A theory of short term spectral analysis, synthesis, and modification is presented with an attempt at pointing out certain practical and theoretical questions. The methods discussed here are useful in designing filter banks when the filter bank outputs are to be used for synthesis after multiplicative modifications are made to the spectrum.

Cognitive control is defined by a set of neural processes that allow us to interact with our complex environment in a goal-directed manner(1). Humans regularly challenge these control processes when attempting to simultaneously accomplish multiple goals (multitasking), generating interference as the result of fundamental information processing limitations(2). It is clear that multitasking behaviour has become ubiquitous in today's technologically dense world(3), and substantial evidence has accrued regarding multitasking difficulties and cognitive control deficits in our ageing population(4). Here we show that multitasking performance, as assessed with a custom-designed three-dimensional video game (NeuroRacer), exhibits a linear age-related decline from 20 to 79 years of age. By playing an adaptive version of NeuroRacer in multitasking training mode, older adults (60 to 85 years old) reduced multitasking costs compared to both an active control group and a no-contact control group, attaining levels beyond those achieved by untrained 20-year-old participants, with gains persisting for 6 months. Furthermore, age-related deficits in neural signatures of cognitive control, as measured with electroencephalography, were remediated by multitasking training (enhanced midline frontal theta power and frontal-posterior theta coherence). Critically, this training resulted in performance benefits that extended to untrained cognitive control abilities (enhanced sustained attention and working memory), with an increase in midline frontal theta power predicting the training-induced boost in sustained attention and preservation of multitasking improvement 6 months later. These findings highlight the robust plasticity of the prefrontal cognitive control system in the ageing brain, and provide the first evidence, to our knowledge, of how a custom-designed video game can be used to assess cognitive abilities across the lifespan, evaluate underlying neural mechanisms, and serve as a powerful tool for cognitive enhancement.

Recent findings indicate that the hippocampus supports not only longterm memory encoding but also plays a role in working memory (WM) maintenance of multiple items; however, the neural mechanism underlying multi-item maintenance is still unclear. Theoretical work suggests that multiple items are being maintained by neural assemblies synchronized in the gamma frequency range (25-100 Hz) that are locked to consecutive phase ranges of oscillatory activity in the theta frequency range (4-8 Hz). Indeed, cross-frequency coupling of the amplitude of high-frequency activity to the phase of slower oscillations has been described both in animals and in humans, but has never been linked to a theoretical model of a cognitive process. Here we used intracranial EEG recordings in human epilepsy patients to test pivotal predictions from theoretical work. First we show that simultaneous maintenance of multiple items in WM is accompanied by cross-frequency coupling of oscillatory activity in the hippocampus, which is recruited during multiitem WM. Second, maintenance of an increasing number of items is associated with modulation of beta/gamma amplitude with theta band activity of lower frequency, consistent with the idea that longer cycles are required for an increased number of representations by gamma cycles. This effect cannot be explained by a difference in theta or beta/gamma power. Third, we describe how the precision of cross-frequency coupling predicts individual WM performance. These data support the idea that working memory in humans depends on a neural code using phase information.

In this study, we find numerical solution of by Newton Interpolation. We determined coefficients such that to be an approximation for u (x). This method give an approximate solution for integral equation and also it is powerful in solving both Fredholm and Volterra integral equations, specially for the first kind. In this study, we use special interpolation and quadrature rule for numerical integration. Effectiveness and accuracy of new method are presented with numerical examples.

The relationship between ongoing occipital alpha rhythm (8–12 Hz) and the generation of visual evoked potentials (VEPs) has been discussed controversially. While the “evoked theory” sees no interaction between VEP generation and the alpha rhythm, the “oscillatory theory” (also known as “phase-reset theory”) postulates VEP generation to be based on alpha rhythm phase resetting. Previous experimental results are contradictory, rendering a straightforward interpretation difficult. Our approach was to theoretically model the implications of the evoked and oscillatory theory also incorporating stimulus-induced alpha-rhythm desynchronization. As a result, the model based on the oscillatory theory predicts alpha-band dependent VEP amplitudes but constant phase locking. The model based on the evoked theory predicts unaffected VEP amplitudes but alpha-band dependent phase locking. Subsequently, we analyzed experimental data in which VEPs were assessed in an “eyes open” and “eyes closed” condition in 17 subjects. For early components of the VEP, findings are in agreement with the evoked theory, i.e. VEP amplitudes remain unaffected and phase locking decreases during periods of high alpha activity. Late VEP component amplitudes (>02175 ms), however, are dependent on pre-stimulus alpha amplitudes. This interaction is contradictory to the oscillatory theory since this VEP amplitude difference is not paralleled by a corresponding difference in alpha-band amplitude in the affected time window. In summary, by using a model-based approach we identified early VEPs to be compatible with the evoked theory, while results of late VEPs support a modulatory but not causative role – the latter implied by the oscillatory theory – of alpha activity for EP generation.

Published in print

Coupling between neural oscillations in different frequency bands has been proposed to coordinate neural processing. In particular, gamma power coupled to alpha phase is proposed to reflect gating of information in the visual system but the existence of such a mechanism remains untested. Here, we recorded ongoing brain activity using magnetoencephalography in subjects who performed a modified Sternberg working memory task in which distractors were presented in the retention interval. During the anticipatory pre-distractor period, we show that the phase of alpha oscillations was coupled with the power of high (80-120Hz) gamma band activity, i.e. gamma power consistently was lower at the trough than at the peak of the alpha cycle (9-12Hz). We further show that high alpha power was associated with weaker gamma power at the trough of the alpha cycle. This result is in line with alpha activity in sensory region implementing a mechanism of pulsed inhibition silencing neuronal firing every ~100 ms.

