scholarly journals Infant functional networks are modulated by state of consciousness and circadian rhythm

2021 ◽  
pp. 1-36
Author(s):  
Rachel J. Smith ◽  
Ehsan Alipourjeddi ◽  
Cristal Garner ◽  
Amy L. Maser ◽  
Daniel W. Shrey ◽  
...  
Keyword(s):  
Circadian Rhythm ◽  
Functional Connectivity ◽  
Principal Component ◽  
Time Of Day ◽  
Clustering Coefficient ◽  
Functional Networks ◽  
Temporal Properties ◽  
Healthy Infants ◽  
Infant Brain ◽  
Eeg Recordings

Abstract Functional connectivity networks are valuable tools for studying development, cognition, and disease in the infant brain. In adults, such networks are modulated by the state of consciousness and the circadian rhythm; however, it is unknown if infant brain networks exhibit similar variation, given the unique temporal properties of infant sleep and circadian patterning. To address this, we analyzed functional connectivity networks calculated from long-term EEG recordings (average duration 20.8 hours) from 19 healthy infants. Networks were subjectspecific, as inter-subject correlations between weighted adjacency matrices were low. However, within individual subjects, both sleep and wake networks were stable over time, with stronger functional connectivity during sleep than wakefulness. Principal component analysis revealed the presence of two dominant networks; visual sleep scoring confirmed that these corresponded to sleep and wakefulness. Lastly, we found that network strength, degree, clustering coefficient, and path length significantly varied with time of day, when measured in either wakefulness or sleep at the group level. Together, these results suggest that modulation of healthy functional networks occurs over ~24 hours and is robust and repeatable. Accounting for such temporal periodicities may improve the physiological interpretation and use of functional connectivity analysis to investigate brain function in health and disease.

scholarly journals Temporal dynamics of functional networks in long-term infant scalp EEG

2020 ◽  
Author(s):  
Rachel J. Smith ◽  
Ehsan Alipourjeddi ◽  
Cristal Garner ◽  
Amy L. Maser ◽  
Daniel W. Shrey ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Time Scales ◽  
Temporal Dynamics ◽  
Time Of Day ◽  
Term Infant ◽  
Clustering Coefficient ◽  
Functional Networks ◽  
Principle Components Analysis ◽  
Long Time

AbstractHuman functional connectivity networks are modulated on time scales ranging from milliseconds to days. Rapid changes in connectivity over short time scales are a feature of healthy cognitive function, and variability over long time scales can impact the likelihood of seizure occurrence. However, relatively little is known about modulation of healthy functional networks over long time scales. To address this, we analyzed functional connectivity networks calculated from long-term EEG recordings from 19 healthy infants. Networks were subject-specific, as inter-subject correlations between weighted adjacency matrices were low. However, within individual subjects, both sleep and wake networks were stable over time, with stronger functional connectivity during sleep than wakefulness. This enabled automatic separation of wakefulness and sleep states via principle components analysis of the functional network time series, with median classification accuracy of 91%. Lastly, we found that network strength, degree, clustering coefficient, and path length significantly varied with time of day, when measured in both wakefulness and sleep. Together, these results suggest that modulation of healthy functional networks occurs over long timescales and is robust and repeatable. Accounting for such temporal periodicities may improve the physiological interpretation and use of functional connectivity analysis to investigate brain function in health and disease.

scholarly journals Top-down contribution to motor network reorganization during action preparation

2021 ◽  
Author(s):  
Alberto Pisoni ◽  
Valentina Bianco ◽  
Eleonora Arrigoni ◽  
Francesco Di Russo ◽  
Leonor Josefina Romero Lauro
Keyword(s):  
Functional Connectivity ◽  
Time Course ◽  
Cortical Excitability ◽  
Stimulus Onset ◽  
Functional Networks ◽  
Beta Band ◽  
Top Down ◽  
Action Preparation ◽  
Eeg Recordings ◽  
Changes Over Time

