Reaction time and brain oscillations in Go/No-go tasks with different meanings of stimulus color.

Color has meaning in particular contexts, and the meaning of color can impact behavioral performance. For example, the meaning of color about traffic rules (blue/green and red mean "go" and "stop" respectively) influences reaction times (RTs) to signals. Specifically, in a Go/No-go task, RTs have been reported to be longer when responding to a red signal and withholding the response to a blue signal (Red Go/Blue No-go task) than when responding to a blue signal and withholding the response to a red signal (Blue Go/Red No-go task). However, the neurophysiological background of this phenomenon has not been fully understood. The purpose of this study was to investigate the brain oscillatory activity associated with the effect of meaning of color on RTs in the Go/No-go task. Twenty participants performed a Blue simple reaction task, a Red simple reaction task, a Blue Go/Red No-go task, and a Red Go/Blue No-go task. We recorded responses to signals and electroencephalogram (EEG) during the tasks and evaluated RTs and changes in spectral power over time, referred to as event-related synchronization (ERS) and event-related desynchronization (ERD). The behavioral results were similar to previous studies. The EEG results showed that frontal beta ERD and theta ERS were greater when signals were presented in blue than red color in both simple reaction and Go/No-go tasks. In addition, the onset of theta ERS was delayed in the Red Go than Blue Go trial in the Go/No-go task. The enhanced beta ERD may indicate that blue signals facilitate motor response, and the delayed onset of theta ERS may indicate the delayed onset of cognitive process when responding to red signals as compared to blue signals in the Go/No-go task. Thus, this delay in cognitive process can be involved in the slow response in the Red Go/Blue No-go task.

Event-related EEG synchronization and desynchronization in patients with obsessive-compulsive disorder.

Symptoms in patients with obsessive-compulsive disorder (OCD) are associated with impairment in cognitive control, attention, and action inhibition. We investigated OCD group differences relative to healthy subjects in terms of event-related alpha and beta range synchronization (ERS) and desynchronization (ERD) during a visually cued Go/NoGo task. Subjects were 62 OCD patients and 296 healthy controls (HC). The OCD group in comparison with HC, showed a changed value of alpha/beta oscillatory power over the central cortex, in particular, an increase in the alpha/beta ERD over the central-parietal cortex during the interstimulus interval (Cue condition) as well as changes in the postmovement beta synchronization topography and frequency. Over the frontal cortex, the OCD group showed an increase in magnitude of the beta ERS in NoGo condition. Within the parietal-occipital ERS/ERD modulations, the OCD group showed an increase in the alpha/beta ERD over the parietal cortex after the presentation of the visual stimuli as well as a decrease in the beta ERD over the occipital cortex after the presentation of the Cue and Go stimuli. The specific properties in the ERS/ERD patterns observed in the OCD group may reflect high involvement of the frontal and central cortex in action preparation and action inhibition processes and, possibly, in maintaining the motor program, which might be a result of the dysfunction of the cortico-striato-thalamo-cortical circuits involving prefrontal cortex. The data about enhanced involvement of the parietal cortex in the evaluation of the visual stimuli are in line with the assumption about overfocused attention in OCD.

Analyzing bursting synchronization in structural connectivity matrix of a human brain under external pulsed currents.

Cognitive tasks in the human brain are performed by various cortical areas located in the cerebral cortex. The cerebral cortex is separated into different areas in the right and left hemispheres. We consider one human cerebral cortex according to a network composed of coupled subnetworks with small-world properties. We study the burst synchronization and desynchronization in a human neuronal network under external periodic and random pulsed currents. With and without external perturbations, the emergence of bursting synchronization is observed. Synchronization can contribute to the processing of information, however, there are evidences that it can be related to some neurological disorders. Our results show that synchronous behavior can be suppressed by means of external pulsed currents.

Cortical oscillations and interareal synchronization as a preparatory activity for postural response.

