scholarly journals Age-dependent electroencephalogram (EEG) patterns during sevoflurane general anesthesia in infants

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Laura Cornelissen ◽  
Seong-Eun Kim ◽  
Patrick L Purdon ◽  
Emery N Brown ◽  
Charles B Berde
Keyword(s):  
General Anesthesia ◽  
Temporal Dynamics ◽  
Brain Activity ◽  
Body Movement ◽  
Video Recording ◽  
Brain State ◽  
Alpha Power ◽  
State Monitoring ◽  
Spatio Temporal ◽  
Electroencephalogram Eeg

Electroencephalogram (EEG) approaches may provide important information about developmental changes in brain-state dynamics during general anesthesia. We used multi-electrode EEG, analyzed with multitaper spectral methods and video recording of body movement to characterize the spatio-temporal dynamics of brain activity in 36 infants 0–6 months old when awake, and during maintenance of and emergence from sevoflurane general anesthesia. During maintenance: (1) slow-delta oscillations were present in all ages; (2) theta and alpha oscillations emerged around 4 months; (3) unlike adults, all infants lacked frontal alpha predominance and coherence. Alpha power was greatest during maintenance, compared to awake and emergence in infants at 4–6 months. During emergence, theta and alpha power decreased with decreasing sevoflurane concentration in infants at 4–6 months. These EEG dynamic differences are likely due to developmental factors including regional differences in synaptogenesis, glucose metabolism, and myelination across the cortex. We demonstrate the need to apply age-adjusted analytic approaches to develop neurophysiologic-based strategies for pediatric anesthetic state monitoring.

scholarly journals Distinct Montages of Slow Oscillatory Transcranial Direct Current Stimulation (so-tDCS) Constitute Different Mechanisms during Quiet Wakefulness

2019 ◽  
Vol 9 (11) ◽  
pp. 324
Author(s):  
Ping Koo-Poeggel ◽  
Verena Böttger ◽  
Lisa Marshall
Keyword(s):  
Slow Wave Sleep ◽  
Brain Activity ◽  
Electrode Placement ◽  
Brain State ◽  
Electrode Pair ◽  
Alpha Power ◽  
Applied Current ◽  
Large Power ◽  
Quiet Wakefulness ◽  
Eyes Closed

Slow oscillatory- (so-) tDCS has been applied in many sleep studies aimed to modulate brain rhythms of slow wave sleep and memory consolidation. Yet, so-tDCS may also modify coupled oscillatory networks. Efficacy of weak electric brain stimulation is however variable and dependent upon the brain state at the time of stimulation (subject and/or task-related) as well as on stimulation parameters (e.g., electrode placement and applied current. Anodal so-tDCS was applied during wakefulness with eyes-closed to examine efficacy when deviating from the dominant brain rhythm. Additionally, montages of different electrodes size and applied current strength were used. During a period of quiet wakefulness bilateral frontolateral stimulation (F3, F4; return electrodes at ipsilateral mastoids) was applied to two groups: ‘Group small’ (n = 16, f:8; small electrodes: 0.50 cm2; maximal current per electrode pair: 0.26 mA) and ‘Group Large’ (n = 16, f:8; 35 cm2; 0.35 mA). Anodal so-tDCS (0.75 Hz) was applied in five blocks of 5 min epochs with 1 min stimulation-free epochs between the blocks. A finger sequence tapping task (FSTT) was used to induce comparable cortical activity across sessions and subject groups. So-tDCS resulted in a suppression of alpha power over the parietal cortex. Interestingly, in Group Small alpha suppression occurred over the standard band (8–12 Hz), whereas for Group Large power of individual alpha frequency was suppressed. Group Small also revealed a decrease in FSTT performance at retest after stimulation. It is essential to include concordant measures of behavioral and brain activity to help understand variability and poor reproducibility in oscillatory-tDCS studies.

The Temporal Dynamics of Spontaneous Emotional Brain States and Their Implications for Mental Health

2021 ◽  
pp. 1-14
Author(s):  
Philip A. Kragel ◽  
Ahmad R. Hariri ◽  
Kevin S. LaBar
Keyword(s):  
Mental Health ◽  
Temporal Dynamics ◽  
Brain Activity ◽  
Resting State Fmri ◽  
State Transitions ◽  
Brain State ◽  
Emotional States ◽  
Affective States ◽  
Emotional Responding ◽  
Brain States

Abstract Temporal processes play an important role in elaborating and regulating emotional responding during routine mind wandering. However, it is unknown whether the human brain reliably transitions among multiple emotional states at rest and how psychopathology alters these affect dynamics. Here, we combined pattern classification and stochastic process modeling to investigate the chronometry of spontaneous brain activity indicative of six emotions (anger, contentment, fear, happiness, sadness, and surprise) and a neutral state. We modeled the dynamic emergence of these brain states during resting-state fMRI and validated the results across two population cohorts—the Duke Neurogenetics Study and the Nathan Kline Institute Rockland Sample. Our findings indicate that intrinsic emotional brain dynamics are effectively characterized as a discrete-time Markov process, with affective states organized around a neutral hub. The centrality of this network hub is disrupted in individuals with psychopathology, whose brain state transitions exhibit greater inertia and less frequent resetting from emotional to neutral states. These results yield novel insights into how the brain signals spontaneous emotions and how alterations in their temporal dynamics contribute to compromised mental health.