AbstractBrian connectivity describes the networks of functional and anatomical connections across the brain. The functional network communications across the brain networks dependent on neuronal oscillations. Detection of the synchronous activation of neurons can be used to determine the wellbeing or integrity of the functional connectivity in the human brain networks. Well-connected highly synchronous functional activity can be measured by Electroencephalography (EEG) or Magnetoencephalography (MEG) and then analyzed with several types of mathematical algorithms. Coherence is one mathematical method that can be used to determine if two or more sensors, or brain regions, have similar neuronal oscillatory activity with each other. Since the 1960 , coherence has generally been assessed on the similarity of the frequency content across EEG sensors. Recently coherence, after it has been imaged in the brain, has been used to assess how coherent or connected specific locations in the brain are networked together in several different neurological disorders. Statistical analysis can then be performed on the coherence results to verify evidence of normal or abnormal network activity in a patient. In this review we highlight how functional brain connectivity is assessed in Source space using coherence technique measured by MEG.

Spectral signal analysis constitutes one of the most important and most commonly used analytical tools for the evaluation of neurophysiological signals. It is not only the spectral parameters per se (amplitude and phase) which are of interest, but there is also a variety of measures derived from them, including important coupling measures like coherence or phase synchrony. After reviewing some of these measures in order to underline the widespread relevance of spectral analysis, this report compares the three classical spectral analysis approaches: Fourier, Hilbert and wavelet transform. Recently, there seems to be increasing acceptance of the notion that Hilbert- or wavelet-based analyses be in some way superior to Fourier-based analyses. The present article counters such views by demonstrating that the three techniques are in fact formally (i.e. mathematically) equivalent when using the class of wavelets that is typically applied in spectral analyses. Moreover, spectral amplitude serves as an example to show that Fourier, Hilbert and wavelet analysis also yield equivalent results in practical applications to neuronal signals.

Since the mid 1990s, the intriguing dynamics of the brain at rest has been attracting a growing body of research in neuroscience. Neuroimaging studies have revealed distinct functional networks that slowly activate and deactivate, pointing to the existence of an underlying network dynamics emerging spontaneously during rest, with specific spatial, temporal and spectral characteristics. Several theoretical scenarios have been proposed and tested with the use of large-scale computational models of coupled brain areas. However, a mechanistic explanation that encompasses all the phenomena observed in the brain during rest is still to come. In this review, we provide an overview of the key findings of resting-state activity covering a range of neuroimaging modalities including fMRI, EEG and MEG. We describe how to best define and analyze anatomical and functional brain networks and how unbalancing these networks may lead to problems with mental health. Finally, we review existing large-scale models of resting-state dynamics in health and disease. An important common feature of resting-state models is that the emergence of resting-state functional networks is obtained when the model parameters are such that the system operates at the edge of a bifurcation. At this critical working point, the global network dynamics reveals correlation patterns that are spatially shaped by the underlying anatomical structure, leading to an optimal fit with the empirical BOLD functional connectivity. However, new insights coming from recent studies, including faster oscillatory dynamics and non-stationary functional connectivity, must be taken into account in future models to fully understand the network mechanisms leading to the resting-state activity.

We observed robust coupling between the high- and low-frequency bands of ongoing electrical activity in the human brain. In particular, the phase of the low-frequency theta (4 to 8 hertz) rhythm modulates power in the high gamma (80 to 150 hertz) band of the electrocorticogram, with stronger modulation occurring at higher theta amplitudes. Furthermore, different behavioral tasks evoke distinct patterns of theta/high gamma coupling across the cortex. The results indicate that transient coupling between low- and high-frequency brain rhythms coordinates activity in distributed cortical areas, providing a mechanism for effective communication during cognitive processing in humans.

Abstract Recent studies suggest that cross-frequency coupling (CFC) might play a functional role in neuronal computation, communication and learning. In particular, the strength of phase-amplitude CFC differs across brain areas in a task-relevant manner, changes quickly in response to sensory, motor and cognitive events, and correlates with performance in learning tasks. Importantly, whereas high-frequency brain activity reflects local domains of cortical processing, low-frequency brain rhythms are dynamically entrained across distributed brain regions by both external sensory input and internal cognitive events. CFC might thus serve as a mechanism to transfer information from large-scale brain networks operating at behavioral timescales to the fast, local cortical processing required for effective computation and synaptic modification, thus integrating functional systems across multiple spatiotemporal scales. Copyright 漏 2010 Elsevier Ltd. All rights reserved.

The relation of gamma-band synchrony to holistic perception in which concerns the effects of sensory processing, high level perceptual gestalt formation, motor planning and response is still controversial. To provide a more direct link to emergent perceptual states we have used holistic EEG/ERP paradigms where the moment of perceptual "discovery" of a global pattern was variable. Using a rapid visual presentation of short-lived Mooney objects we found an increase of gamma-band activity locked to perceptual events. Additional experiments using dynamic Mooney stimuli showed that gamma activity increases well before the report of an emergent holistic percept. To confirm these findings in a data driven manner we have further used a support vector machine classification approach to distinguish between perceptual vs. non perceptual states, based on time-frequency features. Sensitivity, specificity and accuracy were all above 95%. Modulations in the 30-75 Hz range were larger for perception states. Interestingly, phase synchrony was larger for perception states for high frequency bands. By focusing on global gestalt mechanisms instead of local processing we conclude that gamma-band activity and synchrony provide a signature of holistic perceptual states of variable onset, which are separable from sensory and motor processing.

