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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 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.

Optogenetic manipulation of neuronal activity has become an indispensable experimental strategy in neuroscience research. A large repertoire of excitatory and inhibitory tools allows precise activation or inhibition of genetically targetable neuronal populations. However, an optogenetic tool for reliable bidirectional control of neuronal activity allowing both up- and downregulation of the same neurons in a single experiment is still missing. Here we report BiPOLES, an optogenetic tool for potent excitation and inhibition of the same population of neurons with light of two different colors. BiPOLES consists of an inhibitory, blue-light-sensitive anion-conducting channelrhodopsin fused to an excitatory, red-light-sensitive cation-conducting channelrhodopsin in a single, trafficking-optimized tandem protein. BiPOLES enables multiple new applications including potent dual-color spiking and silencing of the same neurons in vivo and dual-color optogenetic control of two independent neuronal populations.

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.

International audience; 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.

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.

Influential accounts postulate distinct roles of the catecholamine and acetylcholine neuromodulatory systems in cognition and behavior. But previous work found similar effects of these modulators on the response properties of individual cortical neurons. Here, we report a double dissociation between catecholamine and acetylcholine effects at the level of cortex-wide network interactions in humans. A pharmacological boost of catecholamine levels increased cortex-wide interactions during a visual task, but not rest. Conversely, an acetylcholine-boost decreased correlations during rest, but not task. Cortical circuit modeling explained this dissociation by differential changes in two circuit properties: the local excitation-inhibition balance (more strongly altered by catecholamines) and intracortical transmission (more strongly reduced by acetylcholine). The inferred catecholaminergic mechanism also predicted increased behavioral exploration, which we confirmed in human behavior during both a perceptual and value-based choice task. In sum, we identified specific circuit mechanisms for shaping cortex-wide network interactions and behavior by key neuromodulatory systems.

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.

Ageing is characterized by changes in sensory and cognitive abilities. While there is evidence that decline in sensory acuity and enhanced multisensory integration predict cognitive status in healthy older adults, potential mechanistic links between these age-related alterations remain unclear. In the current study, we assessed performance of younger and older healthy adults in a visuotactile delayed match-to-sample task and related indices of multisensory integration to unisensory perceptual thresholds and cognitive assessment data. Additionally, we applied transcranial alternating current stimulation (tACS) to modulate cortical networks found to underlie visuotactile interactions and working-memory matching in our previous work. Analysing response times and signal detection measures, we found older adults to show enhanced multisensory integration and benefit more from successful working memory matching. Both measures predicted cognitive status and correlated positively with each other, suggesting that they likely reflect a common underlying tendency to integrate information. Sensory capability, however, independently predicted cognitive status. tACS with beta frequency (20 Hz) accelerated task performance and this effect was more pronounced in the older group. We conclude that sensory capability and information integration represent independent predictors of cognitive status. Finally, we discuss a potential role of the parietal cortex in mediating augmented integration in older adults.

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 towards 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.

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.

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.

The functional relevance of crossmodal activation (e.g. auditory activation of occipital brain regions) in congenitally blind individuals is still not fully understood. The present study tested whether the occipital cortex of blind individuals is integrated into a challenged functional network. A working memory (WM) training over four sessions was implemented. Congenitally blind and matched sighted participants were adaptively trained with an n-back task employing either voices (auditory training) or tactile stimuli (tactile training). In addition, a minimally demanding 1-back task served as an active control condition. Power and functional connectivity of EEG activity evolving during the maintenance period of an auditory 2-back task were analyzed, run prior to and after the WM training. Modality-specific (following auditory training) and modality-independent WM training effects (following both auditory and tactile training) were assessed. Improvements in auditory WM were observed in all groups, and blind and sighted individuals did not differ in training gains. Auditory and tactile training of sighted participants led, relative to the active control group, to an increase in fronto-parietal theta-band power, suggesting a training-induced strengthening of the existing modality-independent WM network. No power effects were observed in the blind. Rather, after auditory training the blind showed a decrease in theta-band connectivity between central, parietal, and occipital electrodes compared to the blind tactile training and active control groups. Furthermore, in the blind auditory training increased beta-band connectivity between fronto-parietal, central and occipital electrodes. In the congenitally blind, these findings suggest a stronger integration of occipital areas into the auditory WM network.

