scholarly journals Revisiting Functional Connectivity for Infraslow Scale-Free Brain Dynamics Using Complex Wavelets

2021 ◽  
Vol 11 ◽  
Author(s):  
Daria La Rocca ◽  
Herwig Wendt ◽  
Virginie van Wassenhove ◽  
Philippe Ciuciu ◽  
Patrice Abry
Keyword(s):  
Functional Connectivity ◽  
Visual Motion ◽  
Temporal Dynamics ◽  
Brain Plasticity ◽  
Brain Activity ◽  
Task Completion ◽  
Phase Lag ◽  
Scale Free ◽  
Connectivity Indices ◽  
Complex Wavelet

The analysis of human brain functional networks is achieved by computing functional connectivity indices reflecting phase coupling and interactions between remote brain regions. In magneto- and electroencephalography, the most frequently used functional connectivity indices are constructed based on Fourier-based cross-spectral estimation applied to specific fast and band-limited oscillatory regimes. Recently, infraslow arrhythmic fluctuations (below the 1 Hz) were recognized as playing a leading role in spontaneous brain activity. The present work aims to propose to assess functional connectivity from fractal dynamics, thus extending the assessment of functional connectivity to the infraslow arrhythmic or scale-free temporal dynamics of M/EEG-quantified brain activity. Instead of being based on Fourier analysis, new Imaginary Coherence and weighted Phase Lag indices are constructed from complex-wavelet representations. Their performances are first assessed on synthetic data by means of Monte-Carlo simulations, and they are then compared favorably against the classical Fourier-based indices. These new assessments of functional connectivity indices are also applied to MEG data collected on 36 individuals both at rest and during the learning of a visual motion discrimination task. They demonstrate a higher statistical sensitivity, compared to their Fourier counterparts, in capturing significant and relevant functional interactions in the infraslow regime and modulations from rest to task. Notably, the consistent overall increase in functional connectivity assessed from fractal dynamics from rest to task correlated with a change in temporal dynamics as well as with improved performance in task completion, which suggests that the complex-wavelet weighted Phase Lag index is the sole index is able to capture brain plasticity in the infraslow scale-free regime.

scholarly journals Dynamic Cortical Connectivity during General Anesthesia in Surgical Patients

2019 ◽  
Vol 130 (6) ◽  
pp. 885-897 ◽  
Author(s):  
Phillip E. Vlisides ◽  
Duan Li ◽  
Mackenzie Zierau ◽  
Andrew P. Lapointe ◽  
Ka I. Ip ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
General Anesthesia ◽  
Temporal Dynamics ◽  
Transition Probabilities ◽  
Surgical Patients ◽  
Phase Lag ◽  
Cortical Connectivity ◽  
Single Measure ◽  
Connectivity Patterns ◽  
Weighted Phase Lag Index

Abstract Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New Background Functional connectivity across the cortex has been posited to be important for consciousness and anesthesia, but functional connectivity patterns during the course of surgery and general anesthesia are unknown. The authors tested the hypothesis that disrupted cortical connectivity patterns would correlate with surgical anesthesia. Methods Surgical patients (n = 53) were recruited for study participation. Whole-scalp (16-channel) wireless electroencephalographic data were prospectively collected throughout the perioperative period. Functional connectivity was assessed using weighted phase lag index. During anesthetic maintenance, the temporal dynamics of connectivity states were characterized via Markov chain analysis, and state transition probabilities were quantified. Results Compared to baseline (weighted phase lag index, 0.163, ± 0.091), alpha frontal–parietal connectivity was not significantly different across the remaining anesthetic and perioperative epochs, ranging from 0.100 (± 0.041) to 0.218 (± 0.136) (P > 0.05 for all time periods). In contrast, there were significant increases in alpha prefrontal–frontal connectivity (peak = 0.201 [0.154, 0.248]; P < 0.001), theta prefrontal–frontal connectivity (peak = 0.137 [0.091, 0.182]; P < 0.001), and theta frontal–parietal connectivity (peak = 0.128 [0.084, 0.173]; P < 0.001) during anesthetic maintenance. Additionally, shifts occurred between states of high prefrontal–frontal connectivity (alpha, beta) with suppressed frontal–parietal connectivity, and high frontal–parietal connectivity (alpha, theta) with reduced prefrontal–frontal connectivity. These shifts occurred in a nonrandom manner (P < 0.05 compared to random transitions), suggesting structured transitions of connectivity during general anesthesia. Conclusions Functional connectivity patterns dynamically shift during surgery and general anesthesia but do so in a structured way. Thus, a single measure of functional connectivity will likely not be a reliable correlate of surgical anesthesia.