Abstract Investigations into action monitoring have consistently detailed a frontocentral voltage deflection in the event-related potential (ERP) following the presentation of negatively valenced feedback, sometimes termed the feedback-related negativity (FRN). The FRN has been proposed to reflect a neural response to prediction errors during reinforcement learning, yet the single-trial relationship between neural activity and the quanta of expectation violation remains untested. Although ERP methods are not well suited to single-trial analyses, the FRN has been associated with theta band oscillatory perturbations in the medial prefrontal cortex. Mediofrontal theta oscillations have been previously associated with expectation violation and behavioral adaptation and are well suited to single-trial analysis. Here, we recorded EEG activity during a probabilistic reinforcement learning task and fit the performance data to an abstract computational model (Q-learning) for calculation of single-trial reward prediction errors. Single-trial theta oscillatory activities following feedback were investigated within the context of expectation (prediction error) and adaptation (subsequent reaction time change). Results indicate that interactive medial and lateral frontal theta activities reflect the degree of negative and positive reward prediction error in the service of behavioral adaptation. These different brain areas use prediction error calculations for different behavioral adaptations, with medial frontal theta reflecting the utilization of prediction errors for reaction time slowing (specifically following errors), but lateral frontal theta reflecting prediction errors leading to working memory-related reaction time speeding for the correct choice. Copyright 2009 Elsevier Inc. All rights reserved.

61Age affects brain rhythms in temporo-spatial attention and conflict resolution.61Posterior attention-related alpha activation declines with age.61Older adults engage motor-related structures through activation in the beta band.61Conflict resolution is slowed by over-engagement of alpha attentional resources.

Abstract Explaining the emergence of a coherent conscious percept and an intentional agent from the activity of distributed neurons is key to understanding how the brain produces higher cognitive processes. Gamma-band synchronization has been proposed to be a mechanism for the functional integration of neural populations that together form a transitory, large-scale, task- and/or percept-specific network. The operation of this mechanism in the context of attention orienting entails that cortical regions representing attended locations should show more gamma-band synchronization with other cortical areas than would those representing unattended locations. This increased synchronization should be apparent in the same time frame as that of the deployment of attention to a particular location. In order to observe this effect, we made electroencephalogram recordings while subjects attended to one side or the other of the visual field (which we confirmed by event-related potential analysis) and calculated phase-locking statistics between the signals recorded at relevant electrode pairs. We observed increased gamma-band phase synchronization between visual cortex contralateral to the attended location and other, widespread, cortical areas approximately 240-380 ms after the directional cue was presented, confirming the prediction of a large-scale gamma synchronous network oriented to the cued location.

Perception results from ongoing interactions between stimulus-driven visual processes and cognitive context. These reciprocal relations are emphasized when a visual stimulus is degraded, forcing the perceiver to fill the missing information in, based on internal representations. The neural mechanisms by which internal representations facilitate visual perception are still unclear. Here we investigated the role of EEG oscillations in the gamma band, thought to reflect the elaboration of internal visual representations, in the experience-based perception of visual scenes. Twelve subjects were trained with degraded images of natural scenes. EEG was recorded while they performed a detection task on trained and untrained degraded stimuli. Non-phase-locked gamma band responses in a large frequency spectrum (55 85 Hz) were observed around 200 ms post-stimulus onset at posterior sites, and were larger when subjects reported an accurate perception based on previous experience. These results suggest that mid-latency gamma oscillations in the visual cortex underlie the experience-based perception of visual scenes.

Abstract Connectivity measures are (typically bivariate) statistical measures that may be used to estimate interactions between brain regions from electrophysiological data. We review both formal and informal descriptions of a range of such measures, suitable for the analysis of human brain electrophysiological data, principally electro- and magnetoencephalography. Methods are described in the space-time, space-frequency, and space-time-frequency domains. Signal processing and information theoretic measures are considered, and linear and nonlinear methods are distinguished. A novel set of cross-time-frequency measures is introduced, including a cross-time-frequency phase synchronization measure. Copyright 2012 Elsevier B.V. All rights reserved.

78 Alpha oscillations indicate internally and externally oriented brain states. 78 Different parameters of alpha oscillatory activity predict visual perception. 78 A neuro-cognitive model is presented to explain the attentional blink.

78An algorithm for the correction of saccade-related transient potentials (COSTRAP). 78Artifact-controlled gamma band oscillations are of cortical origin. 78Induced gamma band responses are sensitive to object recognition.

The prefrontal cortex (PFC) provides the structural basis for numerous higher cognitive functions. However, it is still largely unknown which mechanisms provide the functional basis for flexible cognitive control of goal-directed behavior. Here, we review recent findings, which suggest that the functional architecture of cognition is profoundly rhythmic and propose that the PFC serves as a conductor to orchestrate task-relevant large-scale networks. We highlight several studies that demonstrated that oscillatory dynamics, such as phase resetting, cross-frequency coupling and entrainment, support PFC-dependent recruitment of task-relevant regions into coherent functional networks. Importantly, these findings support the notion that distinct spectral signatures reflect different cortical computations supporting effective multiplexing on different temporal channels along the same anatomical pathways.

Abstract The coupled interaction between slow-wave oscillations and sleep spindles during non-rapid-eye-movement (NREM) sleep has been proposed to support memory consolidation. However, little evidence in humans supports this theory. Moreover, whether such dynamic coupling is impaired as a consequence of brain aging in later life, contributing to cognitive and memory decline, is unknown. Combining electroencephalography (EEG), structural MRI, and sleep-dependent memory assessment, we addressed these questions in cognitively normal young and older adults. Directional cross-frequency coupling analyses demonstrated that the slow wave governs a precise temporal coordination of sleep spindles, the quality of which predicts overnight memory retention. Moreover, selective atrophy within the medial frontal cortex in older adults predicted a temporal dispersion of this slow wave-spindle coupling, impairing overnight memory consolidation and leading to forgetting. Prefrontal-dependent deficits in the spatiotemporal coordination of NREM sleep oscillations therefore represent one pathway explaining age-related memory decline.

