Multiple Sclerosis: Low-Frequency Temporal Blood Oxygen Level–Dependent Fluctuations Indicate Reduced Functional Connectivity—Initial Results

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

doi:10.1148/radiol.2241011005

Cited by 239 publications

(188 citation statements)

References 61 publications

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“…The identified brain regions are largely consistent with those in a previous study by our group, which aimed at discriminating between HC subjects and RRMS patients based on stationary FC (Richiardi et al, 2012); i.e., the left Heschl's gyrus, right rolandic operculum, and right superior parietal gyrus, were identified as being more strongly connected in HC subjects in both studies. Reduced stationary FC in MS patients is indeed commonly observed and is thought to stem from structural damage (Bonavita et al, 2011;Lowe et al, 2002;Richiardi et al, 2012;Roosendaal et al, 2010). However, we also confirmed the bilateral parahippocampal gyri, right amygdala, left thalamus and left midtemporal pole as more strongly connected in RRMS patients (Richiardi et al, 2012).…”

Section: Stationary and Dynamic Fc In Rrms Patientssupporting

confidence: 74%

“…Alternative imaging methods, such as resting-state fMRI, have started to address the issue of hidden damage and shown disrupted stationary FC. While some studies restricted their analysis to the DMN or motor regions (Bonavita et al, 2011;Dogonowski et al, 2013;Lowe et al, 2002;Rocca et al, 2010), others have reported changes in several large-scale resting state networks, including the sensorimotor and executive control networks (Hawellek et al, 2011;Richiardi et al, 2012;Rocca et al, 2012;Roosendaal et al, 2010). Together, these results are very promising for characterizing the functional pathology of MS, but the relationship between structural damage and functional changes is still poorly understood (Schoonheim and Filippi, 2012).…”

Section: Introductionmentioning

confidence: 99%

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Principal components of functional connectivity: A new approach to study dynamic brain connectivity during rest

et al. 2013

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Functional connectivity (FC) as measured by correlation between fMRI BOLD time courses of distinct brain regions has revealed meaningful organization of spontaneous fluctuations in the resting brain. However, an increasing amount of evidence points to non-stationarity of FC; i.e., FC dynamically changes over time reflecting additional and rich information about brain organization, but representing new challenges for analysis and interpretation. Here, we propose a data-driven approach based on principal component analysis (PCA) to reveal hidden patterns of coherent FC dynamics across multiple subjects. We demonstrate the feasibility and relevance of this new approach by examining the differences in dynamic FC between 13 healthy control subjects and 15 minimally disabled relapse-remitting multiple sclerosis patients. We estimated whole-brain dynamic FC of regionally-averaged BOLD activity using sliding time windows. We then used PCA to identify FC patterns, termed "eigenconnectivities", that reflect meaningful patterns in FC fluctuations. We then assessed the contributions of these patterns to the dynamic FC at any given time point and identified a network of connections centered on the default-mode network with altered contribution in patients. Our results complement traditional stationary analyses, and reveal novel insights into brain connectivity dynamics and their modulation in a neurodegenerative disease.© 2013 Elsevier Inc. All rights reserved. IntroductionSpontaneous fluctuations of the functional MRI (fMRI) bloodoxygen-level-dependent (BOLD) signal are not random but temporally coherent between distinct brain regions. While these fluctuations were long considered as "noise", Biswal et al. (1995) showed that fluctuations of motor areas were correlated even in the absence of a motor task. Several other networks of coherent BOLD activity between remote brain regions have since been identified, including visual, auditory, language and attention networks, and a network called the "default mode network" (DMN) which reduces its activity during attentiondemanding tasks. These networks of regions with coherent activity during rest are consistent across subjects and closely resemble the brain's functional organization of evoked responses (Damoiseaux et al., 2006;Fox and Raichle, 2007;Laird et al., 2011;Smith et al., 2009). Coherent BOLD activity persists during sleep and in anesthetized monkeys, suggesting that it reflects a fundamental property of the brain's functional organization (Larson-Prior et al., 2009;Vincent et al., 2007).Coherent BOLD activity, known as "functional connectivity" (FC), is modulated by learning (Bassett et al., 2011), cognitive and affective states (Cribben et al., 2012;Ekman et al., 2012;Eryilmaz et al., 2011;Richiardi et al., 2011;Shirer et al., 2012) and also spontaneously Chang and Glover, 2010; Kitzbichler et al., 2009). Chang andGlover (2010) showed that FC between the posterior cingulate cortex, a key region of the default mode network, and various other brain regions was highly dy...

