Behavioral stochastic resonance associated with large-scale synchronization of human brain activity

2004 ◽  
Author(s):  
Keiichi Kitajo ◽  
Kentaro Yamanaka ◽  
Daichi Nozaki ◽  
Lawrence M. Ward ◽  
Yoshiharu Yamamoto
Keyword(s):  
Human Brain ◽  
Stochastic Resonance ◽  
Large Scale ◽  
Brain Activity

Noise-induced large-scale phase synchronization of human-brain activity associated with behavioural stochastic resonance

2007 ◽  
Vol 80 (4) ◽  
pp. 40009 ◽  
Author(s):  
K. Kitajo ◽  
S. M. Doesburg ◽  
K. Yamanaka ◽  
D. Nozaki ◽  
L. M. Ward ◽  
...  
Keyword(s):  
Human Brain ◽  
Stochastic Resonance ◽  
Large Scale ◽  
Phase Synchronization ◽  
Brain Activity

scholarly journals How the human brain introspects about one’s own episodes of cognitive control

2017 ◽  
Author(s):  
David Soto ◽  
Mona Theodoraki ◽  
Pedro M. Paz-Alonso
Keyword(s):  
Cognitive Control ◽  
Human Brain ◽  
Internal Model ◽  
Large Scale ◽  
Brain Activity ◽  
Temporal Correlation ◽  
Control Networks ◽  
Control Functions ◽  
Cognitive States ◽  
Behavioural Performance

AbstractMetacognition refers to our capacity to reflect upon our experiences, thoughts and actions. Metacognition processes are linked to cognitive control functions that allow keeping our actions on-task. But it is unclear how the human brain builds an internal model of one’s cognition and behaviour. We conducted 2 fMRI experiments in which brain activity was recorded ‘online’ as participants engaged in a memory-guided search task and then later ‘offline’ when participants introspected about their prior experience and cognitive states during performance. In Experiment 1 the memory cues were task-relevant while in Experiment 2 they were irrelevant. Across Experiments, the patterns of brain activity, including frontoparietal regions, were similar during on-task and introspection states. However the connectivity profile amongst frontoparietal areas was distint during introspection and modulated by the relevance of the memory cues. Introspection was also characterized by increased temporal correlation between the default-mode network (DMN), frontoparietal and dorsal attention networks and visual cortex. We suggest that memories of one’s own experience during task performance are encoded in large-scale patterns of brain activity and that coupling between DMN and frontoparietal control networks may be crucial to build an internal model of one’s behavioural performance.

scholarly journals A spatiotemporal complexity architecture of human brain activity

2021 ◽  
Author(s):  
Stephan Krohn ◽  
Nina von Schwanenflug ◽  
Leonhard Waschke ◽  
Amy Romanello ◽  
Martin Gell ◽  
...  
Keyword(s):  
Human Brain ◽  
Neural Activity ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Brain Activity ◽  
Brain Regions ◽  
Brain Organization ◽  
Functional Connections ◽  
Signal Complexity ◽  
The Brain

The human brain operates in large-scale functional networks, collectively subsumed as the functional connectome1-13. Recent work has begun to unravel the organization of the connectome, including the temporal dynamics of brain states14-20, the trade-off between segregation and integration9,15,21-23, and a functional hierarchy from lower-order unimodal to higher-order transmodal processing systems24-27. However, it remains unknown how these network properties are embedded in the brain and if they emerge from a common neural foundation. Here we apply time-resolved estimation of brain signal complexity to uncover a unifying principle of brain organization, linking the connectome to neural variability6,28-31. Using functional magnetic resonance imaging (fMRI), we show that neural activity is marked by spontaneous "complexity drops" that reflect episodes of increased pattern regularity in the brain, and that functional connections among brain regions are an expression of their simultaneous engagement in such episodes. Moreover, these complexity drops ubiquitously propagate along cortical hierarchies, suggesting that the brain intrinsically reiterates its own functional architecture. Globally, neural activity clusters into temporal complexity states that dynamically shape the coupling strength and configuration of the connectome, implementing a continuous re-negotiation between cost-efficient segregation and communication-enhancing integration9,15,21,23. Furthermore, complexity states resolve the recently discovered association between anatomical and functional network hierarchies comprehensively25-27,32. Finally, brain signal complexity is highly sensitive to age and reflects inter-individual differences in cognition and motor function. In sum, we identify a spatiotemporal complexity architecture of neural activity — a functional "complexome" that gives rise to the network organization of the human brain.

