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Abstract: A single brief visual stimulus accompanied by two brief tactile stimuli is frequently perceived incorrectly as two flashes, a phenomenon called double-flash illusion (DFI). We investigated whether the DFI is accompanied by changes in rhythmic neuronal activity, using magnetoencephalography in human subjects. Twenty-two subjects received visuo-tactile stimulation and reported the number of perceived visual stimuli. We sorted trials with identical physical stimulation according to the reported subjective percept and assessed differences in spectral power in somatosensory and occipital sensors. In DFI trials, occipital sensors displayed a contralateral enhancement of gamma-band (80–140Hz) activity in response to stimulation. In somatosensory sensors, the DFI was associated with an increase of spectral power for low frequencies (5–17.5Hz) around stimulation and a decrease of spectral power in the 22.5–30Hz range between 450 and 750ms post-stimulation. In summary, several components of rhythmic activity predicted variable subjective experience for constant physical stimulation. Notably, the enhanced occipital gamma-band activity during DFI was similar in time and frequency extent to the somatosensory gamma-band response to tactile stimulation. We speculate that the DFI might therefore occur when the somatosensory gamma-response is transmitted to visual cortex. This transmission might be supported by the observed modulations in low-frequency activity. [ABSTRACT FROM AUTHOR]

Abstract: The current state of empirical investigations refers to consciousness as an all-or-none phenomenon. However, a recent theoretical account opens up this perspective by proposing a partial level (between nil and full) of conscious perception. In the well-studied case of single-word reading, short-lived exposure can trigger incomplete word-form recognition wherein letters fall short of forming a whole word in one's conscious perception thereby hindering word-meaning access and report. Hence, the processing from incomplete to complete word-form recognition straightforwardly mirrors a transition from partial to full-blown consciousness. We therefore hypothesized that this putative functional bottleneck to consciousness (i.e. the perceptual boundary between partial and full conscious perception) would emerge at a major key hub region for word-form recognition during reading, namely the left occipito-temporal junction. We applied a real-time staircase procedure and titrated subjective reports at the threshold between partial (letters) and full (whole word) conscious perception. This experimental approach allowed us to collect trials with identical physical stimulation, yet reflecting distinct perceptual experience levels. Oscillatory brain activity was monitored with magnetoencephalography and revealed that the transition from partial-to-full word-form perception was accompanied by alpha-band (7–11Hz) power suppression in the posterior left occipito-temporal cortex. This modulation of rhythmic activity extended anteriorly towards the visual word form area (VWFA), a region whose selectivity for word-forms in perception is highly debated. The current findings provide electrophysiological evidence for a functional bottleneck to consciousness thereby empirically instantiating a recently proposed partial perspective on consciousness. Moreover, the findings provide an entirely new outlook on the functioning of the VWFA as a late bottleneck to full-blown conscious word-form perception. [Copyright &y& Elsevier]

Abstract: Groups of activated neurons typically synchronize in the gamma-frequency band (30-100Hz), and gamma-band synchronization has been implicated in numerous cognitive functions. Those functions are ultimately expressed as behavior and therefore, functional gamma-band synchronization should be directly related to behavior. We recorded the magnetoencephalogram in human subjects and used a visual stimulus to induce occipital gamma-band activity. We found that the strength of this gamma-band activity at a given moment predicted the speed with which the subject was able to report a change in the stimulus. This predictive effect was restricted in time, frequency and space: It started only around 200ms before the behaviorally relevant stimulus change, was present only between 50 and 80Hz, and was significant only in bilateral middle occipital gyrus, while the peak of overall visually induced gamma-band activity was found in the calcarine sulcus. These results suggest that visually induced gamma-band activity is functionally relevant for the efficient transmission of stimulus change information to brain regions issuing the corresponding motor response. [Copyright &y& Elsevier]

Abstract: PET and fMRI experiments have previously shown that several brain regions in the frontal and parietal lobe are involved in working memory maintenance. MEG and EEG experiments have shown parametric increases with load for oscillatory activity in posterior alpha and frontal theta power. In the current study we investigated whether the areas found with fMRI can be associated with these alpha and theta effects by measuring simultaneous EEG and fMRI during a modified Sternberg task This allowed us to correlate EEG at the single trial level with the fMRI BOLD signal by forming a regressor based on single trial alpha and theta power estimates. We observed a right posterior, parametric alpha power increase, which was functionally related to decreases in BOLD in the primary visual cortex and in the posterior part of the right middle temporal gyrus. We relate this finding to the inhibition of neuronal activity that may interfere with WM maintenance. An observed parametric increase in frontal theta power was correlated to a decrease in BOLD in regions that together form the default mode network. We did not observe correlations between oscillatory EEG phenomena and BOLD in the traditional WM areas. In conclusion, the study shows that simultaneous EEG–fMRI recordings can be successfully used to identify the emergence of functional networks in the brain during the execution of a cognitive task. [Copyright &y& Elsevier]

