scholarly journals Learning to read the imprints of consciousness on global brain dynamics: an application to intra-operative monitoring of anesthesia

2017 ◽  
Author(s):  
Leandro M. Alonso ◽  
Guillermo Solovey ◽  
Toru Yanagawa ◽  
Alex Proekt ◽  
Guillermo A. Cecchi ◽  
...  
Keyword(s):  
High Performance ◽  
Conscious State ◽  
Brain Dynamics ◽  
Marginal Stability ◽  
Depth Of Anesthesia ◽  
Single Trial ◽  
Learning To Read ◽  
Global Brain ◽  
Operative Monitoring ◽  
State Of Activity

In daily life, in the operating room and in the laboratory, the operational way to assess wakefulness and consciousness is through responsiveness. A number of studies suggest that the awake, conscious state is not the default behavior of an assembly of neurons, but rather a very special state of activity that has to be actively maintained and curated to support its functional properties. Thus responsiveness is a feature that requires active maintenance, such as a homeostatic mechanism to balance excitation and inhibition. In this work we developed a method for monitoring such maintenance processes, focusing on a specific signature of their behavior derived from the theory of dynamical systems: stability analysis of dynamical modes. When such mechanisms are at work, their modes of activity are at marginal stability, neither damped (stable) nor exponentially growing (unstable) but rather hovering in between. We have previously shown that, conversely, under induction of anesthesia those modes become more stable and thus less responsive, then reversed upon emergence to wakefulness. We take advantage of this effect to build a single-trial classifier which detects whether a subject is awake or unconscious achieving high performance. We show that our approach can be developed into a mean for intra-operative monitoring of the depth of anesthesia, an application of fundamental importance to modern clinical practice.

Nonlinear Changes in Brain Dynamics during Emergence from Sevoflurane Anesthesia

2006 ◽  
Vol 105 (5) ◽  
pp. 927-935 ◽  
Author(s):  
Peter T. Walling ◽  
Kenneth N. Hicks
Keyword(s):  
Quantitative Analysis ◽  
Pilot Study ◽  
Real Time ◽  
Conscious State ◽  
Brain Dynamics ◽  
Depth Of Anesthesia ◽  
Sevoflurane Anesthesia ◽  
Electroencephalographic Signals

Background New software was used during a pilot study of nonlinear changes in the electroencephalogram during emergence from sevoflurane anesthesia. Methods Digitized electroencephalographic signals were recorded from bipolar forehead electrodes between 1.2 and 40 k s/sec. Trajectories derived from underlying attractors were displayed continuously, and attractor dimensions were estimated. Observations are reported from 13 patients emerging from sevoflurane anesthesia. Results Qualitative observations and quantitative analysis of the data demonstrated four dynamical stages during emergence from deep anesthesia to consciousness. Conclusions The dynamical stages of emergence from sevoflurane anesthesia into consciousness demonstrate a classic route toward chaos, but the presence of chaos in the conscious state remains unproven. These stages are apparent both pictorially and analytically. Pre-emergent attractor patterns are usually distinctive; their real-time display could be a useful adjunct to depth of anesthesia monitors because they may provide warning of an imminent return to consciousness.

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 Single-trial classification of awareness state during anesthesia by measuring critical dynamics of global brain activity

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Leandro M. Alonso ◽  
Guillermo Solovey ◽  
Toru Yanagawa ◽  
Alex Proekt ◽  
Guillermo A. Cecchi ◽  
...  
Keyword(s):  
Brain Activity ◽  
Critical Dynamics ◽  
Single Trial ◽  
Global Brain

scholarly journals Hierarchical disruption in the cortex of anesthetized monkeys as a new signature of consciousness loss

2020 ◽  
Author(s):  
Camilo Miguel Signorelli ◽  
Lynn Uhrig ◽  
Morten Kringelbach ◽  
Bechir Jarraya ◽  
Gustavo Deco
Keyword(s):  
Neural Activity ◽  
Resting State ◽  
Resting State Fmri ◽  
Hierarchical Organization ◽  
Brain Dynamics ◽  
Depth Of Anesthesia ◽  
Functional Changes ◽  
Cortical Hierarchy ◽  
Brain States ◽  
Structure Similarity