Abstract The problem of controlling locomotion is an area in which neuroscience and robotics can fruitfully interact. In this article, I will review research carried out on locomotor central pattern generators (CPGs), i.e. neural circuits capable of producing coordinated patterns of high-dimensional rhythmic output signals while receiving only simple, low-dimensional, input signals. The review will first cover neurobiological observations concerning locomotor CPGs and their numerical modelling, with a special focus on vertebrates. It will then cover how CPG models implemented as neural networks or systems of coupled oscillators can be used in robotics for controlling the locomotion of articulated robots. The review also presents how robots can be used as scientific tools to obtain a better understanding of the functioning of biological CPGs. Finally, various methods for designing CPGs to control specific modes of locomotion will be briefly reviewed. In this process, I will discuss different types of CPG models, the pros and cons of using CPGs with robots, and the pros and cons of using robots as scientific tools. Open research topics both in biology and in robotics will also be discussed.

To survive in a complex world, it is important that unattended, but salient, input can still draw one's attention. In this article, we suggest that posterior alpha oscillations (8–13Hz) provide a mechanism for prioritizing and ordering unattended visual input according to ‘relevance’. Gamma oscillations (30–100Hz) that are phase-locked to the alpha oscillations keep competing unattended representations apart in time, thus creating a sequence of perceptual cycles. As inhibition gradually lowers within an alpha cycle, the ordered sequence of competing input is activated, producing a temporal phase code for saliency. The proposed mechanism is based on recent experiments indicating that the phase of alpha activity modulates perception and that alpha oscillations are produced by periodic pulses of inhibition.

Analysis of high-frequency (gamma-band) neural activity by means of non-invasive EEG is gaining increasing interest. However, we have recently shown that a saccade-related spike potential (SP) seriously confounds the analysis of EEG induced gamma-band responses (iGBR), as the SP eludes traditional EEG artifact rejection methods. Here we provide a comprehensive profile of the SP and evaluate methods for its detection and suppression, aiming to unveil true cerebral gamma-band activity. The SP appears consistently as a sharp biphasic deflection of about 2202ms starting at the saccade onset, with a frequency band of 6520–9002Hz. On the average, larger saccades elicit higher SP amplitudes. The SP amplitude gradually changes from the extra-ocular channels towards posterior sites with the steepest gradients around the eyes, indicating its ocular source. Although the amplitude and the sign of the SP depend on the choice of reference channel, the potential gradients remain the same and non-zero for all references. The scalp topography is modulated almost exclusively by the direction of saccades, with steeper gradients ipsilateral to the saccade target. We discuss how the above characteristics impede attempts to remove these SPs from the EEG by common temporal filtering, choice of different references, or rejection of contaminated trials. We examine the extent to which SPs can be reliably detected without an eye tracker, assess the degree to which scalp current density derivation attenuates the effect of the SP, and propose a tailored ICA procedure for minimizing the effect of the SP.

Alpha-band oscillations are the dominant oscillations in the human brain and recent evidence suggests that they have an inhibitory function. Nonetheless, there is little doubt that alpha-band oscillations also play an active role in information processing. In this article, I suggest that alpha-band oscillations have two roles (inhibition and timing) that are closely linked to two fundamental functions of attention (suppression and selection), which enable controlled knowledge access and semantic orientation (the ability to be consciously oriented in time, space, and context). As such, alpha-band oscillations reflect one of the most basic cognitive processes and can also be shown to play a key role in the coalescence of brain activity in different frequencies.

Abstract Visual cortical alpha oscillations are involved in attentional gating of incoming visual information. It has been shown that spatial and feature-based attentional selection result in increased alpha oscillations over the cortical regions representing sensory input originating from the unattended visual field and task-irrelevant visual features, respectively. However, whether attentional gating in the case of object based selection is also associated with alpha oscillations has not been investigated before. Here we measured anticipatory electroencephalography (EEG) alpha oscillations while participants were cued to attend to foveal face or word stimuli, the processing of which is known to have right and left hemispheric lateralization, respectively. The results revealed that in the case of simultaneously displayed, overlapping face and word stimuli, attending to the words led to increased power of parieto-occipital alpha oscillations over the right hemisphere as compared to when faces were attended. This object category-specific modulation of the hemispheric lateralization of anticipatory alpha oscillations was maintained during sustained attentional selection of sequentially presented face and word stimuli. These results imply that in the case of object-based attentional selection-similarly to spatial and feature-based attention-gating of visual information processing might involve visual cortical alpha oscillations.

Abstract <p>This article presents, for the first time, a practical method for the direct quantification of frequency-specific synchronization (i.e., transient phase-locking) between two neuroelectric signals. The motivation for its development is to be able to examine the role of neural synchronies as a putative mechanism for long-range neural integration during cognitive tasks. The method, called phase-locking statistics (PLS), measures the significance of the phase covariance between two signals with a reasonable time-resolution (<100 ms). Unlike the more traditional method of spectral coherence, PLS separates the phase and amplitude components and can be directly interpreted in the framework of neural integration. To validate synchrony values against background fluctuations, PLS uses surrogate data and thus makes no a priori assumptions on the nature of the experimental data. We also apply PLS to investigate intracortical recordings from an epileptic patient performing a visual discrimination task. We find large-scale synchronies in the gamma band (45 Hz), e.g., between hippocampus and frontal gyrus, and local synchronies, within a limbic region, a few cm apart. We argue that whereas long-scale effects do reflect cognitive processing, short-scale synchronies are likely to be due to volume conduction. We discuss ways to separate such conduction effects from true signal synchrony. Hum Brain Mapping 8:194鈥208, 1999. 漏 1999 Wiley-Liss, Inc.</p>

Abstract Wavelet analysis has attracted attention for its ability to analyze rapidly changing transient signals. Any application using the Fourier transform can be formulated using wavelets to provide more accurately localized temporal and frequency information. This paper gives an overview of wavelet analysis and describes a software toolbox created by HP Laboratories Japan to aid in the development of wavelet applications.

