. We aimed to identify the neural signatures of the preparatory processing of upcoming speech. Participants selectively attended to one of two competing naturalistic, narrative speech streams, and a temporal response function (TRF) method was applied to derive event-related-like neural responses from electroencephalographic data. The phase responses to the attended speech at the delta band (1-4 Hz) were correlated with the comprehension performance of individual participants, with a latency of - 200-0 ms relative to the onset of speech amplitude envelope fluctuations over the fronto-central and left-lateralized parietal electrodes. The phase responses to the attended speech at the alpha band also correlated with comprehension performance but with a latency of 650-980 ms post-onset over the fronto-central electrodes. Distinct neural signatures were found for the attentional modulation, taking the form of TRF-based amplitude responses at a latency of 240-320 ms post-onset over the left-lateralized fronto-central and occipital electrodes. Our findings reveal how the brain gets prepared to process an upcoming speech in a continuous, naturalistic speech context.

Speaker-Listener Neural Coupling Reveals an Adaptive Mechanism for Speech Comprehension in a Noisy Environment

Comprehending speech in noise is an essential cognitive skill for verbal communication. However, it remains unclear how our brain adapts to the noisy environment to achieve comprehension. The present study investigated the neural mechanisms of speech comprehension in noise using an functional near-infrared spectroscopy-based inter-brain approach. A group of speakers was invited to tell real-life stories. The recorded speech audios were added with meaningless white noise at four signal-to-noise levels and then played to listeners. Results showed that speaker-listener neural couplings of listener's left inferior frontal gyri (IFG), that is, sensorimotor system, and right middle temporal gyri (MTG), angular gyri (AG), that is, auditory system, were significantly higher in listening conditions than in the baseline. More importantly, the correlation between neural coupling of listener's left IFG and the comprehension performance gradually became more positive with increasing noise level, indicating an adaptive role of sensorimotor system in noisy speech comprehension; however, the top behavioral correlations for the coupling of listener's right MTG and AG were only obtained in mild noise conditions, indicating a different and less robust mechanism. To sum up, speaker-listener coupling analysis provides added value and new sight to understand the neural mechanism of speech-in-noise comprehension.

BiPOLES is an optogenetic tool developed for bidirectional dual-color control of neurons

Optogenetic manipulation of neuronal activity through excitatory and inhibitory opsins has become an indispensable experimental strategy in neuroscience research. For many applications bidirectional control of neuronal activity allowing both excitation and inhibition of the same neurons in a single experiment is desired. This requires low spectral overlap between the excitatory and inhibitory opsin, matched photocurrent amplitudes and a fixed expression ratio. Moreover, independent activation of two distinct neuronal populations with different optogenetic actuators is still challenging due to blue-light sensitivity of all opsins. Here we report BiPOLES, an optogenetic tool for potent neuronal excitation and inhibition with light of two different wavelengths. BiPOLES enables sensitive, reliable dual-color neuronal spiking and silencing with single- or two-photon excitation, optical tuning of the membrane voltage, and independent optogenetic control of two neuronal populations using a second, blue-light sensitive opsin. The utility of BiPOLES is demonstrated in worms, flies, mice and ferrets.

Spike-timing-dependent plasticity can account for connectivity aftereffects of dual-site transcranial alternating current stimulation

Transcranial alternating current stimulation (tACS), applied to two brain sites with different phase lags, has been shown to modulate stimulation-outlasting functional EEG connectivity between the targeted regions. Given the lack of knowledge on mechanisms of tACS aftereffects, it is difficult to further enhance effect sizes and reduce variability in experiments. In this computational study, we tested if spike-timing-dependent plasticity (STDP) can explain stimulation-outlasting connectivity modulation by dual-site tACS and explored the effects of tACS parameter choices. Two populations of spiking neurons were coupled with synapses subject to STDP, and results were validated via a re-analysis of EEG data. Our simulations showed stimulation-outlasting connectivity changes between in- and anti-phase tACS, dependent on both tACS frequency and synaptic conduction delays. Importantly, both a simple network entraining to a wide range of tACS frequencies as well as a more realistic network that spontaneously oscillated at alpha frequency predicted that the largest effects would occur for short conduction delays between the stimulated regions. This finding agreed with experimental EEG connectivity modulation by 10Hz tACS, showing a clear negative correlation of tACS effects with estimated conduction delays between regions. In conclusion, STDP can explain connectivity aftereffects of dual-site tACS. However, not all combinations of tACS frequency and application sites are expected to effectively modulate connectivity via STDP. We therefore suggest using appropriate computational models and/or EEG analysis for planning and interpretation of dual-site tACS studies relying on aftereffects.