Contralesional Brain Activity in Acute Ischemic Stroke

2018 ◽  
Vol 45 (1-2) ◽  
pp. 85-92 ◽  
Author(s):  
Ruud C. Van Kaam ◽  
Michel J.A.M. van Putten ◽  
Sarah E. Vermeer ◽  
Jeannette Hofmeijer
Keyword(s):  
Ischemic Stroke ◽  
Functional Connectivity ◽  
Acute Ischemic Stroke ◽  
Functional Recovery ◽  
Brain Activity ◽  
Control Group ◽  
Phase Lag ◽  
Contralateral Hemisphere ◽  
Predictive Values ◽  
Outcome Group

Background: The noninjured, contralateral hemisphere is increasingly acknowledged in the process of recovery from acute ischemic stroke. We estimated the value of conventional electroencephalography (EEG) recordings for identifying contralateral hemisphere involvement in relation to functional recovery. Methods: We analyzed 2-min epochs from 21 electrode EEG registrations of 18 patients with acute hemispheric ischemic stroke and compared with 18 age-matched controls. Outcome was dichotomized as good (modified Rankin Scale [mRS] 0–2) or poor (mRS 3–5 or death) at 3 months. Effects of the infarct on the ipsi-and contralateral hemispheres were analyzed by the delta/alpha ratio (DAR) and 2 measures of functional connectivity (magnitude squared coherence [MSC] and weighted phase lag index [WPLI]). Results: DAR was higher in patients than in controls, both in the ipsilateral and in the contralateral hemisphere (median 4.5 ± 6.7 ipsilateral and 2.4 ± 2.0 contralateral vs. 0.5 ± 0.5 in the control group, p < 0.001), indicating robust EEG changes in both lesioned and non-lesioned hemisphere. MSC and WPLI in the alpha and beta frequency bands were lower in patients than in controls in both hemispheres, indicating clear disturbances of functional connectivity (p < 0.05). In the poor outcome group, contralateral MSC and WPLI were lower than in the good outcome group, although these differences did not reach statistical significance. Conclusions: Short conventional EEG measurements show robust changes of brain activity and functional connectivity in both ipsilateral and contralateral hemispheres of patients with acute ischemic stroke. Changes of remote functional connectivity tend to interact with functional recovery. Future studies should estimate predictive values for individual patients and interactions with plasticity enhancing treatments.

scholarly journals Longitudinal Spatial Patterns of Intrinsic Brain Activity and Functional Connectivity in Upper Limb Amputees Patients

2020 ◽  
Author(s):  
bingbo bao ◽  
xuyun hua ◽  
haifeng wei ◽  
pengbo luo ◽  
hongyi zhu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Spatial Patterns ◽  
Brain Plasticity ◽  
Brain Activity ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Brain Network ◽  
Intrinsic Connectivity ◽  
Intrinsic Brain Activity

Abstract Background: Amputation in adults is a serious condition and most patients were associated with the remapping of representations in motor and sensory brain network. Methods: The present study includes 8 healthy volunteers and 16 patients with amputation. We use resting-state fMRI to investigate the local and extent brain plasticity in patients suffering from amputation simultaneously. Both the amplitude of low-frequency fluctuations (ALFF) and degree centrality (DC) were used for the assessment of neuroplasticity in central level. Results: We described changes in spatial patterns of intrinsic brain activity and functional connectivity in amputees in the present study and we found that not only the sensory and motor cortex, but also the related brain regions involved in the functional plasticity after upper extremity deafferentation. Conclusion: Our findings showed local and extensive cortical changes in the sensorimotor and cognitive-related brain regions, which may imply the dysfunction in not only sensory and motor function, but also sensorimotor integration and motor plan. The activation and intrinsic connectivity in the brain changed a lot showed correlation with the deafferentation status.

