Implications on visual apperception: energy, duration, structure and synchronization.

Although primary visual cortex (V1 or striate) activity per se is not sufficient for visual apperception (normal conscious visual experiences and conscious functions such as detection, discrimination, and recognition), the same is also true for extrastriate visual areas (such as V2, V3, V4/V8/VO, V5/M5/MST, IT, and GF). In the lack of V1 area, visual signals can still reach several extrastriate parts but appear incapable of generating normal conscious visual experiences. It is scarcely emphasized in the scientific literature that conscious perceptions and representations must have also essential energetic conditions. These energetic conditions are achieved by spatiotemporal networks of dynamic mitochondrial distributions inside neurons. However, the highest density of neurons in neocortex (number of neurons per degree of visual angle) devoted to representing the visual field is found in retinotopic V1. It means that the highest mitochondrial (energetic) activity can be achieved in mitochondrial cytochrome oxidase-rich V1 areas. Thus, V1 bear the highest energy allocation for visual representation. In addition, the conscious perceptions also demand structural conditions, presence of adequate duration of information representation, and synchronized neural processes and/or 'interactive hierarchical structuralism.' For visual apperception, various visual areas are involved depending on context such as stimulus characteristics such as color, form/shape, motion, and other features. Here, we focus primarily on V1 where specific mitochondrial-rich retinotopic structures are found; we will concisely discuss V2 where smaller riches of these structures are found. We also point out that residual brain states are not fully reflected in active neural patterns after visual perception. Namely, after visual perception, subliminal residual states are not being reflected in passive neural recording techniques, but require active stimulation to be revealed.

Amplification of asynchronous inhibition-mediated synchronization by feedback in recurrent networks.

Synchronization of 30-80 Hz oscillatory activity of the principle neurons in the olfactory bulb (mitral cells) is believed to be important for odor discrimination. Previous theoretical studies of these fast rhythms in other brain areas have proposed that principle neuron synchrony can be mediated by short-latency, rapidly decaying inhibition. This phasic inhibition provides a narrow time window for the principle neurons to fire, thus promoting synchrony. However, in the olfactory bulb, the inhibitory granule cells produce long lasting, small amplitude, asynchronous and aperiodic inhibitory input and thus the narrow time window that is required to synchronize spiking does not exist. Instead, it has been suggested that correlated output of the granule cells could serve to synchronize uncoupled mitral cells through a mechanism called "stochastic synchronization", wherein the synchronization arises through correlation of inputs to two neural oscillators. Almost all work on synchrony due to correlations presumes that the correlation is imposed and fixed. Building on theory and experiments that we and others have developed, we show that increased synchrony in the mitral cells could produce an increase in granule cell activity for those granule cells that share a synchronous group of mitral cells. Common granule cell input increases the input correlation to the mitral cells and hence their synchrony by providing a positive feedback loop in correlation. Thus we demonstrate the emergence and temporal evolution of input correlation in recurrent networks with feedback. We explore several theoretical models of this idea, ranging from spiking models to an analytically tractable model.

Synchronized activity between the ventral hippocampus and the medial prefrontal cortex during anxiety.

The ventral hippocampus, unlike its dorsal counterpart, is required for anxiety-like behavior. The means by which it acts are unknown. We hypothesized that the hippocampus synchronizes with downstream targets that influence anxiety, such as the medial prefrontal cortex (mPFC). To test this hypothesis, we recorded mPFC and hippocampal activity in mice exposed to two anxiogenic arenas. Theta-frequency activity in the mPFC and ventral, but not dorsal, hippocampus was highly correlated at baseline, and this correlation increased in both anxiogenic environments. Increases in mPFC theta power predicted avoidance of the aversive compartments of each arena and were larger in serotonin 1A receptor knockout mice, a genetic model of increased anxiety-like behavior. These results suggest a role for theta-frequency synchronization between the ventral hippocampus and the mPFC in anxiety. They are consistent with the notion that such synchronization is a general mechanism by which the hippocampus communicates with downstream structures of behavioral relevance.

Sensorimotor synchronization and perception of timing: effects of music training and task experience.