A Spatially-Coded Visual Brain-Computer Interface for Flexible Visual Spatial Information Decoding

Conventional visual BCIs, in which control channels are tagged with stimulation patterns to elicit distinguishable brain patterns, has made impressive progress in terms of the information transfer rates (ITRs). However, less development has been seen with respect to user experience and complexity of the technical setup. The requirement to tag each of targets by a unique stimulus substantially limits the flexibility of conventional visual BCI systems. A method for decoding the targets in the environment flexibly was therefore proposed in the present study. A BCI speller with thirteen symbols drawn on paper was developed. The symbols were interspersed with four flickers with distinct frequencies, but the user did not have to gaze at flickers. Rather, subjects could spell a sequence by looking at the symbols on the paper. In a cue-guided spelling task, the average offline and online accuracies reached 89.3± 7.3% and 90.3± 6.9% for 13 subjects, corresponding to ITRs of 43.0± 7.4 bit/min and 43.8± 6.8 bit/min. In an additional free-spelling task for seven out of thirteen subjects, an accuracy of 92.3± 3.1% and an ITR of 45.6± 3.3 bit/min were achieved. Analysis of a simulated online system showed the possibility to reach an average ITR of 105.8 bit/min by reducing the epoch duration from 4 to 1 second. Reliable BCI control is possible by gazing at targets in the environment instead of dedicated stimuli which encode control channels. The proposed method can drastically reduce the technical effort for visual BCIs and thereby advance their applications outside the laboratory.

Data-Driven Classification of Spectral Profiles Reveals Brain Region-Specific Plasticity in Blindness

Congenital blindness has been shown to result in behavioral adaptation and neuronal reorganization, but the underlying neuronal mechanisms are largely unknown. Brain rhythms are characteristic for anatomically defined brain regions and provide a putative mechanistic link to cognitive processes. In a novel approach, using magnetoencephalography resting state data of congenitally blind and sighted humans, deprivation-related changes in spectral profiles were mapped to the cortex using clustering and classification procedures. Altered spectral profiles in visual areas suggest changes in visual alpha-gamma band inhibitory-excitatory circuits. Remarkably, spectral profiles were also altered in auditory and right frontal areas showing increased power in theta-to-beta frequency bands in blind compared with sighted individuals, possibly related to adaptive auditory and higher cognitive processing. Moreover, occipital alpha correlated with microstructural white matter properties extending bilaterally across posterior parts of the brain. We provide evidence that visual deprivation selectively modulates spectral profiles, possibly reflecting structural and functional adaptation.

Mathematical Relations Between Measures of Brain Connectivity Estimated From Electrophysiological Recordings for Gaussian Distributed Data

A large variety of methods exist to estimate brain coupling in the frequency domain from electrophysiological data measured, e.g., by EEG and MEG. Those data are to reasonable approximation, though certainly not perfectly, Gaussian distributed. This work is based on the well-known fact that for Gaussian distributed data, the cross-spectrum completely determines all statistical properties. In particular, for an infinite number of data, all normalized coupling measures at a given frequency are a function of complex coherency. However, it is largely unknown what the functional relations are. We here present those functional relations for six different measures: the weighted phase lag index, the phase lag index, the absolute value and imaginary part of the phase locking value (PLV), power envelope correlation, and power envelope correlation with correction for artifacts of volume conduction. With the exception of PLV, the final results are simple closed form formulas. In an excursion we also discuss differences between short time Fourier transformation and Hilbert transformation for estimations in the frequency domain. We tested in simulations of linear and non-linear dynamical systems and for empirical resting state EEG on sensor level to what extent a model, namely the respective function of coherency, can explain the observed couplings. For empirical data we found that for measures of phase-phase coupling deviations from the model are in general minor, while power envelope correlations systematically deviate from the model for all frequencies. For power envelope correlation with correction for artifacts of volume conduction the model cannot explain the observed couplings at all. We also analyzed power envelope correlation as a function of time and frequency in an event related experiment using a stroop reaction task and found significant event related deviations mostly in the alpha range.

Blunted neural and psychological stress processing predicts future grey matter atrophy in multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is characterized by two neuropathological key aspects: inflammation and neurodegeneration. Clinical studies support a prospective link between psychological stress and subsequent inflammatory disease activity. However, it is unknown if a similar link exists for grey matter (GM) degeneration as the key driver of irreversible disability.

METHODS

We tested whether neural network activity triggered in a psychological fMRI stress paradigm (a mental arithmetic task including social evaluation) conducted at a baseline time point predicts future GM atrophy in 25 persons with MS (14 females). Atrophy was determined between the baseline and a follow-up time point with a median delay of 1012 (Rg: 717-1439) days. Additionally, atrophy was assessed in 22 healthy subjects (13 females; median delay 771 [Rg: 740-908] days between baseline and follow-up) for comparison.

RESULTS

An analysis of longitudinal atrophy in patients revealed GM loss in frontal, parietal, and cerebellar areas. Cerebellar atrophy was more pronounced in patients than controls. Future parietal and cerebellar atrophy could be predicted based on activity of two networks. Perceived psychological stress was negatively related to future parietal atrophy in patients and activity of the network predictive of parietal atrophy was positively linked to perceived stress.

CONCLUSIONS

We have shown that blunted neural and psychological stress processing have a detrimental effect on the course of MS and are interrelated. Together with research showing that psychological and neural stress processing can be altered through interventions, our findings suggest that stress processing might constitute an important modifiable disease factor.