It is unclear whether the Bereitschaftspotential (BP) recorded in humans during action preparation mirrors motor areas activation escalation, or if its early and late phases reflect the engagement of different functional networks. Here, we aimed at recording the TMS evoked-potentials (TEP) stimulating the supplementary motor area (SMA) to assess whether and how cortical excitability and functional connectivity of this region change as the BP increases. We hypothesize that, at later stages, the SMA functional network should become more connected to regions relevant for the implementation of the final motor plan. We performed TMS-EEG recordings on fourteen healthy subjects during the performance of a visuomotor Go/No-go task, eliciting and recording cortical activity and functional connectivity at -700 ms and -300 ms before the onset of visual stimuli over the SMA. When approaching stimulus onset, and thus BP peak, the SMA increased its functional connectivity with movement-related structures in the gamma and alpha bands, indicating a regional top-down preparation to implement the motor act. Beta-band connectivity, instead, was maintained constant for the whole BP time-course, being potentially related to sustained attention required by the experimental task. These findings reveal that the BP is not a mere result of increased activation of the SMA, but the functional networks in which this region is involved qualitatively changes over time, becoming more related to the execution of the motor act.

scholarly journals Cerebral functional networks during sleep in young and older individuals

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Véronique Daneault ◽  
Pierre Orban ◽  
Nicolas Martin ◽  
Christian Dansereau ◽  
Jonathan Godbout ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Brain Plasticity ◽  
Network Connectivity ◽  
Sleep Stages ◽  
Functional Networks ◽  
Older Individuals ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Age Related ◽  
Light Sleep

AbstractEven though sleep modification is a hallmark of the aging process, age-related changes in functional connectivity using functional Magnetic Resonance Imaging (fMRI) during sleep, remain unknown. Here, we combined electroencephalography and fMRI to examine functional connectivity differences between wakefulness and light sleep stages (N1 and N2 stages) in 16 young (23.1 ± 3.3y; 7 women), and 14 older individuals (59.6 ± 5.7y; 8 women). Results revealed extended, distributed (inter-between) and local (intra-within) decreases in network connectivity during sleep both in young and older individuals. However, compared to the young participants, older individuals showed lower decreases in connectivity or even increases in connectivity between thalamus/basal ganglia and several cerebral regions as well as between frontal regions of various networks. These findings reflect a reduced ability of the older brain to disconnect during sleep that may impede optimal disengagement for loss of responsiveness, enhanced lighter and fragmented sleep, and contribute to age effects on sleep-dependent brain plasticity.

scholarly journals Functional Brain Network Topology Discriminates between Patients with Minimally Conscious State and Unresponsive Wakefulness Syndrome

2019 ◽  
Vol 8 (3) ◽  
pp. 306 ◽  
Author(s):  
Alberto Cacciola ◽  
Antonino Naro ◽  
Demetrio Milardi ◽  
Alessia Bramanti ◽  
Leonardo Malatacca ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Network Topology ◽  
Minimally Conscious State ◽  
Conscious State ◽  
Clustering Coefficient ◽  
Unresponsive Wakefulness Syndrome ◽  
Topological Network ◽  
Functional Brain Network ◽  
Minimally Conscious ◽  
Nodal Level

Consciousness arises from the functional interaction of multiple brain structures and their ability to integrate different complex patterns of internal communication. Although several studies demonstrated that the fronto-parietal and functional default mode networks play a key role in conscious processes, it is still not clear which topological network measures (that quantifies different features of whole-brain functional network organization) are altered in patients with disorders of consciousness. Herein, we investigate the functional connectivity of unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) patients from a topological network perspective, by using resting-state EEG recording. Network-based statistical analysis reveals a subnetwork of decreased functional connectivity in UWS compared to in the MCS patients, mainly involving the interhemispheric fronto-parietal connectivity patterns. Network topological analysis reveals increased values of local-community-paradigm correlation, as well as higher clustering coefficient and local efficiency in UWS patients compared to in MCS patients. At the nodal level, the UWS patients showed altered functional topology in several limbic and temporo-parieto-occipital regions. Taken together, our results highlight (i) the involvement of the interhemispheric fronto-parietal functional connectivity in the pathophysiology of consciousness disorders and (ii) an aberrant connectome organization both at the network topology level and at the nodal level in UWS patients compared to in the MCS patients.