To assess individual differences in basic synchronization skills and in perceptual sensitivity to timing deviations, brief tests made up of isochronous auditory sequences containing phase shifts or tempo changes were administered to 31 college students (most of them with little or no music training) and nine highly trained musicians (graduate students of music performance). Musicians showed smaller asynchronies, lower tapping variability, and greater perceptual sensitivity than college students, on average. They also showed faster phase correction following a tempo change in the pacing sequence. Unexpectedly, however, phase correction following a simple phase shift was unusually quick in both groups, especially in college students. It emerged that some of the musicians, who had previous experience with laboratory synchronization tasks, showed a much slower corrective response to phase shifts than did the other musicians. When these others were retested after having gained some task experience, their phase correction was slower than previously. These results show (1) that instantaneous phase correction in response to phase perturbations is more common than was previously believed, and suggest that (2) gradual phase correction is not a shortcoming but reflects a reduction in the strength of sensorimotor coupling afforded by practice.

Graph properties of synchronized cortical networks during visual working memory maintenance.

Oscillatory synchronization facilitates communication in neuronal networks and is intimately associated with human cognition. Neuronal activity in the human brain can be non-invasively imaged with magneto- (MEG) and electroencephalography (EEG), but the large-scale structure of synchronized cortical networks supporting cognitive processing has remained uncharacterized. We combined simultaneous MEG and EEG (MEEG) recordings with minimum-norm-estimate-based inverse modeling to investigate the structure of oscillatory phase synchronized networks that were active during visual working memory (VWM) maintenance. Inter-areal phase-synchrony was quantified as a function of time and frequency by single-trial phase-difference estimates of cortical patches covering the entire cortical surfaces. The resulting networks were characterized with a number of network metrics that were then compared between delta/theta- (3-6 Hz), alpha- (7-13 Hz), beta- (16-25 Hz), and gamma- (30-80 Hz) frequency bands. We found several salient differences between frequency bands. Alpha- and beta-band networks were more clustered and small-world like but had smaller global efficiency than the networks in the delta/theta and gamma bands. Alpha- and beta-band networks also had truncated-power-law degree distributions and high k-core numbers. The data converge on showing that during the VWM-retention period, human cortical alpha- and beta-band networks have a memory-load dependent, scale-free small-world structure with densely connected core-like structures. These data further show that synchronized dynamic networks underlying a specific cognitive state can exhibit distinct frequency-dependent network structures that could support distinct functional roles.

Hierarchical control of false discovery rate for phase locking measures of EEG synchrony.

Computing phase-locking values (PLVs) between EEG signals is becoming a popular measure for quantifying functional connectivity, because it affords a more detailed picture of the synchrony relationships between channels at different times and frequencies. However, the accompanying increase in data dimensionality incurs a serious multiple testing problem for determining PLV significance. Standard methods for controlling Type I error, which treat all hypotheses as belonging to a single family, can fail to detect any significant discoveries. Instead, we propose a novel application of a hierarchical FDR method, which subsumes multiple families, for detecting significant PLV effects. For simulations and experimental data, we show that the proposed hierarchical FDR method is most powerful. This method revealed significant synchrony effects in the expected regions at an acceptable error rate of 5%, where other methods, including standard FDR correction failed to reveal any significant effects.

The direct relationship between inhibitory currents and local field potentials.

The frequency profiles of various extracellular field oscillations are known to reflect functional brain states, yet we lack detailed explanations of how these brain oscillations arise. Of particular clinical relevance are the high-frequency oscillations (HFOs) associated with interictal events and the onset of seizures. These time periods are also when pyramidal firing appears to be vetoed by high-frequency volleys of inhibitory synaptic currents, thereby providing an inhibitory restraint that opposes epileptiform spread (Trevelyan et al., 2006, 2007). The pattern and timing of this inhibitory volley is suggestive of a causal relationship between the restraint and HFOs. I show that at these times, isolated inhibitory currents from single pyramidal cells have a similarity to the extracellular signal that significantly exceeds chance. The ability to extrapolate from discrete currents in single cells to the extracellular signal arises because these inhibitory currents are synchronized in local populations of pyramidal cells. The visibility of these inhibitory currents in the field recordings is greatest when local pyramidal activity is suppressed: the correlation between the inhibitory currents and the field signal becomes worse when local activity increases, suggestive of a switch from one source of HFO to another as the restraint starts to fail. This association suggests that a significant component of HFOs reflects the last act of defiance in the face of an advancing ictal event.

EEG-based online two-dimensional cursor control.

