Alpha and beta/low-gamma frequency bands may have distinct neural origin and function during post-stroke walking.

Plantarflexors provide propulsion during walking and receive input from both corticospinal and corticoreticulospinal tracts, which exhibit some frequency-specificity that allows potential differentiation of each tract's descending drive. Given that stroke may differentially affect each tract and impair the function of plantarflexors during walking; here, we examined this frequency-specificity and its relation to walking-specific measures during post-stroke walking. Fourteen individuals with chronic stroke walked on an instrumented treadmill at self-selected and fast walking speed (SSWS and FWS, respectively) while surface electromyography (sEMG) from soleus (SOL), lateral gastrocnemius (LG), and medial gastrocnemius (MG) and ground reaction forces (GRF) were collected.

Is there frequency-specificity in the motor control of walking? The putative differential role of alpha and beta oscillations.

Alpha and beta oscillations have been assessed thoroughly during walking due to their potential role as proxies of the corticoreticulospinal tract (CReST) and corticospinal tract (CST), respectively. Given that damage to a descending tract after stroke can cause walking deficits, detailed knowledge of how these oscillations mechanistically contribute to walking could be utilized in strategies for post-stroke locomotor recovery. In this review, the goal was to summarize, synthesize, and discuss the existing evidence on the potential differential role of these oscillations on the motor descending drive, the effect of transcranial alternate current stimulation (tACS) on neurotypical and post-stroke walking, and to discuss remaining gaps in knowledge, future directions, and methodological considerations.

Tuning Neural Synchronization: The Role of Variable Oscillation Frequencies in Neural Circuits.

Brain oscillations emerge during sensory and cognitive processes and have been classified into different frequency bands. Yet, even within the same frequency band and between nearby brain locations, the exact frequencies of brain oscillations can differ. These frequency differences (detuning) have been largely ignored and play little role in current functional theories of brain oscillations.

Empirically constrained network models for contrast-dependent modulation of gamma rhythm in V1.

Gamma oscillations are thought to play a key role in neuronal network function and neuronal communication, yet the underlying generating mechanisms have not been fully elucidated to date. At least partly, this may be due to the fact that even in simple network models of interconnected inhibitory (I) and excitatory (E) neurons, many parameters remain unknown and are set based on practical considerations or by convention. Here, we mitigate this problem by requiring PING (Pyramidal Interneuron Network Gamma) models to simultaneously satisfy a broad set of criteria for realistic behaviour based on empirical data spanning both the single unit (spikes) and local population (LFP) levels while unknown parameters are varied.

Functional brain networks of patients with epilepsy exhibit pronounced multiscale periodicities, which correlate with seizure onset.

Epileptic seizure detection and prediction by using noninvasive measurements such as scalp EEG signals or invasive, intracranial recordings, has been at the heart of epilepsy studies for at least three decades. To this end, the most common approach has been to consider short-length recordings (several seconds to a few minutes) around a seizure, aiming to identify significant changes that occur before or during seizures. An inherent assumption in this approach is the presence of a relatively constant EEG activity in the interictal period, which is interrupted by seizure occurrence.

Graph Theoretical Characteristics of EEG-Based Functional Brain Networks in Patients With Epilepsy: The Effect of Reference Choice and Volume Conduction.

It is well-established that both volume conduction and the choice of recording reference (montage) affect the correlation measures obtained from scalp EEG, both in the time and frequency domains. As a result, a number of correlation measures have been proposed aiming to reduce these effects. In our previous work, we have showed that scalp-EEG based functional brain networks in patients with epilepsy exhibit clear periodic patterns at different time scales and that these patterns are strongly correlated to seizure onset, particularly at shorter time scales (around 3 and 5 h), which has important clinical implications.

Epileptic seizure onset correlates with long term EEG functional brain network properties.

We investigated the correlation of epileptic seizure onset times with long term EEG functional brain network properties. To do so, we constructed binary functional brain networks from long-term, multichannel electroencephalographic data recorded from nine patients with epilepsy. The corresponding network properties were quantified using the average network degree.