scholarly journals Multivariate Brain Functional Connectivity Through Regularized Estimators

2020 ◽  
Vol 14 ◽  
Author(s):  
Raymond Salvador ◽  
Norma Verdolini ◽  
Beatriz Garcia-Ruiz ◽  
Esther Jiménez ◽  
Salvador Sarró ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Random Forest ◽  
Temporal Dynamics ◽  
Brain Connectivity ◽  
Brain Activity ◽  
The Other ◽  
Linear Functions ◽  
Other Hand ◽  
Age Related ◽  
Global Brain

Functional connectivity analyses are typically based on matrices containing bivariate measures of covariability, such as correlations. Although this has been a fruitful approach, it may not be the optimal strategy to fully explore the complex associations underlying brain activity. Here, we propose extending connectivity to multivariate functions relating to the temporal dynamics of a region with the rest of the brain. The main technical challenges of such an approach are multidimensionality and its associated risk of overfitting or even the non-uniqueness of model solutions. To minimize these risks, and as an alternative to the more common dimensionality reduction methods, we propose using two regularized multivariate connectivity models. On the one hand, simple linear functions of all brain nodes were fitted with ridge regression. On the other hand, a more flexible approach to avoid linearity and additivity assumptions was implemented through random forest regression. Similarities and differences between both methods and with simple averages of bivariate correlations (i.e., weighted global brain connectivity) were evaluated on a resting state sample of N = 173 healthy subjects. Results revealed distinct connectivity patterns from the two proposed methods, which were especially relevant in the age-related analyses where both ridge and random forest regressions showed significant patterns of age-related disconnection, almost completely absent from the much less sensitive global brain connectivity maps. On the other hand, the greater flexibility provided by the random forest algorithm allowed detecting sex-specific differences. The generic framework of multivariate connectivity implemented here may be easily extended to other types of regularized models.

scholarly journals Effect of Zolpidem in the Aftermath of Traumatic Brain Injury: An MEG Study

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Praveen Sripad ◽  
Jessica Rosenberg ◽  
Frank Boers ◽  
Christian P. Filss ◽  
Norbert Galldiks ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Functional Connectivity ◽  
Brain Activity ◽  
Brain Regions ◽  
Phase Lag ◽  
Before And After ◽  
Source Level ◽  
Weighted Phase Lag Index

In the past two decades, many studies have shown the paradoxical efficacy of zolpidem, a hypnotic used to induce sleep, in transiently alleviating various disorders of consciousness such as traumatic brain injury (TBI), dystonia, and Parkinson’s disease. The mechanism of action of this effect of zolpidem is of great research interest. In this case study, we use magnetoencephalography (MEG) to investigate a fully conscious, ex-coma patient who suffered from neurological difficulties for a few years due to traumatic brain injury. For a few years after injury, the patient was under medication with zolpidem that drastically improved his symptoms. MEG recordings taken before and after zolpidem showed a reduction in power in the theta-alpha (4–12 Hz) and lower beta (15–20 Hz) frequency bands. An increase in power after zolpidem intake was found in the higher beta/lower gamma (20–43 Hz) frequency band. Source level functional connectivity measured using weighted-phase lag index showed changes after zolpidem intake. Stronger connectivity between left frontal and temporal brain regions was observed. We report that zolpidem induces a change in MEG resting power and functional connectivity in the patient. MEG is an informative and sensitive tool to detect changes in brain activity for TBI.

scholarly journals Scale-invariance in brain activity predicts practice effects in cognitive performance

2020 ◽  
Author(s):  
Omid Kardan ◽  
Elliot Layden ◽  
Kyoung Whan Choe ◽  
Muxuan Lyu ◽  
Xihan Zhang ◽  
...  
Keyword(s):  
Working Memory ◽  
Functional Connectivity ◽  
Brain Activity ◽  
Brain Networks ◽  
Video Clip ◽  
Practice Effect ◽  
Network Activity ◽  
Practice Effects ◽  
Scale Free ◽  
Memory And Attention