Coupling of gamma band activity to sleep spindle oscillations - a combined EEG/MEG study

Sleep spindles are crucial to memory consolidation. Cortical gamma oscillations (30-100 Hz) are considered to reflect processing of memory in local cortical networks. The temporal and regulatory relationship between spindles and gamma activity might therefore provide clues into how sleep strengthens cortical memory representations. Here, combining EEG with MEG recordings during sleep in healthy humans (n = 12), we investigated the temporal relationships of cortical gamma band activity, always measured by MEG, during fast (12-16 Hz) and slow (8-12 Hz) sleep spindles detected in the EEG or MEG. Time-frequency distributions did not show a consistent coupling of gamma to the spindle oscillation, although activity in the low gamma (30-40 Hz) and neighboring beta range (<30 Hz) was generally increased during spindles. However, more fine-grained analyses of cross-frequency interactions revealed that both low and high gamma power (30-100 Hz) was coupled to the phase of slow and fast EEG spindles, importantly, with this coupling at a fixed phase only for the oscillations within an individual spindle, but with variable phase across spindles. We did not observe any coupling of gamma activity for spindles detected solely in the MEG and not in parallel EEG recordings, raising the possibility that these are more local spindles of different quality. Similar to fast spindle activity, low gamma band power followed a ~0.025 Hz infraslow rhythm during sleep whose frequency, however, was significantly faster than that of spindle activity. Our findings suggest a general function of fast and slow spindles that by spanning larger cortical networks might serve to synchronize gamma band activity occurring in more local but distributed networks. Thereby, spindles might help linking local memory processing between distributed networks.

The hippocampal formation of two carnivore species: The feliform banded mongoose and the caniform domestic ferret

Employing cyto-, myelo-, and chemoarchitectural staining techniques, we analyzed the structure of the hippocampal formation in the banded mongoose and domestic ferret, species belonging to the two carnivoran superfamilies, which have had independent evolutionary trajectories for the past 55 million years. Our observations indicate that, despite the time since sharing a last common ancestor, these species show extensive similarities. The four major portions of the hippocampal formation (cornu Ammonis, dentate gyrus, subicular complex, and entorhinal cortex) were readily observed, contained the same internal subdivisions, and maintained the topological relationships of these subdivisions that could be considered typically mammalian. In addition, adult hippocampal neurogenesis was observed in both species, occurring at a rate similar to that observed in other mammals. Despite the overall similarities, several differences to each other, and to other mammalian species, were observed. We could not find evidence for the presence of the CA2 and CA4 fields of the cornu Ammonis region. In the banded mongoose the dentate gyrus appears to be comprised of up to seven lamina, through the sublamination of the molecular and granule cell layers, which is not observed in the domestic ferret. In addition, numerous subtle variations in chemoarchitecture between the two species were observed. These differences may contribute to an overall variation in the functionality of the hippocampal formation between the species, and in comparison to other mammalian species. These similarities and variations are important to understanding to what extent phylogenetic affinities and constraints affect potential adaptive evolutionary plasticity of the hippocampal formation.

The diencephalon of two carnivore species: The feliform banded mongoose and the caniform domestic ferret

This study provides an analysis of the cytoarchitecture, myeloarchitecture, and chemoarchitecture of the diencephalon (dorsal thalamus, ventral thalamus, and epithalamus) of the banded mongoose (Mungos mungo) and domestic ferret (Mustela putorius furo). Using architectural and immunohistochemical stains, we observe that the nuclear organization of the diencephalon is very similar in the two species, and similar to that reported in other carnivores, such as the domestic cat and dog. The same complement of putatively homologous nuclei were identified in both species, with only one variance, that being the presence of the perireticular nucleus in the domestic ferret, that was not observed in the banded mongoose. The chemoarchitecture was also mostly consistent between species, although there were a number of minor variations across a range of nuclei in the density of structures expressing the calcium-binding proteins parvalbumin, calbindin, and calretinin. Thus, despite almost 53 million years since these two species of carnivores shared a common ancestor, strong phylogenetic constraints appear to limit the potential for adaptive evolutionary plasticity within the carnivore order. Apart from the presence of the perireticular nucleus, the most notable difference between the species studied was the physical inversion of the dorsal lateral geniculate nucleus, as well as the lateral posterior and pulvinar nuclei in the domestic ferret compared to the banded mongoose and other carnivores, although this inversion appears to be a feature of the Mustelidae family. While no functional sequelae are suggested, this inversion is likely to result from the altricial birth of Mustelidae species.

