FMRI resting state networks define distinct modes of long-distance interactions in the human brain

Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, UK.
NeuroImage (Impact Factor: 6.36). 03/2006; 29(4):1359-67. DOI: 10.1016/j.neuroimage.2005.08.035
Source: PubMed


Functional magnetic resonance imaging (fMRI) studies of the human brain have suggested that low-frequency fluctuations in resting fMRI data collected using blood oxygen level dependent (BOLD) contrast correspond to functionally relevant resting state networks (RSNs). Whether the fluctuations of resting fMRI signal in RSNs are a direct consequence of neocortical neuronal activity or are low-frequency artifacts due to other physiological processes (e.g., autonomically driven fluctuations in cerebral blood flow) is uncertain. In order to investigate further these fluctuations, we have characterized their spatial and temporal properties using probabilistic independent component analysis (PICA), a robust approach to RSN identification. Here, we provide evidence that: i. RSNs are not caused by signal artifacts due to low sampling rate (aliasing); ii. they are localized primarily to the cerebral cortex; iii. similar RSNs also can be identified in perfusion fMRI data; and iv. at least 5 distinct RSN patterns are reproducible across different subjects. The RSNs appear to reflect "default" interactions related to functional networks related to those recruited by specific types of cognitive processes. RSNs are a major source of non-modeled signal in BOLD fMRI data, so a full understanding of their dynamics will improve the interpretation of functional brain imaging studies more generally. Because RSNs reflect interactions in cognitively relevant functional networks, they offer a new approach to the characterization of state changes with pathology and the effects of drugs.

