Correlations in Low-Frequency BOLD Fluctuations Reflect Cortico-Cortical Connections

Lowe, Mark J.; Džemidžić, Mario; Lurito, Joseph T.; Mathews, Vincent P.; Phillips, Micheal D.

doi:10.1006/nimg.2000.0654

Cited by 290 publications

(195 citation statements)

References 9 publications

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“…A number of recent studies have suggested that the brain remains quite active during the so-called unstimulated state (Shulman, 2001), and that steady data variables such as LFBF could provide important knowledge regarding localized brain activity and connectivity (Maldjian, 2001;Shulman, 2001). Recent studies have used steady-state LFBF correlation data to elucidate connectivity in circuits involved in motor movements (Lowe et al, 2000), speech (Hampson et al, 2002), and working memory . Changes in LFBF correlation as a measure of abnormal connectivity have also been reported in disease states such as multiple sclerosis (Lowe et al, 2002), and in brief reports in schizophrenia (Driesen, 2003), depression (Skudlarski et al, 2000), and bipolar disorder (Blumberg, 2003).…”

Section: Discussionmentioning

confidence: 99%

“…In a recently described method, correlation of low-frequency BOLD weighted temporal fluctuations (LFBF) in steady-state fMRI data has been used as a measure of connectivity between brain regions (Biswal et al, 1995b;Lowe et al, 2000). Spontaneous low-frequency oscillations in regional cerebral blood flow and oxygenation in animals have been observed with laser Doppler flow, fluororeflectometry, fluorescence video microscopy, and polarographic measurement of brain tissue (Lowe et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

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Antidepressant Effect on Connectivity of the Mood-Regulating Circuit: An fMRI Study

Anand

Liu

Wang

et al. 2005

Neuropsychopharmacol

304

206

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The mechanisms by which antidepressant-induced neurochemical changes lead to physiological changes in brain circuitry and ultimately an antidepressant response remain unclear. This study investigated the effects of sertraline, a selective serotonin reuptake inhibitor antidepressant, on corticolimbic connectivity, using functional magnetic resonance imaging (fMRI). In all, 12 unmedicated unipolar depressed patients and 11 closely matched healthy control subjects completed two fMRI scanning sessions at baseline and after 6 weeks. Depressed patients received treatment with sertraline between the two sessions. During each fMRI session, subjects first completed a conventional block-design experiment. Next, connectivity between cortical and limbic regions was measured using correlations of lowfrequency blood oxygen level-dependent (BOLD) fluctuations (LFBF) during continuous exposure to neutral, positive, and negative pictures. At baseline, depressed patients had decreased corticolimbic LFBF correlations compared to healthy subjects during the resting state and on exposure to emotionally valenced pictures. At rest and on exposure to neutral and positive pictures, LFBF correlation between the anterior cingulate cortex and limbic regions was significantly increased in patients after treatment. However, on exposure to negative pictures, corticolimbic LFBF correlations remained decreased in depressed patients. The results of this study are consistent with the hypothesis that antidepressant treatment may increase corticolimbic connectivity, thereby possibly increasing the regulatory influence of cortical mood-regulating regions over limbic regions.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Antidepressant Effect on Connectivity of the Mood-Regulating Circuit: An fMRI Study

Anand

Liu

Wang

et al. 2005

Neuropsychopharmacol

304

206

View full text Add to dashboard Cite

show abstract

“…This phenomenon of so-called 'resting-state activity' resembles the very low-frequency ( < 0.1 Hz) fluctuations of spontaneous neuronal and metabolic activity, which were observed in animals that were deprived of external stimuli (Allers et al, 2002;Dora and Kovach, 1981;Leopold et al, 2003;Ruskin et al, 2003). The observed synchronized fluctuation across distributed regions is suggestive of the underlying functional relationship (Biswal et al, 1995;Cordes et al, 2000;Greicius et al, 2003;Hampson et al, 2002;Lowe et al, 2000). In addition, the regions showing correlated fluctuations are highly consistent within and across subjects (Beckmann et al, 2005;van de Ven et al, 2004), suggesting that they might allow mapping and classification of the networks that underlie human brain function without the need for carefully conditioned stimuli.…”

Section: Introductionmentioning

confidence: 96%

Metabolic Origin of Bold Signal Fluctuations in the Absence of Stimuli

Fukunaga

Horovitz

Zwart

et al. 2008

J Cereb Blood Flow Metab

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Blood oxygen level-dependent (BOLD) functional magnetic resonance imaging studies have shown the existence of ongoing blood flow fluctuations in the absence of stimuli. Although this so-called 'resting-state activity' appears to be correlated across brain regions with apparent functional relationship, its origin might be predominantly vascular and not directly representing neuronal signaling. To investigate this, we simultaneously measured BOLD and perfusion signals on healthy human subjects (n = 11) and used their ratio (BOLD/perfusion ratio or BPR) as an indicator of metabolic demand. BPR during rest and sleep was compared with that during a visual task (VT) and a breath-holding task (BH), which are challenges with substantial and little metabolic involvement, respectively. Within the visual cortex, BPR was 3.76±1.23 during BH, which was significantly higher than during the VT (1.76 ± 0.27) and rest (1.56 ± 0.41). Meanwhile, BPR values during VT and rest were not significantly different, suggesting a similar metabolic involvement. Eight subjects showed stage 1 and 2 sleep, during which temporally correlated BOLD and perfusion activity continued. In these subjects, there was no significant difference in BPR between the sleep and waking conditions (1.79 ± 0.54 and 1.66 ± 0.67, respectively), but both were lower than the BPR during BH. These data suggest that resting-state activity, at least in part, represents a metabolic process.

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“…The organization of these functional networks can be described using the umbrella term 'functional connectivity', defined as the deviations from statistical independence between distributed and often spatially remote neuronal units (Friston, 1994;Craddock et al, 2013). Despite the indirect nature of the blood oxygenation level dependent (BOLD) signal, functional magnetic resonance imaging (fMRI) has proven to be able to extract patterns of co-activation between clusters of voxels (Lowe et al, 2000).…”

Section: Introductionmentioning

confidence: 99%

Structurally-informed Bayesian functional connectivity analysis

et al. 2014

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Functional connectivity refers to covarying activity between spatially segregated brain regions and can be studied by measuring correlation between functional magnetic resonance imaging (fMRI) timeseries. These correlations can be caused either by direct communication via active axonal pathways or indirectly via the interaction with other regions. It is not possible to discriminate between these two kinds of functional interaction simply by considering the covariance matrix. However, the non-diagonal elements of its inverse, the precision matrix, can be naturally related to direct communication between brain areas and interpreted in terms of partial correlations. In this paper, we propose a Bayesian model for functional connectivity analysis which allows estimation of a posterior density over precision matrices, and, consequently, allows one to quantify the uncertainty about estimated partial correlations. In order to make model estimation feasible it is assumed that the sparseness structure of the precision matrices is given by an estimate of structural connectivity obtained using diffusion imaging data. The model was tested on simulated data as well as resting-state fMRI data and compared with a graphical lasso analysis. The presented approach provides a theoretically solid foundation for quantifying functional connectivity in the presence of uncertainty.

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Correlations in Low-Frequency BOLD Fluctuations Reflect Cortico-Cortical Connections

Cited by 290 publications

References 9 publications

Antidepressant Effect on Connectivity of the Mood-Regulating Circuit: An fMRI Study

Antidepressant Effect on Connectivity of the Mood-Regulating Circuit: An fMRI Study

Metabolic Origin of Bold Signal Fluctuations in the Absence of Stimuli

Structurally-informed Bayesian functional connectivity analysis

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