Neural mechanisms of human standing are expected to be elucidated for preventing fallings. Postural response evoked by sudden external perturbation originates from various areas in the central nervous system. Recent studies have revealed that the corticospinal pathway is one of the key nodes for an appropriate postural response. The corticospinal pathway that mediates the early part of the electromyographic response is modulated with prediction before a perturbation occurs. Temporal prediction explicitly exhibiting an onset timing contributes to enhancing corticospinal excitability. However, how the cortical activities in the sensorimotor area with temporal prediction are processed before the corticospinal pathway enhancement remains unclear. In this study, using electroencephalography, we investigated how temporal prediction affects both neural oscillations and synchronization between sensorimotor and distal areas. Our results revealed that desynchronization of cortical oscillation at α- and ß-bands was observed in the sensorimotor and parietooccipital areas (Cz, CPz, Pz and POz), and those are nested in the phase at θ-band frequency. Furthermore, a reduction in the interareal phase synchrony in the α-band was induced after the timing cue for the perturbation onset. The phase synchrony at the low frequency can relay the temporal prediction among the distant areas and initiate the modulation of the local cortical activities. Such modulations contribute to the preparation for sensory processing and motor execution that are necessary for optimal responses.

Cortical VIP neurons locally control the gain but globally control the coherence of gamma band rhythms.

Gamma band synchronization can facilitate local and long-range neural communication. In the primary visual cortex, visual stimulus properties within a specific location determine local synchronization strength, while the match of stimulus properties between distant locations controls long-range synchronization. The neural basis for the differential control of local and global gamma band synchronization is unknown. Combining electrophysiology, optogenetics, and computational modeling, we found that VIP disinhibitory interneurons in mouse cortex linearly scale gamma power locally without changing its stimulus tuning. Conversely, they suppress long-range synchronization when two regions process non-matched stimuli, tuning gamma coherence globally. Modeling shows that like-to-like connectivity across space and specific VIP→SST inhibition capture these opposing effects. VIP neurons thus differentially impact local and global properties of gamma rhythms depending on visual stimulus statistics. They may thereby construct gamma-band filters for spatially extended but continuous image features, such as contours, facilitating the downstream generation of coherent visual percepts.

Fronto-parietal alpha ERD and visuo-spatial attention in pregnant women.

Many pregnant women report impairments in their attentional capacities. However, comparative studies between pregnant and non-pregnant women using standardised attention paradigms are rare and inconsistent. During attention tasks alpha activity is known to suppress irrelevant sensory inputs and previous studies show that a large event-related desynchronisation (ERD) in the alpha range prior to target-onset predicts enhanced attentional processing. We quantified the relationship between performance (accuracy, response time) in a standardised visuo-spatial attention task and alpha ERD (∼6-12 Hz) as well as saliva estradiol level in fifteen pregnant women (M = 26.6, SD = 3.0 years) compared to fifteen non-pregnant, naturally cycling women (M = 23.1, SD = 4.3 years). Compared to non-pregnant women, alpha frequency was increased in pregnant women. Furthermore, pregnant women showed a greater magnitude of the alpha ERD prior to target-onset and a moderate increase in accuracy compared to non-pregnant women. In addition, accuracy correlated negatively with estradiol in pregnant women as well as with frontal alpha ERD in all women. These correlational findings indicate that pregnancy-related enhancement in alpha desynchronisation in a fronto-parietal network might modulate accuracy during a visuo-spatial attention task.

Motor event-related synchronization as an inhibitory biomarker of pain severity, sensitivity, and chronicity in patients with knee osteoarthritis.

