scholarly journals Exploring MEG brain fingerprints: evaluation, pitfalls and interpretations

2021 ◽  
Author(s):  
Ekansh Sareen ◽  
Sélima Zahar ◽  
Dimitri Van De Ville ◽  
Anubha Gupta ◽  
Alessandra Griffa ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Preliminary Investigation ◽  
Phase Coupling ◽  
Scoring Method ◽  
Accurate Identification ◽  
Frequency Bands ◽  
Neuroscience Research ◽  
Human Connectome Project ◽  
Spatial Concordance

AbstractIndividual characterization of subjects based on their functional connectome (FC), termed “FC fingerprinting”, has become a highly sought-after goal in contemporary neuroscience research. Recent functional magnetic resonance imaging (fMRI) studies have demonstrated unique characterization and accurate identification of individuals as an accomplished task. However, FC fingerprinting in magnetoencephalography (MEG) data is still widely unexplored. Here, we study resting-state MEG data from the Human Connectome Project to assess the MEG FC fingerprinting and its relationship with several factors including amplitude- and phase-coupling functional connectivity measures, spatial leakage correction and frequency bands. To this end, we first employ two identification scoring methods, differential identifiability and success rate, to provide quantitative fingerprint scores for each FC measurement. Secondly, we explore the edgewise and nodal MEG fingerprinting patterns across the different frequency bands (delta, theta, alpha, beta, and gamma). Finally, we investigate the cross-modality fingerprinting patterns obtained from MEG and fMRI recordings from the same subjects. Our results suggest that fingerprinting performance is heavily dependent on the functional connectivity measure, frequency band, identification scoring method, and spatial leakage correction. We report higher MEG fingerprints in phase-coupling methods, central frequency bands (alpha and beta), and in the visual, frontoparietal, dorsal-attention and default-mode networks. Furthermore, cross-modality comparisons reveal a certain degree of spatial concordance in fingerprinting patterns between the MEG and fMRI data, especially in the visual system. This comprehensive, albeit preliminary investigation of MEG connectome test-retest identification offers a first characterization of MEG fingerprinting in relation to different methodological and electrophysiological factors and contributes to the understanding of fingerprinting cross-modal relationships. We hope that this first investigation will contribute to setting the grounds for MEG connectome identification.

Toward a Neural Model of the Openness-Psychoticism Dimension: Functional Connectivity in the Default and Frontoparietal Control Networks

2019 ◽  
Author(s):  
Scott D. Blain ◽  
Rachael Grazioplene ◽  
Yizhou Ma ◽  
Colin G. DeYoung
Keyword(s):  
Functional Connectivity ◽  
Structural Equation ◽  
Psychotic Disorders ◽  
Neural Model ◽  
Equation Modeling ◽  
Control Networks ◽  
Psychosis Proneness ◽  
Human Connectome Project ◽  
Intrinsic Connectivity Networks ◽  
Personality Psychopathology

Psychosis proneness has been linked to heightened Openness to Experience and to cognitive deficits. Openness and psychotic disorders are associated with the default and frontoparietal networks, and the latter network is also robustly associated with intelligence. We tested the hypothesis that functional connectivity of the default and frontoparietal networks is a neural correlate of the openness-psychoticism dimension. Participants in the Human Connectome Project (N = 1003) completed measures of psychoticism, openness, and intelligence. Resting state functional magnetic resonance imaging was used to identify intrinsic connectivity networks. Structural equation modeling revealed relations among personality, intelligence, and network coherence. Psychoticism, openness, and especially their shared variance, were related positively to default network coherence and negatively to frontoparietal coherence. These associations remained after controlling for intelligence. Intelligence was positively related to frontoparietal coherence. Research suggests psychoticism and openness are linked in part through their association with connectivity in networks involving experiential simulation and cognitive control. We propose a model of psychosis risk that highlights roles of the default and frontoparietal networks. Findings echo research on functional connectivity in psychosis patients, suggesting shared mechanisms across the personality-psychopathology continuum.

scholarly journals Implantable Optrode Array for Optogenetic Modulation and Electrical Neural Recording

Micromachines ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 725
Author(s):  
Saeyeong Jeon ◽  
Youjin Lee ◽  
Daeho Ryu ◽  
Yoon Kyung Cho ◽  
Yena Lee ◽  
...  
Keyword(s):  
Light Emitting Diode ◽  
Neural Recording ◽  
Electrophysiological Recording ◽  
Light Emitting ◽  
Technological Advances ◽  
Neuroscience Research ◽  
Cell Type Specific ◽  
Novel Design