scholarly journals Lempel-Ziv complexity of cortical activity during sleep and waking in rats

2015 ◽  
Vol 113 (7) ◽  
pp. 2742-2752 ◽  
Author(s):  
Daniel Abásolo ◽  
Samantha Simons ◽  
Rita Morgado da Silva ◽  
Giulio Tononi ◽  
Vladyslav V. Vyazovskiy
Keyword(s):  
Sleep Deprivation ◽  
Eye Movement ◽  
Brain Activity ◽  
Temporal Structure ◽  
Nrem Sleep ◽  
Brain State ◽  
Rapid Eye Movement ◽  
Sleep Regulation ◽  
Spatio Temporal ◽  
Underlying Mechanisms

Understanding the dynamics of brain activity manifested in the EEG, local field potentials (LFP), and neuronal spiking is essential for explaining their underlying mechanisms and physiological significance. Much has been learned about sleep regulation using conventional EEG power spectrum, coherence, and period-amplitude analyses, which focus primarily on frequency and amplitude characteristics of the signals and on their spatio-temporal synchronicity. However, little is known about the effects of ongoing brain state or preceding sleep-wake history on the nonlinear dynamics of brain activity. Recent advances in developing novel mathematical approaches for investigating temporal structure of brain activity based on such measures, as Lempel-Ziv complexity (LZC) can provide insights that go beyond those obtained with conventional techniques of signal analysis. Here, we used extensive data sets obtained in spontaneously awake and sleeping adult male laboratory rats, as well as during and after sleep deprivation, to perform a detailed analysis of cortical LFP and neuronal activity with LZC approach. We found that activated brain states—waking and rapid eye movement (REM) sleep are characterized by higher LZC compared with non-rapid eye movement (NREM) sleep. Notably, LZC values derived from the LFP were especially low during early NREM sleep after sleep deprivation and toward the middle of individual NREM sleep episodes. We conclude that LZC is an important and yet largely unexplored measure with a high potential for investigating neurophysiological mechanisms of brain activity in health and disease.

scholarly journals Movie viewing elicits rich and reliable brain state dynamics

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Johan N. van der Meer ◽  
Michael Breakspear ◽  
Luke J. Chang ◽  
Saurabh Sonkusare ◽  
Luca Cocchi
Keyword(s):  
Resting State ◽  
Brain Function ◽  
Temporal Dynamics ◽  
Brain Activity ◽  
State Transitions ◽  
Brain State ◽  
The Social ◽  
Brain States ◽  
Functional States ◽  
Intrinsic Brain Activity

Abstract Adaptive brain function requires that sensory impressions of the social and natural milieu are dynamically incorporated into intrinsic brain activity. While dynamic switches between brain states have been well characterised in resting state acquisitions, the remodelling of these state transitions by engagement in naturalistic stimuli remains poorly understood. Here, we show that the temporal dynamics of brain states, as measured in fMRI, are reshaped from predominantly bistable transitions between two relatively indistinct states at rest, toward a sequence of well-defined functional states during movie viewing whose transitions are temporally aligned to specific features of the movie. The expression of these brain states covaries with different physiological states and reflects subjectively rated engagement in the movie. In sum, a data-driven decoding of brain states reveals the distinct reshaping of functional network expression and reliable state transitions that accompany the switch from resting state to perceptual immersion in an ecologically valid sensory experience.

scholarly journals Методика пространственно-временного анализа электрической активности головного мозга

2020 ◽  
Vol 46 (11) ◽  
pp. 39
Author(s):  
А.Е. Руннова ◽  
М.О. Журавлев ◽  
А.Р. Киселёв ◽  
А.О. Сельский
Keyword(s):  
Wavelet Transform ◽  
Electrical Activity ◽  
Continuous Wavelet Transform ◽  
Temporal Dynamics ◽  
Brain Activity ◽  
Activity Patterns ◽  
Spatial Dynamics ◽  
Continuous Wavelet ◽  
Brain Electrical Activity ◽  
Spatio Temporal

In the framework of this work a new method based on continuous wavelet transform was proposed for analyzing the spatio-temporal dynamics of brain activity patterns. We described the example of this method application for the analysis of brain electrical activity signals. It is shown that this method has the ability to visually detect the occurrence and spatial dynamics of frequency patterns.

scholarly journals Spotting the path that leads nowhere: Modulation of human theta and alpha oscillations induced by trajectory changes during navigation

2018 ◽  
Author(s):  
Amir-Homayoun Javadi ◽  
Eva Zita Patai ◽  
Aaron Margois ◽  
Heng-Ru M. Tan ◽  
Darshan Kumaran ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Brain Activity ◽  
Cognitive Map ◽  
Lava Flows ◽  
Neural Dynamics ◽  
Alpha Power ◽  
Neural Basis ◽  
Alpha Oscillations ◽  
Fine Grained ◽  
Desert Island

