scholarly journals Decoding brain states on the intrinsic manifold of human brain dynamics across wakefulness and sleep

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Joan Rué-Queralt ◽  
Angus Stevner ◽  
Enzo Tagliazucchi ◽  
Helmut Laufs ◽  
Morten L. Kringelbach ◽  
...  
Keyword(s):  
Human Brain ◽  
Brain Activity ◽  
Group Analysis ◽  
Brain Dynamics ◽  
Sleep Stages ◽  
Temporal Representation ◽  
Current State ◽  
Brain States ◽  
Spatio Temporal ◽  
Low Dimensional

AbstractCurrent state-of-the-art functional magnetic resonance imaging (fMRI) offers remarkable imaging quality and resolution, yet, the intrinsic dimensionality of brain dynamics in different states (wakefulness, light and deep sleep) remains unknown. Here we present a method to reveal the low dimensional intrinsic manifold underlying human brain dynamics, which is invariant of the high dimensional spatio-temporal representation of the neuroimaging technology. By applying this intrinsic manifold framework to fMRI data acquired in wakefulness and sleep, we reveal the nonlinear differences between wakefulness and three different sleep stages, and successfully decode these different brain states with a mean accuracy across participants of 96%. Remarkably, a further group analysis shows that the intrinsic manifolds of all participants share a common topology. Overall, our results reveal the intrinsic manifold underlying the spatiotemporal dynamics of brain activity and demonstrate how this manifold enables the decoding of different brain states such as wakefulness and various sleep stages.

scholarly journals Decoding brain states on the intrinsic manifold of human brain dynamics across wakefulness and sleep

2021 ◽  
Author(s):  
J. Rué-Queralt ◽  
A. Stevner ◽  
E. Tagliazucchi ◽  
H. Laufs ◽  
M. L. Kringelbach ◽  
...  
Keyword(s):  
Human Brain ◽  
Brain Activity ◽  
Group Analysis ◽  
Brain Dynamics ◽  
Sleep Stages ◽  
Temporal Representation ◽  
Average Accuracy ◽  
Brain States ◽  
Spatio Temporal ◽  
Low Dimensional

AbstractCurrent state-of-the-art functional magnetic resonance imaging (fMRI) offers remarkable imaging quality and resolution, yet, the intrinsic dimensionality of brain dynamics in different states (wakefulness, light and deep sleep) remains unknown. Here we present a novel method to reveal the low dimensional intrinsic manifold underlying human brain dynamics, which is invariant of the high dimensional spatio-temporal representation of the neuroimaging technology. By applying this novel intrinsic manifold framework to fMRI data acquired in wakefulness and sleep, we reveal the nonlinear differences between wakefulness and three different sleep stages, and successfully decode these different brain states with an average accuracy of 96%. Remarkably, a further group analysis shows that the intrinsic manifolds of all participants share a common topology. Overall, our results reveal the intrinsic manifold underlying the spatiotemporal dynamics of brain activity and demonstrate how this manifold enables the decoding of different brain states such as wakefulness and various sleep stages.

scholarly journals Connectome-harmonic decomposition of human brain activity reveals dynamical repertoire re-organization under LSD

2017 ◽  
Author(s):  
Selen Atasoy ◽  
Leor Roseman ◽  
Mendel Kaelen ◽  
Morten L. Kringelbach ◽  
Gustavo Deco ◽  
...  
Keyword(s):  
Human Brain ◽  
Brain Activity ◽  
Power Laws ◽  
Lysergic Acid ◽  
Brain Dynamics ◽  
Co Activation ◽  
Harmonic Decomposition ◽  
Health And Disease ◽  
Novel Method ◽  
Brain States

ABSTRACTRecent studies have started to elucidate the effects of lysergic acid diethylamide (LSD) on the human brain but the underlying dynamics are not yet fully understood. Here we used ‘connectome-harmonic decomposition’, a novel method to investigate the dynamical changes in brain states. We found that LSD alters the energy and the power of individual harmonic brain states in a frequency-selective manner. Remarkably, this leads to an expansion of the repertoire of active brain states, suggestive of a general re-organization of brain dynamics given the non-random increase in co-activation across frequencies. Interestingly, the frequency distribution of the active repertoire of brain states under LSD closely follows power-laws indicating a re-organization of the dynamics at the edge of criticality. Beyond the present findings, these methods open up for a better understanding of the complex brain dynamics in health and disease.

scholarly journals Capturing the non-stationarity of whole-brain dynamics underlying human brain states

