Respiration modulates oscillatory neural network activity at rest

Mapping Intimacies ◽

10.1101/2020.04.23.057216 ◽

2020 ◽

Author(s):

Daniel S. Kluger ◽

Joachim Gross

Keyword(s):

Resting State ◽

Sagittal Plane ◽

Respiratory Control ◽

Network Activity ◽

Temporal Modulation ◽

Brain Oscillations ◽

Control Networks ◽

Oscillatory Neural Network ◽

Human Participants ◽

Phase Amplitude

AbstractDespite recent advances in understanding how respiration affects neural signalling to influence perception, cognition, and behaviour, it is yet unclear to what extent breathing modulates brain oscillations at rest. We acquired respiration and resting state magnetoencephalography (MEG) data from human participants to investigate if, where, and how respiration cyclically modulates oscillatory amplitudes (2 – 150 Hz). Using measures of phase-amplitude coupling, we show respiration-modulated brain oscillations (RMBOs) across all major frequency bands. Sources of these modulations spanned a widespread network of cortical and subcortical brain areas with distinct spectro-temporal modulation profiles. Globally, high-frequency gamma modulation increased with distance to the head centre, whereas delta and theta modulation decreased with height in the sagittal plane. Overall, we provide the first comprehensive mapping of RMBOs across the entire brain, highlighting respiration-brain coupling as a fundamental mechanism to shape neural processing within canonical resting-state and respiratory control networks.

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Respiration modulates oscillatory neural network activity at rest

PLoS Biology ◽

10.1371/journal.pbio.3001457 ◽

2021 ◽

Vol 19 (11) ◽

pp. e3001457

Author(s):

Daniel S. Kluger ◽

Joachim Gross

Keyword(s):

Resting State ◽

Respiratory Control ◽

Network Activity ◽

Brain Oscillations ◽

Control Networks ◽

Oscillatory Neural Network ◽

Human Participants ◽

Phase Amplitude ◽

Comprehensive Mapping ◽

Fundamental Mechanism

Despite recent advances in understanding how respiration affects neural signalling to influence perception, cognition, and behaviour, it is yet unclear to what extent breathing modulates brain oscillations at rest. We acquired respiration and resting state magnetoencephalography (MEG) data from human participants to investigate if, where, and how respiration cyclically modulates oscillatory amplitudes (2 to 150 Hz). Using measures of phase–amplitude coupling, we show respiration-modulated brain oscillations (RMBOs) across all major frequency bands. Sources of these modulations spanned a widespread network of cortical and subcortical brain areas with distinct spectrotemporal modulation profiles. Globally, delta and gamma band modulations varied with distance to the head centre, with stronger modulations at distal (versus central) cortical sites. Overall, we provide the first comprehensive mapping of RMBOs across the entire brain, highlighting respiration–brain coupling as a fundamental mechanism to shape neural processing within canonical resting state and respiratory control networks (RCNs).

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Frequency domains of resting state default mode network activity in schizophrenia

Klinische Neurophysiologie ◽

10.1055/s-0034-1371243 ◽

2014 ◽

Vol 45 (01) ◽

Author(s):

G Mingoia ◽

K Langbein ◽

M Dietzek ◽

G Wagner ◽

S Smesny ◽

...

Keyword(s):

Default Mode Network ◽

Resting State ◽

Network Activity ◽

Default Mode ◽

Frequency Domains

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Resting-state brain oscillations predict cognitive function in psychiatric disorders: A transdiagnostic machine learning approach

NeuroImage Clinical ◽

10.1016/j.nicl.2021.102617 ◽

2021 ◽

Vol 30 ◽

pp. 102617

Author(s):

Kaia Sargent ◽

UnYoung Chavez-Baldini ◽

Sarah L. Master ◽

Karin J.H. Verweij ◽

Anja Lok ◽

...