Cortical single neuron activity and local field potential patterns change at different depths of general anesthesia. Here, we investigate the associated network level changes of functional connectivity. We recorded ongoing electrocorticographic (ECoG) activity from temporo-parieto-occipital cortex of 6 ferrets at various levels of isoflurane/nitrous oxide anesthesia and determined functional connectivity by computing amplitude envelope correlations. Through hierarchical clustering, we derived typical connectivity patterns corresponding to light, intermediate and deep anesthesia. Generally, amplitude correlation strength increased strongly with depth of anesthesia across all cortical areas and frequency bands. This was accompanied, at the deepest level, by the emergence of burst-suppression activity in the ECoG signal and a change of the spectrum of the amplitude envelope. Normalization of functional connectivity to the distribution of correlation coefficients showed that the topographical patterns remained similar across depths of anesthesia, reflecting the functional association of the underlying cortical areas. Thus, while strength and temporal properties of amplitude co-modulation vary depending on the activity of local neural circuits, their network-level interaction pattern is presumably most strongly determined by the underlying structural connectivity.

Pathological synchronisation of beta frequency (12–35 Hz) oscillations between the subthalamic nucleus (STN) and cerebral cortex is thought to contribute to motor impairment in Parkinson's disease (PD). For this cortico-subthalamic oscillatory drive to be mechanistically important, it must influence the firing of STN neurons and, consequently, their downstream targets. Here, we examined the dynamics of synchronisation between STN LFPs and units with multiple cortical areas, measured using frontal ECoG, midline EEG and lateral EEG, during rest and movement. STN neurons lagged cortical signals recorded over midline (over premotor cortices) and frontal (over prefrontal cortices) with stable time delays, consistent with strong corticosubthalamic drive, and many neurons maintained these dynamics during movement. In contrast, most STN neurons desynchronised from lateral EEG signals (over primary motor cortices) during movement and those that did not had altered phase relations to the cortical signals. The strength of synchronisation between STN units and midline EEG in the high beta range (25–35 Hz) correlated positively with the severity of akinetic-rigid motor symptoms across patients. Together, these results suggest that sustained synchronisation of STN neurons to premotor-cortical beta oscillations play an important role in disrupting the normal coding of movement in PD., Highlights • Multi-channel EEG with coincident STN single unit and local field potential recordings • Variable time delays between beta oscillations in different cortical areas and STN neurons. • Frontal/premotor cortical areas have most stable oscillatory synchronisation with STN neurons. • Correlation between cortico-subthalamic beta-frequency synchronisation and clinical scores in PD.

Interhemispheric auditory connectivity via the corpus callosum has been demonstrated to be important for normal speech processing. According to the callosal relay model, directed information flow from the right to the left auditory cortex has been suggested, but this has not yet been proven. For this purpose, 33 healthy participants were investigated with 64-channel EEG while performing the dichotic listening task in which two different consonant–vowel syllables were presented simultaneously to the left (LE) and right ear (RE). eLORETA source estimation was used to investigate the functional (lagged phase synchronization/LPS) and effective (isolated effective coherence/ICoh) connectivity between right and left primary (PAC) and secondary auditory cortices (SAC) in the gamma-band (30–100 Hz) during right and left ear reports. The major finding was a significantly increased effective connectivity in the gamma-band from the right to the left SAC during conscious perception of LE stimuli. In addition, effective and functional connectivity was significantly enhanced during LE as compared to RE reports. These findings give novel insight into transcallosal information transfer during auditory perception by showing that LE performance requires causal interhemispheric inputs from the right to the left auditory cortices, and that this interaction is mediated by synchronized gamma-band oscillations.

