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 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.

PHASE TRANSITIONS IN THE HUMAN BRAIN: SPATIAL MODE DYNAMICS

1992 ◽  
Vol 02 (04) ◽  
pp. 917-939 ◽  
Author(s):  
ARMIN FUCHS ◽  
J.A. SCOTT KELSO ◽  
HERMANN HAKEN
Keyword(s):  
Phase Transitions ◽  
Quantum Interference ◽  
Brain Activity ◽  
Superconducting Quantum Interference Device ◽  
Slowing Down ◽  
Self Organized ◽  
Brain Signals ◽  
Spatial Modes ◽  
The Brain ◽  
Qualitative Changes

Pattern formation and switching between self-organized states are often associated with instabilities in open, nonequilibrium systems. We describe an experiment which shows that systematically changing a control parameter induces qualitative changes in sensorimotor coordination and brain activity, as registered by a 37-SQUID (Superconducting Quantum Interference Device) array. Near the instability point, predicted features of nonequilibrium phase transitions (critical slowing down, fluctuation enhancement) are observed in both the psychophysical data and the brain signals obtained from single SQUID sensors. Further analysis reveals that activity from the entire array displays spatial patterns evolving in time. Such spatiotemporal patterns are characterized by the dynamics of only a few coherent spatial modes.

scholarly journals Distinct profiles of spatio-temporal brain dynamics along symptoms dimensions in autism

2021 ◽  
Author(s):  
Emeline Mullier ◽  
Nada Kojovic ◽  
Solange Denervaud ◽  
Jakub Vohryzek ◽  
Patric Hagmann ◽  
...  
Keyword(s):  
Default Mode Network ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Autism Spectrum ◽  
Brain Dynamics ◽  
Default Mode ◽  
Temporal Diversity ◽  
Show Evidence ◽  
Spatio Temporal ◽  
And Gender

ABSTRACTAutism Spectrum Disorders are accompanied by atypical brain activity and impairments in brain connectivity. In particular, dynamic functional connectivity approaches highlighted aberrant brain fluctuations at rest in individuals with autism compared to a group composed of typically developed individuals, matched in age and gender. However, the characterization of these variations remains unclear. Here, we quantified the spatio-temporal network dynamics using two novel dynamic group-based measures, namely system diversity and spatio-temporal diversity. Using the public database ABIDE 1, we explored the differences between individuals with autism and typically developed individuals. Our results show evidence that individuals with autism have atypical connectivity patterns over time characterized by a lower integration of heterogeneous cognitive processes and unstable functional activity, except for the default mode network presenting its own specific dynamic pattern. Within the autism group, we find this pattern of results to be stronger in more severely affected patients with a predominance of symptoms in the social affect domain. However, patients with prominently restricted and repetitive behaviours demonstrate a more conservative profile of brain dynamics characterized by a lower spatio-temporal diversity of the default mode network.

scholarly journals Effects of optogenetic stimulation of basal forebrain parvalbumin neurons on Alzheimer’s disease pathology

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Caroline A. Wilson ◽  
Sarah Fouda ◽  
Shuzo Sakata
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Basal Forebrain ◽  
Gamma Oscillations ◽  
Cortical Region ◽  
Sensory Stimuli ◽  
Beneficial Effects ◽  
Amyloid Load ◽  
5Xfad Mice ◽  
Frontal Cortical Region

Abstract Neuronal activity can modify Alzheimer’s disease pathology. Overexcitation of neurons can facilitate disease progression whereas the induction of cortical gamma oscillations can reduce amyloid load and improve cognitive functions in mouse models. Although previous studies have induced cortical gamma oscillations by either optogenetic activation of cortical parvalbumin-positive (PV+) neurons or sensory stimuli, it is still unclear whether other approaches to induce gamma oscillations can also be beneficial. Here we show that optogenetic activation of PV+ neurons in the basal forebrain (BF) increases amyloid burden, rather than reducing it. We applied 40 Hz optical stimulation in the BF by expressing channelrhodopsin-2 (ChR2) in PV+ neurons of 5xFAD mice. After 1-h induction of cortical gamma oscillations over three days, we observed the increase in the concentration of amyloid-β42 in the frontal cortical region, but not amyloid-β40. Amyloid plaques were accumulated more in the medial prefrontal cortex and the septal nuclei, both of which are targets of BF PV+ neurons. These results suggest that beneficial effects of cortical gamma oscillations on Alzheimer’s disease pathology can depend on the induction mechanisms of cortical gamma oscillations.

