Pediatric epilepsy: Clustering by functional connectivity using phase synchronization

2015 ◽  
Author(s):  
Hoda Rajaei ◽  
Mercedes Cabrerizo ◽  
Saman Sargolzaei ◽  
Alberto Pinzon-Ardila ◽  
Sergio Gonzalez-Arias ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Phase Synchronization ◽  
Pediatric Epilepsy

Selection for Action: The Medial Frontal Cortex Is an Executive Hub for Stimulus and Response Selection

2021 ◽  
pp. 1-28
Author(s):  
Dariusz Asanowicz ◽  
Bartłomiej Panek ◽  
Ilona Kotlewska
Keyword(s):  
Functional Connectivity ◽  
Frontal Cortex ◽  
Phase Synchronization ◽  
Visual Stimulation ◽  
Response Selection ◽  
Flanker Task ◽  
Medial Frontal Cortex ◽  
Conflict Condition ◽  
Underlying Processes ◽  
Selection For Action

Abstract This EEG study investigates the electrophysiological activity underlying processes of stimulus and response selection, and their executive orchestration via long-range functional connectivity under conflict condition, in order to shed more light on how these brain dynamics shape individual behavioral performance. Participants (n = 91) performed a modified flanker task, in which bilateral visual stimulation and a bimanual response pattern were employed to isolate the stimulus and response selection-related lateralized activity. First, we identified conflict-related markers of task-relevant processes; most importantly, the stimulus and response selection were evidenced by contra–ipsilateral differences in visual and motor activity, respectively, and executive control was evidenced by modulations of midfrontal activity. Second, we identified conflict-related functional connectivity between midfrontal and other task-relevant areas. The results showed that interregional phase synchronization in theta band was centered at the midfrontal site, interpreted here as a “hub” of executive communication. Importantly, the theta functional connectivity was more robust under the condition of increased demands for stimulus and response selection, including connectivity between the medial frontal cortex and the lateral frontal and motor areas, as well as cross-frequency theta–alpha coupling between the medial frontal cortex and contralateral visual areas. Third, we showed that individual differences in the measured conflict-related EEG activity, particularly the midfrontal N2, theta power, and global theta connectivity, predict the behavioral efficiency in conflict resolution.

scholarly journals qEEG Analysis in the Diagnosis of Alzheimers Disease; a Comparison of Functional Connectivity and Spectral Analysis

2022 ◽  
Author(s):  
Maria Semeli Frangopoulou ◽  
Maryam Alimardani
Keyword(s):  
Spectral Analysis ◽  
Functional Connectivity ◽  
Data Science ◽  
Phase Synchronization ◽  
Connectivity Analysis ◽  
Alzheimers Disease ◽  
Brain Disorder ◽  
Alternative Analysis ◽  
Functional Connectivity Analysis ◽  
Analysis Methods

Alzheimers disease (AD) is a brain disorder that is mainly characterized by a progressive degeneration of neurons in the brain, causing a decline in cognitive abilities and difficulties in engaging in day-to-day activities. This study compares an FFT-based spectral analysis against a functional connectivity analysis based on phase synchronization, for finding known differences between AD patients and Healthy Control (HC) subjects. Both of these quantitative analysis methods were applied on a dataset comprising bipolar EEG montages values from 20 diagnosed AD patients and 20 age-matched HC subjects. Additionally, an attempt was made to localize the identified AD-induced brain activity effects in AD patients. The obtained results showed the advantage of the functional connectivity analysis method compared to a simple spectral analysis. Specifically, while spectral analysis could not find any significant differences between the AD and HC groups, the functional connectivity analysis showed statistically higher synchronization levels in the AD group in the lower frequency bands (delta and theta), suggesting that the AD patients brains are in a phase-locked state. Further comparison of functional connectivity between the homotopic regions confirmed that the traits of AD were localized in the centro-parietal and centro-temporal areas in the theta frequency band (4-8 Hz). The contribution of this study is that it applies a neural metric for Alzheimers detection from a data science perspective rather than from a neuroscience one. The study shows that the combination of bipolar derivations with phase synchronization yields similar results to comparable studies employing alternative analysis methods.

scholarly journals Theta-Band Functional Connectivity and Single-Trial Cognitive Control in Sports-Related Concussion: Demonstration of Proof-of-Concept for a Potential Biomarker of Concussion

2019 ◽  
Vol 25 (3) ◽  
pp. 314-323 ◽  
Author(s):  
Ezra E. Smith ◽  
John J.B. Allen
Keyword(s):  
Head Injury ◽  
Functional Connectivity ◽  
Cognitive Control ◽  
Phase Synchronization ◽  
Control Measures ◽  
Single Trial ◽  
Brain Health ◽  
Theta Band ◽  
College Age ◽  
Potential Biomarker