In our daily lives, we often make decisions that require the use of self-control, weighing trade-offs between various attributes: for example, selecting a food based on its health rather than its taste. Previous research suggests that re-weighting attributes may rely on selective attention, associated with decreased neural oscillations over posterior brain regions in the alpha (8-12 Hz) frequency range. Here, we utilized the high temporal resolution and whole-brain coverage of electroencephalography (EEG) to test this hypothesis in data collected from hungry human subjects exercising dietary self-control. Prior analysis of this data has found time-locked neural activity associated with each food鈥檚 perceived taste and health properties from approximately 400 to 650 ms after stimulus onset (Harris et al., 2013). We conducted time-frequency analyses to examine the role of alpha-band oscillations in this attribute weighting. Specifically, we predicted that there would be decreased alpha power in posterior electrodes beginning approximately 400 ms after stimulus onset for the presentation of healthy food relative to unhealthy food, reflecting shifts in selective attention. Consistent with this hypothesis, we found a significant decrease in alpha power for presentations of healthy relative to unhealthy foods. As predicted, this effect was most pronounced at posterior occipital and parietal electrodes and was significant from approximately 450 to 700 ms post-stimulus onset. Additionally, we found significant alpha-band decreases in right temporal electrodes during these times. These results extend previous attention research to multi-attribute choice, suggesting that the re-weighting of attributes can be measured neuro-computationally.

It has been long debated whether averaged electrical responses recorded from the scalp result from stimulus-evoked brain events or stimulus-induced changes in ongoing brain dynamics. In a human visual selective attention task, we show that nontarget event-related potentials were mainly generated by partial stimulus-induced phase resetting of multiple electroencephalographic processes. Independent component analysis applied to the single-trial data identified at least eight classes of contributing components, including those producing central and lateral posterior alpha, left and right mu, and frontal midline theta rhythms. Scalp topographies of these components were consistent with their generation in compact cortical domains.

Synchronized high-frequency gamma band oscillations (30-100 Hz) are thought to mediate the binding of single visual features into whole-object representations. For example, induced gamma band oscillations (iGBRs) have been recorded 280 ms after the onset of a coherent Kanizsa triangle, but not after an incoherent equivalent shape. However, several recent studies have provided evidence that the EEG-recorded iGBR may be a by-product of small saccadic eye movements (microsaccades). Considering these two previous findings, one would hypothesis that there should be more microsaccades following the onset of a coherent Kanizsa triangle. However, we found that microsaccade rebound rate was significantly higher after an incoherent triangle was presented. This result suggests that microsaccades are not a reliable indicator of perceptual binding, and, more importantly, implies that iGBR cannot be universally produced by ocular artefacts.

Abstract For researchers and clinical practitioners alike, evoked and event-related responses measured with MEG and EEG provide the means for studying human brain function and dysfunction. However, the generation mechanism of event-related responses remains unclear, hindering our ability to formulate viable theories of neural information processing. Event-related responses are assumed to be generated either (1) separately of ongoing, oscillatory brain activity or (2) through stimulus-induced reorganization of ongoing activity. Here, we approached this issue through examining single-trial auditory MEG data in humans. We demonstrate that phase coherence over trials observed with commonly used signal decomposition methods (e.g., wavelets) can result from both a phase-coherent state of ongoing oscillations and from the presence of a phase-coherent event-related response which is additive to ongoing oscillations. To avoid this problem, we introduce a method based on amplitude variance to establish the relationship between ongoing oscillations and event-related responses. We found that auditory stimuli do not give rise to phase reorganization of ongoing activity. Further, increases in spectral power accompany the emergence of event-related responses, and the relationship between spectral power and the amplitude of these responses can be accounted for by a linear summation of the event-related response and ongoing oscillation with a stochastically distributed phase. Thus, on the basis of our observations, auditory event-related responses are unique descriptors of neural information processing in humans, generated by processes separate from and additive to ongoing brain activity.

Neural mechanisms of object recognition seem to rely on activity of distributed neural assemblies coordinated by synchronous firing in the gamma-band range (>20 Hz). In the present electroencephalogram (EEG) study, we investigated induced gamma band activity during the naming of line drawings of upright objects and objects rotated in the image plane. Such plane-rotation paradigms elicit view-dependent processing, leading to delays in recognition of disoriented objects. Our behavioral results showed reaction time delays for rotated, as opposed to upright, images. These delays were accompanied by delays in the peak latency of induced gamma band responses (GBRs), in the absence of any effects on other measures of EEG activity. The latency of the induced GBRs has thus, for the first time, been selectively modulated by an experimental manipulation that delayed recognition. This finding indicates that induced GBRs have a genuine role as neural markers of late representational processes during object recognition. In concordance with the view that object recognition is achieved through dynamic learning processes, we propose that induced gamma band activity could be one of the possible cortical markers of such dynamic object coding.

We often fail to see something that at other times is readily detectable. Because the visual stimulus itself is unchanged, this variability in conscious awareness is likely related to changes in the brain. Here we show that the phase of EEG α rhythm measured over posterior brain regions can reliably predict both subsequent visual detection and stimulus-elicited cortical activation levels in a metacontrast masking paradigm. When a visual target presentation coincides with the trough of an α wave, cortical activation is suppressed as early as 100 ms after stimulus onset, and observers are less likely to detect the target. Thus, during one α cycle lasting 100 ms, the human brain goes through a rapid oscillation in excitability, which directly influences the probability that an environmental stimulus will reach conscious awareness. Moreover, ERPs to the appearance of a fixation cross before the target predict its detection, further suggesting that cortical excitability level may mediate target detection. A novel theory of cortical inhibition is proposed in which increased α power represents a “pulsed inhibition” of cortical activity that affects visual awareness.

