scholarly journals Loss of consciousness reduces the stability of brain hubs and the heterogeneity of brain dynamics

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Ane López-González ◽  
Rajanikant Panda ◽  
Adrián Ponce-Alvarez ◽  
Gorka Zamora-López ◽  
Anira Escrichs ◽  
...  
Keyword(s):  
Brain Injuries ◽  
Brain Activity ◽  
Structural Connectivity ◽  
Conscious State ◽  
Brain Dynamics ◽  
Disorder Of Consciousness ◽  
Low Level ◽  
States Of Consciousness ◽  
The Stability ◽  
Different Levels

AbstractLow-level states of consciousness are characterized by disruptions of brain activity that sustain arousal and awareness. Yet, how structural, dynamical, local and network brain properties interplay in the different levels of consciousness is unknown. Here, we study fMRI brain dynamics from patients that suffered brain injuries leading to a disorder of consciousness and from healthy subjects undergoing propofol-induced sedation. We show that pathological and pharmacological low-level states of consciousness display less recurrent, less connected and more segregated synchronization patterns than conscious state. We use whole-brain models built upon healthy and injured structural connectivity to interpret these dynamical effects. We found that low-level states of consciousness were associated with reduced network interactions, together with more homogeneous and more structurally constrained local dynamics. Notably, these changes lead the structural hub regions to lose their stability during low-level states of consciousness, thus attenuating the differences between hubs and non-hubs brain dynamics.

scholarly journals Loss of consciousness reduces the stability of brain hubs and the heterogeneity of brain dynamics

2020 ◽  
Author(s):  
Ane López-González ◽  
Rajanikant Panda ◽  
Adrián Ponce-Alvarez ◽  
Gorka Zamora-López ◽  
Anira Escrichs ◽  
...  
Keyword(s):  
Brain Injuries ◽  
Brain Dynamics ◽  
Loss Of Consciousness ◽  
Disorder Of Consciousness ◽  
Low Level ◽  
The Core ◽  
States Of Consciousness ◽  
The Stability ◽  
Different Levels ◽  
Global Reduction

AbstractLow-level states of consciousness are characterised by disruptions of brain dynamics that sustain arousal and awareness. Yet, how structural, dynamical, local and network brain properties interplay in the different levels of consciousness is unknown. Here, we studied the fMRI brain dynamics from patients that suffered brain injuries leading to a disorder of consciousness and from subjects undergoing propofol-induced anaesthesia. We showed that pathological and pharmacological low-level states of consciousness displayed less recurrent, less diverse, less connected, and more segregated synchronization patterns than conscious states. We interpreted these effects using whole-brain models built on healthy and injured connectomes. We showed that altered dynamics arise from a global reduction of network interactions, together with more homogeneous and more structurally constrained local dynamics. These effects were accentuated using injured connectomes. Notably, these changes lead the hub regions to lose their stability during low-level states of consciousness, thus attenuating the core-periphery structure of brain dynamics.

scholarly journals Complexity of brain dynamics as a correlate of consciousness in anaesthetized monkeys

2021 ◽  
Author(s):  
Nicolas Fuentes ◽  
Alexis García ◽  
Ramón Guevara ◽  
Roberto Orofino ◽  
Diego M. Mateos
Keyword(s):  
General Anesthesia ◽  
Brain Activity ◽  
Brain Regions ◽  
The Other ◽  
Brain Dynamics ◽  
General Evaluation ◽  
States Of Consciousness ◽  
Other Hand ◽  
Different Levels

AbstractThe use of anaesthesia is a fundamental tool in the investigation of consciousness. Anesthesia procedures allow to investigate different states of consciousness from sedation to deep anesthesia within controlled scenarios. In this study we use information quantifiers to measure the complexity of electrocorticogram recordings in monkeys. We apply these metrics to compare different stages of general anesthesia for evaluating consciousness in several anesthesia protocols. We find that the complexity of brain activity can be used as a correlate of consciousness. For two of the anaesthetics used, propofol and medetomidine, we find that the anaesthetised state is accompanied by a reduction in the complexity of brain activity. On the other hand we observe that use of ketamine produces an increase in complexity measurements. We relate this observation with increase activity within certain brain regions associated with the ketamine used doses. Our measurements indicate that complexity of brain activity is a good indicator for a general evaluation of different levels of consciousness awareness, both in anesthetized and non anesthetizes states.