HIGH RESOLUTION CALORIMETRIC STUDIES AT PHASE TRANSITIONS OF ALKYLCYANOBIPHENYL LIQUID CRYSTALS CONFINED TO SUBMICRON SIZE CYLINDRICAL CAVITIES

1995 ◽  
Vol 09 (18n19) ◽  
pp. 2247-2283 ◽  
Author(s):  
DANIELE FINOTELLO ◽  
GERMANO S. IANNACCHIONE
Keyword(s):  
Phase Transitions ◽  
Liquid Crystals ◽  
High Resolution ◽  
Specific Heat ◽  
Pore Wall ◽  
Isotropic Phase ◽  
First Order ◽  
Smectic A ◽  
Nematic Director ◽  
Scalar Order Parameter

We review results of a high resolution systematic study of the specific heat for alkyl-cyanobiphenyl liquid crystals confined to the 0.2µm diameter cylindrical pores Anopore membranes. The nematic director alignment at the pore wall is varied from homeotropic to tangential by pore surface treatment. Several phenomena are uncovered by these studies which probed the weakly first order nematic to isotropic, the continuous smectic-A to nematic and the first order smectic-A to isotropic phase transitions. The specific heat is strongly dependent on the nematic director configuration, and confinement effects are remarkably distinct according to the order of the phase transition. The influence of elastic distortions and surface ordering and disordering effects are evident. Despite considerable departures from bulk behavior with regards to specific heat peaks size, rounding and width, and transition temperature shifts, a bulk-like critical behavior appears to be retained. The formation of smectic translational order within the pores is hindered for those liquid crystals that also possess a nematic phase. The average scalar order parameter temperature dependence is extracted from the specific heat results using a simplified Landau-de Gennes type of model, and is shown to be consistent with nuclear magnetic resonance results.

scholarly journals Harmonic Brain Modes: A Unifying Framework for Linking Space and Time in Brain Dynamics

2017 ◽  
Vol 24 (3) ◽  
pp. 277-293 ◽  
Author(s):  
Selen Atasoy ◽  
Gustavo Deco ◽  
Morten L. Kringelbach ◽  
Joel Pearson
Keyword(s):  
Neural Activity ◽  
Brain Activity ◽  
Activity Patterns ◽  
Structural Connectivity ◽  
Building Blocks ◽  
Mental States ◽  
Brain Dynamics ◽  
Space And Time ◽  
Wide Range ◽  
The Brain

A fundamental characteristic of spontaneous brain activity is coherent oscillations covering a wide range of frequencies. Interestingly, these temporal oscillations are highly correlated among spatially distributed cortical areas forming structured correlation patterns known as the resting state networks, although the brain is never truly at “rest.” Here, we introduce the concept of harmonic brain modes—fundamental building blocks of complex spatiotemporal patterns of neural activity. We define these elementary harmonic brain modes as harmonic modes of structural connectivity; that is, connectome harmonics, yielding fully synchronous neural activity patterns with different frequency oscillations emerging on and constrained by the particular structure of the brain. Hence, this particular definition implicitly links the hitherto poorly understood dimensions of space and time in brain dynamics and its underlying anatomy. Further we show how harmonic brain modes can explain the relationship between neurophysiological, temporal, and network-level changes in the brain across different mental states ( wakefulness, sleep, anesthesia, psychedelic). Notably, when decoded as activation of connectome harmonics, spatial and temporal characteristics of neural activity naturally emerge from the interplay between excitation and inhibition and this critical relation fits the spatial, temporal, and neurophysiological changes associated with different mental states. Thus, the introduced framework of harmonic brain modes not only establishes a relation between the spatial structure of correlation patterns and temporal oscillations (linking space and time in brain dynamics), but also enables a new dimension of tools for understanding fundamental principles underlying brain dynamics in different states of consciousness.

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