This study aims to explore whether human intentions to move or cease to move right and left hands can provide four spatiotemporal patterns in single-trial non-invasive EEG signals to achieve a two-dimensional cursor control. Subjects performed motor tasks by either physical movement or motor imagery. Spatial filtering, temporal filtering, feature selection and classification methods were explored to support accurate computer pattern recognition. The performance was evaluated by both offline classification and online two-dimensional cursor control. Event-related desynchronization (ERD) and post-movement event-related synchronization (ERS) were observed on the contralateral hemisphere to the moving hand for both physical movement and motor imagery. The offline classification of four motor tasks provided 10-fold cross-validation accuracy as high as 88% for physical movement and 73% for motor imagery. Subjects participating in experiments with physical movement were able to complete the online game with the average accuracy of 85.5 + or - 4.65%; Subjects participating in motor imagery study also completed the game successfully. The proposed brain-computer interface (BCI) provided a new practical multi-dimensional method by noninvasive EEG signal associated with human natural behavior, which does not need long-term training.

Visualizing dynamical neural assemblies with a fuzzy synchronization clustering analysis.

Phase synchrony has been proposed as a possible communication mechanism between cerebral regions. The participation index method (PIM) may be used to investigate integrating structures within an oscillatory network, based on the eigenvalue decomposition of matrix of bivariate synchronization indices. However, eigenvector orthogonality between clusters may result in categorization difficulties for hub oscillators and pseudoclustering phenomenon. Here, we propose a method of fuzzy synchronization clustering analysis (FSCA) to avoid the constraint of orthogonality by combining the fuzzy c-means algorithm with the phase-locking value. Following mathematical derivation, we cross-validated the FSCA and the PIM using the same multichannel phase time series of event-related EEG from a subject performing a working memory task. Both clustering methods produced consistent findings for the qualitatively salient configuration of the original network-illustrated here by a visualization technique. In contrast to PIM, use of common virtual oscillatory centroids enabled the FSCA to reveal multiple dynamical neural assemblies as well as the unitary phase information within each assembly.

Internally mediated developmental desynchronization of neocortical network activity.

During neocortical development, neurons exhibit highly synchronized patterns of spontaneous activity, with correlated bursts of action potential firing dominating network activity. This early activity is eventually replaced by more sparse and decorrelated firing of cortical neurons, which modeling studies predict is a network state that is better suited for efficient neural coding. The precise time course and mechanisms of this crucial transition in cortical network activity have not been characterized in vivo. We used in vivo two-photon calcium imaging in combination with whole-cell recordings in both unanesthetized and anesthetized mice to monitor how spontaneous activity patterns in ensembles of layer 2/3 neurons of barrel cortex mature during postnatal development. We find that, as early as postnatal day 4, activity is highly synchronous within local clusters of neurons. At the end of the second postnatal week, neocortical networks undergo a transition to a much more desynchronized state that lacks a clear spatial structure. Strikingly, deprivation of sensory input from the periphery had no effect on the time course of this transition. Therefore, developmental desynchronization of spontaneous neuronal activity is a fundamental network transition in the neocortex that appears to be intrinsically generated.

Washout filter aided mean field feedback desynchronization in an ensemble of globally coupled neural oscillators.

We propose an approach for desynchronization in an ensemble of globally coupled neural oscillators. The impact of washout filter aided mean field feedback on population synchronization process is investigated. By blocking the Hopf bifurcation of the mean field, the controller desynchronizes the ensemble. The technique is generally demand-controlled. It is robust and can be easily implemented practically. We suggest it for effective deep brain stimulation in neurological diseases characterized by pathological synchronization.

A generalized framework for quantifying the dynamics of EEG event-related desynchronization.

Brains were built by evolution to react swiftly to environmental challenges. Thus, sensory stimuli must be processed ad hoc, i.e., independent--to a large extent--from the momentary brain state incidentally prevailing during stimulus occurrence. Accordingly, computational neuroscience strives to model the robust processing of stimuli in the presence of dynamical cortical states. A pivotal feature of ongoing brain activity is the regional predominance of EEG eigenrhythms, such as the occipital alpha or the pericentral mu rhythm, both peaking spectrally at 10 Hz. Here, we establish a novel generalized concept to measure event-related desynchronization (ERD), which allows one to model neural oscillatory dynamics also in the presence of dynamical cortical states. Specifically, we demonstrate that a somatosensory stimulus causes a stereotypic sequence of first an ERD and then an ensuing amplitude overshoot (event-related synchronization), which at a dynamical cortical state becomes evident only if the natural relaxation dynamics of unperturbed EEG rhythms is utilized as reference dynamics. Moreover, this computational approach also encompasses the more general notion of a "conditional ERD," through which candidate explanatory variables can be scrutinized with regard to their possible impact on a particular oscillatory dynamics under study. Thus, the generalized ERD represents a powerful novel analysis tool for extending our understanding of inter-trial variability of evoked responses and therefore the robust processing of environmental stimuli.

