1,721,064 research outputs found
The role of local and large-scale neuronal synchronization in human cognition
No full textHuman cognitive functions are subjectively coherent even though the underlying neuronal processing is achieved in many cortical regions in parallel. A number of animal electrophysiological studies have shown that neuronal synchronization may be a mechanism for the integration of such anatomically distributed neuronal processing as well as for the regulation of neuronal communication within these distributed networks. However, less is known about the functional and behavioral significance of the synchronization of neuronal oscillations in human brains. In recent years, several advancements have been made in source localization of the locally and large-scale synchronized networks by using noninvasive human magneto- and electroencephalography (EEG and MEG). These data have revealed the first glimpses into the structures of cortical networks underlying perceptual, attentional, and working memory functions
Measuring large-scale synchronization with human MEG and EEG: challenges and solutions
No full textNo abstract available
Relationship of fast- and slow-timescale neuronal dynamics in human MEG and SEEG
No full textA growing body of evidence suggests that the neuronal dynamics are poised at criticality. Neuronal avalanches and long-range temporal correlations (LRTCs) are hallmarks of such critical dynamics in neuronal activity and occur at fast (subsecond) and slow (seconds to hours) timescales, respectively. The critical dynamics at different timescales can be characterized by their power-law scaling exponents. However, insight into the avalanche dynamics and LRTCs in the human brain has been largely obtained with sensor-level MEG and EEG recordings, which yield only limited anatomical insight and results confounded by signal mixing. We investigated here the relationship between the human neuronal dynamics at fast and slow timescales using both source-reconstructed MEG and intracranial stereotactical electroencephalography (SEEG). Both MEG and SEEG revealed avalanche dynamics that were characterized parameter-dependently by power-law or truncated-power-law size distributions. Both methods also revealed robust LRTCs throughout the neocortex with distinct scaling exponents in different functional brain systems and frequency bands. The exponents of power-law regimen neuronal avalanches and LRTCs were strongly correlated across subjects. Qualitatively similar power-law correlations were also observed in surrogate data without spatial correlations but with scaling exponents distinct from those of original data. Furthermore, we found that LRTCs in the autonomous nervous system, as indexed by heart-rate variability, were correlated in a complex manner with cortical neuronal avalanches and LRTCs in MEG but not SEEG. These scalp and intracranial data hence show that power-law scaling behavior is a pervasive but neuroanatomically inhomogeneous property of neuronal dynamics in central and autonomous nervous systems
Phase and amplitude correlations in resting-state activity in human stereotactical EEG recordings
No full textInter-areal interactions of neuronal oscillations may be a key mechanism in the coordination of anatomically distributed neuronal processing. In humans, invasive stereo-electroencephalography (SEEG) is emerging as a reference method for electrophysiological recordings because of its excellent spatial and temporal resolution. It could thus be also considered an optimal method for mapping neuronal inter-areal interactions. However, the common bipolar (BP) referencing of SEEG data may both confuse signals from distinct sources and suppress true neuronal interactions whereas the alternative monopolar (MP) reference yields data contaminated by volume conduction. We advance here a novel referencing scheme for SEEG data where electrodes in grey matter are referenced to closest white-matter (CW) electrodes. Using a 22 subject cohort and these three referencing schemes, we observed that both inter-areal phase and amplitude correlations decayed as function of distance and frequency but remained significant and stable across distances up to 10 cm. Furthermore, we found that deep and superficial cortical laminae exhibit distinct spectral profiles of oscillation power as well as distinct patterns of inter-areal phase and amplitude interactions. These effects were qualitatively similar in MP and CW but distorted with BP referencing. Importantly CW was not influenced by the apparent large-scale volume conduction inherent to MP. We thus demonstrate here that with CW referencing, the superior anatomical accuracy of SEEG can be leveraged to yield accurate quantification and qualitatively novel insight into phase and amplitude interactions in human brain activity
Modular co-organization of functional connectivity and scale-free dynamics in the human brain.
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Thalamo-cortical interactions and synchronous oscillations in MEG data
No full textThe thalamus has received a renewed interest in systems neuroscience because emerging evidence indicates that the thalamus may modulate cortical responses according to behavioral demands. Moreover, there is evidence to suggest that in addition to normal brain functioning, thalamic–cortical (TC) interactions are critically implicated in neuropsychiatric disorders, such as schizophrenia. In this chapter, we will discuss the possibility to examine TC interactions using magnetoencephalography (MEG), a technique that is commonly considered as too unreliable to monitor activity generated by thalamic sources. Here, we argue that if certain requirements are met, MEG can be employed to investigate TC interactions by combining advanced source reconstruction techniques and novel connectivity measures. Specifically, we summarize evidence from MEG experiments that examined alpha–gamma coupling in TC networks during resting-state recordings as well as data from a study that tested the effects of ketamine on neural oscillations in healthy volunteers. We will discuss the implication of these findings for the understanding of normal and abnormal brain functioning as well as further steps to validate and improve MEG as a noninvasive technique to probe interactions in TC circuits
Multimodal Oscillation-based Connectivity Theory
No full textSystems-level neuronal mechanisms that coordinate the temporally, anatomically, and functionally distributed neuronal activity into coherent cognitive operations in the human brain have remained poorly understood. In humans, neuronal oscillations and synchronization can be recorded non-invasively with electro- and magnetoencephalography (EEG and MEG) that have excellent temporal resolution and an adequate spatial resolution when combined with source-reconstruction methods. In this book, leading authors in the field describe how recent methodological advances have paved the way to several major breakthroughs in the observations of large-scale synchrony from human non-invasive MEG data.