AbstractAnesthesia induces a reconfiguration of the repertoire of functional brain states leading to a high function-structure similarity. However, it is unclear how these functional changes lead to loss of consciousness. Here we suggest that the mechanism of conscious access is related to a general dynamical rearrangement of the intrinsic hierarchical organization of the cortex. To measure cortical hierarchy, we applied the Intrinsic Ignition analysis to resting-state fMRI data acquired in awake and anesthetized macaques. Our results reveal the existence of spatial and temporal hierarchical differences of neural activity within the macaque cortex, with a strong modulation by the depth of anesthesia and the employed anesthetic agent. Higher values of Intrinsic Ignition correspond to rich and flexible brain dynamics whereas lower values correspond to poor and rigid, structurally driven brain dynamics. Moreover, spatial and temporal hierarchical dimensions are disrupted in a different manner, involving different hierarchical brain networks. All together suggest that disruption of brain hierarchy is a new signature of consciousness loss.

scholarly journals Assessment of changes in the electrical activity of the brain during general anesthesia using portable electroencephalography

2020 ◽  
Vol 49 (2) ◽  
Author(s):  
Verónica Gaviria García ◽  
Daniel Loaiza López ◽  
Carolina Serna Rojas ◽  
Sara Ríos Arismendy ◽  
Eduardo Montoya Guevara ◽  
...  
Keyword(s):  
Electrical Activity ◽  
General Anesthesia ◽  
Brain Activity ◽  
Low Cost ◽  
Conscious State ◽  
Depth Of Anesthesia ◽  
Cross Sectional ◽  
Eyes Closed ◽  
Eeg Recordings ◽  
The Brain

Introduction: The analysis of the electrical activity of the brain using scalp electrodes with electroencephalography (EEG) could reveal the depth of anesthesia of a patient during surgery. However, conventional EEG equipment, due to its price and size, are not a practical option for the operating room and the commercial units used in surgery do not provide access to the electrical activity. The availability of low-cost portable technologies could provide for further research on the brain activity under general anesthesia and facilitate our quest for new markers of depth of anesthesia. Objective: To assess the capabilities of a portable EEG technology to capture brain rhythms associated with the state of consciousness and the general anesthesia status of surgical patients anesthetized with propofol. Methods: Observational, cross-sectional trial that reviewed 10 EEG recordings captured using OpenBCI portable low-cost technology, in female patients undergoing general anesthesia with propofol. The signal from the frontal electrodes was analyzed with spectral analysis and the results were compared against the reports in the literature. Results: The signal captured with frontal electrodes, particularly α rhythm, enabled the distinction between resting with eyes closed and with eyes opened in a conscious state, and sustained anesthesia during surgery. Conclusions: It is possible to differentiate a resting state from sustained anesthesia, replicating previous findings with conventional technologies. These results pave the way to the use of portable technologies such as the OpenBCI tool, to explore the brain dynamics during anesthesia.

scholarly journals Resting Brain Fluctuations Are Intrinsically Coupled to Visual Response Dynamics

2020 ◽  
Author(s):  
Michaël E Belloy ◽  
Jacob Billings ◽  
Anzar Abbas ◽  
Amrit Kashyap ◽  
Wen-Ju Pan ◽  
...  
Keyword(s):  
Reticular Formation ◽  
Visual Stimulation ◽  
Activity Patterns ◽  
Brain Dynamics ◽  
Brain State ◽  
Visual Response ◽  
Response Dynamics ◽  
Sensory Stimuli ◽  
Prominent Component ◽  
Global Brain

Abstract How do intrinsic brain dynamics interact with processing of external sensory stimuli? We sought new insights using functional magnetic resonance imaging to track spatiotemporal activity patterns at the whole brain level in lightly anesthetized mice, during both resting conditions and visual stimulation trials. Our results provide evidence that quasiperiodic patterns (QPPs) are the most prominent component of mouse resting brain dynamics. These QPPs captured the temporal alignment of anticorrelation between the default mode (DMN)- and task-positive (TPN)-like networks, with global brain fluctuations, and activity in neuromodulatory nuclei of the reticular formation. Specifically, the phase of QPPs prior to stimulation could significantly stratify subsequent visual response magnitude, suggesting QPPs relate to brain state fluctuations. This is the first observation in mice that dynamics of the DMN- and TPN-like networks, and particularly their anticorrelation, capture a brain state dynamic that affects sensory processing. Interestingly, QPPs also displayed transient onset response properties during visual stimulation, which covaried with deactivations in the reticular formation. We conclude that QPPs appear to capture a brain state fluctuation that may be orchestrated through neuromodulation. Our findings provide new frontiers to understand the neural processes that shape functional brain states and modulate sensory input processing.