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.

scholarly journals Combined behavioral and electrophysiological evidence for a direct cortical effect of prefrontal tDCS on disorders of consciousness

2019 ◽  
Author(s):  
Bertrand Hermann ◽  
Federico Raimondo ◽  
Lukas Hirsch ◽  
Yu Huang ◽  
Mélanie Denis-Valente ◽  
...  
Keyword(s):  
Electric Fields ◽  
Brain Injuries ◽  
Causal Effect ◽  
Brain Activity ◽  
Vegetative State ◽  
Behavioral Assessment ◽  
Minimally Conscious State ◽  
Conscious State ◽  
Disorders Of Consciousness ◽  
Open Label

ABSTRACTSevere brain injuries can lead to long-lasting disorders of consciousness (DoC) such as vegetative state/unresponsive wakefulness syndrome (VS/UWS) or minimally conscious state (MCS). While behavioral assessment remains the gold standard to determine conscious state, EEG has proven to be a promising complementary tool to monitor the effect of new therapeutics. Encouraging results have been obtained with invasive electrical stimulation of the brain, and recent studies identified transcranial direct current stimulation (tDCS) as an effective approach in randomized controlled trials. This non-invasive and inexpensive tool may turn out to be the preferred treatment option. However, its mechanisms of action and physiological effects on brain activity remain unclear and debated. Here, we stimulated 60 DoC patients with the anode placed over left-dorsolateral prefrontal cortex in a prospective open-label study. Clinical behavioral assessment improved in twelve patients (20%) and none deteriorated. This behavioral response after tDCS coincided with an enhancement of putative EEG markers of consciousness: in comparison with non-responders, responders showed increases of power and long-range cortico-cortical functional connectivity in the theta-alpha band, and a larger and more sustained P300 suggesting improved conscious access to auditory novelty. The EEG changes correlated with electric fields strengths in prefrontal cortices, and no correlation was found on the scalp. Taken together, this prospective intervention in a large cohort of DoC patients strengthens the validity of the proposed EEG signatures of consciousness, and is suggestive of a direct causal effect of tDCS on consciousness.

scholarly journals Consciousness and the Dimensionality of DOC Patients via the Generalized Ising Model

2020 ◽  
Vol 9 (5) ◽  
pp. 1342 ◽  
Author(s):  
Pubuditha M. Abeyasinghe ◽  
Marco Aiello ◽  
Emily S. Nichols ◽  
Carlo Cavaliere ◽  
Salvatore Fiorenza ◽  
...  
Keyword(s):  
Ising Model ◽  
Computational Modeling ◽  
Information Transfer ◽  
Brain Injuries ◽  
Structural Connectivity ◽  
Complex Data ◽  
Healthy Controls ◽  
Brain Functions ◽  
States Of Consciousness ◽  
Generalized Ising Model

The data from patients with severe brain injuries show complex brain functions. Due to the difficulties associated with these complex data, computational modeling is an especially useful tool to examine the structure–function relationship in these populations. By using computational modeling for patients with a disorder of consciousness (DoC), not only we can understand the changes of information transfer, but we also can test changes to different states of consciousness by hypothetically changing the anatomical structure. The generalized Ising model (GIM), which specializes in using structural connectivity to simulate functional connectivity, has been proven to effectively capture the relationship between anatomical structures and the spontaneous fluctuations of healthy controls (HCs). In the present study we implemented the GIM in 25 HCs as well as in 13 DoC patients diagnosed at three different states of consciousness. Simulated data were analyzed and the criticality and dimensionality were calculated for both groups; together, those values capture the level of information transfer in the brain. Ratifying previous studies, criticality was observed in simulations of HCs. We were also able to observe criticality for DoC patients, concluding that the GIM is generalizable for DoC patients. Furthermore, dimensionality increased for the DoC group as compared to healthy controls, and could distinguish different diagnostic groups of DoC patients.

scholarly journals The connectome spectrum as a canonical basis for a sparse representation of fast brain activity

2021 ◽  
Author(s):  
Joan Rué-Queralt ◽  
Katharina Glomb ◽  
David Pascucci ◽  
Sebastien Tourbier ◽  
Margherita Carboni ◽  
...  
Keyword(s):  
Visual Processing ◽  
Degrees Of Freedom ◽  
Large Scale ◽  
Functional Organization ◽  
Brain Activity ◽  
Structural Connectivity ◽  
Canonical Basis ◽  
Structural Mri ◽  
Brain Dynamics ◽  
Electrical Brain Activity

ABSTRACTThe functional organization of neural processes is constrained by the brain’s intrinsic structural connectivity. Here, we explore the potential of exploiting this structure in order to improve the signal representation properties of brain activity and its dynamics. Using a multi-modal imaging dataset (electroencephalography, structural MRI and diffusion MRI), we represent electrical brain activity at the cortical surface as a time-varying composition of harmonic modes of structural connectivity. The harmonic modes are termed connectome harmonics, and their representation is known as the connectome spectrum of the signal. We found that: first, the brain activity signal is more compactly represented by the connectome spectrum than by the traditional area-based representation; second, the connectome spectrum characterizes fast brain dynamics in terms of signal broadcasting profile, revealing different temporal regimes of integration and segregation that are consistent across participants. And last, the connectome spectrum characterises fast brain dynamics with fewer degrees of freedom than area-based signal representations. Specifically, we show that with the connectome spectrum representation, fewer dimensions are needed to capture the differences between low-level and high-level visual processing, and the topological properties of the signal. In summary, this work provides statistical, functional and topological evidence supporting that by accounting for the brain’s structural connectivity fosters a more comprehensive understanding of large-scale dynamic neural functioning.

