The connectivity of functional cores reveals different degrees of segregation and integration in the brain at rest

Pasquale, Francesco de; Sabatini, Umberto; Penna, Stefania Della; Sestieri, Carlo; Caravasso, Chiara Falletta; Formisano, Rita; Péran, Patrice

doi:10.1016/j.neuroimage.2012.11.051

Cited by 49 publications

(74 citation statements)

References 58 publications

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“…To compute the inverse equivalent of the stFFT surface data in the alpha-band, we filtered the single EEG trials for each condition and subject in the alpha frequency band, inverted them and then averaged the normed (i.e., scalar) values of all single trials (similar to the approach used by de Pasquale et al, 2013). This results in a temporally resolved representation of alpha-band power distributed across 5018 solution points in the inverse space.…”

Section: Methodsmentioning

confidence: 99%

Left temporal alpha-band activity reflects single word intelligibility

Becker

Pefkou

Michel

et al. 2013

Front. Syst. Neurosci.

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The electroencephalographic (EEG) correlates of degraded speech perception have been explored in a number of recent studies. However, such investigations have often been inconclusive as to whether observed differences in brain responses between conditions result from different acoustic properties of more or less intelligible stimuli or whether they relate to cognitive processes implicated in comprehending challenging stimuli. In this study we used noise vocoding to spectrally degrade monosyllabic words in order to manipulate their intelligibility. We used spectral rotation to generate incomprehensible control conditions matched in terms of spectral detail. We recorded EEG from 14 volunteers who listened to a series of noise vocoded (NV) and noise-vocoded spectrally-rotated (rNV) words, while they carried out a detection task. We specifically sought components of the EEG response that showed an interaction between spectral rotation and spectral degradation. This reflects those aspects of the brain electrical response that are related to the intelligibility of acoustically degraded monosyllabic words, while controlling for spectral detail. An interaction between spectral complexity and rotation was apparent in both evoked and induced activity. Analyses of event-related potentials showed an interaction effect for a P300-like component at several centro-parietal electrodes. Time-frequency analysis of the EEG signal in the alpha-band revealed a monotonic increase in event-related desynchronization (ERD) for the NV but not the rNV stimuli in the alpha band at a left temporo-central electrode cluster from 420–560 ms reflecting a direct relationship between the strength of alpha-band ERD and intelligibility. By matching NV words with their incomprehensible rNV homologues, we reveal the spatiotemporal pattern of evoked and induced processes involved in degraded speech perception, largely uncontaminated by purely acoustic effects.

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Section: Methodsmentioning

confidence: 99%

Left temporal alpha-band activity reflects single word intelligibility

Becker

Pefkou

Michel

et al. 2013

Front. Syst. Neurosci.

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“…However, it can be difficult to determine whether a component represents physiological noise or a brain network (Rosazza et al, 2012). Recent studies are increasingly accepting the view that the brain consists of complex large-scale networks characterized by interregional interactions (de Pasquale et al, 2013; Zahr, 2013). The newly proposed degree centrality (DC) approach is drawing intense attention because it is the most reliable metric among several large-scale network metrics (Li et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Decreased Subcortical and Increased Cortical Degree Centrality in a Nonclinical College Student Sample with Subclinical Depressive Symptoms: A Resting-State fMRI Study

Gao

Liu

et al. 2016

Front. Hum. Neurosci.

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Abnormal functional connectivity (FC) at rest has been identified in clinical depressive disorder. However, very few studies have been conducted to understand the underlying neural substrates of subclinical depression. The newly proposed centrality analysis approach has been increasingly used to explore the large-scale brain network of mental diseases. This study aimed to identify the degree centrality (DC) alteration of the brain network in subclinical depressive subjects. Thirty-seven candidates with subclinical depression and 34 well-matched healthy controls (HCs) were recruited from the same sample of college students. All subjects underwent a resting-state fMRI (rs-fMRI) scan to assess the DC of the whole brain. Compared with controls, subclinical depressive subjects displayed decreased DC in the right parahippocampal gyrus (PHG), left PHG/amygdala, and left caudate and elevated DC in the right posterior parietal lobule (PPL), left inferior frontal gyrus (IFG) and left middle frontal gyrus (MFG). In addition, by using receiver operating characteristic (ROC) analysis, we determined that the DC values in the regions with altered FC between the two groups can be used to differentiate subclinical depressive subjects from HCs. We suggest that decreased DC in subcortical and increased DC in cortical regions might be the neural substrates of subclinical depression.

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“…Each spatial brain component represents a network that includes particular brain regions with specific functions, whereas functional network connectivity (FNC) (Calhoun et al, 2009a; Jafri et al, 2008; Lui et al, 2010; Meda et al, 2012; Yu et al, 2012) examines the integration among components using the temporal correlation of ICA time courses. Recently, graph theory-based analysis of brain connectivity has been widely implemented to reveal the characters of functional segregation and functional integration in human brain (de Pasquale et al, 2013). The clustered connectivity of brain network communities (Ferrarini et al, 2009; He et al, 2009; Meunier et al, 2010; Meunier et al, 2009; Salvador et al, 2005; Shen et al, 2010; Smith et al, 2009) represent functional segregation and specialization, whereas hubs underpin efficient communication and information integration (Bullmore and Sporns, 2012; Sporns, 2013).…”

Section: Introductionmentioning

confidence: 99%

State-related functional integration and functional segregation brain networks in schizophrenia

Yu¹,

Sui²,

Kiehl³

et al. 2013

Schizophrenia Research

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Altered topological properties of brain connectivity networks have emerged as important features of schizophrenia. The aim of this study was to investigate how the state-related modulations to graph measures of functional integration and functional segregation brain networks are disrupted in schizophrenia. Firstly, resting state and auditory oddball discrimination (AOD) fMRI data of healthy controls (HCs) and schizophrenia patients (SZs) were decomposed into spatially independent components (ICs) by group independent component analysis (ICA). Then, weighted positive and negative functional integration (inter-component networks) and functional segregation (intra-component networks) brain networks were built in each subject. Subsequently, connectivity strength, clustering coefficient, and global efficiency of all brain networks were statistically compared between groups (HCs and SZs) in each state and between states (rest and AOD) within group. We found that graph measures of negative functional integration brain network and several positive functional segregation brain networks were altered in schizophrenia during AOD task. The metrics of positive functional integration brain network and one positive functional segregation brain network were higher during the resting state than during the AOD task only in HCs. These findings imply that state-related characteristics of both functional integration and functional segregation brain networks are impaired in schizophrenia which provides new insight into the altered brain performance in this brain disorder.

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The connectivity of functional cores reveals different degrees of segregation and integration in the brain at rest

Cited by 49 publications

References 58 publications

Left temporal alpha-band activity reflects single word intelligibility

Left temporal alpha-band activity reflects single word intelligibility

Decreased Subcortical and Increased Cortical Degree Centrality in a Nonclinical College Student Sample with Subclinical Depressive Symptoms: A Resting-State fMRI Study

State-related functional integration and functional segregation brain networks in schizophrenia

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