Cognitive Control and Brain Network Dynamics during Word Generation Tasks Predicted Using a Novel Event-Related Deep Brain Activity Method

Brain connectivity studies of autism spectrum disorder (ASD) have historically relied on static measures of functional connectivity. Recent work has focused on identifying transient configurations of brain activity, yet several open questions remain regarding the nature of specific brain network dynamics in ASD. We used a dynamic coactivation pattern (CAP) approach to investigate the salience/midcingulo-insular (M-CIN) network, a locus of dysfunction in ASD, in a large multisite resting-state fMRI dataset collected from 172 children (ages 6–13 years; n = 75 ASD; n = 138 male). Following brain parcellation by using independent component analysis, dynamic CAP analyses were conducted and k-means clustering was used to determine transient activation patterns of the M-CIN. The frequency of occurrence of different dynamic CAP brain states was then compared between children with ASD and typically developing (TD) children. Dynamic brain configurations characterized by coactivation of the M-CIN with central executive/lateral fronto-parietal and default mode/medial fronto-parietal networks appeared less frequently in children with ASD compared with TD children. This study highlights the utility of time-varying approaches for studying altered M-CIN function in prevalent neurodevelopmental disorders. We speculate that altered M-CIN dynamics in ASD may underlie the inflexible behaviors commonly observed in children with the disorder.

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Progesterone modulates theta oscillations in the frontal-parietal network

10.1101/2020.01.16.909374 ◽

2020 ◽

Author(s):

Justin Riddle ◽

Sangtae Ahn ◽

Trevor McPherson ◽

Susan Girdler ◽

Flavio Frohlich

Keyword(s):

Cognitive Control ◽

Brain Activity ◽

Specific Effect ◽

Brain Network ◽

Theta Oscillations ◽

Network Activity ◽

Top Down ◽

Frontal Midline Theta ◽

Phase Amplitude ◽

Oscillatory Network

AbstractThe neuroactive metabolites of the steroid hormones progesterone (P4) and testosterone (T) are GABAergic modulators that influence cognitive control, yet the specific effect of P4 and T on brain network activity remains poorly understood. Here, we investigated if a fundamental oscillatory network activity pattern related to cognitive control, frontal midline theta (FMT) oscillations, are modulated by steroids hormones, P4 and T. We measured the concentration P4 and T using salivary enzyme immunoassay and FMT oscillations using high-density electroencephalography (EEG) during the eyes-open resting state in fifty-five healthy female and male participants. Electrical brain activity was analyzed using Morlet wavelet convolution, beamformer source localization, background noise spectral fitting, and phase amplitude coupling analysis. Steroid hormone concentrations and biological sex were used as predictors for scalp and source-estimated theta oscillations and for top-down theta-gamma phase amplitude coupling. Elevated concentrations of P4 predicted increased FMT oscillatory amplitude across both sexes, and no relationship was found with T. The positive correlation with P4 was specific to the frontal-midline electrodes and survived correction for the background noise of the brain. Using source localization, FMT oscillations were localized to the frontal-parietal network. Additionally, theta amplitude within the frontal-parietal network, but not the default mode network, positively correlated with P4 concentration. Finally, P4 concentration correlated with increased coupling between FMT phase and posterior gamma amplitude. Our results suggest that P4 concentration modulates brain activity via upregulation of theta oscillations in the frontal-parietal network and increased top-down control over posterior cortical sites.Significance StatementThe neuroactive metabolites of the steroid hormones progesterone (P4) and testosterone (T) are GABAergic modulators that influence cognitive control, yet the specific effect of P4 and T on brain network activity remains poorly understood. Here, we investigated if a fundamental oscillatory network activity pattern related to cognitive control, frontal midline theta (FMT) oscillations, are modulated by steroids hormones, P4 and T. Our results suggest that P4 concentration modulates brain activity via upregulation of theta oscillations in the frontal-parietal network and increased top-down control over posterior cortical sites.

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Mind-Wandering Tends to Occur under Low Perceptual Demands during Driving

Scientific Reports ◽

10.1038/srep21353 ◽

2016 ◽

Vol 6 (1) ◽

Cited By ~ 21

Author(s):

Chin-Teng Lin ◽

Chun-Hsiang Chuang ◽

Scott Kerick ◽

Tim Mullen ◽

Tzyy-Ping Jung ◽

...