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Section: Stationary and Dynamic Fc In Rrms Patientssupporting

confidence: 74%

Section: Introductionmentioning

confidence: 99%

Principal components of functional connectivity: A new approach to study dynamic brain connectivity during rest

et al. 2013

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“…Nonetheless, timeseries correlation analysis has been utilized in studies of normal cognitive and emotional states (Greicius et al, 2003;Bartels and Zeki, 2005;Fox et al, 2005;Menon and Levitin, 2005), disease states (Lowe et al, 2002;Anand et al, 2005;Koshino et al, 2005;), and pharmacological interventions (Li et al, 2000;Honey et al, 2003;Peltier et al, 2005). Our study contributes to a rapidly growing body of knowledge regarding normal and abnormal functional neural circuitry.…”

Section: Discussionmentioning

confidence: 97%

“…Several specific approaches have been implemented (Horwitz, 2003), and their relative merits have not been established. The timeseries correlation method (Biswal et al, 1995;Lowe et al, 1998) examines interregional correlations within individual subjects over the timecourse of an experiment, and has been effectively applied to measure functional connectivity across a wide range of cognitive and physiological states (Li et al, 2000;Lowe et al, 2002;Greicius et al, 2003;Honey et al, 2003;Anand et al, 2005;Bartels and Zeki, 2005;Fox et al, 2005;Koshino et al, 2005;Menon and Levitin, 2005;Peltier et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

Alterations of fronto-temporal connectivity during word encoding in schizophrenia

Wolf

Gur

Valdez

et al. 2007

Psychiatry Research: Neuroimaging

107

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Cognitive deficits, including impaired verbal memory, are prominent in schizophrenia and lead to increased disability. Functional neuroimaging of patients with schizophrenia performing memory tasks has revealed abnormal activation patterns in prefrontal cortex and temporo-limbic regions. Aberrant fronto-temporal interactions thus represent a potential pathophysiological mechanism underlying verbal memory deficits, yet this hypothesis of disturbed connectivity is not tested directly with standard activation studies. We performed within-subject correlations of frontal and temporal timeseries to measure functional connectivity during verbal encoding. Our results confirm earlier findings of aberrant fronto-temporal connectivity in schizophrenia, and extend them by identifying distinct alterations within dorsal and ventral prefrontal cortex. Relative to healthy controls, patients with schizophrenia had reduced connectivity between the dorsolateral prefrontal cortex (DLPFC) and temporal lobe areas including parahippocampus and superior temporal gyrus. In contrast, patients showed increased connectivity between a region of ventrolateral prefrontal cortex (VLPFC) and these same temporal lobe regions. Higher temporal-DLPFC connectivity during encoding was associated with better subsequent recognition accuracy in controls, but not patients. Temporal-VLPFC connectivity was uncorrelated with recognition accuracy in either group. The results suggest that reduced temporal-DLPFC connectivity in schizophrenia could underlie encoding deficits, and increased temporal-VLPFC connectivity may represent an ineffective compensatory effort.

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“…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). Biswal and colleagues demonstrated that very low-frequency (o0.08 Hz) temporal fluctuations in BOLD weighted echoplanar imaging data are phase locked between areas of plausible functional connectivity (Biswal et al, 1995b).…”

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

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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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Multiple Sclerosis: Low-Frequency Temporal Blood Oxygen Level–Dependent Fluctuations Indicate Reduced Functional Connectivity—Initial Results

Abstract: On the basis of the connectivity measure of low-frequency BOLD fluctuations, patients with MS exhibited lower functional connectivity between right- and left-hemisphere primary motor cortices when compared with that in control subjects.

Cited by 239 publications

References 61 publications

Principal components of functional connectivity: A new approach to study dynamic brain connectivity during rest

Principal components of functional connectivity: A new approach to study dynamic brain connectivity during rest

Alterations of fronto-temporal connectivity during word encoding in schizophrenia

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

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