The cerebral cortex continuously undergoes changes in its state, which are manifested in transient modulations of the cortical power spectrum. Cortical state changes also occur at full wakefulness and during rapid cognitive acts, such as perceptual decisions. Previous studies found a global modulation of beta-band (12–30 Hz) activity in human and monkey visual cortex during an elementary visual decision: reporting the appearance or disappearance of salient visual targets surrounded by a distractor. The previous studies disentangled neither the motor action associated with behavioral report nor other secondary processes, such as arousal, from perceptual decision processing per se. Here, we used magnetoencephalography in humans to pinpoint the factors underlying the beta-band modulation. We found that disappearances of a salient target were associated with beta-band suppression, and target reappearances with beta-band enhancement. This was true for both overt behavioral reports (immediate button presses) and silent counting of the perceptual events. This finding indicates that the beta-band modulation was unrelated to the execution of the motor act associated with a behavioral report of the perceptual decision. Further, changes in pupil-linked arousal, fixational eye movements, or gamma-band responses were not necessary for the beta-band modulation. Together, our results suggest that the beta-band modulation was a top-down signal associated with the process of converting graded perceptual signals into a categorical format underlying flexible behavior. This signal may have been fed back from brain regions involved in decision processing to visual cortex, thus enforcing a “decision-consistent” cortical state. SIGNIFICANCE STATEMENT Elementary visual decisions are associated with a rapid state change in visual cortex, indexed by a modulation of neural activity in the beta-frequency range. Such decisions are also followed by other events that might affect the state of visual cortex, including the motor command associated with the report of the decision, an increase in pupil-linked arousal, fixational eye movements, and fluctuations in bottom-up sensory processing. Here, we ruled out the necessity of these events for the beta-band modulation of visual cortex. We propose that the modulation reflects a decision-related state change, which is induced by the conversion of graded perceptual signals into a categorical format underlying behavior. The resulting decision signal may be fed back to visual cortex.

Compared to the different brain signals used in brain–computer interface (BCI) paradigms, the s teady-state visually evoked potential (SSVEP) features a high signal to noise ratio, enabling reliable and fast classification of neural activity patterns without extensive training requirements. In this paper, we present methods to further increase the information transfer rates (ITRs) of SSVEP-based BCIs. Starting with stimulus parameter optimizations methods, we develop an improved approach for the use of Canonical correlation analysis and analyze properties of the SSVEP when the user fixates a target and during transitions between targets. These transitions show a negative effect on the system's ITR which we trace back to delays and dead times of the SSVEP. Using two classifier types adapted to continuous and transient SSVEPs and two control modes (fast feedback and fast input), we present a simulated online BCI implementation which addresses the challenges introduced by transient SSVEPs. The resulting system reaches an average ITR of 181 Bits/min and peak ITR values of up to 295 Bits/min for individual users.

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.

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.

Highlights • Closer association of structural connectivity with cognition than standard MRI. • Loss of structural connectivity associated with poorer cognitive performance. • Higher functional connectivity associated with dominantly poorer task performance. • Associations are accentuated in the default mode and the visual network. • Increased functional connectivity might point towards a maladaptive response., 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.

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.

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.

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 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.

Parkinson's disease (PD) is a heterogeneous disorder that leads to variable expression of several different motor symptoms. While changes in firing rate, pattern, and oscillation of basal ganglia neurons have been observed in PD patients and experimental animals, there is limited evidence linking them to specific motor symptoms. Here we examined this relationship using extracellular recordings of subthalamic nucleus neurons from 19 PD patients undergoing surgery for deep brain stimulation. For each patient, ≥10 single units and/or multi-units were recorded in the OFF medication state. We correlated the proportion of neurons displaying different activities with preoperative Unified Parkinson's Disease Rating Scale subscores (OFF medication). The mean spectral power at sub-beta frequencies and percentage of units oscillating at beta frequencies were positively correlated with the axial and limb rigidity scores, respectively. The percentage of units oscillating at gamma frequency was negatively correlated with the bradykinesia scores. The mean intraburst rate was positively correlated with both bradykinesia and axial scores, while the related ratio of interspike intervals below/above 10 ms was positively correlated with these symptoms and limb rigidity. None of the activity parameters correlated with tremor. The grand average of all the significantly correlated subthalamic nucleus activities accounted for >60% of the variance of the combined bradykinetic-rigid and axial scores. Our results demonstrate that the occurrence of alterations in the rate and pattern of basal ganglia neurons could partly underlie the variability in parkinsonian phenotype.

