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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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