scholarly journals Imaging of neural oscillations with embedded inferential and group prevalence statistics

2017 ◽  
Author(s):  
Peter W. Donhauser ◽  
Esther Florin ◽  
Sylvain Baillet
Keyword(s):  
Brain Activity ◽  
Signal Strength ◽  
Brain Regions ◽  
Oscillatory Activity ◽  
Neural Oscillations ◽  
Source Reconstruction ◽  
Signal To Noise ◽  
Source Imaging ◽  
Methodological Challenges ◽  
Oscillatory Power

AbstractMagnetoencephalography and electroencephalography (MEG, EEG) are essential techniques for studying distributed signal dynamics in the human brain. In particular, the functional role of neural oscillations remains to be clarified. Imaging methods need to identify distinct brain regions that concurrently generate oscillatory activity, with adequate separation in space and time. Yet, spatial smearing and inhomogeneous signal-to-noise are challenging factors to source reconstruction from external sensor data. The detection of weak sources in the presence of stronger regional activity nearby is a typical complication of MEG/EEG source imaging. We propose a novel, hypothesis-driven source reconstruction approach to address these methodological challenges1. The imaging with embedded statistics (iES) method is a subspace scanning technique that constrains the mapping problem to the actual experimental design. A major benefit is that, regardless of signal strength, the contributions from all oscillatory sources, which activity is consistent with the tested hypothesis, are equalized in the statistical maps produced. We present extensive evaluations of iES on group MEG data, for mapping 1) induced oscillations using experimental contrasts, 2) ongoing narrow-band oscillations in the resting-state, 3) co-modulation of brain-wide oscillatory power with a seed region, and 4) co-modulation of oscillatory power with peripheral signals (pupil dilation). Along the way, we demonstrate several advantages of iES over standard source imaging approaches. These include the detection of oscillatory coupling without rejection of zero-phase coupling, and detection of ongoing oscillations in deeper brain regions, where signal-to-noise conditions are unfavorable. We also show that iES provides a separate evaluation of oscillatory synchronization and desynchronization in experimental contrasts, which has important statistical advantages. The flexibility of iES allows it to be adjusted to many experimental questions in systems neuroscience.Author summaryThe oscillatory activity of the brain produces a repertoire of signal dynamics that is rich and complex. Noninvasive recording techniques such as scalp magnetoencephalography and electroencephalography (MEG, EEG) are key methods to advance our comprehension of the role played by neural oscillations in brain functions and dysfunctions. Yet, there are methodological challenges in mapping these elusive components of brain activity that have remained unresolved. We introduce a new mapping technique, called imaging with embedded statistics (iES), which alleviates these difficulties. With iES, signal detection is constrained explicitly to the operational hypotheses of the study design. We show, in a variety of experimental contexts, how iES emphasizes the oscillatory components of brain activity, if any, that match the experimental hypotheses, even in deeper brain regions where signal strength is expected to be weak in MEG. Overall, the proposed method is a new imaging tool to respond to a wide range of neuroscience questions concerning the scaffolding of brain dynamics via anatomically-distributed neural oscillations.

scholarly journals Visual predictions, neural oscillations and naïve physics

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Blake W. Saurels ◽  
Wiremu Hohaia ◽  
Kielan Yarrow ◽  
Alan Johnston ◽  
Derek H. Arnold
Keyword(s):  
Brain Activity ◽  
Dynamic Environment ◽  
Predictive Performance ◽  
Brain Regions ◽  
Internal Models ◽  
Oscillatory Activity ◽  
Alpha Band ◽  
Core Property ◽  
Ball Tracking ◽  
Band Activity