scholarly journals Monolingual and bilingual infants rely on the same brain networks: Evidence from resting-state functional connectivity

2020 ◽  
Author(s):  
Borja Blanco ◽  
Monika Molnar ◽  
Manuel Carreiras ◽  
Liam H. Collins-Jones ◽  
Ernesto Vidal ◽  
...  
Keyword(s):  
Human Brain ◽  
Large Scale ◽  
Near Infrared ◽  
Functional Organization ◽  
Brain Activity ◽  
Functional Brain Imaging ◽  
Resting State Functional Connectivity ◽  
Functional Near Infrared Spectroscopy ◽  
Behavioural Research ◽  
Infant Brain

AbstractThis study examines whether bilingual exposure has a profound effect on the functional organization of the developing human brain during infancy. Recent behavioural research attests that monolingual vs. bilingual experience affects cognitive and linguistic processes already during the first months of life. However, to what extent the intrinsic organization of the infant human brain adapts to monolingual vs. bilingual environments is unclear. We measured spontaneous hemodynamic brain activity using functional near-infrared spectroscopy (fNIRS) in a large cohort (N=99) of 4-month-old monolingual and bilingual infants. We implemented well-established analysis approaches of functional brain imaging that enabled us to reveal the functional organization of the infant brain in large-scale cortical networks, and to perform group-level comparisons (i.e., monolingual vs. bilingual groups) in a reliable manner. Our results revealed no differences between the intrinsic functional organization of the developing monolingual and bilingual infant brain at 4 months of age.

scholarly journals Combining Noninvasive Electromagnetic and Hemodynamic Measures of Human Brain Activity

2020 ◽  
pp. 179-193
Author(s):  
Fa-Hsuan Lin ◽  
Thomas Witzel ◽  
Matti S. Hämäläinen ◽  
Aapo Nummenmaa
Keyword(s):  
Human Brain ◽  
Neuronal Activity ◽  
Large Scale ◽  
Brain Activity ◽  
High Sensitivity ◽  
Minimum Norm ◽  
Source Modeling ◽  
Physiological Basis ◽  
Fusion Technique ◽  
Minimum Norm Estimate

AbstractMagnetoencephalography (MEG) is directly sensitive to postsynaptic neuronal activity with the millisecond temporal resolution. MEG is ideally to complement functional MRI (fMRI), which measures hemodynamic responses secondary to neuronal activity with the millimeter spatial resolution, for noninvasive imaging of human brain function. Here, using the Minimum-Norm Estimate as an example, we review how fMRI can be integrated with MEG (and electroencephalography, EEG) source modeling and summarize potential advantages and pitfalls of this data fusion technique. Neurovascular coupling as the physiological basis for MEG/EEG/fMRI integration is also discussed. Ultimately, we expect to develop multimodal MEG/EEG/fMRI neuroimaging methodology for characterizing spatiotemporal functional connectivity in large-scale neural networks of the human brain with high sensitivity and accuracy.