Download full-text


Available from: Paul M Matthews, Jan 11, 2015
  • Source
    • "The functional images were band-pass filtered for low frequencies fluctuations (hz 0.01-0.08) to reduce the interference of physiological noise, such as respiratory and cardiac artifacts – occurring at higher frequencies (0.3-0.5 Hz) (Birn, Diamond et al. 2006, Van Dijk, Hedden et al. 2010). Lowfrequency fluctuations below 0.1 Hz have been demonstrated to predominate in the crosscorrelation coefficients for functionally related regions (Biswal, Yetkin et al. 1995, Cordes, Haughton et al. 2000, De Luca, Beckmann et al. 2006), with the most consistent correlations occurring within a range of 0.01-0.08 Hz (Van Dijk, Hedden et al. 2010, Cong, Puoliväli et al. 2014). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Single-nucleotide polymorphisms (SNPs) of the fat mass and obesity associated (FTO) gene are linked to obesity, but how these SNPs influence resting-state neural activation is unknown. Few brain-imaging studies have investigated the influence of obesity-related SNPs on neural activity, and no study has investigated resting-state connectivity patterns. We tested connectivity within three, main resting-state networks: default mode (DMN), sensorimotor (SMN), and salience network (SN) in thirty male participants, grouped based on genotype for the rs9939609 FTO SNP, as well as punishment and reward sensitivity measured by the Behavioral Inhibition (BIS) and Behavioral Activation System (BAS) questionnaires. Because obesity is associated with anomalies in both systems, we calculated a BIS/BAS ratio (BBr) accounting for features of both scores. A prominence of BIS over BAS (higher BBr) resulted in increased connectivity in frontal and paralimbic regions. These alterations were more evident in the obesity-associated AA genotype, where a high BBr was also associated with increased SN connectivity in dopaminergic circuitries, and in a subnetwork involved in somatosensory integration regarding food. Participants with AA genotype and high BBr, compared to corresponding participants in the TT genotype, also showed greater DMN connectivity in regions involved in the processing of food cues, and in the SMN for regions involved in visceral perception and reward-based learning. These findings suggest that neural connectivity patterns influence the sensitivity toward punishment and reward more closely in the AA carriers, predisposing them to developing obesity. Our work explains a complex interaction between genetics, neural patterns, and behavioral measures in determining the risk for obesity and may help develop individually-tailored strategies for obesity prevention.
    Full-text · Article · Feb 2016 · Frontiers in Human Neuroscience
  • Source
    • "The procedure identifies synchronized spontaneous lowfrequency (<0.1 Hz) fluctuation of blood oxygen leveldependent (BOLD) signals across the brain in the resting state (Biswal et al. 1995; Lowe et al. 1998; Cordes et al. 2000 ). Based on consistent patterns across healthy subjects (Beckmann and Smith 2005; Damoiseaux et al. 2006; De Luca et al. 2006; Fox and Raichle 2007), resting-state FC procedures have been applied widely in various functional brain network studies, ranging from psychiatric disorders to neurological conditions (Fox and Greicius 2010), as well as in exploration of human brain functions (Smith et al. 2009; Laird et al. 2013; Sadaghiani and Kleinschmidt 2013). The procedures may be useful in assessing functional brain networks in OSA subjects, since the condition is accompanied by severe behavioral and physiological sequelae. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Obstructive sleep apnea (OSA) subjects show impaired autonomic, affective, executive, sensorimotor, and cognitive functions. Brain injury in OSA subjects appears in multiple sites regulating these functions, but the integrity of functional networks within the regulatory sites remains unclear. Our aim was to examine the functional interactions and the complex network organization of these interactions across the whole brain in OSA, using regional functional connectivity (FC) and brain network topological properties. We collected resting-state functional magnetic resonance imaging (MRI) data, using a 3.0-Tesla MRI scanner, from 69 newly diagnosed, treatment-naïve, moderate-to-severe OSA (age, 48.3 ± 9.2 years; body mass index, 31 ± 6.2 kg/m2; apnea–hypopnea index (AHI), 35.6 ± 23.3 events/h) and 82 control subjects (47.6 ± 9.1 years; body mass index, 25.1 ± 3.5 kg/m2). Data were analyzed to examine FC in OSA over controls as interregional correlations and brain network topological properties. Obstructive sleep apnea subjects showed significantly altered FC in the cerebellar, frontal, parietal, temporal, occipital, limbic, and basal ganglia regions (FDR, P < 0.05). Entire functional brain networks in OSA subjects showed significantly less efficient integration, and their regional topological properties of functional integration and specialization characteristics also showed declined trends in areas showing altered FC, an outcome which would interfere with brain network organization (P < 0.05; 10,000 permutations). Brain sites with abnormal topological properties in OSA showed significant relationships with AHI scores. Our findings suggest that the dysfunction extends to resting conditions, and the altered FC and impaired network organization may underlie the impaired responses in autonomic, cognitive, and sensorimotor functions. The outcomes likely result from the prominent structural changes in both axons and nuclear structures, which occur in the condition.
    Full-text · Article · Feb 2016 · Brain and Behavior
  • Source
    • "Aliasing of those physiological signals into the resting-state frequencies is known to occur, which can contribute to the synchronization of the intrinsic low-frequency oscillations (Birn et al., 2006;Biswal et al., 2007). However, it has been shown that by applying multiple regression techniques like ICA, cardiac and respiratory induced signal variations can be separated from signal fluctuations of interest (Beckmann et al., 2005;De Luca et al., 2006;Fukunaga et al., 2006;Birn et al., 2008), thus somewhat reducing this concern. Finally, it is likely that incorporating additional modalities such as diffusion tensor imaging (DTI) could shed light on the extent to which loss of structural connectivity underlies changes in age-associated functional connectivity, particularly the loss of synchronization between aDMN and pDMN observed in this study. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Healthy aging is associated with brain changes that reflect an alteration to a functional unit in response to the available resources and architecture. Even before the onset of noticeable cognitive decline, the neural scaffolds underlying cognitive function undergo considerable change. Prior studies have suggested a disruption of the connectivity pattern within the "default-mode" network (DMN), and more specifically a disruption of the anterio-posterior connectivity. In this study, we explored the effects of aging on within-network connectivity of three DMN subnetworks: a posterior DMN (pDMN), an anterior DMN (aDMN), and a ventral DMN (vDMN); as well as between-network connectivity during resting-state. Using groupICA on 43 young and 43 older healthy adults, we showed a reduction of network co-activation in two of the DMN subnetworks (pDMN and aDMN) and demonstrated a difference in between-component connectivity levels. The older group exhibited more numerous high-correlation pairs (Pearson's rho > 0.3, Number of comp-pairs = 46) in comparison to the young group (Number of comp-pairs = 34), suggesting a more connected/less segregated cortical system. Moreover, three component-pairs exhibited statistically significant differences between the two populations. Visual areas V2-V1 and V2-V4 were more correlated in the older adults, while aDMN-pDMN correlation decreased with aging. The increase in the number of high-correlation component-pairs and the elevated correlation in the visual areas are consistent with the prior hypothesis that aging is associated with a reduction of functional segregation. However, the aDMN-pDMN dis-connectivity may be occurring under a different mechanism, a mechanism more related to a breakdown of structural integrity along the anterio-posterior axis.
    Full-text · Article · Dec 2015 · Frontiers in Aging Neuroscience
Show more