Control of synchronization of brain dynamics leads to control of epileptic seizures in rodents.

We have designed and implemented an automated, just-in-time stimulation, seizure control method using a seizure prediction method from nonlinear dynamics coupled with deep brain stimulation in the centromedial thalamic nuclei in epileptic rats. A comparison to periodic stimulation, with identical stimulation parameters, was also performed. The two schemes were compared in terms of their efficacy in control of seizures, as well as their effect on synchronization of brain dynamics. The automated just-in-time (JIT) stimulation showed reduction of seizure frequency and duration in 5 of the 6 rats, with significant reduction of seizure frequency (>50%) in 33% of the rats. This constituted a significant improvement over the efficacy of the periodic control scheme in the same animals. Actually, periodic stimulation showed an increase of seizure frequency in 50% of the rats, reduction of seizure frequency in 3 rats and significant reduction in 1 rat. Importantly, successful seizure control was highly correlated with desynchronization of brain dynamics. This study provides initial evidence for the use of closed-loop feedback control systems in epileptic seizures combining methods from seizure prediction and deep brain stimulation.

Comparison between spontaneous and kainate-induced gamma oscillations in the mouse hippocampus in vitro.

Neuronal synchronization at gamma frequency, implicated in cognition, can be evoked in hippocampal slices by pharmacological activation. We characterized spontaneous small-amplitude gamma oscillations (SgammaO) recorded in area CA3 of mouse hippocampal slices and compared it with kainate-induced gamma oscillations (KgammaO). SgammaO had a lower peak frequency, a more sinusoidal waveform and was spatially less coherent than KgammaO, irrespective of oscillation amplitude. CA3a had the smallest oscillation power, phase-led CA3c by approximately 4 ms and had the highest SgammaO frequency in isolated subslices. During SgammaO CA3c neurons fired at the rebound of inhibitory postsynaptic potentials (IPSPs) that were associated with a current source in stratum lucidum, whereas CA3a neurons often fired from spikelets, 3-4 ms earlier in the cycle, and had smaller IPSPs. Kainate induced faster/larger IPSPs that were associated with an earlier current source in stratum pyramidale. SgammaO and KgammaO power were dependent on alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors, gap junctions and gamma-aminobutyric acid (GABA)(A) receptors. SgammaO was suppressed by elevating extracellular KCl, blocking N-methyl-d-aspartate (NMDA) receptors or muscarinic receptors, or activating GluR5-containing kainate receptors. SgammaO was not affected by blocking metabotropic glutamate receptors or hyperpolarization-activated currents. The adenosine A(1) receptor antagonist 8-cyclopentyl-1,3-dimethoxyxanthine (8-CPT) and the CB1 cannabinoid receptor antagonist N-(piperidin-1-yl)-5-(4-iodophenyl)-1-(2,4-dichlorophenyl)-4-methyl-1H-pyrazole-3-carboxamide (AM251) increased SgammaO power, indicating that endogenous adenosine and/or endocannabinoids suppress or prevent SgammaO in vitro. SgammaO emerges from a similar basic network as KgammaO, but differs in involvement of somatically projecting interneurons and pharmacological modulation profile. These observations advocate the use of SgammaO as a natural model for hippocampal gamma oscillations, particularly during less activated behavioural states.

Bi-phase locking - a tool for probing non-linear interaction in the human brain.

We present a novel method for detecting frequency-frequency coupling between the electrical output of cortical areas as measured by electrocorticography (ECoG), electroencephalography (EEG) and magnetoencephalography (MEG), the biphase-locking value (bPLV). Our method is an extension of the well known phase-locking value (PLV) and is specifically sensitive to non-linear interactions, i.e. quadratic phase coupling across frequencies. Due to its sensitivity to non-linear interactions, it is robust to spurious synchronization arising from linear crosstalk, which is an especially useful property when analyzing data recorded by EEG/MEG. We discuss the statistical properties of the bPLV, specifically the distribution of the bPLV under assumption of random phases between the signals of interest. We also compare the bPLV to the PLV for cortical interactions that are computed for simulated EEG/MEG data. These data were mapped to the cortex using an inverse solution. We demonstrate our method for event related ECoG data recorded from the motor cortex of an epileptic patient, who performed a cued finger movement task. We find highly significant, movement related increase of the bPLV between the alpha (12 Hz) and high gamma (77 Hz) band in a pre-motor area, coupling to high gamma at 89 Hz in the motor cortex.