During the last decade, optogenetics has become an essential tool for neuroscience research due to its unrivaled feature of cell-type-specific neuromodulation. There have been several technological advances in light delivery devices. Among them, the combination of optogenetics and electrophysiology provides an opportunity for facilitating optogenetic approaches. In this study, a novel design of an optrode array was proposed for realizing optical modulation and electrophysiological recording. A 4 × 4 optrode array and five-channel recording electrodes were assembled as a disposable part, while a reusable part comprised an LED (light-emitting diode) source and a power line. After the characterization of the intensity of the light delivered at the fiber tips, in vivo animal experiment was performed with transgenic mice expressing channelrhodopsin, showing the effectiveness of optical activation and neural recording.

scholarly journals Heritability and interindividual variability of regional structure-function coupling

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Zijin Gu ◽  
Keith Wakefield Jamison ◽  
Mert Rory Sabuncu ◽  
Amy Kuceyeski
Keyword(s):  
Functional Connectivity ◽  
Structure Function ◽  
Regional Differences ◽  
Regional Scale ◽  
Brain Regions ◽  
Diffusion Weighted Mri ◽  
Regional Structure ◽  
Human Connectome Project ◽  
Structural Connections ◽  
The Relationship

AbstractWhite matter structural connections are likely to support flow of functional activation or functional connectivity. While the relationship between structural and functional connectivity profiles, here called SC-FC coupling, has been studied on a whole-brain, global level, few studies have investigated this relationship at a regional scale. Here we quantify regional SC-FC coupling in healthy young adults using diffusion-weighted MRI and resting-state functional MRI data from the Human Connectome Project and study how SC-FC coupling may be heritable and varies between individuals. We show that regional SC-FC coupling strength varies widely across brain regions, but was strongest in highly structurally connected visual and subcortical areas. We also show interindividual regional differences based on age, sex and composite cognitive scores, and that SC-FC coupling was highly heritable within certain networks. These results suggest regional structure-function coupling is an idiosyncratic feature of brain organisation that may be influenced by genetic factors.

scholarly journals Association Between Brain Activation and Functional Connectivity

2018 ◽  
Vol 29 (5) ◽  
pp. 1984-1996 ◽  
Author(s):  
Dardo Tomasi ◽  
Nora D Volkow
Keyword(s):  
Functional Connectivity ◽  
Brain Activity ◽  
Low Frequency ◽  
Brain Activation ◽  
Blood Oxygen Level Dependent ◽  
Common Source ◽  
Functional Connectivity Density ◽  
Density Mapping ◽  
Human Connectome Project ◽  
Bold Responses

Abstract The origin of the “resting-state” brain activity recorded with functional magnetic resonance imaging (fMRI) is still uncertain. Here we provide evidence for the neurovascular origins of the amplitude of the low-frequency fluctuations (ALFF) and the local functional connectivity density (lFCD) by comparing them with task-induced blood-oxygen level dependent (BOLD) responses, which are considered a proxy for neuronal activation. Using fMRI data for 2 different tasks (Relational and Social) collected by the Human Connectome Project in 426 healthy adults, we show that ALFF and lFCD have linear associations with the BOLD response. This association was significantly attenuated by a novel task signal regression (TSR) procedure, indicating that task performance enhances lFCD and ALFF in activated regions. We also show that lFCD predicts BOLD activation patterns, as was recently shown for other functional connectivity metrics, which corroborates that resting functional connectivity architecture impacts brain activation responses. Thus, our findings indicate a common source for BOLD responses, ALFF and lFCD, which is consistent with the neurovascular origin of local hemodynamic synchrony presumably reflecting coordinated fluctuations in neuronal activity. This study also supports the development of task-evoked functional connectivity density mapping.

scholarly journals Impaired functional connectivity at EEG alpha and theta frequency bands in major depression

2006 ◽  
Vol 28 (3) ◽  
pp. 247-261 ◽  
Author(s):  
Andrew A. Fingelkurts ◽  
Alexander A. Fingelkurts ◽  
Heikki Rytsälä ◽  
Kirsi Suominen ◽  
Erkki Isometsä ◽  
...  
Keyword(s):  
Major Depression ◽  
Functional Connectivity ◽  
Frequency Bands ◽  
Theta Frequency ◽  
Eeg Alpha

scholarly journals High-accuracy individual identification using a “thin slice” of the functional connectome