OBJECTIVE: The study aimed to examine the clinical and neurophysiological predictors of motor event-related desynchronization (ERD) and synchronization (ERS) in patients with chronic pain due to knee osteoarthritis (KOA). METHODS: We performed a cross-sectional analysis of our cohort study (DEFINE cohort), KOA arm, with 71 patients, including demographic, functionality, genetic and neurophysiological measures. ERD/ERS was evaluated during hand motor tasks (motor execution, active and passive observation, and imagery). Multivariate regression models were used to explore predictors of ERD/ERS. RESULTS: Although we found an altered ERD/ERS pattern during motor execution and active observation, the ERS pattern could only be clearly differentiated after passive observation.`. We found no predictors of ERD (excitatory biomarker). For ERS (inhibitory biomarker), our results showed that the main predictors differ across EEG frequency bands. Considering pain measures, we found that visual analogue scale (VAS, right knee) and chronicity of pain negatively predict low beta and high beta ERS, respectively. Pain threshold was positively correlated with alpha ERS, while 36-Item Short Form Survey (SF-36) emotional domain positively predicted beta ERS. Regarding transcranial magnetic stimulation (TMS) markers, intracortical inhibition (ICF) negatively predicted beta and low beta ERS, and left hemisphere cortical silent period (CSP) negatively predicted low beta ERS. CONCLUSION: Considering that higher power of ERS indicates a stronger cortical organization and inhibitory drive, our results show that limitation of activities due to emotional factors, lower pain threshold, higher VAS pain, and longer duration of pain are associated with lower ERS power (in alpha and beta frequencies), thus indicating a lower inhibitory drive. In the same direction, a lower inhibitory drive as indicated by higher ERS power is associated with higher ICF amplitude. Although there was a negative association between ERS and CSP, this may indicate that ICF values are adjusting CSP results. Our findings support the idea that a less organized cortical response as indicated by changes to the ERS is associated with higher pain correlates in subjects with KOA.

Long-range cortical synchronization supports abrupt visual learning.

Visual plasticity declines sharply after the critical period, yet we easily learn to recognize new faces and places, even as adults. Such learning is often characterized by a "moment of insight," an abrupt and dramatic improvement in recognition. The mechanisms that support abrupt learning are unknown, but one hypothesis is that they involve changes in synchronization between brain regions. To test this hypothesis, we used a behavioral task in which non-human primates rapidly learned to recognize novel images and to associate them with specific responses. Simultaneous recordings from inferotemporal and prefrontal cortices revealed a transient synchronization of neural activity between these areas that peaked around the moment of insight. Synchronization was strongest between inferotemporal sites that encoded images and reward-sensitive prefrontal sites. Moreover, its magnitude intensified gradually over image exposures, suggesting that abrupt learning is the culmination of a search for informative signals within a circuit linking sensory information to task demands.

Binding events through the mutual synchronization of spintronic nano-neurons.

The brain naturally binds events from different sources in unique concepts. It is hypothesized that this process occurs through the transient mutual synchronization of neurons located in different regions of the brain when the stimulus is presented. This mechanism of 'binding through synchronization' can be directly implemented in neural networks composed of coupled oscillators. To do so, the oscillators must be able to mutually synchronize for the range of inputs corresponding to a single class, and otherwise remain desynchronized. Here we show that the outstanding ability of spintronic nano-oscillators to mutually synchronize and the possibility to precisely control the occurrence of mutual synchronization by tuning the oscillator frequencies over wide ranges allows pattern recognition. We demonstrate experimentally on a simple task that three spintronic nano-oscillators can bind consecutive events and thus recognize and distinguish temporal sequences. This work is a step forward in the construction of neural networks that exploit the non-linear dynamic properties of their components to perform brain-inspired computations.

Cortical signatures of auditory object binding in children with autism spectrum disorder are anomalous in concordance with behavior and diagnosis.

Organizing sensory information into coherent perceptual objects is fundamental to everyday perception and communication. In the visual domain, indirect evidence from cortical responses suggests that children with autism spectrum disorder (ASD) have anomalous figure-ground segregation. While auditory processing abnormalities are common in ASD, especially in environments with multiple sound sources, to date, the question of scene segregation in ASD has not been directly investigated in audition. Using magnetoencephalography, we measured cortical responses to unattended (passively experienced) auditory stimuli while parametrically manipulating the degree of temporal coherence that facilitates auditory figure-ground segregation. Results from 21 children with ASD (aged 7-17 years) and 26 age- and IQ-matched typically developing children provide evidence that children with ASD show anomalous growth of cortical neural responses with increasing temporal coherence of the auditory figure. The documented neurophysiological abnormalities did not depend on age, and were reflected both in the response evoked by changes in temporal coherence of the auditory scene and in the associated induced gamma rhythms. Furthermore, the individual neural measures were predictive of diagnosis (83% accuracy) and also correlated with behavioral measures of ASD severity and auditory processing abnormalities. These findings offer new insight into the neural mechanisms underlying auditory perceptual deficits and sensory overload in ASD, and suggest that temporal-coherence-based auditory scene analysis and suprathreshold processing of coherent auditory objects may be atypical in ASD.