Keyword(s):

Machine Learning ◽

Cognitive Function ◽

Psychiatric Disorders ◽

Resting State ◽

Learning Approach ◽

Brain Oscillations ◽

Machine Learning Approach

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Sex Differences in Functional Connectivity Between Resting State Brain Networks in Autism Spectrum Disorder

Journal of Autism and Developmental Disorders ◽

10.1007/s10803-021-05191-6 ◽

2021 ◽

Author(s):

Vânia Tavares ◽

Luís Afonso Fernandes ◽

Marília Antunes ◽

Hugo Ferreira ◽

Diana Prata

Keyword(s):

Autism Spectrum Disorder ◽

Sex Differences ◽

Resting State ◽

Brain Connectivity ◽

Autism Spectrum ◽

Spectrum Disorder ◽

Control Networks ◽

Highly Sensitive ◽

Female Specific ◽

Main Effects

AbstractFunctional brain connectivity (FBC) has previously been examined in autism spectrum disorder (ASD) between-resting-state networks (RSNs) using a highly sensitive and reproducible hypothesis-free approach. However, results have been inconsistent and sex differences have only recently been taken into consideration using this approach. We estimated main effects of diagnosis and sex and a diagnosis by sex interaction on between-RSNs FBC in 83 ASD (40 females/43 males) and 85 typically developing controls (TC; 43 females/42 males). We found increased connectivity between the default mode (DM) and (a) the executive control networks in ASD (vs. TC); (b) the cerebellum networks in males (vs. females); and (c) female-specific altered connectivity involving visual, language and basal ganglia (BG) networks in ASD—in suggestive compatibility with ASD cognitive and neuroscientific theories.

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Detecting functional connectivity disruptions in a translational pediatric traumatic brain injury porcine model using resting-state and task-based fMRI

Scientific Reports ◽

10.1038/s41598-021-91853-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Gregory Simchick ◽

Kelly M. Scheulin ◽

Wenwu Sun ◽

Sydney E. Sneed ◽

Madison M. Fagan ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Functional Connectivity ◽

Resting State ◽

Correlation Coefficients ◽

Brain Network ◽

Network Activity ◽

Anatomical Structures ◽

Healthy Control ◽

And Task

AbstractFunctional magnetic resonance imaging (fMRI) has significant potential to evaluate changes in brain network activity after traumatic brain injury (TBI) and enable early prognosis of potential functional (e.g., motor, cognitive, behavior) deficits. In this study, resting-state and task-based fMRI (rs- and tb-fMRI) were utilized to examine network changes in a pediatric porcine TBI model that has increased predictive potential in the development of novel therapies. rs- and tb-fMRI were performed one day post-TBI in piglets. Activation maps were generated using group independent component analysis (ICA) and sparse dictionary learning (sDL). Activation maps were compared to pig reference functional connectivity atlases and evaluated using Pearson spatial correlation coefficients and mean ratios. Nonparametric permutation analyses were used to determine significantly different activation areas between the TBI and healthy control groups. Significantly lower Pearson values and mean ratios were observed in the visual, executive control, and sensorimotor networks for TBI piglets compared to controls. Significant differences were also observed within several specific individual anatomical structures within each network. In conclusion, both rs- and tb-fMRI demonstrate the ability to detect functional connectivity disruptions in a translational TBI piglet model, and these disruptions can be traced to specific affected anatomical structures.

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Binge drinking is associated with altered resting state functional connectivity of reward-salience and top down control networks

Brain Imaging and Behavior ◽

10.1007/s11682-019-00107-6 ◽

2019 ◽

Vol 14 (5) ◽

pp. 1731-1746 ◽

Cited By ~ 1

Author(s):

Donatello Arienzo ◽

Joseph P. Happer ◽

Sean M. Molnar ◽

Austin Alderson-Myers ◽

Ksenija Marinkovic

Keyword(s):

Functional Connectivity ◽

Binge Drinking ◽

Resting State ◽

Resting State Functional Connectivity ◽

Top Down ◽

Control Networks

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Error-related Persistence of Motor Activity in Resting-state Networks