scholarly journals Resting-State Functional Connectivity in the Infant Brain: Methods, Pitfalls, and Potentiality

2017 ◽  
Vol 5 ◽  
Author(s):  
Chandler R. L. Mongerson ◽  
Russell W. Jennings ◽  
David Borsook ◽  
Lino Becerra ◽  
Dusica Bajic
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Resting State Functional Connectivity ◽  
Infant Brain

scholarly journals Beyond the low frequency fluctuations morning and evening differences in human brain

2019 ◽  
Author(s):  
Magdalena Fafrowicz ◽  
Bartosz Bohaterewicz ◽  
Anna Ceglarek ◽  
Monika Cichocka ◽  
Koryna Lewandowska ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Human Performance ◽  
Brain Activity ◽  
Activity Patterns ◽  
Low Frequency ◽  
Basic Mechanism ◽  
Time Of Day ◽  
Resting State Functional Connectivity ◽  
Circadian Typology

Human performance, alertness, and most biological functions express rhythmic fluctuations across a 24-hour-period. This phenomenon is believed to originate from differences in both circadian and homeostatic sleep-wake regulatory processes. Interactions between these processes result in time-of-day modulations of behavioral performance as well as brain activity patterns. Although the basic mechanism of the 24-hour clock is conserved across evolution, there are interindividual differences in the timing of sleep-wake cycles, subjective alertness and functioning throughout the day. The study of circadian typology differences has increased during the last few years, especially research on extreme chronotypes, which provide a unique way to investigate the effects of sleep-wake regulation on cerebral mechanisms. Using functional magnetic resonance imaging (fMRI), we assessed the influence of chronotype and time-of-day on resting-state functional connectivity. 29 extreme morning- and 34 evening-type participants underwent two fMRI sessions: about one hour after wake-up time (morning) and about ten hours after wake-up time (evening), scheduled according to their declared habitual sleep-wake pattern on a regular working day. Analysis of obtained neuroimaging data disclosed only an effect of time of day on resting-state functional connectivity; there were different patterns of functional connectivity between morning and evening sessions. The results of our study showed no differences between extreme morning-type and evening-type individuals. We demonstrate that circadian and homeostatic influences on the resting-state functional connectivity have a universal character, unaffected by circadian typology.

scholarly journals Intrinsic functional connectivity resembles cortical architecture at various levels of isoflurane anesthesia

2016 ◽  
Author(s):  
Felix Fischer ◽  
Florian Pieper ◽  
Edgar Galindo-Leon ◽  
Gerhard Engler ◽  
Claus C. Hilgetag ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Activity Patterns ◽  
Structural Connectivity ◽  
Occipital Cortex ◽  
Amplitude Envelope ◽  
Cortical Areas ◽  
Temporal Properties ◽  
Connectivity Patterns ◽  
Different Depths ◽  
Amplitude Correlation

AbstractCortical activity patterns change in different depths of general anesthesia. Here we investigate the associated network level changes of functional connectivity. We recorded ongoing electrocorticographic (ECoG) activity from the ferret temporo-parieto-occipital cortex under various levels of isoflurane and determined the functional connectivity by computing amplitude envelope correlations. Through hierarchical clustering, we derived typical connectivity patterns corresponding to light, intermediate and deep anesthesia. Generally, amplitude correlation strength increased strongly with depth of anesthesia across all cortical areas and frequency bands. This was accompanied by the emergence of burstsuppression activity in the ECoG signal and a change of the spectrum of the amplitude envelope. Normalizing the functional connectivity patterns showed that the topographical structure remained similar across depths of anesthesia, resembling the functional association of the underlying cortical areas. Thus, while strength and temporal properties of amplitude co-modulation vary depending on the activity of local neural circuits, their network-level interaction pattern is presumably most strongly determined by the underlying structural connectivity.