The human brain exhibits rhythms that are characteristic for anatomical areas and presumably involved in perceptual and cognitive processes. Visual deprivation results in behavioral adaptation and cortical reorganization. Whether neuroplasticity-related mechanisms involve altered spectral properties of neural signals and which brain areas are particularly affected, is unknown. We analyzed magnetoencephalography resting state data of congenitally blind and matched sighted individuals. First, using clustering procedures (k-means and Gaussian Mixture Models) we identified brain region-specific spectral clusters. Second, a classifier was employed testing the specificity of the spectral profiles within and the differences between groups. We replicated previously reported findings of area-specific spectral profiles, indicated by high classification performance in the sighted. Additionally, we found high classification performance in the blind, suggesting that area-specific spectral profiles were consistently identified after deprivation-related reorganization. Crucially, in the cross-group classification (sighted vs. blind), several sensory (visual and auditory) and right frontal areas were classified worse compared to the control (within sighted classification) condition. Overall the spectral profiles of these areas showed increased neuronal power in higher frequency bands in the blind compared to the sighted, possibly reflecting acceleration of regionally prevalent brain rhythms. The spectral profiles in areas where group differences were observed correlated with microstructural white matter properties in an extended posterior and bilateral cluster. We provide evidence that visual deprivation-related plasticity particulary alters the spectral profiles of right frontal, visual and auditory brain regions, possibly reflecting increased temporal processing capabilities (auditory, frontal cortices) and changes in the visual inhibitory-excitatory circuits in the blind.

Transcranial electric stimulation (tES) induces electric fields that are subject to a complex interaction with individual anatomical properties, such as the low-conducting human skull, the distribution of cerebrospinal fluid or the sulcal depth, as well as stimulation target location and orientation. This complex interaction might contribute to the heterogenous results that are commonly observed in applications of tES in humans. Targeted tES, on the other hand, might be able to account for some of these individual factors. In the present study, we used the finite-element method (FEM) and head models of twenty-one participants to evaluate the effect of individually targeted tES on simulated intracranial current densities. Head models were based on an automated segmentation algorithm to facilitate processing in experimental sample sizes. We compared a standard stimulation montage to two individually optimized tES montages using an Alternating Direction Method of Multipliers (ADMM) and a Constrained Maximum Intensity (CMI) approach. A right parietal target was defined with three different orientations. Individual current densities showed varying intensity and spatial extent near the lower limit at which physiological efficacy of electric fields can be assumed. Both individually optimized targeting algorithms were able to control the electric field properties, with respect to intensities and/or spatial extent of the electric fields. Still, across head models, intensity in the stimulation target was constrained by individual anatomical properties. Thus, our results underline the importance of targeted tES in enhancing the effectiveness of future tES applications and in elucidating the underlying mechanisms.

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.

The phase of neural oscillatory activity 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 processes. 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.

Detrended fluctuation analysis (DFA) is a popular method to analyze long-range temporal correlations in time series of many different research areas but in particular also for electrophysiological recordings. Using the classical DFA method, the cumulative sum of data are divided into segments, and the variance of these sums is studied as a function of segment length after linearly detrending them in each segment. The starting point of the proposed new method is the observation that the classical method is inherently non-stationary without justification by a corresponding non-stationarity of the data. This leads to unstable estimates of fluctuations to the extent that it is impossible to estimate slopes of the fluctuations other than by fitting a line over a wide range of temporal scales. We here use a modification of the classical method by formulating the detrending as a strictly stationary operation. With this modification the detrended fluctuations can be expressed as a weighted average across the power spectrum of a signal. Most importantly, we can also express the slopes, calculated as analytic derivatives of the fluctuations with respect to the scales, as statistically robust weighted averages across the power spectra. The method is applied to amplitudes of brain oscillations measured with magnetoencephalography in resting state condition. We found for envelopes of the the alpha rhythm that fluctuations as a function of time scales in a double-logarithmic plot differ substantially from a linear relation for time scales below 10 seconds. In particular we will show that model selections fail to determine accurate scaling laws, and that standard parameter settings are likely to yield results depending on signal to noise ratios than on true long range temporal correlations.