AbstractObjectives: This report examined theta-band neurodynamics for potential biomarkers of brain health in athletes with concussion. Methods: Participants included college-age contact/collision athletes with (N=24) and without a history of concussion (N=16) in Study 1. Study 2 (N=10) examined changes over time in contact/collision athletes. There were two primary dependent variables: (1) theta-band phase-synchronization (e.g., functional connectivity) between medial and right-lateral electrodes; and (2) the within-subject correlation between synchronization strength on error trials and post-error reaction time (i.e., operationalization of cognitive control). Results: Head injury history was inversely related with medial-lateral connectivity. Head injury was also related to declines in a neurobehavioral measure of cognitive control (i.e., the single-trial relationship between connectivity and post-error slowing). Conclusions: Results align with a theory of connectivity-mediated cognitive control. Mild injuries undetectable by behavioral measures may still be apparent on direct measures of neural functioning. This report demonstrates that connectivity and cognitive control measures may be useful for tracking recovery from concussion. Theoretically relevant neuroscientific findings in healthy adults may have applications in patient populations, especially with regard to monitoring brain health. (JINS 2019, 25, 314–323)

scholarly journals Comparison of Phase Synchronization Measures for Identifying Stimulus-Induced Functional Connectivity in Human Magnetoencephalographic and Simulated Data

2020 ◽  
Vol 14 ◽  
Author(s):  
Kenji Yoshinaga ◽  
Masao Matsuhashi ◽  
Tatsuya Mima ◽  
Hidenao Fukuyama ◽  
Ryosuke Takahashi ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Phase Synchronization ◽  
Simulated Data

Relation between EEG source functional connectivity and the negative symptom severity in schizophrenia: a preliminary report from a multicentre study

2016 ◽  
Vol 33 (S1) ◽  
pp. s246-s246
Author(s):  
G. Di Lorenzo ◽  
A. Mucci ◽  
A. Daverio ◽  
F. Ferrentino ◽  
A. Vignapiano ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Multicentre Study ◽  
Negative Symptom ◽  
Resting State ◽  
Symptom Severity ◽  
Negative Symptoms ◽  
Phase Synchronization ◽  
Lower Quartile ◽  
Eyes Closed ◽  
Significant Difference

IntroductionNeural dysconnectivity is hypothesized to be a key element in pathophysiology of schizophrenia. However, the relation of disordered connectivity with the different clinical characteristics of the syndrome is not fully elucidated.ObjectivesThe current research investigated the relations between resting-state EEG Source Functional Connectivity (EEG-SFC) and the two main clusters of negative symptoms derived from the Brief Negative Symptom Scale, the Expressive Deficit (ED) and the Avolition (AV), in subjects with schizophrenia (SCZ) enrolled to the multicentre study of the Italian Network for Research on Psychoses.MethodsOut of 97 chronic, stabilized SCZ included, we selected subjects according the lower and the upper quartile of the ED and AV value distribution: 25 were in upper and 24 in the lower quartile of ED (respectively, HIGH-ED and LOW-ED); 27 were in upper and 24 in the lower quartile of AV (respectively, HIGH-AV and LOW-AV). Fifty-five healthy controls (HC) were included, comparable to SCZ for gender, age and educational level. EEG-SFC analysis was based on the lagged phase synchronization (LPS) computed by eLORETA from 5 minutes resting-state EEG recordings in eyes closed condition. LPS indices were determined for each spectrum band and between all 28 regions of interest (ROI) pairs. Group differences were significant for corrected P-value < 0.05.ResultsSCZ had higher theta band LPS than HC. Respect to LOW-ED, HIGH-ED showed significant increased alpha LPS in fronto-cingulate, para-hippocampal and insular inter-hemispheric ROI pairs. No significant difference emerged between HIGH-AV and LOW-AV.ConclusionsSubgrouping SCZ according to negative symptom severity reveals heterogeneous patterns of resting-state LPS connectivity.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Phase Synchronization Operator for On-Chip Brain Functional Connectivity Computation

2019 ◽  
Vol 13 (5) ◽  
pp. 957-970
Author(s):  
Manuel Delgado-Restituto ◽  
James Brian Romaine ◽  
Angel Rodriguez-Vazquez
Keyword(s):  
Functional Connectivity ◽  
Phase Synchronization ◽  
On Chip ◽  
Brain Functional Connectivity

scholarly journals Inferring Functional Neural Connectivity with Phase Synchronization Analysis: A Review of Methodology

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Junfeng Sun ◽  
Zhijun Li ◽  
Shanbao Tong
Keyword(s):  
Functional Connectivity ◽  
Phase Synchronization ◽  
Significance Test ◽  
Neural Connectivity ◽  
Neural Signals ◽  
Instantaneous Phase ◽  
Neuroscience Research ◽  
Observational Noise ◽  
Relationship Of ◽  
The Relationship

Functional neural connectivity is drawing increasing attention in neuroscience research. To infer functional connectivity from observed neural signals, various methods have been proposed. Among them, phase synchronization analysis is an important and effective one which examines the relationship of instantaneous phase between neural signals but neglecting the influence of their amplitudes. In this paper, we review the advances in methodologies of phase synchronization analysis. In particular, we discuss the definitions of instantaneous phase, the indexes of phase synchronization and their significance test, the issues that may affect the detection of phase synchronization and the extensions of phase synchronization analysis. In practice, phase synchronization analysis may be affected by observational noise, insufficient samples of the signals, volume conduction, and reference in recording neural signals. We make comments and suggestions on these issues so as to better apply phase synchronization analysis to inferring functional connectivity from neural signals.

Sign in / Sign up

Export Citation Format

Share Document