scholarly journals FMRI Functional Connectivity Evaluation in Alzheimer’s Stages: Linear and Non-Linear Approaches

2021 ◽  
Author(s):  
Hessam Ahmadi ◽  
Emad Fatemizadeh ◽  
Ali Motie Nasrabadi
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Functional Connectivity ◽  
Permutation Test ◽  
Pearson Correlation ◽  
Functional Integration ◽  
Clustering Coefficient ◽  
Kernel Trick ◽  
Non Linear ◽  
The Brain

Abstract Neuroimaging data analysis reveals the underlying interactions in the brain. It is essential, yet controversial, to choose a proper tool to manifest brain functional connectivity. In this regard, researchers have not reached a definitive conclusion between the linear and non-linear approaches, as both have pros and cons. In this study, to evaluate this concern, the functional Magnetic Resonance Imaging (fMRI) data of different stages of Alzheimer’s disease are investigated. In the linear approach, the Pearson Correlation Coefficient (PCC) is employed as a common technique to generate brain functional graphs. On the other hand, for non-linear approaches, two methods including Distance Correlation (DC) and the kernel trick are utilized. By the use of the three mentioned routines and graph theory, functional brain networks of all stages of Alzheimer’s disease (AD) are constructed and then sparsed. Afterwards, graph global measures are calculated over the networks and a non-parametric permutation test is conducted. Results reveal that the non-linear approaches have more potential to discriminate groups in all stages of AD. Moreover, the kernel trick method is more powerful in comparison to the DC technique. Nevertheless, AD degenerates the brain functional graphs more at the beginning stages of the disease. At the first phase, both functional integration and segregation of the brain degrades, and as AD progressed brain functional segregation further declines. The most distinguishable feature in all stages is the clustering coefficient that reflects brain functional segregation.

scholarly journals Cognitive function, disease burden and the structural connectome in systemic lupus erythematosus

Lupus ◽  
2018 ◽  
Vol 27 (8) ◽  
pp. 1329-1337 ◽  
Author(s):  
S J Wiseman ◽  
M E Bastin ◽  
E N Amft ◽  
J F F Belch ◽  
S H Ralston ◽  
...  
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Cognitive Function ◽  
Lupus Erythematosus ◽  
Cognitive Abilities ◽  
Structural Connectivity ◽  
Principal Component ◽  
Clustering Coefficient ◽  
Screening Tests ◽  
Systemic Lupus ◽  
Network Metrics

Objective To investigate brain structural connectivity in relation to cognitive abilities and systemic damage in systemic lupus erythematosus (SLE). Methods Structural and diffusion MRI data were acquired from 47 patients with SLE. Brains were segmented into 85 cortical and subcortical regions and combined with whole brain tractography to generate structural connectomes using graph theory. Global cognitive abilities were assessed using a composite variable g, derived from the first principal component of three common clinical screening tests of neurological function. SLE damage ( LD) was measured using a composite of a validated SLE damage score and disease duration. Relationships between network connectivity metrics, cognitive ability and systemic damage were investigated. Hub nodes were identified. Multiple linear regression, adjusting for covariates, was employed to model the outcomes g and LD as a function of network metrics. Results The network measures of density (standardised ß = 0.266, p = 0.025) and strength (standardised ß = 0.317, p = 0.022) were independently related to cognitive abilities. Strength (standardised ß = –0.330, p = 0.048), mean shortest path length (standardised ß = 0.401, p = 0.020), global efficiency (standardised ß = –0.355, p = 0.041) and clustering coefficient (standardised ß = –0.378, p = 0.030) were independently related to systemic damage. Network metrics were not related to current disease activity. Conclusion Better cognitive abilities and more SLE damage are related to brain topological network properties in this sample of SLE patients, even those without neuropsychiatric involvement and after correcting for important covariates. These data show that connectomics might be useful for understanding and monitoring cognitive function and white matter damage in SLE.

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