Very High Frequency Oscillations (VHFO) as a Predictor of Movement Intentions

Gamma band (30-80 Hz) oscillations arising in neuronal ensembles are thought to be a crucial component of the neural code. Recent studies in animals suggest a similar functional role for very high frequency oscillations (VHFO) in the range 80-200Hz. Since some intracerebral studies in humans link VHFO to epileptogenesis, it remains unclear if VHFO appear in the healthy human brain and if so which is their role. This study uses EEG recordings from twelve healthy volunteers, engaged in a visuo-motor reaction time task, to show that VHFO are not necessarily pathological but rather code information about upcoming movements. Oscillations within the range (30-200Hz) occurring in the period between stimuli presentation and the fastest hand responses allow highly accurate (>96%) prediction of the laterality of the responding hand in single trials. Our results suggest that VHFO belong in functional terms to the gamma band that must be considerably enlarged to better understand the role of oscillatory activity in brain functioning. This study has therefore important implications for the recording and analysis of electrophysiological data in normal subjects and patients

The influence of serotonin transporter polymorphisms on cortical activity: A resting EEG study

<p>Abstract</p> <p>Background</p> <p>The serotonin transporter gene (<it>5-HTT</it>) is a key regulator of serotonergic neurotransmission and has been linked to various psychiatric disorders. Among the genetic variants, polymorphisms in the <it>5-HTT </it>gene-linked polymorphic region (<it>5-HTTLPR</it>) and variable-number-of-tandem-repeat in the second intron (<it>5-HTTVNTR</it>) have functional consequences. However, their genetic impact on cortical oscillation remains unclear. This study examined the modulatory effects of <it>5-HTTLPR </it>(L-allele carriers vs. non-carriers) and <it>5-HTTVNTR </it>(10-repeat allele carriers vs. non-carriers) polymorphism on regional neural activity in a young female population.</p> <p>Methods</p> <p>Blood samples and resting state eyes-closed electroencephalography (EEG) signals were collected from 195 healthy women and stratified into 2 sets of comparisons of 2 groups each: L-allele carriers (<it>N </it>= 91) vs. non-carriers for <it>5-HTTLPR </it>and 10-repeat allele carriers (<it>N </it>= 25) vs. non-carriers for <it>5-HTTVNTR</it>. The mean power of 18 electrodes across theta, alpha, beta, gamma, gamma1, and gamma2 frequencies was analyzed. Between-group statistics were performed by an independent t-test, and global trends of regional power were quantified by non-parametric analyses.</p> <p>Results</p> <p>Among <it>5-HTTVNTR </it>genotypes, 10-repeat allele carriers showed significantly low regional power at gamma frequencies across the brain. We noticed a consistent global trend that carriers with low transcription efficiency of 5-HTT possessed low regional powers, regardless of frequency bands. The non-parametric analyses confirmed this observation, with <it>P </it>values of 3.071 × 10^-8and 1.459 × 10^-12for <it>5-HTTLPR </it>and <it>5-HTTVNTR</it>, respectively.</p> <p>Conclusions and Limitations</p> <p>Our analyses showed that genotypes with low 5-HTT activity are associated with less local neural synchronization during relaxation. The implication with respect to genetic vulnerability of 5-HTT across a broad range of psychiatric disorders is discussed. Given the low frequency of 10-repeat allele of <it>5-HTTVNTR </it>in our research sample, the possibility of false positive findings should also be considered.</p

What Happens in Between? Human Oscillatory Brain Activity Related to Crossmodal Spatial Cueing

Previous studies investigated the effects of crossmodal spatial attention by comparing the responses to validly versus invalidly cued target stimuli. Dynamics of cortical rhythms in the time interval between cue and target might contribute to cue effects on performance. Here, we studied the influence of spatial attention on ongoing oscillatory brain activity in the interval between cue and target onset. In a first experiment, subjects underwent periods of tactile stimulation (cue) followed by visual stimulation (target) in a spatial cueing task as well as tactile stimulation as a control. In a second experiment, cue validity was modified to be 50%, 75%, or else 25%, to separate effects of exogenous shifts of attention caused by tactile stimuli from that of endogenous shifts. Tactile stimuli produced: 1) a stronger lateralization of the sensorimotor beta-rhythm rebound (15–22 Hz) after tactile stimuli serving as cues versus not serving as cues; 2) a suppression of the occipital alpha-rhythm (7–13 Hz) appearing only in the cueing task (this suppression was stronger contralateral to the endogenously attended side and was predictive of behavioral success); 3) an increase of prefrontal gamma-activity (25–35 Hz) specifically in the cueing task. We measured cue-related modulations of cortical rhythms which may accompany crossmodal spatial attention, expectation or decision, and therefore contribute to cue validity effects. The clearly lateralized alpha suppression after tactile cues in our data indicates its dependence on endogenous rather than exogenous shifts of visuo-spatial attention following a cue independent of its modality