Abstract: Neuronal gamma-band (30–100 Hz) synchronization subserves fundamental functions in neuronal processing. However, different experimental approaches differ widely in their success in finding gamma-band activity. We aimed at linking animal and human studies of gamma-band activity and at preparing optimized methods for an in-depth investigation of the mechanisms and functions of gamma-band activity and gamma-band coherence in humans. In the first step described here, we maximized the signal-to-noise ratio with which we can observe visually induced gamma-band activity in human magnetoencephalographic recordings. We used a stimulus and task design that evoked strong gamma-band activity in animals and combined it with multi-taper methods for spectral analysis and adaptive spatial filtering for source analysis. With this approach, we found human visual gamma-band activity very reliably across subjects and across multiple recording sessions of a given subject. While increases in gamma-band activity are typically accompanied by decreases in alpha- and beta-band activity, the gamma-band enhancement was often the spectral component with the highest signal-to-noise ratio. Furthermore, some subjects demonstrated two clearly separate visually induced gamma bands, one around 40 Hz and another between 70 and 80 Hz. Gamma-band activity was sustained for the entire stimulation period, which was up to 3 s. The sources of gamma-band activity were in the calcarine sulcus in all subjects. The results localize human visual gamma-band activity in frequency, time and space and the described methods allow its further investigation with great sensitivity. [Copyright &y& Elsevier]

Learning to associate written letters with speech sounds is crucial for the initial phase of acquiring reading skills. However, little is known about the cortical reorganization for supporting letter-speech sound learning, particularly the brain dynamics during the learning of grapheme-phoneme associations. In the present study, we trained 30 Finnish participants (mean age: 24.33 years, SD: 3.50 years) to associate novel foreign letters with familiar Finnish speech sounds on two consecutive days (first day ​~ ​50 ​min; second day ​~ ​25 ​min), while neural activity was measured using magnetoencephalography (MEG). Two sets of audiovisual stimuli were used for the training in which the grapheme-phoneme association in one set (Learnable) could be learned based on the different learning cues provided, but not in the other set (Control). The learning progress was tracked at a trial-by-trial basis and used to segment different learning stages for the MEG source analysis. The learning-related changes were examined by comparing the brain responses to Learnable and Control uni/multi-sensory stimuli, as well as the brain responses to learning cues at different learning stages over the two days. We found dynamic changes in brain responses related to multi-sensory processing when grapheme-phoneme associations were learned. Further, changes were observed in the brain responses to the novel letters during the learning process. We also found that some of these learning effects were observed only after memory consolidation the following day. Overall, the learning process modulated the activity in a large network of brain regions, including the superior temporal cortex and the dorsal (parietal) pathway. Most interestingly, middle- and inferior-temporal regions were engaged during multi-sensory memory encoding after the cross-modal relationship was extracted from the learning cues. Our findings highlight the brain dynamics and plasticity related to the learning of letter-speech sound associations and provide a more refined model of grapheme-phoneme learning in reading acquisition. • Brain activity during grapheme-phoneme association learning measured in MEG. • Learning progress tracked at trial-by-trial basis to split different learning stages. • Dynamic changes observed in brain responses of cross-modal association learning. • Middle and inferior temporal regions engaged in multisensory memory encoding. [ABSTRACT FROM AUTHOR]

It has been demonstrated that alpha activity is lateralized when attention is directed to the left or right visual hemifield. We investigated whether real-time neurofeedback training of the alpha lateralization enhances participants' ability to modulate posterior alpha lateralization and causes subsequent short-term changes in visual detection performance. The experiment consisted of three phases: (i) pre-training assessment, (ii) neurofeedback phase and (iii) post-training assessment. In the pre- and post-training phases we measured the threshold to covertly detect a cued faint Gabor stimulus presented in the left or right hemifield. During magnetoencephalography (MEG) neurofeedback, two face stimuli superimposed with noise were presented bilaterally. Participants were cued to attend to one of the hemifields. The transparency of the superimposed noise and thus the visibility of the stimuli were varied according to the momentary degree of hemispheric alpha lateralization. In a double-blind procedure half of the participants were provided with sham feedback. We found that hemispheric alpha lateralization increased with the neurofeedback training; this was mainly driven by an ipsilateral alpha increase. Surprisingly, comparing pre- to post-training, detection performance decreased for a Gabor stimulus presented in the hemifield that was un-attended during neurofeedback. This effect was not observed in the sham group. Thus, neurofeedback training alters alpha lateralization, which in turn decreases performances in the untrained hemifield. Our findings suggest that alpha oscillations play a causal role for the allocation of attention. Furthermore, our neurofeedback protocol serves to reduce the detection of unattended visual information and could therefore be of potential use for training to reduce distractibility in attention deficit patients, but also highlights that neurofeedback paradigms can have negative impact on behavioral performance and should be applied with caution. [ABSTRACT FROM AUTHOR]