AbstractThe capacity to take efficient detours and exploit novel shortcuts during navigation is thought to be supported by a cognitive map of the environment. Despite advances in understanding the neural basis of the cognitive map, little is known about the neural dynamics associated with detours and shortcuts. Here, we recorded magnetoencephalography from humans as they navigated a virtual desert island riven by shifting lava flows. The task probed their ability to take efficient detours and shortcuts to remembered goals. We report modulation in event-related fields and theta power as participants identified real shortcuts and differentiated these from false shortcuts that led along suboptimal paths. Additionally, we found that a decrease in alpha power preceded ‘back-tracking’ where participants spontaneously turned back along a previous path. These findings help advance our understanding of the fine-grained temporal dynamics of human brain activity during navigation and support the development of models of brain networks that support navigation.

scholarly journals From categories to dimensions: spatio-temporal dynamics of the cerebral representations of emotion in voice

2018 ◽  
Author(s):  
Bruno L. Giordano ◽  
Whiting Whiting ◽  
Nikolaus Kriegeskorte ◽  
Sonja A. Kotz ◽  
Pascal Belin ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Brain Activity ◽  
Functional Magnetic Resonance ◽  
Emotional Stimuli ◽  
Cerebral Activity ◽  
Dimensional Models ◽  
Spatio Temporal ◽  
Perceptual Assessment ◽  
The Voice ◽  
Perceived Emotion

AbstractWhether the human brain represents emotional stimuli as discrete categories or continuous dimensions is still widely debated. Here we directly contrasted the power of categorical and dimensional models at explaining behavior and cerebral activity in the context of perceived emotion in the voice. We combined functional magnetic resonance imaging (fMRI) and magneto-encephalography (MEG) to measure with high spatiotemporal precision the dynamics of cerebral activity in participants who listened to voice stimuli expressing a range of emotions. The participants also provided a detailed perceptual assessment of the stimuli. By using representational similarity analysis (RSA), we show that the participants’ perceptual representation of the stimuli was initially dominated by discrete categories and an early (<200ms) cerebral response. These responses showed significant associations between brain activity and the categorical model in the auditory cortex starting as early as 77ms. Furthermore, we observed strong associations between the arousal and valence dimensions and activity in several cortical and subcortical areas at later latencies (>500ms). Our results thus show that both categorical and dimensional models account for patterns of cerebral responses to emotions in voices but with a different timeline and detail as to how these patterns evolve from discrete categories to progressively refined continuous dimensions.One Sentence Summary: Emotions expressed in the voice are instantly categorized in cortical processing and their distinct qualities are refined dimensionally only later on.

scholarly journals Dynamics of Alpha Control: Preparatory Suppression of Posterior Alpha Oscillations by Frontal Modulators Revealed with Combined EEG and Event-related Optical Signal

2014 ◽  
Vol 26 (10) ◽  
pp. 2400-2415 ◽  
Author(s):  
Kyle E. Mathewson ◽  
Diane M. Beck ◽  
Tony Ro ◽  
Edward L. Maclin ◽  
Kathy A. Low ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Brain Activity ◽  
Conscious Experience ◽  
Optical Signal ◽  
Alpha Power ◽  
Top Down ◽  
Spatiotemporal Resolution ◽  
Attention Networks ◽  
Alpha Oscillations ◽  
Eeg Alpha

We investigated the dynamics of brain processes facilitating conscious experience of external stimuli. Previously, we proposed that alpha (8–12 Hz) oscillations, which fluctuate with both sustained and directed attention, represent a pulsed inhibition of ongoing sensory brain activity. Here we tested the prediction that inhibitory alpha oscillations in visual cortex are modulated by top–down signals from frontoparietal attention networks. We measured modulations in phase-coherent alpha oscillations from superficial frontal, parietal, and occipital cortices using the event-related optical signal (EROS), a measure of neuronal activity affording high spatiotemporal resolution, along with concurrently recorded EEG, while participants performed a visual target detection task. The pretarget alpha oscillations measured with EEG and EROS from posterior areas were larger for subsequently undetected targets, supporting alpha's inhibitory role. Using EROS, we localized brain correlates of these awareness-related alpha oscillations measured at the scalp to the cuneus and precuneus. Crucially, EROS alpha suppression correlated with posterior EEG alpha power across participants. Sorting the EROS data based on EEG alpha power quartiles to investigate alpha modulators revealed that suppression of posterior alpha was preceded by increased activity in regions of the dorsal attention network and decreased activity in regions of the cingulo-opercular network. Cross-correlations revealed the temporal dynamics of activity within these preparatory networks before posterior alpha modulation. The novel combination of EEG and EROS afforded localization of the sources and correlates of alpha oscillations and their temporal relationships, supporting our proposal that top–down control from attention networks modulates both posterior alpha and awareness of visual stimuli.

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