Integrative Visuomotor Behavior Is Associated With Interregionally Coherent Oscillations in the Human Brain

1998 ◽  
Vol 79 (3) ◽  
pp. 1567-1573 ◽  
Author(s):  
Joseph Classen ◽  
Christian Gerloff ◽  
Manabu Honda ◽  
Mark Hallett
Keyword(s):  
Motor Cortex ◽  
Human Brain ◽  
Large Scale ◽  
Isometric Force ◽  
Brain Activity ◽  
Motor Task ◽  
Low Frequency ◽  
Visuomotor Behavior ◽  
Electrical Brain Activity ◽  
Eeg Recordings

Classen, Joseph, Christian Gerloff, Manabu Honda, and Mark Hallett. Integrative visuomotor behavior is associated with interregionally coherent oscillations in the human brain. J. Neurophysiol. 79: 1567–1573, 1998. Coherent electrical brain activity has been demonstrated to be associated with perceptual events in mammals. It is unclear whether or not it is also a mechanism instrumental in the performance of sensorimotor tasks requiring the continuous processing of information between primarily executive and receptive brain areas. In particular it is unknown whether or not interregional coherent activity detectable in electroencephalographic (EEG) recordings on the scalp reflects interareal functional cooperativity in humans. We studied patterns of changes in EEG-coherence associated with a visuomotor force-tracking task in seven subjects. Interregional coherence of EEG signals recorded from scalp regions overlying the visual and the motor cortex increased in comparison to a resting condition when subjects tracked a visual target by producing an isometric force with their right index finger. Coherence between visual and motor cortex decreased when the subjects produced a similar motor output in the presence of a visual distractor and was unchanged in a purely visual and purely motor task. Increases and decreases of coherence were best differentiated in the low beta frequency range (13–21 Hz). This observation suggests a special functional significance of low frequency oscillations in information processing in large-scale networks. These findings substantiate the view that coherent brain activity underlies integrative sensorimotor behavior.

scholarly journals On the edge of criticality: strength-dependent perturbation unveils delicate balance between fluctuation and oscillation in brain dynamics

2021 ◽  
Author(s):  
Yontatan Sanz Perl ◽  
Anira Escrichs ◽  
Enzo Tagliazucchi ◽  
Morten L Kringelbach ◽  
Gustavo Deco
Keyword(s):  
Human Brain ◽  
Brain Function ◽  
Large Scale ◽  
Brain Activity ◽  
Brain Dynamics ◽  
Functional Networks ◽  
Oscillatory Regime ◽  
Delicate Balance ◽  
Local Strength ◽  
Global Strength

Going beyond previous research, we use strength-dependent perturbation to obtain a deeper understanding of the mechanisms underlying the emergence of large-scale brain activity. Despite decades of research, we still have a shallow understanding of the role and generating mechanisms of the ubiquitous fluctuations and oscillations found in recordings of brain dynamics. Here, we used global strength-dependent perturbation to give a causal mechanistic description of human brain function providing a delicate balance between fluctuation and oscillation on the edge of criticality. After application of precise local strength-dependent perturbations and measuring the well-known perturbative complexity index, we demonstrated that the overall balance is shifted towards a fluctuating regime which is superior in terms of enhancing different functional networks compared to the oscillatory regime. This framework can generate specific, testable empirical predictions to be tested in human stimulation studies with strength-dependent rather than constant perturbation. Overall, our novel strength-dependent perturbation framework demonstrates that the human brain is poised on the edge of criticality, between fluctuations to oscillations, allowing for maximal flexibility.

scholarly journals Characterization of functional diversity of the human brain based on intrinsic connectivity networks

2018 ◽  
Author(s):  
Congying Chu ◽  
Lingzhong Fan ◽  
Tianzi Jiang
Keyword(s):  
Human Brain ◽  
Functional Diversity ◽  
Functional Properties ◽  
Large Scale ◽  
Primary Motor Cortex ◽  
Brain Activity ◽  
Brain Regions ◽  
Intrinsic Connectivity ◽  
Intrinsic Connectivity Networks ◽  
The Brain