The amygdaloid body of two carnivore species: The feliform banded mongoose and the caniform domestic ferret

The current study provides an analysis of the cytoarchitecture, myeloarchitecture, and chemoarchitecture of the amygdaloid body of the banded mongoose (Mungos mungo) and domestic ferret (Mustela putorius furo). Using architectural and immunohistochemical stains, we observe that the organization of the nuclear and cortical portions of the amygdaloid complex is very similar in both species. The one major difference is the presence of a cortex-amygdala transition zone observed in the domestic ferret that is absent in the banded mongoose. In addition, the chemoarchitecture is, for the most part, quite similar in the two species, but several variances, such as differing densities of neurons expressing the calcium-binding proteins in specific nuclei are noted. Despite this, certain aspects of the chemoarchitecture, such as the cholinergic innervation of the magnocellular division of the basal nuclear cluster and the presence of doublecortin expressing neurons in the shell division of the accessory basal nuclear cluster, appear to be consistent features of the Eutherian mammal amygdala. The domestic ferret presented with an overall lower myelin density throughout the amygdaloid body than the banded mongoose, a feature that may reflect artificial selection in the process of domestication for increased juvenile-like behavior in the adult domestic ferret, such as a muted fear response. The shared, but temporally distant, ancestry of the banded mongoose and domestic ferret allows us to generate observations relevant to understanding the relative influence that phylogenetic constraints, adaptive evolutionary plasticity, and the domestication process may play in the organization and chemoarchitecture of the amygdaloid body.

Parkinson's disease uncovers an underlying sensitivity of subthalamic nucleus neurons to beta-frequency cortical input in vivo

Abnormally sustained beta-frequency synchronisation between the motor cortex and subthalamic nucleus (STN) is associated with motor symptoms in Parkinson's disease (PD). It is currently unclear whether STN neurons have a preference for beta-frequency input (12-35 Hz), rather than cortical input at other frequencies, and how such a preference would arise following dopamine depletion. To address this question, we combined analysis of cortical and STN recordings from awake human PD patients undergoing deep brain stimulation surgery with recordings of identified STN neurons in anaesthetised rats. In these patients, we demonstrate that a subset of putative STN neurons is strongly and selectively sensitive to magnitude fluctuations of cortical beta oscillations over time, linearly increasing their phase-locking strength with respect to the full range of instantaneous amplitude in the beta-frequency range. In rats, we probed the frequency response of STN neurons in the cortico-basal-ganglia-network more precisely, by recording spikes evoked by short bursts of cortical stimulation with variable frequency (4-40 Hz) and constant amplitude. In both healthy and dopamine-depleted rats, only beta-frequency stimulation led to a progressive reduction in the variability of spike timing through the stimulation train. This suggests, that the interval of beta-frequency input provides an optimal window for eliciting the next spike with high fidelity. We hypothesize, that abnormal activation of the indirect pathway, via dopamine depletion and/or cortical stimulation, could trigger an underlying sensitivity of the STN microcircuit to beta-frequency input.

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STN-neurons are selectively entrained to cortical beta oscillations in PD patients.

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Phase-locking of STN-neurons is linearly dependent on oscillation magnitude.

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Beta bursts in LFP/EEG are accompanied by transient synchronisation of STN spiking.

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STN neurons are selectively entrained to cortical beta stimulation in rats.

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Beta-selectivity of STN neurons is present in control and dopamine-depleted rats.

Stress Impairs Intentional Memory Control through Altered Theta Oscillations in Lateral Parietal Cortex

Accumulating evidence suggests that forgetting is not necessarily a passive process but that we can, to some extent, actively control what we remember and what we forget. Although this intentional control of memory has potentially far-reaching implications, the factors that influence our capacity to intentionally control our memory are largely unknown. Here, we tested whether acute stress may disrupt the intentional control of memory and, if so, through which neural mechanism. We exposed healthy men and women to a stress (n = 27) or control (n = 26) procedure before they aimed repeatedly to retrieve some previously learned cue-target pairs and to actively suppress others. While control participants showed reduced memory for suppressed compared with baseline pairs in a subsequent memory test, this suppression-induced forgetting was completely abolished after stress. Using magnetoencephalography (MEG), we show that the reduced ability to suppress memories after stress is associated with altered theta activity in the inferior temporal cortex when the control process (retrieval or suppression) is triggered and in the lateral parietal cortex when control is exerted, with the latter being directly correlated with the stress hormone cortisol. Moreover, the suppression-induced forgetting was linked to altered connectivity between the hippocampus and right dorsolateral prefrontal cortex (PFC), which in turn was negatively correlated to stress-induced cortisol increases. These findings provide novel insights into conditions under which our capacity to actively control our memory breaks down and may have considerable implications for stress-related psychopathologies, such as posttraumatic stress disorder (PTSD), that are characterized by unwanted memories of distressing events.SIGNIFICANCE STATEMENT It is typically assumed that forgetting is a passive process that can hardly be controlled. There is, however, evidence that we may actively control, to some extent, what we remember and what we forget. This intentional memory control has considerable implications for mental disorders in which patients suffer from unwanted (e.g., traumatic) memories. Here, we demonstrate that the capacity to intentionally control our memory breaks down after stress. Using magnetoencephalography (MEG), we show that this stress-induced memory control deficit is linked to altered activity in the lateral parietal cortex and the connectivity between the hippocampus and right prefrontal cortex (PFC). These findings provide novel insights into conditions under which memory control fails and are highly relevant in the context of stress-related psychopathologies.