LRRTM3 regulates activity-dependent synchronization of synapse properties in topographically connected hippocampal neural circuits.

Synaptic cell-adhesion molecules (CAMs) organize the architecture and properties of neural circuits. However, whether synaptic CAMs are involved in activity-dependent remodeling of specific neural circuits is incompletely understood. Leucine-rich repeat transmembrane protein 3 (LRRTM3) is required for the excitatory synapse development of hippocampal dentate gyrus (DG) granule neurons. Here, we report that Lrrtm3-deficient mice exhibit selective reductions in excitatory synapse density and synaptic strength in projections involving the medial entorhinal cortex (MEC) and DG granule neurons, accompanied by increased neurotransmitter release and decreased excitability of granule neurons. LRRTM3 deletion significantly reduced excitatory synaptic innervation of hippocampal mossy fibers (Mf) of DG granule neurons onto thorny excrescences in hippocampal CA3 neurons. Moreover, LRRTM3 loss in DG neurons significantly decreased mossy fiber long-term potentiation (Mf-LTP). Remarkably, silencing MEC-DG circuits protected against the decrease in the excitatory synaptic inputs onto DG and CA3 neurons, excitability of DG granule neurons, and Mf-LTP in Lrrtm3-deficient mice. These results suggest that LRRTM3 may be a critical factor in activity-dependent synchronization of the topography of MEC-DG-CA3 excitatory synaptic connections. Collectively, our data propose that LRRTM3 shapes the target-specific structural and functional properties of specific hippocampal circuits.

Phase synchronization and measure of criticality in a network of neural mass models.

Synchronization has an important role in neural networks dynamics that is mostly accompanied by cognitive activities such as memory, learning, and perception. These activities arise from collective neural behaviors and are not totally understood yet. This paper aims to investigate a cortical model from this perspective. Historically, epilepsy has been regarded as a functional brain disorder associated with excessive synchronization of large neural populations. Epilepsy is believed to arise as a result of complex interactions between neural networks characterized by dynamic synchronization. In this paper, we investigated a network of neural populations in a way the dynamics of each node corresponded to the Jansen-Rit neural mass model. First, we study a one-column Jansen-Rit neural mass model for four different input levels. Then, we considered a Watts-Strogatz network of Jansen-Rit oscillators. We observed an epileptic activity in the weak input level. The network is considered to change various parameters. The detailed results including the mean time series, phase spaces, and power spectrum revealed a wide range of different behaviors such as epilepsy, healthy, and a transition between synchrony and asynchrony states. In some points of coupling coefficients, there is an abrupt change in the order parameters. Since the critical state is a dynamic candidate for healthy brains, we considered some measures of criticality and investigated them at these points. According to our study, some markers of criticality can occur at these points, while others may not. This occurrence is a result of the nature of the specific order parameter selected to observe these markers. In fact, The definition of a proper order parameter is key and must be defined properly. Our view is that the critical points exhibit clear characteristics and invariance of scale, instead of some types of markers. As a result, these phase transition points are not critical as they show no evidence of scaling invariance.

Neural correlates of impaired response inhibition in the antisaccade task in Parkinson's disease.

Deficits in response inhibition are a central feature of the highly prevalent dysexecutive syndrome found in Parkinson's disease (PD). Such deficits are related to a range of common clinically relevant symptoms including cognitive impairment as well as impulsive and compulsive behaviors. In this study, we explored the cortical dynamics underlying response inhibition during the mental preparation for the antisaccade task by recording magnetoencephalography (MEG) and eye-movements in 21 non-demented patients with early to mid-stage Parkinson's disease and 21 age-matched healthy control participants (HC). During the pre-stimulus preparatory period for antisaccades we observed: Taken together, the results indicate that alterations in pre-stimulus prefrontal alpha and beta activity hinder proactive response inhibition and in turn result in higher error rates and prolonged response latencies in PD.

Mate preference and brain oscillations: Initial romantic attraction is associated with decreases in alpha- and lower beta-band power.