2019 ◽  
Vol 3 (2) ◽  
pp. 363-383 ◽  
Author(s):  
Lisa Byrge ◽  
Daniel P. Kennedy
Keyword(s):  
High Accuracy ◽  
Individual Identification ◽  
Brain Functioning ◽  
Replication Sample ◽  
Thin Slice ◽  
Functional Connections ◽  
Random Samples ◽  
Human Connectome Project ◽  
Independent Replication

Connectome fingerprinting—a method that uses many thousands of functional connections in aggregate to identify individuals—holds promise for individualized neuroimaging. A better characterization of the features underlying successful fingerprinting performance—how many and which functional connections are necessary and/or sufficient for high accuracy—will further inform our understanding of uniqueness in brain functioning. Thus, here we examine the limits of high-accuracy individual identification from functional connectomes. Using ∼3,300 scans from the Human Connectome Project in a split-half design and an independent replication sample, we find that a remarkably small “thin slice” of the connectome—as few as 40 out of 64,620 functional connections—was sufficient to uniquely identify individuals. Yet, we find that no specific connections or even specific networks were necessary for identification, as even small random samples of the connectome were sufficient. These results have important conceptual and practical implications for the manifestation and detection of uniqueness in the brain.

scholarly journals Functional connectivity of fMRI using differential covariance predicts structural connectivity and behavioral reaction times

2021 ◽  
Author(s):  
Yusi Chen ◽  
Qasim Bukhari ◽  
Tiger Wutu Lin ◽  
Terrence J Sejnowski
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Connectivity ◽  
Resting State ◽  
Structural Connectivity ◽  
Reaction Times ◽  
Resonance Imaging ◽  
Brain Areas ◽  
Human Connectome Project ◽  
Wide Range

Recordings from resting state functional magnetic resonance imaging (rs-fMRI) reflect the influence of pathways between brain areas. A wide range of methods have been proposed to measure this functional connectivity (FC), but the lack of ''ground truth'' has made it difficult to systematically validate them. Most measures of FC produce connectivity estimates that are symmetrical between brain areas. Differential covariance (dCov) is an algorithm for analyzing FC with directed graph edges. Applied to synthetic datasets, dCov-FC was more effective than covariance and partial correlation in reducing false positive connections and more accurately matching the underlying structural connectivity. When we applied dCov-FC to resting state fMRI recordings from the human connectome project (HCP) and anesthetized mice, dCov-FC accurately identified strong cortical connections from diffusion Magnetic Resonance Imaging (dMRI) in individual humans and viral tract tracing in mice. In addition, those HCP subjects whose rs-fMRI were more integrated, as assessed by a graph-theoretic measure, tended to have shorter reaction times in several behavioral tests. Thus, dCov-FC was able to identify anatomically verified connectivity that yielded measures of brain integration causally related to behavior.

scholarly journals The Okur-Chung Neurodevelopmental Syndrome (OCNDS) mutation CK2K198R leads to a rewiring of kinase specificity

2021 ◽  
Author(s):  
Danielle M Caefer ◽  
Nhat Q Phan ◽  
Jennifer C Liddle ◽  
Jeremy L Balsbaugh ◽  
Joseph P O’Shea ◽  
...  
Keyword(s):  
High Resolution ◽  
Substrate Specificity ◽  
Tyrosine Phosphorylation ◽  
Initial Step ◽  
Loss Of Function ◽  
Scoring Method ◽  
Disease Condition ◽  
The Impact ◽  
First Time

AbstractOkur-Chung Neurodevelopmental Syndrome (OCNDS) is caused by heterozygous mutations to the CSNK2A1 gene, which encodes the alpha subunit of casein kinase II (CK2). The most frequently occurring mutation is lysine 198 to arginine (K198R). To investigate the impact of this mutation, we first generated a high-resolution phosphorylation motif of CK2WT, including the first characterization of specificity for tyrosine phosphorylation activity. A second high resolution motif representing CK2K198R substrate specificity was also generated. Here we report for the first time the impact of the OCNDS associated CK2K198R mutation. Contrary to prior speculation, the mutation does not result in a loss of function, but rather shifts the substrate specificity of the kinase. Broadly speaking the mutation leads to 1) a decreased preference for acidic residues in the +1 position, 2) a decreased preference for threonine phosphorylation, 3) an increased preference for tyrosine phosphorylation, and 4) an alteration of the tyrosine phosphorylation specificity motif. To further investigate the result of this mutation we have developed a probability-based scoring method, allowing us to predict shifts in phosphorylation in the K198R mutant relative to the wild type kinase. As an initial step we have applied the methodology to the set of axonally localized ion channels in an effort to uncover potential alterations of the phosphoproteome associated with the OCNDS disease condition.

Sign in / Sign up

Export Citation Format

Share Document