Non-rhythmic temporal prediction involves phase resets of low-frequency delta oscillations

The phase of neural oscillatory signals aligns to the predicted onset of upcoming stimulation. Whether such phase alignments represent phase resets of underlying neural oscillations or just rhythmically evoked activity, and whether they can be observed in a rhythm-free visual context, however, remains unclear. Here, we recorded the magnetoencephalogram while participants were engaged in a temporal prediction task, judging the visual or tactile reappearance of a uniformly moving stimulus. The prediction conditions were contrasted with a control condition to dissociate phase adjustments of neural oscillations from stimulus-driven activity. We observed stronger delta band inter-trial phase consistency (ITPC) in a network of sensory, parietal and frontal brain areas, but no power increase reflecting stimulus-driven or prediction-related evoked activity. Delta ITPC further correlated with prediction performance in the cerebellum and visual cortex. Our results provide evidence that phase alignments of low-frequency neural oscillations underlie temporal predictions in a non-rhythmic visual and crossmodal context.

Sex Disparities in the Self-Evaluation of Subthalamic Deep Brain Stimulation Effects on Mood and Personality in Parkinson's Disease Patients

Changes in personality are one of the main concerns Parkinson's disease (PD) patients raise when facing the decision to undergo neurosurgery for deep brain stimulation (DBS) of the subthalamic nucleus (STN). While clinical instruments for monitoring functional changes following DBS surgery are well-established in the daily therapeutic routine, personality issues are far less systematically encompassed. Moreover, while sex disparities in the outcomes of STN-DBS therapy have been reported, little is known about the different effects that DBS treatment may have on mood and personality traits in female and male patients. To this aim, the effect of STN-DBS on personality traits was assessed in 46 PD patients (12 women and 34 men) by means of the Freiburg Personality Inventory. The Becks Depression Inventory (BDI-I) and the Parkinson's Disease Questionnaire were used to evaluate patients' level of depression and quality of life (QoL). Patients completed the questionnaires a few days before, within the first year, and 2 years after surgery. The 12 personality traits defined by the FPI-R questionnaire did not change significantly after STN-DBS surgery (p = 0.198). Women declared higher depression scores through all study stages (p = 0.009), but also showed a stronger QoL amelioration after surgery than male patients (p = 0.022). The BDI-I scores of female patients clearly correlated with their levodopa equivalent daily dose (LEDD; r = 0.621, p = 0.008). Remarkably, in both male and female patients, higher pre-operative LEDDs were related to worse post-operative QoL scores (p = 0.034). These results mitigate the concerns about systematic personality changes due to STN-DBS treatment in PD patients and encourage an early DBS approach, before severe levodopa-induced sequelae may irreparably compromise the patients' QoL. In the future, more focus should lie on sex-related effects, since female patients seem to profit more than male patients from STN-DBS, in terms of reduced depressive symptoms associated with a reduction of the LEDD and amelioration of QoL. These aspects may help to redress the sex imbalance in PD patients treated with DBS, given that women are still strongly under-represented.

Subjective Evaluation of Performance in a Collaborative Task Is Better Predicted From Autonomic Response Than From True Achievements

Whereas the fundamental role of the body in social cognition seems to be generally accepted, elucidating the bodily mechanisms associated with non-verbal communication and cooperation between two or more persons is still a challenging endeavor. In this article we propose a fresh approach for investigating the function of the autonomic nervous system that is reflected in parameters of heart rate variability, respiration, and electrodermal activity in a social setting. We analyzed autonomic parameters of dyads solving a target-tracking task together with the partner or individually. A machine classifier was trained to predict the subjects' rating of performance and collaboration either from tracking error data or from the set of autonomic parameters. When subjects collaborated, this classifier could predict the subjective performance ratings better from the autonomic response than from the objective performance of the subjects. However, when they solved the task individually, predictability from autonomic parameters dropped to the level of objective performance, indicating that subjects were more rational in rating their performance in this condition. Moreover, the model captured general knowledge about the population that allows it to predict the performance ratings of an unseen subject significantly better than chance. Our results suggest that, in particular in situations that require collaboration with others, evaluation of performance is shaped by the bodily processes that are quantified by autonomic parameters. Therefore, subjective performance assessments appear to be modulated not only by the output of a rational or discriminative system that tracks the objective performance but to a significant extent also by interoceptive processes.

Aerobic Exercise Induces Functional and Structural Reorganization of CNS Networks in Multiple Sclerosis: A Randomized Controlled Trial

Objectives: Evidence from animal studies suggests that aerobic exercise may promote neuroplasticity and could, therefore, provide therapeutic benefits for neurological diseases such as multiple sclerosis (MS). However, the effects of exercise in human CNS disorders on the topology of brain networks, which might serve as an outcome at the interface between biology and clinical performance, remain poorly understood.

Methods: We investigated functional and structural networks in patients with relapsing-remitting MS in a clinical trial of standardized aerobic exercise. Fifty-seven patients were randomly assigned to moderate-intensity exercise for 3 months or a non-exercise control group. We reconstructed functional networks based on resting-state functional magnetic resonance imaging (MRI) and used probabilistic tractography on diffusion-weighted imaging data for structural networks.