Multisensory perception is shaped by both attentional selection of relevant sensory inputs and exploitation of stimulus-driven factors that promote cross-modal binding. Underlying mechanisms of both top-down and bottom-up modulations have been linked to changes in alpha/gamma dynamics in primary sensory cortices and temporoparietal cortex. Accordingly, it has been proposed that alpha oscillations provide pulsed inhibition for gamma activity and thereby dynamically route cortical information flow. In this study, we employed a recently introduced multisensory paradigm incorporating both bottom-up and top-down aspects of cross-modal attention in an EEG study. The same trimodal stimuli were presented in two distinct attentional conditions, focused on visual-tactile or audio-visual components, for which cross-modal congruence of amplitude changes had to be evaluated. Neither top-down nor bottom-up cross-modal attention modulated alpha or gamma power in primary sensory cortices. Instead, we found alpha band effects in bilateral frontal and right parietal cortex. We propose that frontal alpha oscillations reflect the origin of top-down control regulating perceptual gains and that modulations of parietal alpha oscillations relates to intersensory re-orienting. Taken together, we suggest that the idea of selective cortical routing via alpha oscillations can be extended from sensory cortices to the frontoparietal attention network.

BackgroundOscillatory 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, phase-specific modulation of oscillations by transcranial alternating current stimulation (tACS) emerged as a promising approach. However, the effectiveness of tACS in humans is still critically debated.ObjectiveHere, we investigated the phase-specificity of tACS effects on visually evoked steady state responses (SSRs) in 24 healthy human participants of either sex.MethodsTo this end, we used an intermittent electrical stimulation protocol and assessed the influence of tACS on SSR amplitude in the interval immediately following tACS.ResultsWe observed that the phase shift between flicker and tACS modulates evoked SSR amplitudes. The tACS effect size was dependent on the strength of flicker-evoked oscillatory activity, with larger effects in participants showing weaker locking of neural responses to flicker phase. 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 cortical SSR onset delays over the visual cortex.ConclusionsOverall, our data provide electrophysiological evidence for phase-specific modulations of oscillatory activity by tACS in humans. As the optimal timing of tACS application was dependent on neural conduction times as measured by SSR onset delays, data suggest that the interaction between tACS effect and SSR was cortical in nature. These findings corroborate the physiological efficacy of tACS and highlight its potential for controlled modulations of brain signals.

Complex and variable behavior requires fast changes of functional connectivity in large-scale cortical networks. Here, we report on the cortical dynamics of functional coupling across visual, auditory and parietal areas during a lateralized detection task in the ferret. We hypothesized that fluctuations in coupling, indicative of dynamic variations in the network state, might predict the animals’ performance. While power for hit and miss trials showed significant differences only around stimulus and response onset, phase coupling already differed before stimulus onset. Principal component analysis of directed coupling at the single-trial level during this period revealed subnetworks that most strongly related to behavior. While higher global phase coupling of visual and auditory regions to parietal cortex was predictive of task performance, a second component showed that a reduction in coupling between subnetworks of sensory modalities was also necessary, probably to allow a better detection of the unimodal signals. Furthermore, we observed that long-range coupling became more predominant during the task period compared to the pre-stimulus baseline. Taken together, these results suggest that fluctuations in the network state, particular with respect to long-range connectivity, are key determinants of the animals’ behavior.

Long-range functional connectivity in the brain is considered fundamental for cognition and is known to be altered in many neuropsychiatric disorders. To modify such coupling independent of sensory input, non-invasive brain stimulation could be of utmost value. In particular, transcranial alternating current stimulation (tACS) has been proposed to modulate oscillatory coupling, while evidence for frequency- and space-specific modification of connectivity is missing so far. Therefore, we investigated the aftereffects of bifocal high-definition tACS at 10 Hz on alpha-coupling. Healthy participants were stimulated in counter-balanced order (1) in-phase, with identical electric fields in both hemispheres, (2) anti-phase, with phase-reversed electric fields in the two hemispheres, and (3) jittered-phase, generated by subtle frequency shifts continuously changing the relative phase between the two fields. Global pre-post stimulation changes in EEG connectivity were larger for in-phase stimulation than for anti-phase or jittered-phase stimulation. The differences in connectivity change were restricted to the stimulated frequency band and decayed within a time window of 100 s after stimulation offset. Source reconstruction localized the maximum effect between the stimulated occipito-parietal areas. In conclusion, the relative phase of bifocal alpha-tACS determined alpha-band connectivity shifts between the targeted regions. We thus suggest bifocal high-definition tACS as a tool to specifically modulate long-range cortico-cortical coupling which outlasts the electrical stimulation period.