Distinct Gamma-Band Components Reflect the Short-Term Memory Maintenance of Different Sound Lateralization Angles

Oscillatory activity in human electro- or magnetoencephalogram has been related to cortical stimulus representations and their modulation by cognitive processes. Whereas previous work has focused on gamma-band activity (GBA) during attention or maintenance of representations, there is little evidence for GBA reflecting individual stimulus representations. The present study aimed at identifying stimulus-specific GBA components during auditory spatial short-term memory. A total of 28 adults were assigned to 1 of 2 groups who were presented with only right- or left-lateralized sounds, respectively. In each group, 2 sample stimuli were used which differed in their lateralization angles (15° or 45°) with respect to the midsagittal plane. Statistical probability mapping served to identify spectral amplitude differences between 15° versus 45° stimuli. Distinct GBA components were found for each sample stimulus in different sensors over parieto-occipital cortex contralateral to the side of stimulation peaking during the middle 200–300 ms of the delay phase. The differentiation between “preferred” and “nonpreferred” stimuli during the final 100 ms of the delay phase correlated with task performance. These findings suggest that the observed GBA components reflect the activity of distinct networks tuned to spatial sound features which contribute to the maintenance of task-relevant information in short-term memory

Power-Law Scaling in the Brain Surface Electric Potential

Recent studies have identified broadband phenomena in the electric potentials produced by the brain. We report the finding of power-law scaling in these signals using subdural electrocorticographic recordings from the surface of human cortex. The power spectral density (PSD) of the electric potential has the power-law form from 80 to 500 Hz. This scaling index, , is conserved across subjects, area in the cortex, and local neural activity levels. The shape of the PSD does not change with increases in local cortical activity, but the amplitude, , increases. We observe a “knee” in the spectra at , implying the existence of a characteristic time scale . Below , we explore two-power-law forms of the PSD, and demonstrate that there are activity-related fluctuations in the amplitude of a power-law process lying beneath the rhythms. Finally, we illustrate through simulation how, small-scale, simplified neuronal models could lead to these power-law observations. This suggests a new paradigm of non-oscillatory “asynchronous,” scale-free, changes in cortical potentials, corresponding to changes in mean population-averaged firing rate, to complement the prevalent “synchronous” rhythm-based paradigm

High-Frequency Oscillations in Distributed Neural Networks Reveal the Dynamics of Human Decision Making

We examine the relative timing of numerous brain regions involved in human decisions that are based on external criteria, learned information, personal preferences, or unconstrained internal considerations. Using magnetoencephalography (MEG) and advanced signal analysis techniques, we were able to non-invasively reconstruct oscillations of distributed neural networks in the high-gamma frequency band (60–150 Hz). The time course of the observed neural activity suggested that two-alternative forced choice tasks are processed in four overlapping stages: processing of sensory input, option evaluation, intention formation, and action execution. Visual areas are activated first, and show recurring activations throughout the entire decision process. The temporo-occipital junction and the intraparietal sulcus are active during evaluation of external values of the options, 250–500 ms after stimulus presentation. Simultaneously, personal preference is mediated by cortical midline structures. Subsequently, the posterior parietal and superior occipital cortices appear to encode intention, with different subregions being responsible for different types of choice. The cerebellum and inferior parietal cortex are recruited for internal generation of decisions and actions, when all options have the same value. Action execution was accompanied by activation peaks in the contralateral motor cortex. These results suggest that high-gamma oscillations as recorded by MEG allow a reliable reconstruction of decision processes with excellent spatiotemporal resolution

Directed Cortical Information Flow during Human Object Recognition: Analyzing Induced EEG Gamma-Band Responses in Brain's Source Space