AbstractSpontaneous fluctuations underlying the brain activity can reflect the intrinsic organization of the system, such as the functional brain networks. In large scale, a network perspective has emerged as a new avenue to explore the functional properties of human brain. Here, we studied functional diversity in healthy subjects based on the network perspective. We hypothesized that the patterns of participation of different functional networks were related with the functional diversity of particular brain regions. Independent component analysis (ICA) was adopted to detect the intrinsic connectivity networks (ICNs) based on the data of resting-state functional MRI. An index of functional diversity (FD index) was proposed to quantitatively describe the degree of anisotropic distribution related with participation of various ICNs. We found that FD index continuously varied across the brain, for example, the primary motor cortex with low FD value and the precuneus with significantly high FD value. The FD values indicated the different functional roles of the corresponding brain regions, which were reflected by the various patterns of participation of ICNs. The FD index can be used as a new approach to quantitatively characterize the functional diversity of human brain, even for the changed functional properties caused by the psychiatric disorders.

scholarly journals Cognitive chimera states in human brain networks

2019 ◽  
Vol 5 (4) ◽  
pp. eaau8535 ◽  
Author(s):  
Kanika Bansal ◽  
Javier O. Garcia ◽  
Steven H. Tompson ◽  
Timothy Verstynen ◽  
Jean M. Vettel ◽  
...  
Keyword(s):  
Human Brain ◽  
Large Scale ◽  
Brain Activity ◽  
Brain Network ◽  
Brain Dynamics ◽  
Cognitive Systems ◽  
Regional Variability ◽  
Chimera States ◽  
Regional Brain ◽  
The Impact

The human brain is a complex dynamical system, and how cognition emerges from spatiotemporal patterns of regional brain activity remains an open question. As different regions dynamically interact to perform cognitive tasks, variable patterns of partial synchrony can be observed, forming chimera states. We propose that the spatial patterning of these states plays a fundamental role in the cognitive organization of the brain and present a cognitively informed, chimera-based framework to explore how large-scale brain architecture affects brain dynamics and function. Using personalized brain network models, we systematically study how regional brain stimulation produces different patterns of synchronization across predefined cognitive systems. We analyze these emergent patterns within our framework to understand the impact of subject-specific and region-specific structural variability on brain dynamics. Our results suggest a classification of cognitive systems into four groups with differing levels of subject and regional variability that reflect their different functional roles.

scholarly journals Intrinsic/extrinsic duality of large-scale neural functional integration in the human brain

2020 ◽  
Author(s):  
Martin Sjøgård ◽  
Mathieu Bourguignon ◽  
Lars Costers ◽  
Alexandru Dumitrescu ◽  
Tim Coolen ◽  
...  
Keyword(s):  
Human Brain ◽  
Brain Function ◽  
Large Scale ◽  
Phase Synchronization ◽  
Brain Activity ◽  
Functional Integration ◽  
Neural Communication ◽  
Amplitude Correlation ◽  
Long Timescales ◽  
Coupling Mechanisms

AbstractHuman brain activity is not merely responsive to environmental context but includes intrinsic dynamics, as suggested by the discovery of functionally meaningful neural networks at rest, i.e., even without explicit engagement of the corresponding function. Yet, the neurophysiological coupling mechanisms distinguishing intrinsic (i.e., task-invariant) from extrinsic (i.e., task-dependent) brain networks remain indeterminate. Here, we investigated functional brain integration using magnetoencephalography throughout rest and various tasks recruiting different functional systems and modulating perceptual/cognitive loads. We demonstrated that two distinct modes of neural communication continually operate in parallel: extrinsic coupling supported by phase synchronization and intrinsic integration encoded in amplitude correlation. Intrinsic integration also contributes to phase synchronization, especially over short (second-long) timescales, through modulatory effects of amplitude correlation. Our study establishes the foundations of a novel conceptual framework for human brain function that fundamentally relies on electrophysiological features of functional integration. This framework blurs the boundary between resting-state and task-related neuroimaging.

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