Parametric variation of gamma frequency and power with luminance contrast: A comparative study of human MEG and monkey LFP and spike responses.

Gamma oscillations contribute significantly to the manner in which neural activity is bound into functional assemblies. The mechanisms that underlie the human gamma response, however, are poorly understood. Previous computational models of gamma rely heavily on the results of invasive recordings in animals, and it is difficult to assess whether these models hold in humans.

Input-dependent frequency modulation of cortical gamma oscillations shapes spatial synchronization and enables phase coding.

Fine-scale temporal organization of cortical activity in the gamma range (∼25-80Hz) may play a significant role in information processing, for example by neural grouping ('binding') and phase coding. Recent experimental studies have shown that the precise frequency of gamma oscillations varies with input drive (e.g.

Periodicity in functional brain networks: application to scalp EEG from epilepsy patients.

Seizure detection and prediction studies using scalp- or intracranial-EEG measurements often focus on short-length recordings around the occurrence of the seizure, normally ranging between several seconds and up to a few minutes before and after the event. The underlying assumption in these studies is the presence of a relatively constant EEG activity in the interictal period, that is presumably interrupted by the occurrence of a seizure, at the time the seizure starts or slightly earlier. In this study, we put this assumption under test, by examining long-duration scalp EEG recordings, ranging between 22 and 72 hours, of five patients with epilepsy.

Estimation of functional connectivity from electromagnetic signals and the amount of empirical data required.

An increasing number of neuroimaging studies are concerned with the identification of interactions or statistical dependencies between brain areas. Dependencies between the activities of different brain regions can be quantified with functional connectivity measures such as the cross-correlation coefficient. An important factor limiting the accuracy of such measures is the amount of empirical data available.

Using brain-computer interfaces and brain-state dependent stimulation as tools in cognitive neuroscience.

Large efforts are currently being made to develop and improve online analysis of brain activity which can be used, e.g., for brain-computer interfacing (BCI).

The relationship between the visual evoked potential and the gamma band investigated by blind and semi-blind methods.

Gamma Band Activity (GBA) is increasingly studied for its relation with attention, change detection, maintenance of working memory and the processing of sensory stimuli. Activity around the gamma range has also been linked with early visual processing, although the relationship between this activity and the low frequency visual evoked potential (VEP) remains unclear. This study examined the ability of blind and semi-blind source separation techniques to extract sources specifically related to the VEP and GBA in order to shed light on the relationship between them.

The role of oscillatory brain activity in object processing and figure-ground segmentation in human vision.

The perception of an object as a single entity within a visual scene requires that its features are bound together and segregated from the background and/or other objects. Here, we used magnetoencephalography (MEG) to assess the hypothesis that coherent percepts may arise from the synchronized high frequency (gamma) activity between neurons that code features of the same object. We also assessed the role of low frequency (alpha, beta) activity in object processing.

Identifying spatially overlapping local cortical networks with MEG.

Recent modelling studies (Hadjipapas et al. [2009]: Neuroimage 44:1290-1303) have shown that it may be possible to distinguish between different neuronal populations on the basis of their macroscopically measured (EEG/MEG) mean field. We set out to test whether the different orientation columns contributing to a signal at a specific cortical location could be identified based on the measured MEG signal.

Cortical oscillatory activity associated with the perception of illusory and real visual contours.

We used magnetoencephalography (MEG) to examine the nature of oscillatory brain rhythms when passively viewing both illusory and real visual contours. Three stimuli were employed: a Kanizsa triangle; a Kanizsa triangle with a real triangular contour superimposed; and a control figure in which the corner elements used to form the Kanizsa triangle were rotated to negate the formation of illusory contours. The MEG data were analysed using synthetic aperture magnetometry (SAM) to enable the spatial localisation of task-related oscillatory power changes within specific frequency bands, and the time-course of activity within given locations-of-interest was determined by calculating time-frequency plots using a Morlet wavelet transform.

Induced Gamma activity in primary visual cortex is related to luminance and not color contrast: An MEG study.