Keyword(s):

Brain Activity ◽

Network Dynamics ◽

Sensory Information ◽

Significant Risk ◽

Brain Network ◽

Driver Assistance Systems ◽

Modes Of Processing ◽

Vehicle Motion ◽

On The Road ◽

Task Positive Network

Abstract Fluctuations in attention behind the wheel poses a significant risk for driver safety. During transient periods of inattention, drivers may shift their attention towards internally-directed thoughts or feelings at the expense of staying focused on the road. This study examined whether increasing task difficulty by manipulating involved sensory modalities as the driver detected the lane-departure in a simulated driving task would promote a shift of brain activity between different modes of processing, reflected by brain network dynamics on electroencephalographic sources. Results showed that depriving the driver of salient sensory information imposes a relatively more perceptually-demanding task, leading to a stronger activation in the task-positive network. When the vehicle motion feedback is available, the drivers may rely on vehicle motion to perceive the perturbations, which frees attentional capacity and tends to activate the default mode network. Such brain network dynamics could have major implications for understanding fluctuations in driver attention and designing advance driver assistance systems.

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Large-Scale Brain Network Dynamics Supporting Adolescent Cognitive Control

Journal of Neuroscience ◽

10.1523/jneurosci.1634-14.2014 ◽

2014 ◽

Vol 34 (42) ◽

pp. 14096-14107 ◽

Cited By ~ 64

Author(s):

D. B. Dwyer ◽

B. J. Harrison ◽

M. Yucel ◽

S. Whittle ◽

A. Zalesky ◽

...

Keyword(s):

Cognitive Control ◽

Large Scale ◽

Network Dynamics ◽

Brain Network

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Neural Mechanisms Underlying Adaptive Actions after Slips

Journal of Cognitive Neuroscience ◽

10.1162/jocn.2008.20117 ◽

2008 ◽

Vol 20 (9) ◽

pp. 1595-1610 ◽

Cited By ~ 93

Author(s):

Josep Marco-Pallarés ◽

Estela Camara ◽

Thomas F. Münte ◽

Antoni Rodríguez-Fornells

Keyword(s):

Cognitive Control ◽

Frontal Cortex ◽

Brain Activity ◽

Brain Network ◽

Neurophysiological Mechanism ◽

Electrical Brain Activity ◽

Dorsolateral Prefrontal ◽

Increase In Accuracy ◽

The Right ◽

Superior Frontal Cortex

An increase in cognitive control has been systematically observed in responses produced immediately after the commission of an error. Such responses show a delay in reaction time (post-error slowing) and an increase in accuracy. To characterize the neurophysiological mechanism involved in the adaptation of cognitive control, we examined oscillatory electrical brain activity by electroencephalogram and its corresponding neural network by event-related functional magnetic resonance imaging in three experiments. We identified a new oscillatory theta-beta component related to the degree of post-error slowing in the correct responses following an erroneous trial. Additionally, we found that the activity of the right dorsolateral prefrontal cortex, the right inferior frontal cortex, and the right superior frontal cortex was correlated with the degree of caution shown in the trial following the commission of an error. Given the overlap between this brain network and the regions activated by the need to inhibit motor responses in a stop-signal manipulation, we conclude that the increase in cognitive control observed after the commission of an error is implemented through the participation of an inhibitory mechanism.

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Brain network dynamics fingerprints are resilient to data heterogeneity

10.1101/2020.01.26.920637 ◽

2020 ◽

Author(s):

Tommaso Menara ◽

Giuseppe Lisi ◽

Fabio Pasqualetti ◽

Aurelio Cortese

Keyword(s):

Resting State ◽

Large Scale ◽

Brain Activity ◽

Network Dynamics ◽

Brain Network ◽

Fmri Data ◽

Dynamical Models ◽

Subject Specific ◽

Data Heterogeneity ◽

Data Collections

AbstractLarge multi-site neuroimaging datasets have significantly advanced our quest to understand brain-behaviour relationships and to develop biomarkers of psychiatric and neurodegenerative disorders. Yet, such data collections come at a cost, as the inevitable differences across samples may lead to biased or erroneous conclusions. Previous work has investigated this critical issue in resting-state functional magnetic resonance imaging (rs-fMRI) data in terms of effects on static measures, such as functional connectivity and brain parcellations. Here, we depart from prior approaches and utilize dynamical models to examine how diverse scanning factors in multi-site fMRI recordings affect our ability to infer the brain’s spatiotemporal wandering between large-scale networks of activity. Building upon this premise, we first confirm the emergence of robust subject-specific dynamical patterns of brain activity. Next, we exploit these individual fingerprints to show that scanning sessions belonging to different sites and days tend to induce high variability, while other factors, such as the scanner manufacturer or the number of coils, affect the same metrics to a lesser extent. These results concurrently indicate that we can recover the unique trajectories of brain activity changes in each individual, but also that our ability to infer such patterns is affected by how, where and when we try to do so.Author summaryWe investigate the important issue of data heterogeneity in large multi-site data collections of brain activity recordings. At a time in which appraising the source of variability in large datasets is gaining increasing attention, this study provides a novel point of view based on data-driven dynamical models. By employing subject-specific signatures of brain network dynamics, we find that certain scanning factors significantly affect the quality of resting-state fMRI data. More specifically, we first validate the existence of subject-specific brain dynamics fingerprints. As a proof of concept, we show that dynamical states can be estimated reliably, even across different datasets. Finally, we assess which scanning factors, and to what extent, influence the variability of such fingerprints.