This volume also presents the caveats influencing analyses of synchronization. These include the non-homogeneous sensitivity of MEG to superficial cortical sources, and, most importantly, the multitude of consequences of linear mixing. Linear mixing is an immense confounder in the sensor-level analyses of synchronization, but is also present at the source level. Approaches that can be used to avoid or compensate for these issues are then discussed.
Thereafter, several authors take up a number of the functional roles that large-scale synchronization has in cognition. The authors assess how the spatio–temporal and –spectral organization and strength of both local and large-scale synchronized networks are associated with conscious sensory perception, visual working memory functions, and attention. These chapters summarize several lines of research showing how the strength of local and inter-areal oscillations in both cortical and subcortical brain structures is correlated with cognitive functions. Together these data suggest that synchronized neuronal oscillations may be a systems-level neuronal mechanism underlying the coordination of distributed processing in human cognition. In line with this argument, other authors go on to describe how oscillations and synchronization are altered in clinical populations, complementing the data presented on healthy subjects.
Importantly, this book includes chapters from authors using many different approaches to the analyses of neuronal oscillations, ranging from local oscillatory activities to the usage of graph theoretical tools in the analyses of synchronization. In this way the present volume provides a comprehensive view on the analyses and functional significance of neuronal oscillations in humans. This book is aimed at doctoral and post-doctoral students as well as research scientists in the fields of cognitive neuroscience, psychology, medicine, and neurosciences
Multimodal Oscillation-based Connectivity Theory
No full textSystems-level neuronal mechanisms that coordinate the temporally, anatomically, and functionally distributed neuronal activity into coherent cognitive operations in the human brain have remained poorly understood. In humans, neuronal oscillations and synchronization can be recorded non-invasively with electro- and magnetoencephalography (EEG and MEG) that have excellent temporal resolution and an adequate spatial resolution when combined with source-reconstruction methods. In this book, leading authors in the field describe how recent methodological advances have paved the way to several major breakthroughs in the observations of large-scale synchrony from human non-invasive MEG data.
This volume also presents the caveats influencing analyses of synchronization. These include the non-homogeneous sensitivity of MEG to superficial cortical sources, and, most importantly, the multitude of consequences of linear mixing. Linear mixing is an immense confounder in the sensor-level analyses of synchronization, but is also present at the source level. Approaches that can be used to avoid or compensate for these issues are then discussed.
Thereafter, several authors take up a number of the functional roles that large-scale synchronization has in cognition. The authors assess how the spatio–temporal and –spectral organization and strength of both local and large-scale synchronized networks are associated with conscious sensory perception, visual working memory functions, and attention. These chapters summarize several lines of research showing how the strength of local and inter-areal oscillations in both cortical and subcortical brain structures is correlated with cognitive functions. Together these data suggest that synchronized neuronal oscillations may be a systems-level neuronal mechanism underlying the coordination of distributed processing in human cognition. In line with this argument, other authors go on to describe how oscillations and synchronization are altered in clinical populations, complementing the data presented on healthy subjects.
Importantly, this book includes chapters from authors using many different approaches to the analyses of neuronal oscillations, ranging from local oscillatory activities to the usage of graph theoretical tools in the analyses of synchronization. In this way the present volume provides a comprehensive view on the analyses and functional significance of neuronal oscillations in humans. This book is aimed at doctoral and post-doctoral students as well as research scientists in the fields of cognitive neuroscience, psychology, medicine, and neurosciences
Whole-brain source-reconstructed MEG-data reveal reduced longrange synchronization in chronic schizophrenia
Full text linkCurrent theories of schizophrenia (ScZ) posit that the symptoms and cognitive dysfunctions arise from a dysconnection syndrome. However, studies that have examined this hypothesis with physiological data at realistic time scales are so far scarce. The current study employed a state-of-the-art approach using Magnetoencephalography (MEG) to test alterations in large-scale phase synchronization in a sample of n = 16 chronic ScZ patients, 10 males and n = 19 healthy participants, 10 males, during a perceptual closure task. We identified large-scale networks from source reconstructed MEG data using data-driven analyses of neuronal synchronization. Oscillation amplitudes and interareal phase-synchronization in the 3–120 Hz frequency range were estimated for 400 cortical parcels and correlated with clinical symptoms and neuropsychological scores. ScZ patients were characterized by a reduction in γ-band (30–120 Hz) oscillation amplitudes that was accompanied by a pronounced deficit in large-scale synchronization at γ-band frequencies. Synchronization was reduced within visual regions as well as between visual and frontal cortex and the reduction of synchronization correlated with elevated clinical disorganization. Accordingly, these data highlight that ScZ is associated with a profound disruption of transient synchronization, providing critical support for the notion that core aspect of the pathophysiology arises from an impairment in coordination of distributed neural activity
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