Journal of Cognitive Neuroscience ◽

10.1162/jocn_a_01323 ◽

2018 ◽

Vol 30 (12) ◽

pp. 1883-1901 ◽

Cited By ~ 2

Author(s):

Nicolò F. Bernardi ◽

Floris T. Van Vugt ◽

Ricardo Ruy Valle-Mena ◽

Shahabeddin Vahdat ◽

David J. Ostry

Keyword(s):

Motor Learning ◽

Resting State ◽

Brain Connectivity ◽

Brain Activity ◽

Brain Networks ◽

Neural Activation ◽

Resting State Functional Connectivity ◽

Movement Training ◽

Movement Error ◽

Human Participants

The relationship between neural activation during movement training and the plastic changes that survive beyond movement execution is not well understood. Here we ask whether the changes in resting-state functional connectivity observed following motor learning overlap with the brain networks that track movement error during training. Human participants learned to trace an arched trajectory using a computer mouse in an MRI scanner. Motor performance was quantified on each trial as the maximum distance from the prescribed arc. During learning, two brain networks were observed, one showing increased activations for larger movement error, comprising the cerebellum, parietal, visual, somatosensory, and cortical motor areas, and the other being more activated for movements with lower error, comprising the ventral putamen and the OFC. After learning, changes in brain connectivity at rest were found predominantly in areas that had shown increased activation for larger error during task, specifically the cerebellum and its connections with motor, visual, and somatosensory cortex. The findings indicate that, although both errors and accurate movements are important during the active stage of motor learning, the changes in brain activity observed at rest primarily reflect networks that process errors. This suggests that error-related networks are represented in the initial stages of motor memory formation.

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Evidence against altered excitatory/inhibitory balance in the posteromedial cortex of young adult APOE E4 carriers: a resting state 1H-MRS study

10.1101/2021.05.12.443879 ◽

2021 ◽

Author(s):

Alison G Costigan ◽

Katja Umla-Runge ◽

C John Evans ◽

Rachel Raybould ◽

Kim S Graham ◽

...

Keyword(s):

Resting State ◽

Genetic Risk ◽

Occipital Cortex ◽

Network Activity ◽

Resonance Spectroscopy ◽

1H Mrs ◽

Gaba A ◽

Spatio Temporal ◽

E4 Allele

A strategy to gain insight into early changes that may predispose people to Alzheimer's disease is to study the brains of younger cognitively healthy people that are at increased genetic risk of AD. The Apolipoprotein (APOE) E4 allele is the strongest genetic risk factor for AD, and several neuroimaging studies comparing APOE E4 carriers with non-carriers at age ~20-30 have detected hyperactivity (or reduced deactivation) in posteromedial cortex (PMC), a key hub of the default network (DN) which has a high susceptibility to early amyloid deposition in AD. Transgenic mouse models suggest such early network activity alterations may result from altered excitatory/inhibitory (E/I) balance, but this is yet to be examined in humans. Here we test the hypothesis that PMC fMRI hyperactivity could be underpinned by altered levels of excitatory (glutamate) and/or inhibitory (GABA) neurotransmitters in this brain region. Forty-seven participants (20 APOE E4 carriers and 27 non-carriers) aged 18-25 underwent resting-state proton magnetic resonance spectroscopy (1H-MRS), a non-invasive neuroimaging technique to measure glutamate and GABA in vivo. Metabolites were measured in a PMC voxel of interest and in a comparison voxel in the occipital cortex (OCC). There was no difference in either glutamate or GABA between the E4 carriers and non-carriers in either MRS voxel, nor in the ratio of glutamate to GABA, a measure of E/I balance. Default Bayesian t-tests revealed evidence in support of this null finding. Results suggest that PMC hyperactivity in APOE E4 carriers is unlikely to be associated with, or indeed may precede, alterations in local resting-state PMC neurotransmitters, thus informing the spatio-temporal order and the cause/effect dynamic of neuroimaging differences in APOE E4 carriers.

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