Results: At baseline, compared to 30 healthy controls, patients exhibited decreased structural connectivity that was most pronounced in hub regions of the brain. Vice versa, functional connectivity was increased in hubs. After 3 months, we observed hub independent increased functional connectivity in the exercise group while the control group presented a loss of functional hub connectivity. On a structural level, the control group remained unchanged, while the exercise group had also increased connectivity. Increased clustering of hubs indicates a better structural integration and internal connectivity at the top of the network hierarchy.

Conclusion: Increased functional connectivity of hubs contrasts a loss of structural connectivity in relapsing-remitting MS. Under an exercise condition, a further hub independent increase of functional connectivity seems to translate in higher structural connectivity of the whole brain.

Distinct Functional Connectivity Signatures of Impaired Social Cognition in Multiple Sclerosis

Objective: Multiple sclerosis (MS) is characterized by impairments in basic cognitive functions such as information processing speed as well as in more complex, higher-order domains such as social cognition. However, as these deficits often co-occur, it has remained challenging to determine whether they have a specific pathological basis or are driven by shared biology.

Methods: To identify neural signatures of social cognition deficits in MS, data were analyzed from n = 29 patients with relapsing–remitting MS and n = 29 healthy controls matched for age, sex, and education. We used neuropsychological assessments of information processing speed, attention, learning, working memory, and relevant aspects of social cognition (theory of mind, emotion recognition (ER), empathy) and employed neuroimaging of CNS networks using resting-state functional connectivity.

Results: MS patients showed significant deficits in verbal learning and memory, as well as implicit ER. Performance in these domains was uncorrelated. Functional connectivity analysis identified a distinct network characterized by significant associations between poorer ER and lower connectivity of the fusiform gyrus (FFG) with the right lateral occipital cortex, which also showed lower connectivity in patients compared to controls. Moreover, while ER was correlated with MS symptoms such as fatigue and motor/sensory functioning on a behavioral level, FFG connectivity signatures of social cognition deficits showed no overlap with these symptoms.

Conclusions: Our analyses identify distinct functional connectivity signatures of social cognition deficits in MS, indicating that these alterations may occur independently from those in other neuropsychological functions.

Phase-specific manipulation of rhythmic brain activity by transcranial alternating current stimulation

BACKGROUND

Oscillatory phase has been proposed as a key parameter defining the spatiotemporal structure of neural activity. To enhance our understanding of brain rhythms and improve clinical outcomes in pathological conditions, modulation of neural activity by transcranial alternating current stimulation (tACS) emerged as a promising approach. However, the phase-specificity of tACS effects in humans is still critically debated.

OBJECTIVE

Here, we investigated the phase-specificity of tACS on visually evoked steady state responses (SSRs) in 24 healthy human participants.

METHODS

We used an intermittent electrical stimulation protocol and assessed the influence of tACS on SSR amplitude in the interval immediately following tACS. A neural network model served to validate the plausibility of experimental findings.

RESULTS

We observed a modulation of SSR amplitudes dependent on the phase shift between flicker and tACS. The tACS effect size was negatively correlated with the strength of flicker-evoked activity. Supported by simulations, data suggest that strong network synchronization limits further neuromodulation by tACS. Neural sources of phase-specific effects were localized in the parieto-occipital cortex within flicker-entrained regions. Importantly, the optimal phase shift between flicker and tACS associated with strongest SSRs was correlated with SSR phase delays in the tACS target region.

CONCLUSIONS

Overall, our data provide electrophysiological evidence for phase-specific modulations of rhythmic brain activity by tACS in humans. As the optimal timing of tACS application was dependent on cortical SSR phase delays, our data suggest that tACS effects were not mediated by retinal co-stimulation. These findings highlight the potential of tACS for controlled, phase-specific modulations of neural activity.

Post-training Load-Related Changes of Auditory Working Memory - An EEG Study

Working memory (WM) refers to the temporary retention and manipulation of information, and its capacity is highly susceptible to training. Yet, the neural mechanisms that allow for increased performance under demanding conditions are not fully understood. We expected that post-training efficiency in WM performance modulates neural processing during high load tasks. We tested this hypothesis, using electroencephalography (EEG) (N = 39), by comparing source space spectral power of healthy adults performing low and high load auditory WM tasks. Prior to the assessment, participants either underwent a modality-specific auditory WM training, or a modality-irrelevant tactile WM training, or were not trained (active control). After a modality-specific training participants showed higher behavioral performance, compared to the control. EEG data analysis revealed general effects of WM load, across all training groups, in the theta-, alpha-, and beta-frequency bands. With increased load theta-band power increased over frontal, and decreased over parietal areas. Centro-parietal alpha-band power and central beta-band power decreased with load. Interestingly, in the high load condition a tendency toward reduced beta-band power in the right medial temporal lobe was observed in the modality-specific WM training group compared to the modality-irrelevant and active control groups. Our finding that WM processing during the high load condition changed after modality-specific WM training, showing reduced beta-band activity in voice-selective regions, possibly indicates a more efficient maintenance of task-relevant stimuli. The general load effects suggest that WM performance at high load demands involves complementary mechanisms, combining a strengthening of task-relevant and a suppression of task-irrelevant processing.