This study measured the changes in the spectrum of the EEG (electroencephalogram) and in the event-related potentials (ERPs) as subjects detected an improbable target in a train of standard stimuli. The intent was to determine how these measurements are related, and to what extent the ERPs might represent phase-locked changes in EEG rhythms. The experimental manipulations were the stimulus modality (auditory or visual), the discriminability of the target, and the presence or absence of distraction. The ERPs showed sensory-evoked potentials that were specific to the modality and a target-evoked P300 wave that was later in the visual modality than in the auditory, and later and smaller when the discrimination was more difficult. The averaged EEG spectrograms showed that targets increased the frontal theta activity, decreased posterior and central alpha and beta activity, and decreased the central gamma activity. The scalp topography of the changes in the alpha and beta activity indicated a posterior desynchronization specific for the visual task and occurring with both targets and standards and a more widespread desynchronization for targets in either modality. Increased phase synchronization occurred during the event-related potentials, but modeling demonstrated that this can be seen when an evoked potential waveform is simply added to the background EEG. However, subtracting the spectrogram of the average ERP from the average spectrogram of the single trials indicated that phase-resetting of the background EEG rhythms can occur during the ERP. The idea that the ERPs and the EEG rhythms hare generators can explain these findings.

In a previous study of visual-spatial attention, Martinez et al. (2007) replicated the well-known finding that stimuli at attended locations elicit enlarged early components in the averaged event-related potential (ERP), which were localized to extrastriate visual cortex. The mechanisms that underlie these attention-related ERP modulations in the latency range of 80-200 ms, however, remain unclear. The main question is whether attention produces increased ERP amplitudes in time-domain averages by augmenting stimulus-triggered neural activity, or alternatively, by increasing the phase-locking of ongoing EEG oscillations to the attended stimuli. We compared these alternative mechanisms using Morlet wavelet decompositions of event-related EEG changes. By analyzing single-trial spectral amplitudes in the theta (4-8 Hz) and alpha (8-12 Hz) bands, which were the dominant frequencies of the early ERP components, it was found that stimuli at attended locations elicited enhanced neural responses in the theta band in the P1 (88-120 ms) and N1 (148-184 ms) latency ranges that were additive with the ongoing EEG. In the alpha band there was evidence for both increased additive neural activity and increased phase-synchronization of the EEG following attended stimuli, but systematic correlations between pre- and post-stimulus alpha activity were more consistent with an additive mechanism. These findings provide the strongest evidence to date in humans that short-latency neural activity elicited by stimuli within the spotlight of spatial attention is boosted or amplified at early stages of processing in extrastriate visual cortex.

Wavelet analysis, being a popular time-frequency analysis method has been applied in various fields to analyze a wide range of signals covering biological signals, vibration signals, acoustic and ultrasonic signals, to name a few. With the capability to provide both time and frequency domains information, wavelet analysis is mainly for time-frequency analysis of signals, signal compression, signal denoising, singularity analysis and features extraction. The main challenge in using wavelet transform is to select the most optimum mother wavelet for the given tasks, as different mother wavelet applied on to the same signal may produces different results. This paper reviews on the mother wavelet selection methods with particular emphasis on the quantitative approaches. A brief description of the proposed new technique to determine the optimum mother wavelet specifically for machinery faults diagnosis is also presented in this paper.

This chapter is devoted to reviewing some fundamental transforms and analysis procedures commonly used for both signal and data processing in fluid mechanics measurements. The chapter begins with a brief review of the Fourier transform and its digital counterpart the discrete Fourier transform. In particular its use for estimating power spectral density is discussed in detail. This is followed by an introduction of the correlation function and its relation to the Fourier transform. The Hilbert transform completes the introductory topics. The chapter then turns to a rigorous presentation of the proper orthogonal decomposition (POD) in the context of the approximation theory and as an application of singular value decomposition (SVD). The relationship between POD and SVD is discussed and POD is described in a statistical setting using an averaging operation for use with turbulent flows. The different POD approaches are briefly introduced, whereby the main differences between the classical POD and the snapshot POD are highlighted. This section closes with a presentation of the POD as a generalization of the classical Fourier analysis to inhomogeneous directions. The chapter continues with a discussion of conditional averages and stochastic estimation as a means of studying coherent structures in turbulent flows before moving in a final section to a comprehensive discussion of wavelets as a combination of data processing in time and frequency domain. After first introducing the continuous wavelet transform and orthogonal wavelet transform their application in experimental fluid mechanics is illustrated through numerous examples.

Abstract Periodic visual stimulation and analysis of the resulting steady-state visual evoked potentials were first introduced over 80 years ago as a means to study visual sensation and perception. From the first single-channel recording of responses to modulated light to the present use of sophisticated digital displays composed of complex visual stimuli and high-density recording arrays, steady-state methods have been applied in a broad range of scientific and applied settings.The purpose of this article is to describe the fundamental stimulation paradigms for steady-state visual evoked potentials and to illustrate these principles through research findings across a range of applications in vision science.

EEG signals recorded from scalp contain useful information about the activity of a large number of neurons. Signal processing is needed to extract this information from the EEG signal. Here we study the effects of configurations of Short Time Fourier Transform (STFT) to determine how the parameters of STFT affect spectral estimations of the mean and relative power in beta and gamma frequency bands of the EEG signal. A statistic analysis was performed showing the effects of several window types and window lengths. The estimation of power in a specific frequency band is affected by the configuration of the STFT.

If long-range phase synchrony really is a hallmark of consciousness, it should be present most of the time the subject is conscious. Our results confirm this prediction, and suggest that consciousness may involve not only gamma frequencies, but the whole range from theta to epsilon. The mechanism of synchrony establishment at the scalp as shown by the present method is relatively slow and thus more likely to involve chemical synapses than gap junctions, electric fields or quantum non-locality.