AbstractPrediction is a core function of the human visual system. Contemporary research suggests the brain builds predictive internal models of the world to facilitate interactions with our dynamic environment. Here, we wanted to examine the behavioural and neurological consequences of disrupting a core property of peoples’ internal models, using naturalistic stimuli. We had people view videos of basketball and asked them to track the moving ball and predict jump shot outcomes, all while we recorded eye movements and brain activity. To disrupt people’s predictive internal models, we inverted footage on half the trials, so dynamics were inconsistent with how movements should be shaped by gravity. When viewing upright videos people were better at predicting shot outcomes, at tracking the ball position, and they had enhanced alpha-band oscillatory activity in occipital brain regions. The advantage for predicting upright shot outcomes scaled with improvements in ball tracking and occipital alpha-band activity. Occipital alpha-band activity has been linked to selective attention and spatially-mapped inhibitions of visual brain activity. We propose that when people have a more accurate predictive model of the environment, they can more easily parse what is relevant, allowing them to better target irrelevant positions for suppression—resulting in both better predictive performance and in neural markers of inhibited information processing.

scholarly journals To See, Not to See, or to See Poorly: Perceptual Quality and Guess Rate as a Function of Electroencephalography (EEG) Brain Activity in an Orientation Perception Task

2020 ◽  
Author(s):  
Sarah S. Sheldon ◽  
Kyle E. Mathewson
Keyword(s):  
Standard Deviation ◽  
Brain Activity ◽  
Oscillatory Activity ◽  
Perceptual Quality ◽  
Perception Task ◽  
Oscillatory Power ◽  
Within Subjects ◽  
Orientation Perception ◽  
Errors Analysis ◽  
Response Errors

AbstractBrain oscillations are known to modulate detection of visual stimuli, but it is unclear if this is due to increased guess rate or decreased precision of the mental representation. Here we estimated quality and guess rate as a function of electroencephalography (EEG) brain activity using an orientation perception task. Errors on each trial were quantified as the difference between the target orientation and the orientation reported by participants with a response stimulus. Response errors were fitted to standard mixed model by Zhang and Luck (2008) to quantify how participants’ guess rate and standard deviation parameters varied as a function of brain activity. Twenty-four participants were included in the analysis.Within subjects, the power and phase of delta and theta post-target oscillatory activity were found to vary along with performance on the orientation perception task in that greater power and phase coherence in the 2-5 Hz band range was measured in trials with more accurate responses. In addition, the phase of delta and theta correlated with the degree of response error while oscillatory power did not have a relationship with trial-by-trial response errors. Analysis of task-related alpha activity yielded no significant results implying that alpha oscillations do not play an important role in orientation perception at single trial level. Across participants, only the standard deviation parameter correlated with oscillatory power in the high alpha and low beta frequency ranges. These results indicate that post-target power is associated with the precision of mental representations rather than the guess rate, both across trials within subjects and across subjects.

scholarly journals Neural correlates of the DMT experience assessed with multivariate EEG

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Christopher Timmermann ◽  
Leor Roseman ◽  
Michael Schartner ◽  
Raphael Milliere ◽  
Luke T. J. Williams ◽  
...  
Keyword(s):  
Subjective Experience ◽  
Brain Activity ◽  
Plasma Concentrations ◽  
Oscillatory Activity ◽  
Visual Component ◽  
Eyes Closed ◽  
Drug Plasma Concentrations ◽  
Drug Plasma ◽  
Oscillatory Power ◽  
Signal Diversity

AbstractStudying transitions in and out of the altered state of consciousness caused by intravenous (IV) N,N-Dimethyltryptamine (DMT - a fast-acting tryptamine psychedelic) offers a safe and powerful means of advancing knowledge on the neurobiology of conscious states. Here we sought to investigate the effects of IV DMT on the power spectrum and signal diversity of human brain activity (6 female, 7 male) recorded via multivariate EEG, and plot relationships between subjective experience, brain activity and drug plasma concentrations across time. Compared with placebo, DMT markedly reduced oscillatory power in the alpha and beta bands and robustly increased spontaneous signal diversity. Time-referenced and neurophenomenological analyses revealed close relationships between changes in various aspects of subjective experience and changes in brain activity. Importantly, the emergence of oscillatory activity within the delta and theta frequency bands was found to correlate with the peak of the experience - particularly its eyes-closed visual component. These findings highlight marked changes in oscillatory activity and signal diversity with DMT that parallel broad and specific components of the subjective experience, thus advancing our understanding of the neurobiological underpinnings of immersive states of consciousness.