Crossmodal Congruency Enhances Performance of Healthy Older Adults in Visual-Tactile Pattern Matching

One of the pivotal challenges of aging is to maintain independence in the activities of daily life. In order to adapt to changes in the environment, it is crucial to continuously process and accurately combine simultaneous input from different sensory systems, i.e., crossmodal or multisensory integration. With aging, performance decreases in multiple domains, affecting bottom-up sensory processing as well as top-down control. However, whether this decline leads to impairments in crossmodal interactions remains an unresolved question. While some researchers propose that crossmodal interactions degrade with age, others suggest that they are conserved or even gain compensatory importance. To address this question, we compared the behavioral performance of older and young participants in a well-established crossmodal matching task, requiring the evaluation of congruency in simultaneously presented visual and tactile patterns. Older participants performed significantly worse than young controls in the crossmodal task when being stimulated at their individual unimodal visual and tactile perception thresholds. Performance increased with adjustment of stimulus intensities. This improvement was driven by better detection of congruent stimulus pairs, while the detection of incongruent pairs was not significantly enhanced. These results indicate that age-related impairments lead to poor performance in complex crossmodal scenarios and demanding cognitive tasks. Crossmodal congruency effects attenuate the difficulties of older adults in visuotactile pattern matching and might be an important factor to drive the benefits of older adults demonstrated in various crossmodal integration scenarios. Congruency effects might, therefore, be used to develop strategies for cognitive training and neurological rehabilitation.

Pallidal lead placement in dystonia: leads of non-responders are contained within an anatomical range defined by responders

Background

Deep brain stimulation (DBS) within the pallidum represents an effective and well-established treatment for isolated dystonia. However, clinical outcome after surgery may be variable with limited response in 10–25% of patients. The effect of lead location on clinical improvement is still under debate.

Objective

To identify stimulated brain regions associated with the most beneficial clinical outcome in dystonia patients.

Methods

18 patients with cervical and generalized dystonia with chronic DBS of the internal pallidum were investigated. Patients were grouped according to their clinical improvement into responders, intermediate responders and non-responders. Magnetic resonance and computed tomography images were co-registered, and the volume of tissue activated (VTA) with respect to the pallidum of individual patients was analysed.

Results

VTAs in responders (n = 11), intermediate responders (n = 3) and non-responders (n = 4) intersected with the posterior internal (GPi) and external (GPe) pallidum and the subpallidal area. VTA heat maps showed an almost complete overlap of VTAs of responders, intermediate and non-responders. VTA coverage of the GPi was not higher in responders. In contrast, VTAs of intermediate and non-responders covered the GPi to a significantly larger extent in the left hemisphere (p < 0.01).

Conclusions

DBS of ventral parts of the posterior GPi, GPe and the adjacent subpallidal area containing pallidothalamic output projections resulted in favourable clinical effects. Of note, non-responders were also stimulated within the same area. This suggests that factors other than mere lead location (e.g., clinical phenotype, genetic background) have determined clinical outcome in the present cohort.

Electronic supplementary material

The online version of this article (10.1007/s00415-020-09753-z) contains supplementary material, which is available to authorized users.

Functional and structural connectivity substrates of cognitive performance in relapsing remitting multiple sclerosis with mild disability

Multiple Sclerosis (MS) is the most common chronic inflammatory and neurodegenerative disease of the central nervous system (CNS), which can lead to severe cognitive impairment over time. Magnetic resonance imaging (MRI) is currently the best available biomarker to track MS pathophysiology in vivo and examine the link to clinical disability. However, conventional MRI metrics have limited sensitivity and specificity to detect direct associations between symptoms and their underlying CNS substrates. In this study, we aimed to investigate structural and resting state functional connectomes and subnetworks associated with neuropsychological (NP) performance using a graph theoretical approach. A comprehensive NP test battery was administered in a sample of patients with relapsing remitting MS (RRMS) and mild disability [n = 33, F/M = 20/13, age = 40.9 ± 9.7, median [Expanded Disability Status Scale] (EDSS) = 2, range =0-4] and compared to healthy controls (HC) [n = 29, F/M = 19/10, age = 41.0 ± 8.5] closely matched for age, sex, and level of education. The NP battery comprised the most relevant domains of cognitive dysfunction in MS including attention, processing speed, verbal and spatial learning and memory, and executive function. While standard MRI metrics showed good correlations with TAP Alertness test, disease duration and neurological exams, structural networks showed closer associations with 9-hole peg test and cognitive performances. Decreased graph strength was associated with two out of the 5 NP tests in the spatial learning and memory domain specified by BVMT [Sum 1-3] and BVMT [Recall], and with also SDMT which is one out of the 9 NP tests in the attention/processing speed domain, while no correlation was found between these scores and functional connectivity. Nodal strength was decreased in all subnetworks based on Yeo atlas in patients compared to HC; however, no difference was observed in nodal level of functional connectivity between the groups. The difference in structural and functional nodal connectivity between the groups was also observed in the relationship between structural and functional connectivity within the groups; the relationship between nodal degree and nodal strength was reversed in patients but positive in controls. On a nodal level, structural and functional networks (mainly the default mode network) were correlated with more than one cognitive domain rather than one specific network for each domain within patients. Interestingly, poorer cognitive performance was mostly correlated with increased functional connectivity but decreased structural connectivity in patients. Increased functional connectivity in the default mode network had both positive as well as negative associations with verbal and spatial learning and memory, possibly indicating adaptive and maladaptive mechanisms. In conclusion, our results suggest that cognitive performance, even in patients with RRMS and very mild disability, may reflect a loss of structural connectivity. In contrast, widespread increases in functional connectivity may be the result of maladaptive processes.