scholarly journals Is Brain Dynamics Preserved in the EEG After Automated Artifact Removal? A Validation of the Fingerprint Method and the Automatic Removal of Cardiac Interference Approach Based on Microstate Analysis

2021 ◽  
Vol 14 ◽  
Author(s):  
Gabriella Tamburro ◽  
Pierpaolo Croce ◽  
Filippo Zappasodi ◽  
Silvia Comani
Keyword(s):  
Visual Inspection ◽  
Transition Probabilities ◽  
Brain Dynamics ◽  
Denoising Method ◽  
Eyes Closed ◽  
Eeg Recordings ◽  
Microstate Analysis ◽  
Global Brain ◽  
Automatic Removal

The assessment of a method for removing artifacts from electroencephalography (EEG) datasets often disregard verifying that global brain dynamics is preserved. In this study, we verified that the recently introduced optimized fingerprint method and the automatic removal of cardiac interference (ARCI) approach not only remove physiological artifacts from EEG recordings but also preserve global brain dynamics, as assessed with a new approach based on microstate analysis. We recorded EEG activity with a high-resolution EEG system during two resting-state conditions (eyes open, 25 volunteers, and eyes closed, 26 volunteers) known to exhibit different brain dynamics. After signal decomposition by independent component analysis (ICA), the independent components (ICs) related to eyeblinks, eye movements, myogenic interference, and cardiac electromechanical activity were identified with the optimized fingerprint method and ARCI approach and statistically compared with the outcome of the expert classification of the ICs by visual inspection. Brain dynamics in two different groups of denoised EEG signals, reconstructed after having removed the artifactual ICs identified by either visual inspection or the automated methods, was assessed by calculating microstate topographies, microstate metrics (duration, occurrence, and coverage), and directional predominance (based on transition probabilities). No statistically significant differences between the expert and the automated classification of the artifactual ICs were found (p > 0.05). Cronbach’s α values assessed the high test–retest reliability of microstate parameters for EEG datasets denoised by the automated procedure. The total EEG signal variance explained by the sets of global microstate templates was about 80% for all denoised EEG datasets, with no significant differences between groups. For the differently denoised EEG datasets in the two recording conditions, we found that the global microstate templates and the sequences of global microstates were very similar (p < 0.01). Descriptive statistics and Cronbach’s α of microstate metrics highlighted no significant differences and excellent consistency between groups (p > 0.5). These results confirm the ability of the optimized fingerprint method and the ARCI approach to effectively remove physiological artifacts from EEG recordings while preserving global brain dynamics. They also suggest that microstate analysis could represent a novel approach for assessing the ability of an EEG denoising method to remove artifacts without altering brain dynamics.

scholarly journals Global brain dynamics during social exclusion predict subsequent behavioral conformity

2018 ◽  
Vol 13 (2) ◽  
pp. 182-191 ◽  
Author(s):  
Nick Wasylyshyn ◽  
Brett Hemenway Falk ◽  
Javier O Garcia ◽  
Christopher N Cascio ◽  
Matthew Brook O’Donnell ◽  
...  
Keyword(s):  
Social Exclusion ◽  
Brain Dynamics ◽  
Global Brain

scholarly journals Global Brain Dynamics Embed the Motor Command Sequence of Caenorhabditis elegans

Cell ◽  
2015 ◽  
Vol 163 (3) ◽  
pp. 656-669 ◽  
Author(s):  
Saul Kato ◽  
Harris S. Kaplan ◽  
Tina Schrödel ◽  
Susanne Skora ◽  
Theodore H. Lindsay ◽  
...  
Keyword(s):  
Caenorhabditis Elegans ◽  
Motor Command ◽  
Brain Dynamics ◽  
Command Sequence ◽  
Global Brain
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