Interhemispheric connectivity between auditory areas is highly relevant for normal auditory perception and alterations are a major factor for the development of auditory verbal hallucinations. Surprisingly, there is no combined EEG-DTI study directly addressing the role of functional and structural connectivity in the same group of subjects. Accordingly, nothing is known about the relationship between functional connectivity such as gamma-band synchrony, structural integrity of the interhemispheric auditory pathways (IAPs) and language lateralization as well as whether the gamma-band synchrony is configured on the backbone of IAPs. By applying multimodal imaging of 64-channel EEG and DTI tractography, we investigated in 27 healthy volunteers the functional gamma-band synchrony between either bilateral primary or secondary auditory cortices from eLORETA source-estimation during dichotic listening, as well as the correspondent IAPs from which fractional anisotropy (FA) values were extracted. Correlation and regression analyses revealed highest values for gamma-band synchrony, followed by FA for secondary auditory cortices, which were both significantly related to a reduced language lateralization. There was no such association between the white-matter microstructure and gamma-band synchrony, suggesting that structural connectivity might also be relevant for other (minor) aspects of information transfer in addition to gamma-band synchrony, which are not detected in the present coupling analyses. The combination of multimodal EEG-DTI imaging provides converging evidence of neural correlates by showing that both stronger pathways and increased gamma-band synchrony within one cohort of subjects are related to a reduced leftward-lateralization for language.

Controlling an event through one’s own action usually induces a sense of agency, a feeling that arises when an expected outcome matches the intention. The neural correlates of this feeling remain controversial however, as experimental manipulation of the action-outcome chain often introduces mismatch or prediction errors that strongly correlate with the sense of agency. Here, we took a different approach and manipulated the causal belief (self-attribution vs. computer-attribution) by external cues during matched visuo-motor tapping conditions. With magneto-encephalography, we studied the sense of agency from a network perspective, investigating in source space the modulation of local population activity and changes in functional connectivity with motor cortex. Our results show that during the belief of agency primary motor cortex (M1) shows stronger functional connectivity (mediated by the beta band) to inferior parietal lobe and right middle temporal gyrus (MTG). Furthermore, the local feed-forward activity (gamma band power) in extrastriate body area and MTG disappears with that belief. After changes in action context, left M1 shows stronger connectivity in the alpha band with right premotor cortex and left insular-temporal cortex a network that might support active inference in social action context. Finally, a better tapping performance in this rhythmic task was related to alpha power modulations in the bilateral cerebellum and bilateral fusiform body-area, with power suppression during a more precise performance. These findings highlight the role of multiple networks supporting the sense of agency by changing their relative contribution for different causal beliefs.

The goal of the study was to compare the tolerability and the effects of conventional subthalamic nucleus (STN) and combined subthalamic nucleus and substantia nigra (STN+SNr) high-frequency stimulation in regard to neuropsychiatric symptoms in Parkinson’s disease patients. In this single center, randomized, double-blind, cross-over clinical trial, twelve patients with advanced Parkinson’s disease (1 female; age:61.3±7.3years; disease duration:12.3±5.4years; Hoehn and Yahr stage:2.2±0.39) were included. Apathy, fatigue, depression, and impulse control disorder were assessed using a comprehensive set of standardized rating scales and questionnaires such as the Lille Apathy Rating Scale (LARS), Modified Fatigue Impact Scale (MFIS), Becks Depression Inventory (BDI-I), Questionnaire for Impulsive-Compulsive Disorders in Parkinson’s Disease Rating Scale (QUIP-RS), and Parkinson’s Disease Questionnaire (PDQ-39). Three patients that were initially assigned to the STN+SNr stimulation mode withdrew from the study within the first week due to discomfort. Statistical comparison of data retrieved from patients who completed the study revealed no significant differences between both stimulation conditions in terms of mean scores of scales measuring apathy, fatigue, depression, impulse control disorder, and quality of life. Individual cases showed an improvement of apathy under combined STN+SNr stimulation. In general, combined STN+SNr stimulation seems to be safe in terms of neuropsychiatric side effects, although careful patient selection and monitoring in the short-term period after changing stimulation settings are recommended.