AbstractAlthough practicing a task generally benefits later performance on that same task (‘practice effect’), there are large—and mostly unexplained—individual differences in reaping the benefits from practice. One promising avenue to model and predict such differences comes from recent research showing that brain networks can extract functional advantages from operating in the vicinity of criticality, a state in which brain network activity is more scale-free. As such, we hypothesized that individuals with more scale-free fMRI activity, indicated by BOLD time series with a higher Hurst exponent (H), gain more benefits from practice. In this study, participants practiced a test of working memory and attention, the dual n-back task (DNB), watched a video clip as a break, and then performed the DNB again, during MRI. To isolate the practice effect, we divided the participants into two groups based on improvement in performance from the first to second DNB task run. We identified regions and connections in which H and functional connectivity related to practice effects in the last run. More scale-free brain activity in these regions during the preceding runs (either first DNB or video) distinguished individuals who showed greater DNB performance improvements over time. In comparison, functional connectivity (r2) in the identified connections did not reliably classify the two groups in the preceding runs. Finally, we replicated both H and r2 results from study 1 in an independent fMRI dataset of participants performing multiple runs of another working memory and attention task (word completion). We conclude that the brain networks can accommodate further practice effects in individuals with higher scale-free BOLD activity.

scholarly journals Self-similarity and multifractality in human brain activity: a wavelet-based analysis of scale-free brain dynamics☆

2018 ◽  
Author(s):  
Daria La Rocca ◽  
Nicolas Zilber ◽  
Patrice Abry ◽  
Virginie van Wassenhove ◽  
Philippe Ciuciu
Keyword(s):  
Human Brain ◽  
Resting State ◽  
Temporal Dynamics ◽  
Brain Activity ◽  
Temporal Structure ◽  
Estimation Methods ◽  
Brain Dynamics ◽  
List Type ◽  
Self Similarity ◽  
Scale Free

AbstractBackgroundThe temporal structure of macroscopic brain activity displays both oscillatory and scale-free dynamics. While the functional relevance of neural oscillations has been largely investigated, both the nature and the role of scale-free dynamics in brain processing have been disputed.New MethodHere, we offer a novel method to rigorously enrich the characterization of scale-free brain activity using a robust wavelet-based assessment of self-similarity and multifractality. For this, we analyzed human brain activity recorded with magnetoencephalography (MEG) while participants were at rest or performing a task.ResultsFirst, we report consistent infraslow (from 0.1 to 1.5 Hz) scalefree dynamics (i.e., self-similarity and multifractality) in resting-state and task data. Second, we observed a fronto-occipital gradient of self-similarity reminiscent of the known hierarchy of temporal scales from sensory to higherorder cortices; the anatomical gradient was more pronounced in task than in rest. Third, we observed a significant increase of multifractality during task as compared to rest. Additionally, the decrease in self-similarity and the increase in multifractality from rest to task were negatively correlated in regions involved in the task, suggesting a shift from structured global temporal dynamics in resting-state to locally bursty and non Gaussian scalefree structures during task.Comparison with Existing Method(s)We showed that the wavelet leader based multifractal approach extends power spectrum estimation methods in the way of characterizing finely scale-free brain dynamics.ConclusionsAltogether, our approach provides novel fine-grained characterizations of scale-free dynamics in human brain activity.HighlightsWe estimated scale-free human brain dynamics using wavelet-leader formalism.High-to-low self-similarity defined a fronto-occipital gradient.The gradient was enhanced in task compared to resting-state.Scale-free brain dynamics showed multifractal properties.Self-similarity decreased whereas multifractality increased from rest to task.

scholarly journals Longitudinal Spatial Patterns of Intrinsic Brain Activity and Functional Connectivity in Upper Limb Amputees Patients

2020 ◽  
Author(s):  
Bingbo Bao ◽  
Lei Duan ◽  
Haifeng Wei ◽  
Pengbo Luo ◽  
Hongyi Zhu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Spatial Patterns ◽  
Upper Limb ◽  
Large Scale ◽  
Brain Plasticity ◽  
Brain Activity ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Intrinsic Brain Activity