Un appareil a été mis au point pour étudier la réponse occipitale en phase à une fréquence de stimulation évoquée par une lamière modulée. L'intensité et la phase sont mesurées sur toute une gamme de fréquences à modulation sinuso07dales, pour des stimuli stables. Une réponse transitoire et une réponse stable moyenne ont été trouvées et principalement identifiées à la région rétinienne centrale. La réponse stable moyenne est indépendante de l'activité alpha. La fréquence alpha est indépendante du stimulus. La réponse stable atteint un maximum, et montre un décalage de phase rapide, au voisinage de 10 c/sec. A des fréquences plus élevées de stimulation modulée, la durée moyenne du décalage de phase de la réponse est proportionnelle à la fréquence du stimulus. Une estimation est faite de la durée de propagation de la composante synchrone. L'atténuation à haute fréquence est moindre que celle obtenue pour le flicker subjectif, mesurée par De Lange. La nature de la réponse en phase et des modéles théoriques sont discutés.

Abstract The integration of different visual attributes into the percept of a single global shape is a central aspect of object processing. In hierarchically organized stimuli with local and global levels, the attentional focus largely determines which level is processed. Here we tested the hypothesis that object processing during attention to the global aspect of the stimulus is characterized by an increased neural coupling between visual areas reflecting the integration of local features. In the present experiment, we used global letters that were constructed by smaller local letters, and a cue signaled which spatial level should be identified. On the local level, only 1 relevant letter was presented laterally in 1 visual hemifield. In contrast, the global letter extended into both hemifields, and the integration of information from both hemispheres was necessary to identify the global stimulus. Therefore, we expected an increased functional coupling between hemispheres during global processing. This hypothesis was investigated using electroencephalographic recordings and an analysis of phase locking and coherence. The results show that stimulus-locked neural coupling within the gamma band (30-40 Hz) across hemispheres in visual cortex increased for global processing after stimulus presentation and could therefore reflect the integration of local visual information.

react-text: 433 The electrophysiological study of cochlear microphonics (CM), whole nerve action potential (AP) and endocochlear potential (EP) were examined. (1) With the extension of the exposure time of 500 Hz tone, a decrease of CM maximum output voltage in test frequency from 2 to 6 kHz was observed. (2) N1 potential of AP decreased very significantly by 500 Hz tone exposure. (3) A very pronounced... /react-text react-text: 434 /react-text [Show full abstract]

Abstract Event-related potentials and ongoing oscillatory electroencephalogram (EEG) activity were measured while subjects performed a cued visual spatial attention task. They were instructed to shift their attention to either the left or right visual hemifield according to a cue, which could be valid or invalid. Thereafter, a peripheral target had to be evaluated. At posterior parietal brain areas early components of the event-related potential (P1 and N1) were higher when the cue had been valid compared with invalid. An anticipatory attention effect was found in EEG alpha magnitude at parieto-occipital electrode sites. Starting 200ms before target onset alpha amplitudes were significantly stronger suppressed at sites contralateral to the attended visual hemifield than ipsilateral to it. In addition, phase coupling between prefrontal and posterior parietal electrode sites was calculated. It was found that prefrontal cortex shows stronger phase coupling with posterior sites that are contralateral to the attended hemifield than ipsilateral sites. The results suggest that a shift of attention selectively modulates excitability of the contralateral posterior parietal cortex and that this posterior modulation of alpha activity is controlled by prefrontal regions.

This paper describes a discrete-time wavelet transform for which the Q-factor is easily specified. Hence, the transform can be tuned according to the oscillatory behavior of the signal to which it is applied. The transform is based on a real-valued scaling factor (dilation-factor) and is implemented using a perfect reconstruction over-sampled filter bank with real-valued sampling factors. Two forms of the transform are presented. The first form is defined for discrete-time signals defined on all of Z. The second form is defined for discrete-time signals of finite-length and can be implemented efficiently with FFTs. The transform is parameterized by its Q-factor and its oversampling rate (redundancy), with modest oversampling rates (e.g., three to four times overcomplete) being sufficient for the analysis/synthesis functions to be well localized.

An electroencephalogram is a recording of brains spontaneous electrical activity. This is controlled by billions of neurons. These neurons continually send messages to each other which can be picked up as electrical impulses from the scalp. The process of picking up and recording the impulses is known as EEG. An EEG can be divided into four basic frequency bands namely delta, theta, alpha and beta. This paper shows changes in the power of alpha frequency band on performing attention tasks. It is observed that mean alpha power decreased while performing attention task as compared to mean alpha power in relaxed state in the frontal and occipital region of the brain. No statistically significant changes in alpha power are found in prefrontal region of the brain during attention tasks.

Neuronal oscillations are ubiquitous in the brain and contribute to perception and attention. However, most associated evidence derives from post hoc correlations between brain dynamics and behavior. Although a few recent studies demonstrate rhythms in behavior, it remains largely unknown whether behavioral performances manifest spectrotemporal dynamics in a neurophysiologically relevant manner (e. g., the temporal modulation of ongoing oscillations, the cross-frequency coupling). To investigate the issue, we examined fine spectrotemporal dynamics of behavioral time courses in a large sample of human participants (n=49), by taking a high time-resolved psychophysical measurement in a precuing attentional task. We observed compelling dynamic oscillatory patterns directly in behavior. First, typical attentional effects are demonstrated in low-pass (0-2 Hz) filtered time courses of behavioral responses. Second, an uninformative peripheral cue elicits recurring alpha-band (8-20 Hz) pulses in behavioral performances, and the elicited alpha pulses for cued and uncued conditions are in a temporally alternating relationship. Finally, ongoing alpha-band power is phase locked to ongoing theta-bands (3-5 Hz) in behavioral time courses. Our findings constitute manifestation of oscillations at physiologically relevant rhythms and power-phase locking, as widely observed in neurophysiological recordings, in behavior. The findings suggest that behavioral performance actually consists of rich dynamic information and may reflect underlying neuronal oscillatory substrates. Our data also speak to a neural mechanism for item attention based on successive cycles (theta) of a sequential attentional sampling (alpha) process.