Ambiguous stimuli have been widely used to study the neuronal correlates of consciousness. Recently, it has been suggested that conscious perception might arise from the dynamic interplay of functionally specialized but widely distributed cortical areas. While previous research mainly focused on phase coupling as a correlate of cortical communication, more recent findings indicated that additional coupling modes might coexist and possibly subserve distinct cortical functions. Here, we studied two coupling modes, namely phase and envelope coupling, which might differ in their origins, putative functions and dynamics. Therefore, we recorded 128-channel EEG while participants performed a bistable motion task and utilized state-of-the-art source-space connectivity analysis techniques to study the functional relevance of different coupling modes for cortical communication. Our results indicate that gamma-band phase coupling in extrastriate visual cortex might mediate the integration of visual tokens into a moving stimulus during ambiguous visual stimulation. Furthermore, our results suggest that long-range fronto-occipital gamma-band envelope coupling sustains the horizontal percept during ambiguous motion perception. Additionally, our results support the idea that local parieto-occipital alpha-band phase coupling controls the inter-hemispheric information transfer. These findings provide correlative evidence for the notion that synchronized oscillatory brain activity reflects the processing of sensory input as well as the information integration across several spatiotemporal scales. The results indicate that distinct coupling modes are involved in different cortical computations and that the rich spatiotemporal correlation structure of the brain might constitute the functional architecture for cortical processing and specific multi-site communication. Hum Brain Mapp 37:4099-4111, 2016. © 2016 Wiley Periodicals, Inc.

Rhythmic neuronal activity in the gamma range is a signature of active cortical processing and its synchronization across distant sites has been proposed as a fundamental mechanism of network communication. While this has been shown within sensory modalities, we tested whether crosstalk between the senses relies on similar mechanisms. In two consecutive experiments, we used a task in which human participants (male and female) matched amplitude changes of concurrent visual, auditory and tactile stimuli. In this task, matching of congruent stimuli was associated with a behavioral benefit compared to matching of incongruent stimuli. In the first experiment, we used source-level analysis of high-density electroencephalography (EEG) and observed that cross-modal matching of congruent inputs was associated with relatively weaker coherence between gamma oscillations in early sensory regions. Next, we used bifocal high-definition transcranial alternating current stimulation (hd-tACS) to manipulate the strength of coupling between sensory cortices. Here, we used a lateralized version of the task in which hd-tACS was applied either ipsilateral or contralateral to the hemisphere receiving sensory stimuli. Ipsilateral gamma, but not alpha stimulation slowed responses to congruent trials whereas responding to incongruent trials was not changed by tACS. We speculate that fast responding to congruent stimuli involves decoupling of sensory gamma oscillations, which was prevented by tACS. These results indicate that synchronization of gamma oscillations promotes direct communication between sensory modalities. The framework of coupled gamma oscillations underlying cortical communication might thus be generalizable from processing within sensory streams to interactions between sensory networks.Significance statementCortical gamma oscillations structure segregated neural activity and were suggested to represent a fundamental mechanism of network communication. While there is ample evidence for the role of long-range gamma synchronization in unisensory processing, its significance in multisensory networks is still unclear. We show that direct interactions between sensory cortices rely on synchronization of gamma band activity. To that end, we carried out two consecutive experiments using state-of-the-art high-density electroencephalography (EEG) and high-definition transcranial alternating current stimulation (hd-tACS). By complementing an observational with an interventional method, we provide novel evidence for the role of synchronized gamma oscillations in multisensory communication.