scholarly journals Harmonic brain modes: a unifying framework for linking space and time in brain dynamics

2017 ◽  
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

AbstractA 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; i.e. 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, anaesthesia, 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.

scholarly journals Measures of states of consciousness during attentional and cognitive load

2019 ◽  
Author(s):  
André S. Nilsen ◽  
Bjørn E. Juel ◽  
Johan F. Storm
Keyword(s):  
Cognitive Load ◽  
Brain Activity ◽  
Effective Connectivity ◽  
Memory Task ◽  
Basic Research ◽  
Conscious State ◽  
Auditory Pattern ◽  
States Of Consciousness ◽  
Attentional Load ◽  
Brain States

AbstractBackgroundDeveloping and testing methods for reliably assessing states of consciousness in humans is important for both basic research and clinical purposes. Several potential measures, partly grounded in theoretical developments, have been proposed, and some of them seem to reliably distinguish between conscious and unconscious brain states. However, the degrees to which these measures may also be affected by changes in brain activity or conditions that can occur within conscious brain states have rarely been tested. In this study we test whether several of these measures are modulated by attentional load and related use of cognitive resources.MethodsWe recorded EEG from 12 participants while they passively received three types of stimuli: (1) transcranial magnetic stimulation (TMS) pulses (for measuring perturbational complexity), (2) auditory stimuli (for detection of auditory pattern deviants), or (3) audible clicks from a clock (spontaneous EEG, for measures of signal diversity and functional connectivity). We investigated whether the measures significantly differed between the passive condition and a attentional and cognitively demanding working memory task.ResultsOur results showed that in the attention-based auditory P3b ERP measure (global auditory pattern deviant) was significantly affected by increased attentional and cognitive load, while the various measures based on spontaneous and perturbed EEG were not affected.ConclusionMeasures of conscious state based on complexity, diversity, and effective connectivity, are not affected by attentional and cognitive load, suggesting that these measures can be used to test both for the presence and absence of consciousness.

Memory Processes, Aging, Cognitive Decline, and Neurodegenerative Diseases

2006 ◽  
Vol 11 (4) ◽  
pp. 304-311 ◽  
Author(s):  
Lars-Göran Nilsson
Keyword(s):  
Cognitive Impairment ◽  
Cognitive Decline ◽  
Neurodegenerative Disease ◽  
Genetic Markers ◽  
Brain Activity ◽  
Memory Performance ◽  
Modeling And Simulations ◽  
Aging And Health ◽  
Explained Variance ◽  
Different Levels

This paper presents four domains of markers that have been found to predict later cognitive impairment and neurodegenerative disease. These four domains are (1) data patterns of memory performance, (2) cardiovascular factors, (3) genetic markers, and (4) brain activity. The critical features of each domain are illustrated with data from the longitudinal Betula Study on memory, aging, and health ( Nilsson et al., 1997 ; Nilsson et al., 2004 ). Up to now, early signs regarding these domains have been examined one by one and it has been found that they are associated with later cognitive impairment and neurodegenerative disease. However, it was also found that each marker accounts for only a very small part of the total variance, implying that single markers should not be used as predictors for cognitive decline or neurodegenerative disease. It is discussed whether modeling and simulations should be used as tools to combine markers at different levels to increase the amount of explained variance.

Implications of Person Fluctuation for the Stability and Validity of Test Scores

Methodology ◽  
2006 ◽  
Vol 2 (4) ◽  
pp. 142-148 ◽  
Author(s):  
Pere J. Ferrando
Keyword(s):  
Item Response ◽  
Test Scores ◽  
Temporal Stability ◽  
Person Fit ◽  
Item Parameters ◽  
Individual Trait ◽  
The Stability ◽  
The Individual ◽  
Different Levels ◽  
Fluctuation Model

In the IRT person-fluctuation model, the individual trait levels fluctuate within a single test administration whereas the items have fixed locations. This article studies the relations between the person and item parameters of this model and two central properties of item and test scores: temporal stability and external validity. For temporal stability, formulas are derived for predicting and interpreting item response changes in a test-retest situation on the basis of the individual fluctuations. As for validity, formulas are derived for obtaining disattenuated estimates and for predicting changes in validity in groups with different levels of fluctuation. These latter formulas are related to previous research in the person-fit domain. The results obtained and the relations discussed are illustrated with an empirical example.

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