Assessment of linear and nonlinear synchronization measures for analyzing EEG in a mild epileptic paradigm.

Epilepsy is one of the most common brain disorders and may result in brain dysfunction and cognitive disturbances. Epileptic seizures usually begin in childhood without being accommodated by brain damage and are tolerated by drugs that produce no brain dysfunction. In this study, cognitive function is evaluated in children with mild epileptic seizures controlled with common antiepileptic drugs. Under this prism, we propose a concise technical framework of combining and validating both linear and nonlinear methods to efficiently evaluate (in terms of synchronization) neurophysiological activity during a visual cognitive task consisting of fractal pattern observation. We investigate six measures of quantifying synchronous oscillatory activity based on different underlying assumptions. These measures include the coherence computed with the traditional formula and an alternative evaluation of it that relies on autoregressive models, an information theoretic measure known as minimum description length, a robust phase coupling measure known as phase-locking value, a reliable way of assessing generalized synchronization in state-space and an unbiased alternative called synchronization likelihood. Assessment is performed in three stages; initially, the nonlinear methods are validated on coupled nonlinear oscillators under increasing noise interference; second, surrogate data testing is performed to assess the possible nonlinear channel interdependencies of the acquired EEGs by comparing the synchronization indexes under the null hypothesis of stationary, linear dynamics; and finally, synchronization on the actual data is measured. The results on the actual data suggest that there is a significant difference between normal controls and epileptics, mostly apparent in occipital-parietal lobes during fractal observation tests.

Brains swinging in concert: cortical phase synchronization while playing guitar.

BACKGROUND: Brains interact with the world through actions that are implemented by sensory and motor processes. A substantial part of these interactions consists in synchronized goal-directed actions involving two or more individuals. Hyperscanning techniques for assessing fMRI simultaneously from two individuals have been developed. However, EEG recordings that permit the assessment of synchronized neuronal activities at much higher levels of temporal resolution have not yet been simultaneously assessed in multiple individuals and analyzed in the time-frequency domain. In this study, we simultaneously recorded EEG from the brains of each of eight pairs of guitarists playing a short melody together to explore the extent and the functional significance of synchronized cortical activity in the course of interpersonally coordinated actions. RESULTS: By applying synchronization algorithms to intra- and interbrain analyses, we found that phase synchronization both within and between brains increased significantly during the periods of (i) preparatory metronome tempo setting and (ii) coordinated play onset. Phase alignment extracted from within-brain dynamics was related to behavioral play onset asynchrony between guitarists. CONCLUSION: Our findings show that interpersonally coordinated actions are preceded and accompanied by between-brain oscillatory couplings. Presumably, these couplings reflect similarities in the temporal properties of the individuals' percepts and actions. Whether between-brain oscillatory couplings play a causal role in initiating and maintaining interpersonal action coordination needs to be clarified by further research.

A role of beta oscillatory synchrony in biasing response competition?

Beta-range oscillatory activity measured over the motor cortex and beta synchrony between cortex and spinal cord can be up- or downregulated in anticipation of a postural challenge or the initiation of movement. Based on these properties of beta activity in the preparation for future events, the present investigation addressed whether simultaneous up- and downregulation of beta activity might act as an online mechanism to suppress and select competing responses. Measures of local and long-range beta synchrony were obtained from electroencephalographic and electromyographic signals recorded during a cued choice reaction task. Analyses focused on task-related changes in beta synchrony during a 2-s delay period between cue and response signal. Analyzed separately, none of the beta measures (spectral power, corticospinal coherence, corticospinal phase synchronization) showed simultaneous up- and downregulation over opposite hemispheres controlling the competing responses. However, the combined pattern of beta measures showed beta power desynchronization associated with selection of a response and increased corticospinal coherence and phase synchronization associated with suppression of a response. These results indicate that concurrent up- and downregulation of different components of beta oscillatory activity is likely to have a functional role in response selection, resembling attentional modulation of alpha activity in visual selection.