BACKGROUND: In cortical networks, synchronized oscillatory activity of neuronal populations enables communication, and its disturbance is related to a range of pathologies. Transcranial alternating current stimulation (tACS) has been explored as a flexible, noninvasive tool for the modulation and restoration of synchronized oscillatory signals. While numerous studies have addressed cognitive or behavioural effects of electrical stimulation, the neural changes underlying the effects of tACS and their persistence after stimulation offset have remained unclear. OBJECTIVE: Here, we screened for lasting aftereffects of prolonged tACS on intrinsic network activity and audiovisual processing in the anesthetized ferret brain. METHODS: Electrical stimulation was applied via subcutaneous wire electrodes. Current waveforms were synthesized from two frequencies in the alpha or gamma range, respectively. Flashes and clicks were used for audiovisual stimulation. Electrocorticographic recordings from an extended network including occipital, temporal and parietal cortical areas were obtained before and after tACS. RESULTS: Changes in local synchrony (continuous and spike-triggered power of LFP), synchrony across recording sites (imaginary coherence) and altered dynamics of sensory response-features (peak-to-peak amplitude, extremum latency) following electrical stimulation consistently point to a synchronizing effect of tACS that can outlast stimulation offset by at least 10 min. Gamma-band tACS proved particularly effective. In line with previous reports on cross-frequency interactions, we observed effects on coherence and power of baseline activity at frequencies other than the ones targeted by tACS. These cross-frequency interactions appeared to underlie the strengthening and stabilizing effect on audiovisual responses. CONCLUSION: We demonstrate aftereffects of tACS on synchrony and stimulus processing in an extended cortical network, measured intracranially in a setting that resembles tACS stimulation in humans. The data provide direct evidence for the efficacy of tACS as a tool for sustained modulation of cortical network dynamics.

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., Author summary 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.

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 (12-35Hz), 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 PD patients undergoing deep brain stimulation surgery with recordings of identified STN neurons in anaesthetised rats. In PD patients, we demonstrate that a subset of STN neurons are strongly and selectively sensitive to fluctuations of cortical beta oscillations over time, linearly increasing their phase-locking strength with respect to full range of instantaneous amplitude. In rats, we probed the frequency response of STN neurons more precisely, by recording spikes evoked by short bursts of cortical stimulation with variable frequency (4-40Hz) and constant amplitude. In both healthy and dopamine-depleted animals, only beta-frequency stimulation selectively led to a progressive reduction in the variability of spike timing through the stimulation train. 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.

Audiovisual integration is facilitated by the context-specific dynamical reconfiguration of cortical intrinsic coupling., Intrinsically generated patterns of coupled neuronal activity are associated with the dynamics of specific brain states. Sensory inputs are extrinsic factors that can perturb these intrinsic coupling modes, creating a complex scenario in which forthcoming stimuli are processed. Studying this intrinsic-extrinsic interplay is necessary to better understand perceptual integration and selection. Here, we show that this interplay leads to a reconfiguration of functional cortical connectivity that acts as a mechanism to facilitate stimulus processing. Using audiovisual stimulation in anesthetized ferrets, we found that this reconfiguration of coupling modes is context specific, depending on long-term modulation by repetitive sensory inputs. These reconfigured coupling modes lead to changes in latencies and power of local field potential responses that support multisensory integration. Our study demonstrates that this interplay extends across multiple time scales and involves different types of intrinsic coupling. These results suggest a previously unknown large-scale mechanism that facilitates multisensory integration.

The feasibility of a steady-state visual evoked potential (SSVEP) brain&ndash, computer interface (BCI) with a single-flicker stimulus for multiple-target decoding has been demonstrated in a number of recent studies. The single-flicker BCIs have mainly employed the direction information for encoding the targets, i.e., different targets are placed at different spatial directions relative to the flicker stimulus. The present study explored whether visual eccentricity information can also be used to encode targets for the purpose of increasing the number of targets in the single-flicker BCIs. A total number of 16 targets were encoded, placed at eight spatial directions, and two eccentricities (2.5&deg, and 5&deg, ) relative to a 12 Hz flicker stimulus. Whereas distinct SSVEP topographies were elicited when participants gazed at targets of different directions, targets of different eccentricities were mainly represented by different signal-to-noise ratios (SNRs). Using a canonical correlation analysis-based classification algorithm, simultaneous decoding of both direction and eccentricity information was achieved, with an offline 16-class accuracy of 66.8 &plusmn, 16.4% averaged over 12 participants and a best individual accuracy of 90.0%. Our results demonstrate a single-flicker BCI with a substantially increased target number towards practical applications.

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.