The melody of the immature brain

e-Neuroforum ◽  
2013 ◽  
Vol 19 (1) ◽  
Author(s):  
K. Sieben ◽  
H. Hartung ◽  
A. Wolff ◽  
I. Hanganu-Opatz
Keyword(s):  
Energy Efficient ◽  
Brain Activity ◽  
Sensory Perception ◽  
Brain Regions ◽  
Adult Brain ◽  
Oscillatory Activity ◽  
Recent Experimental Data ◽  
Immature Brain ◽  
Rodent Brain ◽  
The Brain

AbstractThe periodicity of brain activity became ob­vious even after the first attempt to capture it, with Hans Berger noting in 1929 that the “electroencephalogram represents a con­tinuous curve with continuous oscillations”. This rhythmicity of neural activity, the ‘melo­dy’ of the brain, has since gained interest as an energy-efficient strategy for the organisa­tion and communication both within and be­tween brain regions. While it is now known that these oscillations actively contribute to sensory perception and cognition in the adult brain, their function during development is still largely unknown. Recent experimental data revealed the ability of immature human and rodent brain to generate various patterns of electrical activity. Their properties and un­derlying mechanisms may vary among dif­ferent brain areas. However, these early pat­terns of activity seem to facilitate the refine­ment of cortical maps involved in sensory perception as well as mnemonic and execu­tive processing. Here we review recent stud­ies, which characterize the early oscillatory activity and demonstrate its impact on brain development.

scholarly journals Enhancing the brain's emotion regulation capacity with a randomised trial of a 5-week heart rate variability biofeedback intervention

2021 ◽  
Author(s):  
Kaoru Nashiro ◽  
Jungwon Min ◽  
Hyun Joo Yoo ◽  
Christine Cho ◽  
Shelby L Bachman ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Emotion Regulation ◽  
Brain Activity ◽  
Randomised Trial ◽  
Well Being ◽  
Brain Regions ◽  
Oscillatory Activity ◽  
High Heart Rate ◽  
Rate Oscillations

Heart rate variability is a robust biomarker of emotional well-being, consistent with the shared brain networks regulating emotion regulation and heart rate. While high heart rate oscillatory activity clearly indicates healthy regulatory brain systems, can increasing this oscillatory activity also enhance brain function? To test this possibility, we randomly assigned 106 young adult participants to one of two 5-week interventions involving daily biofeedback that either increased heart rate oscillations (Osc+ condition) or had little effect on heart rate oscillations (Osc- condition) and examined effects on brain activity during rest and during regulating emotion. In this healthy cohort, the two conditions did not differentially affect anxiety, depression or mood. However, the Osc+ intervention increased low-frequency heart rate variability and increased brain oscillatory dynamics and functional connectivity in emotion-related resting-state networks. It also increased down-regulation of activity in somatosensory brain regions during an emotion regulation task. The Osc- intervention did not have these effects. These findings indicate that heart rate oscillatory activity not only reflects the current state of regulatory brain systems but also changes how the brain operates beyond the moments of high oscillatory activity.

scholarly journals Coherent neural representation of hand speed in humans revealed by MEG imaging

2007 ◽  
Vol 104 (18) ◽  
pp. 7676-7681 ◽  
Author(s):  
Karim Jerbi ◽  
Jean-Philippe Lachaux ◽  
Karim N′Diaye ◽  
Dimitrios Pantazis ◽  
Richard M. Leahy ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Long Range ◽  
Large Scale ◽  
Primary Motor Cortex ◽  
Phase Synchronization ◽  
Motor Behavior ◽  
Brain Regions ◽  
Neural Representation ◽  
Oscillatory Activity ◽  
Source Imaging