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Beyond the AJR: “MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14468 individuals worldwide”

American Journal of Roentgenology ◽

10.2214/ajr.20.24985 ◽

2020 ◽

Author(s):

Cyrus A. Raji ◽

Tammie L.S. Benzinger

Keyword(s):

Brain Network ◽

Brain Age ◽

Deep Brain

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Applying a Sensing-Enabled System for Ensuring Safe Anterior Cingulate Deep Brain Stimulation for Pain

Brain Sciences ◽

10.3390/brainsci9070150 ◽

2019 ◽

Vol 9 (7) ◽

pp. 150 ◽

Cited By ~ 5

Author(s):

Yongzhi Huang ◽

Binith Cheeran ◽

Alexander L. Green ◽

Timothy J. Denison ◽

Tipu Z. Aziz

Keyword(s):

Deep Brain Stimulation ◽

Pain Relief ◽

Brain Stimulation ◽

Brain Activity ◽

Anterior Cingulate ◽

Chronic Therapy ◽

Provide Pain Relief ◽

Surgical Options ◽

Effective Pain Relief ◽

Deep Brain

Deep brain stimulation (DBS) of the anterior cingulate cortex (ACC) was offered to chronic pain patients who had exhausted medical and surgical options. However, several patients developed recurrent seizures. This work was conducted to assess the effect of ACC stimulation on the brain activity and to guide safe DBS programming. A sensing-enabled neurostimulator (Activa PC + S) allowing wireless recording through the stimulating electrodes was chronically implanted in three patients. Stimulation patterns with different amplitude levels and variable ramping rates were tested to investigate whether these patterns could provide pain relief without triggering after-discharges (ADs) within local field potentials (LFPs) recorded in the ACC. In the absence of ramping, AD activity was detected following stimulation at amplitude levels below those used in chronic therapy. Adjustment of stimulus cycling patterns, by slowly ramping on/off (8-s ramp duration), was able to prevent ADs at higher amplitude levels while maintaining effective pain relief. The absence of AD activity confirmed from the implant was correlated with the absence of clinical seizures. We propose that AD activity in the ACC could be a biomarker for the likelihood of seizures in these patients, and the application of sensing-enabled techniques has the potential to advance safer brain stimulation therapies, especially in novel targets.

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Brain reactivity to humorous films is affected by insomnia

SLEEP ◽

10.1093/sleep/zsab081 ◽

2021 ◽

Author(s):

Ernesto Sanz-Arigita ◽

Yannick Daviaux ◽

Marc Joliot ◽

Bixente Dilharreguy ◽

Jean-Arthur Micoulaud-Franchi ◽

...

Keyword(s):

Emotional Reactivity ◽

Brain Activity ◽

Brain Network ◽

Anterior Cingulate ◽

Neural Representation ◽

Cingulate Gyrus ◽

Anterior Cingulate Gyrus ◽

Left Caudate ◽

Neural Reactivity ◽

The Right

Abstract Study objectives Emotional reactivity to negative stimuli has been investigated in insomnia, but little is known about emotional reactivity to positive stimuli and its neural representation. Methods We used 3T fMRI to determine neural reactivity during the presentation of standardized short, 10-40-s, humorous films in insomnia patients (n=20, 18 females, aged 27.7 +/- 8.6 years) and age-matched individuals without insomnia (n=20, 19 females, aged 26.7 +/- 7.0 years), and assessed humour ratings through a visual analogue scale (VAS). Seed-based functional connectivity was analysed for left and right amygdala networks: group-level mixed-effects analysis (FLAME; FSL) was used to compare amygdala connectivity maps between groups. Results fMRI seed-based analysis of the amygdala revealed stronger neural reactivity in insomnia patients than in controls in several brain network clusters within the reward brain network, without humour rating differences between groups (p = 0.6). For left amygdala connectivity, cluster maxima were in the left caudate (Z=3.88), left putamen (Z=3.79) and left anterior cingulate gyrus (Z=4.11), while for right amygdala connectivity, cluster maxima were in the left caudate (Z=4.05), right insula (Z=3.83) and left anterior cingulate gyrus (Z=4.29). Cluster maxima of the right amygdala network were correlated with hyperarousal scores in insomnia patients only. Conclusions Presentation of humorous films leads to increased brain activity in the neural reward network for insomnia patients compared to controls, related to hyperarousal features in insomnia patients, in the absence of humor rating group differences. These novel findings may benefit insomnia treatment interventions.

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