Initial romantic attraction (IRA) refers to a series of positive reactions (such as feelings of exhilaration and compulsive thinking) toward desirable potential partners, usually at initial or early-stage encounters when no close relationship has yet been established. After decades of effort, the evolutionary value and key characteristics of IRA are well understood. However, the brain mechanisms associated with IRA are unclear. To address this question, we simulated a mate selection platform similar to that of Tinder. When participants assessed their romantic interest in potential partners on the platform, their electroencephalogram (EEG) signals were recorded in real time. The behavioral data demonstrated that IRA to ideal potential partners mainly reflects the dimensions of arousal and domination. The main study finding was that processing of the individual preference faces that resulted in IRA was associated with a decrease in power in the alpha and lower beta bands over the posterior and anterior sensor clusters; this occurred between 870 and 2,000 ms post-stimulus. Key findings regarding event-related potentials (ERPs) sensitive to individual stimuli preferences were replicated. The results support the hypothesis that brain oscillations in the alpha and lower beta range may reflect modulation in cortical activity associated with individual mate preferences.

Investigating the effect of losses and gains on effortful engagement during an incentivized Go/NoGo task through anticipatory cortical oscillatory changes.

Losses usually have greater subjective value (SV) than gains of equal nominal value but often cause a relative deterioration in effortful performance. Since losses and gains induce differing approach/avoidance behavioral tendencies, we explored whether incentive type interacted with approach/avoidance motor-sets. Alpha- and beta-band event-related desynchronization (ERD) was hypothesized to be weakest when participants expected a loss and prepared an inhibitory motor-set, and strongest when participants expected a gain and prepared an active motor-set. It was also hypothesized that effort would modulate reward and motor-set-related cortical activation patterns. Participants completed a cued Go/NoGo task while expecting a reward (+10p), avoiding a loss (-10p), or receiving no incentive (0p); and while expecting a NoGo cue with a probability of either .75 or .25. Pre-movement alpha- and beta-band EEG power was analyzed using the ERD method, and the SV of effort was evaluated using a cognitive effort discounting task. Gains incentivized faster RTs and stronger preparatory alpha band ERD compared to loss and no incentive conditions, while inhibitory motor-sets resulted in significantly weaker alpha-band ERD. However, there was no interaction between incentive and motor-sets. Participants were more willing to expend effort in losses compared to gain trials, although the SV of effort was not associated with ERD patterns or RTs. Results suggest that incentive and approach/avoidance motor tendencies modulate cortical activations prior to a speeded RT movement independently, and are not associated with the economic value of effort. The present results favor attentional explanations of the effect of incentive modality on effort.

Phase synchronized 6 Hz transcranial electric and magnetic stimulation boosts frontal theta activity and enhances working memory.

Network-level synchronization of theta oscillations in the cerebral cortex is linked to many vital cognitive functions across daily life, such as executive functions or regulation of arousal and consciousness. However, while neuroimaging has uncovered the ubiquitous functional relevance of theta rhythms in cognition, there remains a limited set of techniques for externally enhancing and stabilizing theta in the human brain non-invasively. Here, we developed and employed a new phase-synchronized low-intensity electric and magnetic stimulation technique to induce and stabilize narrowband 6-Hz theta oscillations in a group of healthy human adult participants, and then demonstrated how this technique also enhances cognitive processing by assaying working memory. Our findings demonstrate a technological advancement of brain stimulation methods, while also validating the causal link between theta activity and concurrent cognitive behavior, which may ultimately help to not only explain mechanisms, but offer perspectives for restoring deficient theta-band network activity observed in neuropsychiatric diseases.

Alpha-to-beta- and gamma-band activity reflect predictive coding in affective visual processing.

Processing of negative affective pictures typically leads to desynchronization of alpha-to-beta frequencies (ERD) and synchronization of gamma frequencies (ERS). Given that in predictive coding higher frequencies have been associated with prediction errors, while lower frequencies have been linked to expectations, we tested the hypothesis that alpha-to-beta ERD and gamma ERS induced by aversive pictures are associated with expectations and prediction errors, respectively. We recorded EEG while volunteers were involved in a probabilistically cued affective picture task using three different negative valences to produce expectations and prediction errors. Our data show that alpha-to-beta band activity after stimulus presentation was related to the expected valence of the stimulus as predicted by a cue. The absolute mismatch of the expected and actual valence, which denotes an absolute prediction error was related to increases in alpha, beta and gamma band activity. This demonstrates that top-down predictions and bottom-up prediction errors are represented in typical spectral patterns associated with affective picture processing. This study provides direct experimental evidence that negative affective picture processing can be described by neuronal predictive coding computations.