Abstract Oscillatory synchrony in the gamma (30-120 Hz) range has initially been related both theoretically and experimentally to visual grouping. Its functional role in human visual cognition turns out to be much broader, especially when attention, memory or awareness are concerned. Induced gamma oscillations are thus not related to a single cognitive function, and are probably better understood in terms of a population mechanism taking advantage of the neuron's fine temporal tuning: the 10-30 ms time precision imposed by gamma-band rhythms could favor the selective transmission of synchronized information (attention) and foster synaptic plasticity (memory). Besides, gamma oscillatory synchrony also seems related to the emergence of visual awareness. The recent discovery that gamma oscillations could appear simultaneously in distinct areas at distinct frequencies and with different functional correlates further suggests the existence of a flexible multiplexing schema, integrating frequency bands within the gamma range but also at lower frequency bands. Understanding how and when oscillations at different frequencies interact has become a major challenge for the years to come.

Abstract We experience objects as whole, complete entities irrespective of whether they are perceived by our sensory systems or are recalled from memory. However, it is also known that many of the properties of objects are encoded and processed in different areas of the brain. How then, do coherent representations emerge? One theory suggests that rhythmic synchronization of neural discharges in the gamma band (around 40 Hz) may provide the necessary spatial and temporal links that bind together the processing in different brain areas to build a coherent percept. In this article we propose that this mechanism could also be used more generally for the construction of object representations that are driven by sensory input or internal, top-down processes. The review will focus on the literature on gamma oscillatory activities in humans and will describe the different types of gamma responses and how to analyze them. Converging evidence that suggests that one particular type of gamma activity (induced gamma activity) is observed during the construction of an object representation will be discussed.

Phase-amplitude cross-frequency coupling (CFC) between theta (4-12 Hz) and gamma (30-100 Hz) oscillations occurs frequently in the hippocampus. However, it still remains unclear whether theta-gamma coupling has any functional significance. To address this issue, we studied CFC in local field potential oscillations recorded from the CA3 region of the dorsal hippocampus of rats as they learned to associate items with their spatial context. During the course of learning, the amplitude of the low gamma subband (30-60 Hz) became more strongly modulated by theta phase in CA3, and higher levels of theta-gamma modulation were maintained throughout overtraining sessions. Furthermore, the strength of theta-gamma coupling was directly correlated with the increase in performance accuracy during learning sessions. These findings suggest a role for hippocampal theta-gamma coupling in memory recall.

Recent progress in cognitive neuroscience suggests that alpha activity may reflect selective cortical inhibition involved in signal amplification, rather than neural idling. Unfortunately, these theoretical advances remain largely ignored in affective neuroscience. To address this limitation the present paper proposes a novel research avenue aimed at using alpha to elucidate cortical inhibitory mechanisms involved in affective processes. The proposal is illustrated by developing inhibitory accounts of affective attention and affective tuning phenomena. The emergent predictions were tested using event-related perturbations from 73 students evaluating affective and nonaffective aspects of five types of emotional images. The results revealed that upper alpha power was increased by affective content in general and aversive stimuli in particular from 350 ms at posterior and from 575 ms at central sites. The evaluation task interacted with affective content only at a liberal statistical significance level in late posterior alpha. These results are generally in line with the proposed inhibitory accounts of affective attention and tuning, although the evidence is preliminary rather than conclusive. As confirmation of functional origins of alpha in affect remains beyond the scope of a single study, this paper aims to inspire further extrapolation of the inhibitory account of alpha within affective neuroscience.

Abstract Brain activity can be used as a control signal for brain-machine interfaces (BMIs). A powerful and widely acknowledged BMI approach, so far only applied in invasive recording techniques, uses neuronal signals related to limb movements for equivalent, multidimensional control of an external effector. Here, we investigated whether this approach is also applicable for noninvasive recording techniques. To this end, we recorded whole-head MEG during center-out movements with the hand and found significant power modulation of MEG activity between rest and movement in three frequency bands: an increase for < or = 7 Hz (low-frequency band) and 62-87 Hz (high-gamma band) and a decrease for 10-30 Hz (beta band) during movement. Movement directions could be inferred on a single-trial basis from the low-pass filtered MEG activity as well as from power modulations in the low-frequency band, but not from the beta and high-gamma bands. Using sensors above the motor area, we obtained a surprisingly high decoding accuracy of 67% on average across subjects. Decoding accuracy started to rise significantly above chance level before movement onset. Based on simultaneous MEG and EEG recordings, we show that the inference of movement direction works equally well for both recording techniques. In summary, our results show that neuronal activity associated with different movements of the same effector can be distinguished by means of noninvasive recordings and might, thus, be used to drive a noninvasive BMI.

Abstract The induced gamma-band EEG response (iGBR) recorded on the scalp is widely assumed to reflect synchronous neural oscillation associated with object representation, attention, memory, and consciousness. The most commonly reported EEG iGBR is a broadband transient increase in power at the gamma range approximately 200-300 ms following stimulus onset. A conspicuous feature of this iGBR is the trial-to-trial poststimulus latency variability, which has been insufficiently addressed. Here, we show, using single-trial analysis of concomitant EEG and eye tracking, that this iGBR is tightly time locked to the onset of involuntary miniature eye movements and reflects a saccadic "spike potential." The time course of the iGBR is related to an increase in the rate of saccades following a period of poststimulus saccadic inhibition. Thus, whereas neuronal gamma-band oscillations were shown conclusively with other methods, the broadband transient iGBR recorded by scalp EEG reflects properties of miniature saccade dynamics rather than neuronal oscillations.