Dataset Information

Dynamic properties of functional connectivity in the rodent.

ABSTRACT: Functional connectivity mapping with resting-state magnetic resonance imaging (MRI) has become an immensely powerful technique that provides insight into both normal cognitive function and disruptions linked to neurological disorders. Traditionally, connectivity is mapped using data from an entire scan (minutes), but it is well known that cognitive processes occur on much shorter time scales (seconds). Recent studies have demonstrated that the correlation between the blood oxygenation level-dependent (BOLD) MRI signal from different areas varies over time, motivating a further exploration of these fluctuations in apparent connectivity. However, it has also been shown that similar changes in correlation can arise when the timing relationships between voxels are randomized (Handwerker et al., 2012 ). In this work, we show that functional connectivity in the anesthetized rat exhibits dynamic properties that are similar to those previously observed in awake humans (Chang and Glover, 2010 ) and anesthetized monkeys (Hutchison et al., 2012 ). Sliding window correlation between BOLD time courses obtained from bilateral cortical and subcortical regions of interest results in periods of variable positive and negative correlation for most pairs of areas except homologous areas in opposite hemispheres, which exhibit a primarily positive correlation. A comparison with sliding window correlation of randomly matched time courses suggests that with the exception of homologous areas and sensorimotor connections, the dynamics cannot be distinguished from random fluctuations in correlation over time, supporting the idea that some of these dynamic patterns may be due to inherent properties of the signal rather than variations in neural coherence. Within the pairs of areas where the dynamics are most different from those of randomly matched time courses, ten common patterns of connectivity are identified, and their occurrence as a function of time is plotted for all animals. The observation of time-varying correlation in the rodent model will facilitate the future multimodal experiments needed to determine whether the changes in apparent connectivity are linked to underlying neural variability.

SUBMITTER: Keilholz SD

PROVIDER: S-EPMC3621313 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dynamic properties of functional connectivity in the rodent.

Keilholz Shella D SD Magnuson Matthew E ME Pan Wen-Ju WJ Willis Martha M Thompson Garth J GJ

Brain connectivity 20130129 1

Functional connectivity mapping with resting-state magnetic resonance imaging (MRI) has become an immensely powerful technique that provides insight into both normal cognitive function and disruptions linked to neurological disorders. Traditionally, connectivity is mapped using data from an entire scan (minutes), but it is well known that cognitive processes occur on much shorter time scales (seconds). Recent studies have demonstrated that the correlation between the blood oxygenation level-depe ...[more]

PMID: 23106103

Similar Datasets

Project description:Major depressive disorder (MDD) is a complex mood disorder characterized by persistent and overwhelming depression. Previous studies have identified abnormalities in large scale functional brain networks in MDD, yet most of them were based on static functional connectivity. In contrast, here we explored disrupted topological organization of dynamic functional network connectivity (dFNC) in MDD based on graph theory. One hundred and eighty-two MDD patients and 218 healthy controls were included in this study, all Chinese Han people. By applying group information guided independent component analysis (GIG-ICA) to resting-state functional magnetic resonance imaging (fMRI) data, the dFNCs of each subject were estimated using a sliding window method and k-means clustering. Network properties including global efficiency, local efficiency, node strength and harmonic centrality, were calculated for each subject. Five dynamic functional states were identified, three of which demonstrated significant group differences in their percentage of state occurrence. Interestingly, MDD patients spent much more time in a weakly-connected State 2, which includes regions previously associated with self-focused thinking, a representative feature of depression. In addition, the FNCs in MDD were connected differently in different states, especially among prefrontal, sensorimotor, and cerebellum networks. MDD patients exhibited significantly reduced harmonic centrality primarily involving parietal lobule, lingual gyrus and thalamus. Moreover, three dFNCs with disrupted node properties were commonly identified in different states, and also correlated with depressive symptom severity and cognitive performance. This study is the first attempt to investigate the dynamic functional abnormalities in MDD in a Chinese population using a relatively large sample size, which provides new evidence on aberrant time-varying brain activity and its network disruptions in MDD, which might underscore the impaired cognitive functions in this mental disorder.

Dataset Information

Dynamic properties of functional connectivity in the rodent.

Publications

Dynamic properties of functional connectivity in the rodent.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets