scholarly journals A unified approach for characterizing static/dynamic connectivity frequency profiles using filter banks

2020 ◽  
pp. 1-27
Author(s):  
Ashkan Faghiri ◽  
Armin Iraji ◽  
Eswar Damaraju ◽  
Jessica Turner ◽  
Vince D. Calhoun
Keyword(s):  
Low Frequency ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Unified Approach ◽  
Full Spectrum ◽  
Additional Information ◽  
Multiple Frequencies ◽  
Network States ◽  
Window Approach ◽  
Dynamic Connectivity

Static and dynamic functional network connectivity (FNC) are typically studied separately, which makes us unable to see the full spectrum of connectivity in each analysis. Here, we propose an approach called filter-banked connectivity (FBC) to estimate connectivity while preserving its full frequency range and subsequently examine both static and dynamic connectivity in one unified approach. First, we demonstrate that FBC can estimate connectivity across multiple frequencies missed by a sliding-window approach. Next, we use FBC to estimate FNC in a resting-state fMRI dataset including schizophrenia patients (SZ) and typical controls (TC). The FBC results are clustered into different network states. Some states showed weak low-frequency strength and as such were not captured in the window-based approach. Additionally, we found that SZs tend to spend more time in states exhibiting higher frequencies compared with TCs who spent more time in lower frequency states. Finally, we show that FBC enables us to analyze static and dynamic connectivity in a unified way. In summary, FBC offers a novel way to unify static and dynamic connectivity analyses and can provide additional information about the frequency profile of connectivity patterns.

scholarly journals A unified approach for characterizing static/dynamic connectivity frequency profiles using filter banks

2019 ◽  
Author(s):  
Ashkan Faghiri ◽  
Armin Iraji ◽  
Eswar Damaraju ◽  
Jessica Turner ◽  
Vince D. Calhoun
Keyword(s):  
Pearson Correlation ◽  
Low Frequency ◽  
Sliding Window ◽  
Group Differences ◽  
Unified Approach ◽  
Data Set ◽  
New Approach ◽  
Window Approach ◽  
Dynamic Connectivity ◽  
Activity Domain

AbstractStudying dynamic functional connectivity (dFC) has been the focus of many studies in recent years. The most commonly used estimator for dFC uses a sliding window in combination with a connectivity estimator such as Pearson correlation. Here, we propose a new approach to estimate connectivity while preserving its full frequency range and subsequently examine both static and dynamic connectivity in one unified approach. This approach which we call filter banked connectivity (FBC), implements frequency tiling directly in the connectivity domain contrary to other studies where frequency tiling is done in the activity domain. This leads to more accurate modeling, and a unified approach to capture connectivity ranging from static to highly dynamic, avoiding the need to pick a specific band as in a sliding window approach.First, we demonstrated that our proposed approach, can estimate connectivity at frequencies that sliding window approach fails. Next we evaluated the ability of the approach to identify group differences by using the FBC approach to estimate dFNC in a resting fMRI data set including schizophrenia patients (SZ, n=151) and typical controls (TC, n=163). To summarize the results, we used k-means to cluster the FBC values into different clusters. Some states showed very weak low frequency strength and as such SWPC was not well suited to capture them. Additionally, we found that SZs tend to spend more time in states exhibiting higher frequencies and engaging the default mode network and its anticorrelations with other networks compared to TCs which spent more time in lower frequency states which primarily includes strong intercorrelations within the sensorimotor domains. In summary, the proposed approach offers a novel way to estimate connectivity while unifying static and dynamic connectivity analyses and can provide additional otherwise missed information about the frequency profile of connectivity patterns.

scholarly journals Cognitive vulnerability to sleep deprivation is robustly associated with two dynamic connectivity states

2019 ◽  
Author(s):  
James Teng ◽  
Ju Lynn Ong ◽  
Amiya Patanaik ◽  
Jesisca Tandi ◽  
Juan Helen Zhou ◽  
...  
Keyword(s):  
Sleep Deprivation ◽  
Resting State ◽  
Cognitive Vulnerability ◽  
Resting State Fmri ◽  
Good Evidence ◽  
Psychomotor Vigilance Test ◽  
Single Night ◽  
Highly Correlated ◽  
Window Approach ◽  
Dynamic Connectivity

AbstractRobustly linking dynamic functional connectivity (DFC) states to behaviour is an important goal of the fledgling research using these methods. Previously, using a sliding window approach, we identified two dynamic connectivity states (DCS) linked to arousal. Here, in an independent dataset, 32 healthy participants underwent two sets of resting-state functional magnetic resonance imaging (fMRI) scans, once in a well-rested state and once after a single night of total sleep deprivation. Using a temporal differencing method, DFC and clustering analysis on the resting state fMRI data revealed five centroids that were highly correlated with those found in previous work, including the two states associated with high and low arousal. Individual differences in cognitive vulnerability to sleep deprivation were measured using changes in Psychomotor Vigilance Test (PVT) performance (lapses and median reaction speed), Changes in the percentage of time spent in the arousal states from the well-rested to the sleep-deprived condition specifically were correlated with declines in PVT performance. Our results provide good evidence of the validity and reproducibility of DFC measures, particularly with regard to measuring arousal and attention, and are an encouraging base from which to build a chronnectome mapping DCS to cognition.

scholarly journals Transient patterns of functional dysconnectivity in youth with psychosis spectrum symptoms

2018 ◽  
Author(s):  
Eva Mennigen ◽  
Dietsje D. Jolles ◽  
Catherine E. Hegarty ◽  
Mohan Gupta ◽  
Maria Jalbrzikowski ◽  
...  
Keyword(s):  
Help Seeking ◽  
Large Scale ◽  
Brain Connectivity ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Psychotic Symptoms ◽  
Whole Brain ◽  
State Dependent ◽  
Functional Brain Networks ◽  
Window Approach

AbstractPsychosis spectrum disorders are conceptualized as neurodevelopmental disorders accompanied by disruption of large-scale functional brain networks. Both static and dynamic dysconnectivity have been described in patients with schizophrenia and, more recently, in help-seeking individuals at clinical high-risk for psychosis. Less is known, however, about developmental aspects of dynamic functional network connectivity (FNC) associated with psychotic symptoms (PS) in the general population. Here, we investigate resting state fMRI data using established dynamic FNC methods in the Philadelphia Neurodevelopmental Cohort (ages 8-22), including 129 participants experiencing PS and 452 participants without PS (non-PS).Applying a sliding window approach and k-means clustering, 5 dynamic states with distinct whole-brain connectivity patterns were identified. PS-associated dysconnectivity was most prominent in states characterized by synchronization or antagonism of the default mode network (DMN) and cognitive control (CC) domains. Hyperconnectivity between DMN, salience, and CC domains in PS youth only occurred in a state characterized by synchronization of the DMN and CC domains, a state that also becomes less frequent with age. However, dysconnectivity of the sensorimotor and visual systems in PS youth was revealed in other transient states completing the picture of whole-brain dysconnectivity patterns associated with PS.Overall, state-dependent dysconnectivity was observed in PS youth, providing the first evidence that disruptions of dynamic functional connectivity are present across a broader psychosis continuum.

Effects of combat sports on cerebellar function in adolescents: a resting-state fMRI study

2021 ◽  
Author(s):  
Wei Li ◽  
Xin Kong ◽  
Jun Ma
Keyword(s):  
Resting State ◽  
Brain Plasticity ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Combat Sports ◽  
Additional Information ◽  
Cerebellar Function ◽  
Compensatory Adaptation ◽  
Fmri Study ◽  
Intracranial Lesions

Objectives: To evaluate the effects of combat sports on cerebellar function in adolescents based on resting-state functional MRI (rs-fMRI). Methods: Rs-fMRI data were acquired from the combat sports (CS) group (n = 32, aged 14.2 ± 1.1 years) and non-athlete healthy control (HC) group (n = 29, aged 14.8 ± 0.9 years). The amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) within the cerebellum was calculated and then compared between the two groups. Results: None of these participants displayed intracranial lesions on conventional MRI and microhemorrhages on SWI. Compared with the HC group, the CS group showed decreased ALFF and ReHo in the bilateral cerebellum, mainly located in the inferior regions of the cerebellum (Cerebellum_8, Cerebellum_9, Cerebellum_7b, and Cerebellum_Crus2). While increased FC was found within the cerebellar network, mainly located in the superior regions near the midline (bilateral Cerebellum_6, Cerebellum_Crus1_R, and Vermis_6). There is no inter network FC change between the CEN and other networks. Conclusion: This study confirmed extensive effects of combat sports on cerebellar rs-fMRI in adolescents, which could enhance the understanding of cerebellar regulatory mechanism under combat conditions, and provide additional information about cerebellar protective inhibition and compensatory adaptation. Advances in knowledge: Adolescent combat participants are an ideal model to study training-induced brain plasticity and vulnerability. Relative to task-related fMRI, rs-fMRI can bring more information about cerebellar regulation and explain the Central Governor Model more comprehensively.

scholarly journals Acute ischemic stroke alters the brain’s preference for distinct dynamic connectivity states

2019 ◽  
Author(s):  
Anna K. Bonkhoff ◽  
Flor A. Espinoza ◽  
Harshvardhan Gazula ◽  
Victor M. Vergara ◽  
Lukas Hensel ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Resting State ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Cortical Reorganization ◽  
Connectivity Pattern ◽  
Healthy Controls ◽  
Stroke Patients ◽  
Dynamic Connectivity

AbstractAcute ischemic stroke disturbs healthy brain organization, prompting subsequent plasticity and reorganization to compensate for loss of specialized neural tissue and function. Static resting-state functional magnetic resonance imaging (fMRI) studies have already furthered our understanding of cerebral reorganization by estimating stroke-induced changes in network connectivity aggregated over the duration of several minutes. In this study, we utilized dynamic resting-state fMRI analyses to increase temporal resolution to seconds and explore transient configurations of motor network connectivity in acute stroke. To this end, we collected resting-state fMRI data of 31 acute ischemic stroke patients and 17 age-matched healthy controls. Stroke patients presented with moderate to severe hand motor deficits. By estimating dynamic connectivity within a sliding window framework, we identified three distinct connectivity configurations of motor-related networks. Motor networks were organized into three regional domains, i.e. a cortical, subcortical and cerebellar domain. Temporal connectivity patterns of stroke patients markedly diverged from those of healthy controls depending on the severity of the initial motor impairment. Moderately affected patients (n=18) spent significantly more time in a weakly connected configuration that was characterized by low levels of connectivity, both locally as well as between distant regions. In contrast, severely affected patients (n=13) showed a significant preference for transitions into a spatially segregated connectivity configuration. This configuration featured particularly high levels of local connectivity within the three regional domains as well as anti-correlated connectivity between distant networks across domains. A third connectivity configuration represented an intermediate connectivity pattern compared to the preceding two, and predominantly encompassed decreased inter-hemispheric connectivity between cortical motor networks independent of individual deficit severity. Alterations within this third configuration thus closely resembled previously reported ones originating from static resting-state fMRI studies post-stroke.In summary, acute ischemic stroke not only prompted changes in connectivity between distinct functional networks, yet also caused severe aberrations in temporal properties of large-scale network interactions depending on the individual deficit severity. These findings offer new vistas on the dynamic neural mechanisms underlying acute neurological symptoms, cortical reorganization and treatment effects in stroke patients.

Spectral broadening of the Soret band in myoglobin: an interpretation by the full spectrum of low-frequency modes from a normal modes analysis

2005 ◽  
Vol 34 (7) ◽  
pp. 881-889 ◽  
Author(s):  
Antonio Cupane ◽  
Marco Cammarata ◽  
Lorenzo Cordone ◽  
Maurizio Leone ◽  
Eugenio Vitrano ◽  
...  
Keyword(s):  
Normal Modes ◽  
Low Frequency ◽  
Soret Band ◽  
Spectral Broadening ◽  
Full Spectrum ◽  
Normal Modes Analysis

Functional abnormalities in Broca’s area in adolescents with ADHD: A resting-state fMRI study

2015 ◽  
Vol 51 (1) ◽  
Author(s):  
Michał Pikusa ◽  
Rafał Jończyk
Keyword(s):  
Resting State ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Broca’S Area ◽  
Broca's Area ◽  
Hyperactivity Disorder ◽  
Spontaneous Neural Activity ◽  
Fmri Study ◽  
Brodmann Areas ◽  
Underlying Causes

AbstractThere is evidence that attention-deficit/hyperactivity disorder (ADHD) is associated with linguistic difficulties. However, the pathophysiology underlying these difficulties is yet to be determined. This study investigates functional abnormalities in Broca’s area, which is associated with speech production and processing, in adolescents with ADHD by means of resting-state fMRI. Data for the study was taken from the ADHD-200 project and included 267 ADHD patients (109 with combined inattentive/hyperactive subtype and 158 with inattentive subtype) and 478 typically-developing control (TDC) subjects. An analysis of fractional amplitude of low-frequency fluctuations (fALFF), which reflects spontaneous neural activity, in Broca’s area (Brodmann Areas 44/45) was performed on the data and the results were compared statistically across the participant groups. fALFF was found to be significantly lower in the ADHD inattentive group as compared to TDC in BA 44, and in the ADHD combined group as compared to TDC in BA 45. The results suggest that there are functional abnormalities in Broca’s area with people suffering from ADHD, and that the localization of these abnormalities might be connected to particular language deficits associated with ADHD subtypes, which we discuss in the article. The findings might help explore the underlying causes of specific language difficulties in ADHD.

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