Parkin deficiency perturbs striatal circuit dynamics

Loss-of-function mutations in the parkin-encoding PARK2 gene are a frequent cause of young-onset, autosomal recessive Parkinson's disease (PD). Parkin knockout mice have no nigro-striatal neuronal loss but exhibit abnormalities of striatal dopamine transmission and cortico-striatal synaptic function. How these predegenerative changes observed in vitro affect neural dynamics at the intact circuit level, however, remains hitherto elusive. Here, we recorded from motor cortex, striatum and globus pallidus (GP) of anesthetized parkin-deficient mice to assess cortex-basal ganglia circuit dynamics and to dissect cell type-specific functional connectivity in the presymptomatic phase of genetic PD. While ongoing activity of presumed striatal spiny projection neurons and their downstream counterparts in the GP was not different from controls, parkin deficiency had a differential impact on striatal interneurons: In parkin-mutant mice, tonically active neurons displayed elevated activity levels. Baseline firing rates of transgenic striatal fast spiking interneurons (FSI), on the contrary, were reduced and the correlational structure of the FSI microcircuitry was disrupted. The entire transgenic striatal microcircuit showed enhanced and phase-shifted phase coupling to slow (1-3 Hz) cortical population oscillations. Unexpectedly, local field potentials recorded from striatum and GP of parkin-mutant mice robustly displayed amplified beta oscillations (~22 Hz), phase-coupled to cortex. Parkin deficiency selectively increased spike-field coupling of FSIs to beta oscillations. Our findings suggest that loss of parkin function leads to amplifications of synchronized cortico-striatal oscillations and an intrastriatal reconfiguration of interneuronal circuits. This presymptomatic disarrangement of dynamic functional connectivity may precede nigro-striatal neurodegeneration and predispose to imbalance of striatal outflow accompanying symptomatic PD.

Probing neural networks for dynamic switches of communication pathways

Dynamic communication and routing play important roles in the human brain in order to facilitate flexibility in task solving and thought processes. Here, we present a network perturbation methodology that allows investigating dynamic switching between different network pathways based on phase offsets between two external oscillatory drivers. We apply this method in a computational model of the human connectome with delay-coupled neural masses. To analyze dynamic switching of pathways, we define four new metrics that measure dynamic network response properties for pairs of stimulated nodes. Evaluating these metrics for all network pathways, we found a broad spectrum of pathways with distinct dynamic properties and switching behaviors. We show that network pathways can have characteristic timescales and thus specific preferences for the phase lag between the regions they connect. Specifically, we identified pairs of network nodes whose connecting paths can either be (1) insensitive to the phase relationship between the node pair, (2) turned on and off via changes in the phase relationship between the node pair, or (3) switched between via changes in the phase relationship between the node pair. Regarding the latter, we found that 33% of node pairs can switch their communication from one pathway to another depending on their phase offsets. This reveals a potential mechanistic role that phase offsets and coupling delays might play for the dynamic information routing via communication pathways in the brain.

A big challenge in elucidating information processing in the brain is to understand the neural mechanisms that dynamically organize the communication between different brain regions in a flexible and task-dependent manner. In this theoretical study, we present an approach to investigate the routing and gating of information flow along different pathways from one region to another. We show that stimulation of the brain at two sites with different frequencies and oscillatory phases can reveal the underlying effective connectivity. This yields new insights into the underlying processes that govern dynamic switches in the communication pathways between remote sites of the brain.

An Oscillator Ensemble Model of Sequence Learning

Learning and memorizing sequences of events is an important function of the human brain and the basis for forming expectations and making predictions. Learning is facilitated by repeating a sequence several times, causing rhythmic appearance of the individual sequence elements. This observation invites to consider the resulting multitude of rhythms as a spectral “fingerprint” which characterizes the respective sequence. Here we explore the implications of this perspective by developing a neurobiologically plausible computational model which captures this “fingerprint” by attuning an ensemble of neural oscillators. In our model, this attuning process is based on a number of oscillatory phenomena that have been observed in electrophysiological recordings of brain activity like synchronization, phase locking, and reset as well as cross-frequency coupling. We compare the learning properties of the model with behavioral results from a study in human participants and observe good agreement of the errors for different levels of complexity of the sequence to be memorized. Finally, we suggest an extension of the model for processing sequences that extend over several sensory modalities.