The increase of induced gamma-band responses (iGBRs; oscillations >30 Hz) elicited by familiar (meaningful) objects is well established in electroencephalogram (EEG) research. This frequency-specific change at distinct locations is thought to indicate the dynamic formation of local neuronal assemblies during the activation of cortical object representations. As analytically power increase is just a property of a single location, phase-synchrony was introduced to investigate the formation of large-scale networks between spatially distant brain sites. However, classical phase-synchrony reveals symmetric, pair-wise correlations and is not suited to uncover the directionality of interactions. Here, we investigated the neural mechanism of visual object processing by means of directional coupling analysis going beyond recording sites, but rather assessing the directionality of oscillatory interactions between brain areas directly. This study is the first to identify the directionality of oscillatory brain interactions in source space during human object recognition and suggests that familiar, but not unfamiliar, objects engage widespread reciprocal information flow. Directionality of cortical information-flow was calculated based upon an established Granger-Causality coupling-measure (partial-directed coherence; PDC) using autoregressive modeling. To enable comparison with previous coupling studies lacking directional information, phase-locking analysis was applied, using wavelet-based signal decompositions. Both, autoregressive modeling and wavelet analysis, revealed an augmentation of iGBRs during the presentation of familiar objects relative to unfamiliar controls, which was localized to inferior-temporal, superior-parietal and frontal brain areas by means of distributed source reconstruction. The multivariate analysis of PDC evaluated each possible direction of brain interaction and revealed widespread reciprocal information-transfer during familiar object processing. In contrast, unfamiliar objects entailed a sparse number of only unidirectional connections converging to parietal areas. Considering the directionality of brain interactions, the current results might indicate that successful activation of object representations is realized through reciprocal (feed-forward and feed-backward) information-transfer of oscillatory connections between distant, functionally specific brain areas

Concordance of MEG and fMRI patterns in adolescents during verb generation

In this study we focused on direct comparison between the spatial distributions of activation detected by functional magnetic resonance imaging (fMRI) and localization of sources detected by magnetoencephalography (MEG) during identical language tasks. We examined the spatial concordance between MEG and fMRI results in 16 adolescents performing a three-phase verb generation task that involves repeating the auditorily presented concrete noun and generating verbs either overtly or covertly in response to the auditorily presented noun. MEG analysis was completed using a synthetic aperture magnetometry (SAM) technique, while the fMRI data were analyzed using the general linear model approach with random-effects. To quantify the agreement between the two modalities, we implemented voxel-wise concordance correlation coefficient (CCC) and identified the left inferior frontal gyrus and the bilateral motor cortex with high CCC values. At the group level, MEG and fMRI data showed spatial convergence in the left inferior frontal gyrus for covert or overt generation versus overt repetition, and the bilateral motor cortex when overt generation versus covert generation. These findings demonstrate the utility of the CCC as a quantitative measure of spatial convergence between two neuroimaging techniques

A Blueprint for Real-Time Functional Mapping via Human Intracranial Recordings

International audienceBACKGROUND: The surgical treatment of patients with intractable epilepsy is preceded by a pre-surgical evaluation period during which intracranial EEG recordings are performed to identify the epileptogenic network and provide a functional map of eloquent cerebral areas that need to be spared to minimize the risk of post-operative deficits. A growing body of research based on such invasive recordings indicates that cortical oscillations at various frequencies, especially in the gamma range (40 to 150 Hz), can provide efficient markers of task-related neural network activity. PRINCIPAL FINDINGS: Here we introduce a novel real-time investigation framework for mapping human brain functions based on online visualization of the spectral power of the ongoing intracranial activity. The results obtained with the first two implanted epilepsy patients who used the proposed online system illustrate its feasibility and utility both for clinical applications, as a complementary tool to electrical stimulation for presurgical mapping purposes, and for basic research, as an exploratory tool used to detect correlations between behavior and oscillatory power modulations. Furthermore, our findings suggest a putative role for high gamma oscillations in higher-order auditory processing involved in speech and music perception. CONCLUSION/SIGNIFICANCE: The proposed real-time setup is a promising tool for presurgical mapping, the investigation of functional brain dynamics, and possibly for neurofeedback training and brain computer interfaces

Sparse Gamma Rhythms Arising through Clustering in Adapting Neuronal Networks

Gamma rhythms (30–100 Hz) are an extensively studied synchronous brain state responsible for a number of sensory, memory, and motor processes. Experimental evidence suggests that fast-spiking interneurons are responsible for carrying the high frequency components of the rhythm, while regular-spiking pyramidal neurons fire sparsely. We propose that a combination of spike frequency adaptation and global inhibition may be responsible for this behavior. Excitatory neurons form several clusters that fire every few cycles of the fast oscillation. This is first shown in a detailed biophysical network model and then analyzed thoroughly in an idealized model. We exploit the fact that the timescale of adaptation is much slower than that of the other variables. Singular perturbation theory is used to derive an approximate periodic solution for a single spiking unit. This is then used to predict the relationship between the number of clusters arising spontaneously in the network as it relates to the adaptation time constant. We compare this to a complementary analysis that employs a weak coupling assumption to predict the first Fourier mode to destabilize from the incoherent state of an associated phase model as the external noise is reduced. Both approaches predict the same scaling of cluster number with respect to the adaptation time constant, which is corroborated in numerical simulations of the full system. Thus, we develop several testable predictions regarding the formation and characteristics of gamma rhythms with sparsely firing excitatory neurons