The spiking activity of single neurons in the primate motor cortex is correlated with various limb movement parameters, including velocity. Recent findings obtained using local field potentials suggest that hand speed may also be encoded in the summed activity of neuronal populations. At this macroscopic level, the motor cortex has also been shown to display synchronized rhythmic activity modulated by motor behavior. Yet whether and how neural oscillations might be related to limb speed control is still poorly understood. Here, we applied magnetoencephalography (MEG) source imaging to the ongoing brain activity in subjects performing a continuous visuomotor (VM) task. We used coherence and phase synchronization to investigate the coupling between the estimated activity throughout the brain and the simultaneously recorded instantaneous hand speed. We found significant phase locking between slow (2- to 5-Hz) oscillatory activity in the contralateral primary motor cortex and time-varying hand speed. In addition, we report long-range task-related coupling between primary motor cortex and multiple brain regions in the same frequency band. The detected large-scale VM network spans several cortical and subcortical areas, including structures of the frontoparietal circuit and the cerebello–thalamo–cortical pathway. These findings suggest a role for slow coherent oscillations in mediating neural representations of hand kinematics in humans and provide further support for the putative role of long-range neural synchronization in large-scale VM integration. Our findings are discussed in the context of corticomotor communication, distributed motor encoding, and possible implications for brain–machine interfaces.

Neural Oscillations: Understanding a Neural Code of Pain

2020 ◽  
pp. 107385842095862
Author(s):  
Junseok A. Kim ◽  
Karen D. Davis
Keyword(s):  
Chronic Pain ◽  
Brain Regions ◽  
Oscillatory Activity ◽  
Neural Oscillations ◽  
Brain Functions ◽  
Disease States ◽  
Efficient Communication ◽  
Nociceptive Processing ◽  
The Brain

Neural oscillations play an important role in the integration and segregation of brain regions that are important for brain functions, including pain. Disturbances in oscillatory activity are associated with several disease states, including chronic pain. Studies of neural oscillations related to pain have identified several functional bands, especially alpha, beta, and gamma bands, implicated in nociceptive processing. In this review, we introduce several properties of neural oscillations that are important to understand the role of brain oscillations in nociceptive processing. We also discuss the role of neural oscillations in the maintenance of efficient communication in the brain. Finally, we discuss the role of neural oscillations in healthy and chronic pain nociceptive processing. These data and concepts illustrate the key role of regional and interregional neural oscillations in nociceptive processing underlying acute and chronic pains.

scholarly journals Neural correlates of the DMT experience as assessed via multivariate EEG

2019 ◽  
Author(s):  
Christopher Timmermann ◽  
Leor Roseman ◽  
Michael Schartner ◽  
Raphael Milliere ◽  
Luke Williams ◽  
...  
Keyword(s):  
Subjective Experience ◽  
Brain Activity ◽  
Plasma Concentrations ◽  
Oscillatory Activity ◽  
Visual Component ◽  
Eyes Closed ◽  
Drug Plasma Concentrations ◽  
Drug Plasma ◽  
Oscillatory Power ◽  
Signal Diversity

AbstractStudying transitions in and out of the altered state of consciousness caused by intravenous (IV) N,N-Dimethyltryptamine (DMT – a fast-acting tryptamine psychedelic) offers a safe and powerful means of advancing knowledge on the neurobiology of conscious states. Here we sought to investigate the effects of IV DMT on the power spectrum and signal diversity of human brain activity (6 female, 7 male) recorded via multivariate EEG, and plot relationships between subjective experience, brain activity and drug plasma concentrations across time. Compared with placebo, DMT markedly reduced oscillatory power in the alpha and beta bands and robustly increased spontaneous signal diversity. Time-referenced analyses revealed close relationships between changes in various aspects of subjective experience and changes in brain activity. Importantly, the emergence of oscillatory activity within the delta and theta frequency bands was found to correlate with the peak of the experience, and particularly its eyes-closed visual component. These findings highlight marked changes in oscillatory activity and signal diversity with DMT that parallel broad and specific components of the relevant subjective experience and thus further our understanding of the neurobiological underpinnings of immersive states of consciousness.