Abstract: Magnetoencephalography (MEG) is measured above the head, which makes it sensitive to variations of the head position with respect to the sensors. Head movements blur the topography of the neuronal sources of the MEG signal, increase localization errors, and reduce statistical sensitivity. Here we describe two novel and readily applicable methods that compensate for the detrimental effects of head motion on the statistical sensitivity of MEG experiments. First, we introduce an online procedure that continuously monitors head position. Second, we describe an offline analysis method that takes into account the head position time-series. We quantify the performance of these methods in the context of three different experimental settings, involving somatosensory, visual and auditory stimuli, assessing both individual and group-level statistics. The online head localization procedure allowed for optimal repositioning of the subjects over multiple sessions, resulting in a 28% reduction of the variance in dipole position and an improvement of up to 15% in statistical sensitivity. Offline incorporation of the head position time-series into the general linear model resulted in improvements of group-level statistical sensitivity between 15% and 29%. These tools can substantially reduce the influence of head movement within and between sessions, increasing the sensitivity of many cognitive neuroscience experiments. [Copyright &y& Elsevier]

Abstract: Magnetoencephalographic (MEG) recordings are a rich source of information about the neural dynamics underlying cognitive processes in the brain, with excellent temporal and good spatial resolution. In recent years there have been considerable advances in MEG hardware developments and methods. Sophisticated analysis techniques are now routinely applied and continuously improved, leading to fascinating insights into the intricate dynamics of neural processes. However, the rapidly increasing level of complexity of the different steps in a MEG study make it difficult for novices, and sometimes even for experts, to stay aware of possible limitations and caveats. Furthermore, the complexity of MEG data acquisition and data analysis requires special attention when describing MEG studies in publications, in order to facilitate interpretation and reproduction of the results. This manuscript aims at making recommendations for a number of important data acquisition and data analysis steps and suggests details that should be specified in manuscripts reporting MEG studies. These recommendations will hopefully serve as guidelines that help to strengthen the position of the MEG research community within the field of neuroscience, and may foster discussion in order to further enhance the quality and impact of MEG research. [Copyright &y& Elsevier]

Abstract: Insight into how brain structures interact is critical for understanding the principles of functional brain architectures and may lead to better diagnosis and therapy for neuropsychiatric disorders. We recorded, simultaneously, magnetoencephalographic (MEG) signals and subcortical local field potentials (LFP) in a Parkinson''s disease (PD) patient with bilateral deep brain stimulation (DBS) electrodes in the subthalamic nucleus (STN). These recordings offer a unique opportunity to characterize interactions between the subcortical structures and the neocortex. However, high-amplitude artefacts appeared in the MEG. These artefacts originated from the percutaneous extension wire, rather than from the actual DBS electrode and were locked to the heart beat. In this work, we show that MEG beamforming is capable of suppressing these artefacts and quantify the optimal regularization required. We demonstrate how beamforming makes it possible to localize cortical regions whose activity is coherent with the STN-LFP, extract artefact-free virtual electrode time-series from regions of interest and localize cortical areas exhibiting specific task-related power changes. This furnishes results that are consistent with previously reported results using artefact-free MEG data. Our findings demonstrate that physiologically meaningful information can be extracted from heavily contaminated MEG signals and pave the way for further analysis of combined MEG-LFP recordings in DBS patients. [Copyright &y& Elsevier]

The Human Connectome Project (HCP) was launched in 2010 as an ambitious effort to accelerate advances in human neuroimaging, particularly for measures of brain connectivity; apply these advances to study a large number of healthy young adults; and freely share the data and tools with the scientific community. NIH awarded grants to two consortia; this retrospective focuses on the "WU-Minn-Ox" HCP consortium centered at Washington University, the University of Minnesota, and University of Oxford. In just over 6 years, the WU-Minn-Ox consortium succeeded in its core objectives by: 1) improving MR scanner hardware, pulse sequence design, and image reconstruction methods, 2) acquiring and analyzing multimodal MRI and MEG data of unprecedented quality together with behavioral measures from more than 1100 HCP participants, and 3) freely sharing the data (via the ConnectomeDB database) and associated analysis and visualization tools. To date, more than 27 Petabytes of data have been shared, and 1538 papers acknowledging HCP data use have been published. The "HCP-style" neuroimaging paradigm has emerged as a set of best-practice strategies for optimizing data acquisition and analysis. This article reviews the history of the HCP, including comments on key events and decisions associated with major project components. We discuss several scientific advances using HCP data, including improved cortical parcellations, analyses of connectivity based on functional and diffusion MRI, and analyses of brain-behavior relationships. We also touch upon our efforts to develop and share a variety of associated data processing and analysis tools along with detailed documentation, tutorials, and an educational course to train the next generation of neuroimagers. We conclude with a look forward at opportunities and challenges facing the human neuroimaging field from the perspective of the HCP consortium. [ABSTRACT FROM AUTHOR]