NeuroImage ◽  
2021 ◽  
pp. 118551
Author(s):  
J.A. Galadí ◽  
S. Silva Pereira ◽  
Y. Sanz Perl ◽  
M.L. Kringelbach ◽  
I. Gayte ◽  
...  
Keyword(s):  
Human Brain ◽  
Brain Dynamics ◽  
Whole Brain ◽  
Brain States

scholarly journals EEG activity during balance platform test in humans

2019 ◽  
pp. 132-136 ◽  
Author(s):  
Vladimir Khorev ◽  
Artem Badarin ◽  
Vladimir Antipov ◽  
Vladimir Maksimenko ◽  
Semen Kurkin
Keyword(s):  
Cerebral Cortex ◽  
Human Brain ◽  
Brain Activity ◽  
Body Posture ◽  
Future Research ◽  
Eeg Activity ◽  
Common Features ◽  
Computer Interfaces ◽  
New Directions ◽  
Brain States

In order to analyze different human brain states related to perception and maintaining of body posture, we implemented an experiment with a balance platform. It is known the cerebral cortex regulates subcortical postural centers to maintain upright balance and posture and balance demands. However, the cortical mechanisms that support standing balance remain elusive. In this work, we present an EEG-based analysis during execution of balance responses with distinct postural demands. The results suggest the existence of common features in the EEG structure associated with distinct activity during balance maintaining. This may give new directions for future research in the field of brain activity, and for the development of brain-computer interfaces.

scholarly journals Evolutionary Advantages of Stimulus-Driven EEG Phase Transitions in the Upper Cortical Layers

2021 ◽  
Vol 15 ◽  
Author(s):  
Robert Kozma ◽  
Bernard J. Baars ◽  
Natalie Geld
Keyword(s):  
Phase Transitions ◽  
Brain Activity ◽  
Large Body ◽  
Gamma Oscillations ◽  
Rapid Expansion ◽  
Brain Dynamics ◽  
Isotropic Phase ◽  
Sensory Stimuli ◽  
Self Organized ◽  
Spatio Temporal

Spatio-temporal brain activity monitored by EEG recordings in humans and other mammals has identified beta/gamma oscillations (20–80 Hz), which are self-organized into spatio-temporal structures recurring at theta/alpha rates (4–12 Hz). These structures have statistically significant correlations with sensory stimuli and reinforcement contingencies perceived by the subject. The repeated collapse of self-organized structures at theta/alpha rates generates laterally propagating phase gradients (phase cones), ignited at some specific location of the cortical sheet. Phase cones have been interpreted as neural signatures of transient perceptual experiences according to the cinematic theory of brain dynamics. The rapid expansion of essentially isotropic phase cones is consistent with the propagation of perceptual broadcasts postulated by Global Workspace Theory (GWT). What is the evolutionary advantage of brains operating with repeatedly collapsing dynamics? This question is answered using thermodynamic concepts. According to neuropercolation theory, waking brains are described as non-equilibrium thermodynamic systems operating at the edge of criticality, undergoing repeated phase transitions. This work analyzes the role of long-range axonal connections and metabolic processes in the regulation of critical brain dynamics. Historically, the near 10 Hz domain has been associated with conscious sensory integration, cortical “ignitions” linked to conscious visual perception, and conscious experiences. We can therefore combine a very large body of experimental evidence and theory, including graph theory, neuropercolation, and GWT. This cortical operating style may optimize a tradeoff between rapid adaptation to novelty vs. stable and widespread self-organization, therefore resulting in significant Darwinian benefits.

scholarly journals The Dynamics of Error Processing in the Human Brain as Reflected by High-Gamma Activity in Noninvasive and Intracranial EEG

2017 ◽  
Author(s):  
Martin Völker ◽  
Lukas D. J. Fiederer ◽  
Sofie Berberich ◽  
Jiří Hammer ◽  
Joos Behncke ◽  
...  
Keyword(s):  
Information Processing ◽  
Human Brain ◽  
Brain Activity ◽  
Local Level ◽  
Error Processing ◽  
Intracranial Eeg ◽  
High Gamma ◽  
Related Response ◽  
Spatio Temporal ◽  
Oscillatory Brain Activity