scholarly journals Structural templates for imaging EEG cortical sources in infants

2020 ◽  
Author(s):  
Christian O’Reilly ◽  
Eric Larson ◽  
John E. Richards ◽  
Mayada Elsabbagh
Keyword(s):  
Age Differences ◽  
Brain Activity ◽  
Multiple Time ◽  
List Type ◽  
Source Reconstruction ◽  
Pia Mater ◽  
Source Imaging ◽  
Cortical Sources ◽  
Topological Errors ◽  
Eeg Recordings

AbstractElectroencephalographic (EEG) source reconstruction is a powerful approach that helps to unmix scalp signals, mitigates volume conduction issues, and allows anatomical localization of brain activity. Algorithms used to estimate cortical sources require an anatomical model of the head and the brain, generally reconstructed using magnetic resonance imaging (MRI). When such scans are unavailable, a population average can be used for adults, but no average surface template is available for cortical source imaging in infants. To address this issue, this paper introduces a new series of 12 anatomical models for subjects between zero and 24 months of age. These templates are built from MRI averages and volumetric boundary element method segmentation of head tissues available as part of the Neurodevelopmental MRI Database. Surfaces separating the pia mater, the gray matter, and the white matter were estimated using the Infant FreeSurfer pipeline. The surface of the skin as well as the outer and inner skull surfaces were extracted using a cube marching algorithm followed by Laplacian smoothing and mesh decimation. We post-processed these meshes to correct topological errors and ensure watertight meshes. The use of these templates for source reconstruction is demonstrated and validated using 100 high-density EEG recordings in 7-month-old infants. Hopefully, these templates will support future studies based on EEG source reconstruction and functional connectivity in healthy infants as well as in clinical pediatric populations. Particularly, they should make EEG-based neuroimaging more feasible in longitudinal neurodevelopmental studies where it may not be possible to scan infants at multiple time points.Graphical abstractHighlightsTwelve surface templates for infants in the 0-2 years old range are proposedThese templates can be used for EEG source reconstruction using existing toolboxesA relatively modest impact of age differences was found in this age rangeCorrelation analysis confirms increasing source differences with age differencesSources reconstructed with infants versus adult templates significantly differ

scholarly journals When tension is exciting: an EEG exploration of excitement in music

2019 ◽  
Author(s):  
Amelia Turrell ◽  
Andrea R Halpern ◽  
Amir-Homayoun Javadi
Keyword(s):  
Strong Correlation ◽  
Positive Emotions ◽  
Brain Activity ◽  
Inferior Frontal Gyrus ◽  
Brain Regions ◽  
Middle Frontal Gyrus ◽  
Source Reconstruction ◽  
Eeg Data ◽  
Continuous Eeg ◽  
Before And After

AbstractMusic powerfully affects people’s emotions. In particular, moments of tension and deviation in musical features, including frequency, pitch, and rhythm (known as a Drop), are associated with positive emotions. However, the neuro-correlates of Drops emotive effects have never been explored. Thirty-six participants listened to music pieces containing a Drop, while undergoing continuous EEG, and rated felt excitement. Source reconstruction of EEG data showed significantly different activity in five brain regions before and after Drops: pre- and post-central gyri (PreCG and PostCG), and precuneus (PCUN) were more active before Drops and the inferior frontal gyrus (IFG), and middle frontal gyrus (MFG) were more active after Drops. Importantly, activity in the IFG and MFG showed a strong correlation with subjective excitement ratings during Drop apprehension. These results suggest expectancy is important to the induction of musical emotions, in agreement with the ITPRA theory. Specifically, when Drops are expected but do not occur immediately, moderate tension is induced. Strong positive emotions then ensue when expected deviations finally occur, due to contrastive valence. This is reflected in significant brain activity for regions associated with high arousing, pleasurable emotions, such as excitement.

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