Abstract Background: Amputation in adults is a serious condition and previous studies suggested a remapping of representations in motor and sensory brain networks. However, little is known about the longitudinal reorganizing pattern in upper limb amputees’ patients.Methods: The present study included 8 healthy volunteers and 16 patients with amputation. We use resting-state fMRI to investigate the local and large-scale brain plasticity in patients suffering from amputation. Both the amplitude of low-frequency fluctuations (ALFF) and degree centrality (DC) were used for the assessment of neuroplasticity.Results: We described changes in spatial patterns of intrinsic brain activity and functional connectivity in amputees; and we found that not only the sensory and motor cortex, but also the cognitive-related brain regions involved in the functional plasticity after upper extremity deafferentation.Conclusion: Our findings showed local and extensive cortical changes in the sensorimotor and cognitive-related brain regions, which may imply the dysfunction in not only sensory and motor function, but also sensorimotor integration and motor plan. The changes in activation and intrinsic connectivity in the brain showed correlation with the deafferentation status.

scholarly journals Modular co-organization of functional connectivity and scale-free dynamics in the human brain

2017 ◽  
Vol 1 (2) ◽  
pp. 143-165 ◽  
Author(s):  
Alexander Zhigalov ◽  
Gabriele Arnulfo ◽  
Lino Nobili ◽  
Satu Palva ◽  
J. Matias Palva
Keyword(s):  
Functional Connectivity ◽  
Brain Activity ◽  
Neuronal Dynamics ◽  
Scale Free ◽  
Temporal Correlations ◽  
Electrophysiological Recordings ◽  
Avalanche Propagation ◽  
Modular Structures ◽  
Neuronal Avalanches ◽  
Dynamic States

Scale-free neuronal dynamics and interareal correlations are emergent characteristics of spontaneous brain activity. How such dynamics and the anatomical patterns of neuronal connectivity are mutually related in brain networks has, however, remained unclear. We addressed this relationship by quantifying the network colocalization of scale-free neuronal activity—both neuronal avalanches and long-range temporal correlations (LRTCs)—and functional connectivity (FC) by means of intracranial and noninvasive human resting-state electrophysiological recordings. We found frequency-specific colocalization of scale-free dynamics and FC so that the interareal couplings of LRTCs and the propagation of neuronal avalanches were most pronounced in the predominant pathways of FC. Several control analyses and the frequency specificity of network colocalization showed that the results were not trivial by-products of either brain dynamics or our analysis approach. Crucially, scale-free neuronal dynamics and connectivity also had colocalized modular structures at multiple levels of network organization, suggesting that modules of FC would be endowed with partially independent dynamic states. These findings thus suggest that FC and scale-free dynamics—hence, putatively, neuronal criticality as well—coemerge in a hierarchically modular structure in which the modules are characterized by dense connectivity, avalanche propagation, and shared dynamic states.

scholarly journals Emotional Information in News Reporting on Audience Cognitive Processing in the Age of Posttruth: An Electroencephalogram and Functional Connectivity Approach

2021 ◽  
Vol 12 ◽  
Author(s):  
Ya Yang ◽  
Lichao Xiu ◽  
Guoming Yu
Keyword(s):  
Functional Connectivity ◽  
Cognitive Processing ◽  
Emotional Expression ◽  
Brain Activity ◽  
Cognitive Resources ◽  
Phase Lag ◽  
Emotional Information ◽  
News Reporting ◽  
Brain Functional Connectivity ◽  
Weighted Phase Lag Index

The purpose of the present study is to explore how the emotionalized expression of news content in the posttruth era affects the cognitive processing of the audiences. One news that was text-written with two different expression types (emotional expression vs. neutral expression) was adopted as an experiment material in the study, and changes in cortical activity during news reporting reading tasks were examined with electroencephalograms, sampled from nine sites and four channels and analyzed with weighted phase lag index (wPLI) based on brain functional connectivity (FC) method. The results show that emotional discourses caused a stronger cortical brain activity and more robust brain FC (beta oscillations); besides, reading emotionalized expression consumed more attention resources but fewer cognitive resources, which may impede further rational thinking of the audiences.

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