Gamma activity in the visual cortex has been reported in numerous EEG studies of coherent and illusory figures. A dominant theme of many such findings has been that temporal synchronization in the gamma band in response to these identifiable percepts is related to perceptual binding of the common features of the stimulus. In two recent studies using magnetoencephalography (MEG) and the beamformer analysis technique, we have shown that the magnitude of induced gamma activity in visual cortex is dependent upon independent stimulus features such as spatial frequency and contrast.

Can we observe collective neuronal activity from macroscopic aggregate signals?

The fundamental problem faced by noninvasive neuroimaging techniques such as EEG/MEG(1) is to elucidate functionally important aspects of the microscopic neuronal network dynamics from macroscopic aggregate measurements. Due to the mixing of the activities of large neuronal populations in the observed macroscopic aggregate, recovering the underlying network that generates the signal in the absence of any additional information represents a considerable challenge. Recent MEG studies have shown that macroscopic measurements contain sufficient information to allow the differentiation between patterns of activity, which are likely to represent different stimulus-specific collective modes in the underlying network (Hadjipapas, A.

Functional source separation applied to induced visual gamma activity.

Objective of this work was to explore the performance of a recently introduced source extraction method, FSS (Functional Source Separation), in recovering induced oscillatory change responses from extra-cephalic magnetoencephalographic (MEG) signals. Unlike algorithms used to solve the inverse problem, FSS does not make any assumption about the underlying biophysical source model; instead, it makes use of task-related features (functional constraints) to estimate source/s of interest. FSS was compared with blind source separation (BSS) approaches such as Principal and Independent Component Analysis, PCA and ICA, which are not subject to any explicit forward solution or functional constraint, but require source uncorrelatedness (PCA), or independence (ICA).

Stimuli of varying spatial scale induce gamma activity with distinct temporal characteristics in human visual cortex.

Gamma activity to stationary grating stimuli was studied non-invasively using MEG recordings in humans. Using a spatial filtering technique, we localized gamma activity to primary visual cortex. We tested the hypothesis that spatial frequency properties of visual stimuli may be related to the temporal frequency characteristics of the associated cortical responses.

Assessing interactions of linear and nonlinear neuronal sources using MEG beamformers: a proof of concept.

Objective: This study aimed to explore methods of assessing interactions between neuronal sources using MEG beamformers. However, beamformer methodology is based on the assumption of no linear long-term source interdependencies [VanVeen BD, vanDrongelen W, Yuchtman M, Suzuki A. Localization of brain electrical activity via linearly constrained minimum variance spatial filtering.

Imaging the dynamics of the auditory steady-state evoked response.

This study used magnetoencephalography (MEG) to examine the dynamic patterns of neural activity underlying the auditory steady-state response. We examined the continuous time-series of responses to a 32-Hz amplitude modulation. Fluctuations in the amplitude of the evoked response were found to be mediated by non-linear interactions with oscillatory processes both at the same source, in the alpha and beta frequency bands, and in the opposite hemisphere.

The missing link: analogous human and primate cortical gamma oscillations.

Recent animal studies highlighting the relationship between functional imaging signals and the underlying neuronal activity have revealed the potential capabilities of non-invasive methods. However, the valuable exchange of information between animal and human studies remains restricted by the limited evidence of direct physiological links between species. In this study we used magnetoencephalography (MEG) to investigate the occurrence of 30-70 Hz (gamma) oscillations in human visual cortex, induced by the presentation of visual stimuli of varying contrast.

Induced visual illusions and gamma oscillations in human primary visual cortex.

Using magnetoencephalography, we studied the spatiotemporal properties of cortical responses in terms of event-related synchronization and event-related desynchronization to a range of stripe patterns in subjects with no neurological disorders. These stripes are known for their tendency to induce a range of abnormal sensations, such as illusions, nausea, dizziness, headache and attacks of pattern-sensitive epilepsy. The optimal stimulus must have specific physical properties, and maximum abnormalities occur at specific spatial frequency and contrast.