Early prediction of developing spontaneous activity in cultured neuronal networks.

Synchronization and bursting activity are intrinsic electrophysiological properties of in vivo and in vitro neural networks. During early development, cortical cultures exhibit a wide repertoire of synchronous bursting dynamics whose characterization may help to understand the parameters governing the transition from immature to mature networks. Here we used machine learning techniques to characterize and predict the developing spontaneous activity in mouse cortical neurons on microelectrode arrays (MEAs) during the first three weeks in vitro. Network activity at three stages of early development was defined by 18 electrophysiological features of spikes, bursts, synchrony, and connectivity. The variability of neuronal network activity during early development was investigated by applying k-means and self-organizing map (SOM) clustering analysis to features of bursts and synchrony. These electrophysiological features were predicted at the third week in vitro with high accuracy from those at earlier times using three machine learning models: Multivariate Adaptive Regression Splines, Support Vector Machines, and Random Forest. Our results indicate that initial patterns of electrical activity during the first week in vitro may already predetermine the final development of the neuronal network activity. The methodological approach used here may be applied to explore the biological mechanisms underlying the complex dynamics of spontaneous activity in developing neuronal cultures.

Brain oscillatory correlates of visuomotor adaptive learning.

Sensorimotor adaptation involves the recalibration of the mapping between motor command and sensory feedback in response to movement errors. Although adaptation operates within individual movements on a trial-to-trial basis, it can also undergo learning when adaptive responses improve over the course of many trials. Brain oscillatory activities related to these "adaptation" and "learning" processes remain unclear. The main reason for this is that previous studies principally focused on the beta band, which confined the outcome message to trial-to-trial adaptation. To provide a wider understanding of adaptive learning, we decoded visuomotor tasks with constant, random or no perturbation from EEG recordings in different bandwidths and brain regions using a multiple kernel learning approach. These different experimental tasks were intended to separate trial-to-trial adaptation from the formation of the new visuomotor mapping across trials. We found changes in EEG power in the post-movement period during the course of the visuomotor-constant rotation task, in particular an increased (i) theta power in prefrontal region, (ii) beta power in supplementary motor area, and (iii) gamma power in motor regions. Classifying the visuomotor task with constant rotation versus those with random or no rotation, we were able to relate power changes in beta band mainly to trial-to-trial adaptation to error while changes in theta band would relate rather to the learning of the new mapping. Altogether, this suggested that there is a tight relationship between modulation of the synchronization of low (theta) and higher (essentially beta) frequency oscillations in prefrontal and sensorimotor regions, respectively, and adaptive learning.

Effects of social and emotional context on neural activation and synchrony during movie viewing.

Sharing emotional experiences impacts how we perceive and interact with the world, but the neural mechanisms that support this sharing are not well characterized. In this study, participants (N = 52) watched videos in an MRI scanner in the presence of an unfamiliar peer. Videos varied in valence and social context (i.e., participants believed their partner was viewing the same (joint condition) or a different (solo condition) video). Reported togetherness increased during positive videos regardless of social condition, indicating that positive contexts may lessen the experience of being alone. Two analysis approaches were used to examine both sustained neural activity averaged over time and dynamic synchrony throughout the videos. Both approaches revealed clusters in the medial prefrontal cortex that were more responsive to the joint condition. We observed a time-averaged social-emotion interaction in the ventromedial prefrontal cortex, although this region did not demonstrate synchrony effects. Alternatively, social-emotion interactions in the amygdala and superior temporal sulcus showed greater neural synchrony in the joint compared to solo conditions during positive videos, but the opposite pattern for negative videos. These findings suggest that positive stimuli may be more salient when experienced together, suggesting a mechanism for forming social bonds.