AbstractError detection in motor behavior is a fundamental cognitive function heavily relying on cortical information processing. Neural activity in the high-gamma frequency band (HGB) closely reflects such local cortical processing, but little is known about its role in error processing, particularly in the healthy human brain. Here we characterize the error-related response of the human brain based on data obtained with noninvasive EEG optimized for HGB mapping in 31 healthy subjects (15 females, 16 males), and additional intracranial EEG data from 9 epilepsy patients (4 females, 5 males). Our findings reveal a comprehensive picture of the global and local dynamics of error-related HGB activity in the human brain. On the global level as reflected in the noninvasive EEG, the error-related response started with an early component dominated by anterior brain regions, followed by a shift to parietal regions, and a subsequent phase characterized by sustained parietal HGB activity. This phase lasted for more than 1 s after the error onset. On the local level reflected in the intracranial EEG, a cascade of both transient and sustained error-related responses involved an even more extended network, spanning beyond frontal and parietal regions to the insula and the hippocampus. HGB mapping appeared especially well suited to investigate late, sustained components of the error response, possibly linked to downstream functional stages such as error-related learning and behavioral adaptation. Our findings establish the basic spatio-temporal properties of HGB activity as a neural correlate of error processing, complementing traditional error-related potential studies.Significance StatementThere is great interest to understand how the human brain reacts to errors in goal-directed behavior. An important index of cortical and subcortical information processing is fast oscillatory brain activity, particularly in the high-gamma band (above 50 Hz). Here we show that it is possible to detect signatures of errors in event-related high-gamma responses with noninvasive techniques, characterize these responses comprehensively, and validate the EEG procedure for the detection of such signals. In addition, we demonstrate the added value of intracranial recordings pinpointing the fine-grained spatio-temporal patterns in error-related brain networks. We anticipate that the optimized noninvasive EEG techniques as described here will be helpful in many areas of cognitive neuroscience where fast oscillatory brain activity is of interest.

scholarly journals Connectome Harmonic Decomposition of Human Brain Dynamics Reveals a Landscape of Consciousness

2020 ◽  
Author(s):  
A.I. Luppi ◽  
J. Vohryzek ◽  
M.L. Kringelbach ◽  
P.A.M. Mediano ◽  
M.M. Craig ◽  
...  
Keyword(s):  
Human Brain ◽  
Wide Spectrum ◽  
Brain Activity ◽  
Conscious Experience ◽  
Brain Dynamics ◽  
Biological Phenomena ◽  
Level Of Consciousness ◽  
Harmonic Decomposition ◽  
Meaningful Relationships ◽  
Constituent Elements

ABSTRACTA central question in neuroscience is how cognition and consciousness arise from human brain activity. Here, we decompose cortical dynamics of resting-state functional MRI into their constituent elements: the harmonics of the human connectome. Mapping a wide spectrum of consciousness onto these elementary brain states reveals a generalisable connectome harmonic signature of loss of consciousness, whether due to anaesthesia or severe brain injury. Remarkably, its mirror-reversed image corresponds to the harmonic signature of the psychedelic state induced by ketamine or LSD, identifying meaningful relationships between neurobiology, brain function, and conscious experience. The repertoire of connectome harmonics further provides a fine-tuned indicator of level of consciousness, sensitive to differences in anaesthetic dose and clinically relevant sub-categories of patients with disorders of consciousness. Overall, we reveal that the emergence of consciousness from human brain dynamics follows the same universal principles shared by a multitude of physical and biological phenomena: the mathematics of harmonic modes.

scholarly journals Self-similarity and multifractality in human brain activity: A wavelet-based analysis of scale-free brain dynamics

2018 ◽  
Vol 309 ◽  
pp. 175-187 ◽  
Author(s):  
Daria La Rocca ◽  
Nicolas Zilber ◽  
Patrice Abry ◽  
Virginie van Wassenhove ◽  
Philippe Ciuciu
Keyword(s):  
Human Brain ◽  
Brain Activity ◽  
Brain Dynamics ◽  
Self Similarity ◽  
Scale Free

scholarly journals Instantaneous Brain Dynamics Mapped to a Continuous State Space

2017 ◽  
Author(s):  
Jacob Billings ◽  
Alessio Medda ◽  
Sadia Shakil ◽  
Xiaohong Shen ◽  
Amrit Kashyap ◽  
...  
Keyword(s):  
State Space ◽  
Dimensional Space ◽  
Brain Activity ◽  
Dimensional Structure ◽  
Brain Dynamics ◽  
Whole Brain ◽  
Human Connectome Project ◽  
Continuous State ◽  
Brain States ◽  
Space Dynamics

AbstractMeasures of whole-brain activity, from techniques such as functional Magnetic Resonance Imaging, provide a means to observe the brain’s dynamical operations. However, interpretation of whole-brain dynamics has been stymied by the inherently high-dimensional structure of brain activity. The present research addresses this challenge through a series of scale transformations in the spectral, spatial, and relational domains. Instantaneous multispectral dynamics are first developed from input data via a wavelet filter bank. Voxel-level signals are then projected onto a representative set of spatially independent components. The correlation distance over the instantaneous wavelet-ICA state vectors is a graph that may be embedded onto a lower-dimensional space to assist the interpretation of state-space dynamics. Applying this procedure to a large sample of resting and task data (acquired through the Human Connectome Project), we segment the empirical state space into a continuum of stimulus-dependent brain states. We also demonstrate that resting brain activity includes brain states that are very similar to those adopted during some tasks, as well as brain states that are distinct from experimentally-defined tasks. Back-projection of segmented brain states onto the brain’s surface reveals the patterns of brain activity that support each experimental state.

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