The effect of resting condition on resting-state fMRI reliability and consistency: A comparison between resting with eyes open, closed, and fixated
Introduction
Resting-state functional Magnetic Resonance Imaging (rs-fMRI) can provide an estimate of functional connectivity by computing the correlation of low-frequency (< 0.1 Hz) blood-oxygen-level-dependent (BOLD) signal fluctuations in the resting brain, to infer neuronal activity, between regions of interest (Biswal et al., 1995). Fluctuations during this resting-state are thought to represent both spontaneous neuronal activation as well as unconstrained mental activity, such as “day dreaming” or “mind wandering” (Fox et al., 2005, Mason et al., 2007). Although this unconstrained mental activity may be affected by the resting conditions, the instructions given to subjects vary widely across studies. The most common instructions are to rest with either eyes closed, eyes open, or eyes fixating on a cross. Inconsistencies in the resting condition across studies could create difficulties replicating results from one research site to the next. In addition, it is unclear which of these resting conditions provide the most reliable estimates of functional connectivity. The application of resting state functional connectivity using MRI (rs-fcMRI) to clinical studies and the investigation of individual differences in functional connectivity critically depend not only on a consistent spatial pattern of connectivity but also on a repeatable measure of the strength of connectivity. The goal of our current study is to compare the reliability of functional connectivity estimates, as well as the consistency of those estimates, derived from three different resting conditions: eyes closed (EC), eyes open (EO), and eyes fixating (EF).
Several previous studies have examined differences in functional connectivity across these three resting conditions. Feige et al. demonstrated the average BOLD signal intensity in visual processing areas to be higher for EO when compared to EC (Feige et al., 2005); and a study by Yan et al. reported that although the functional connectivity maps of the default mode network (DMN, see Raichle et al., 2001 for details on DMN) appear similar across different resting conditions, the strength of connectivity was lower for EC when compared to EF (Yan et al., 2009). Similarly, a study by Van Dijk et al. found lower correlations within the default mode and attention networks for EC when compared to both EF and EO (Van Dijk et al., 2010). Other studies have found the amplitude of low frequency fluctuation to be greater for EC when compared to both EO and EF as well as that the BOLD signal power is greater for EC (McAvoy et al., 2008, Yan et al., 2009).
One potential source for these differences is that the physiological state of the subject (breathing and cardiac cycles) depends on the resting state condition, and that this, in turn, causes differences in the rs-fMRI data. However, it has been shown that the resting condition has no significant effect on those physiological cycles (McAvoy et al., 2008). Rather, the observed differences were hypothesized to arise from discrepancies in BOLD oscillations depending upon the resting condition itself (McAvoy et al., 2008). This could be due to changes in the alpha rhythm, the most prominent rhythmic electrical potential fluctuation, which is greater when the subject has his/her eyes closed compared to when the eyes are opened (Berger, 1929, Berger, 1930). Prior studies have shown that the amplitude of alpha rhythms is positively correlated to the BOLD signal (Goldman et al., 2002, Moosmann et al., 2003), although, it should be noted that Laufs et al. failed to reproduce this result (Laufs et al., 2003). The differences in functional connectivity during EO and EC conditions could also originate from the possibility that while subjects have their eyes open the increase in visual information gathered and evaluated may contribute to an increase in mind wandering or daydreaming, thus making the activity within the DMN more coherent, a possibility suggested by Yan et al. (2009).
While this prior research provides important insights into the effect of different resting conditions, it does not indicate which of these conditions provide the most reliable estimates of functional connectivity. We therefore compare not only the strength of functional connectivity but also examine the test–retest reliability of functional connectivity and its consistency under the three different resting conditions.
Section snippets
Materials and methods
In this study, we use three different measures to assess reliability, consistency, and overlap of repeated estimates of connectivity matrices and maps. The intraclass correlation coefficient compares within- to between-subject variance and was used to assess test–retest reliability. The Kendall's W is also a measure of repeatability, but compares the rankings of subjects or connections between sessions. To distinguish this from test–retest reliability measured with the ICC, we refer to this
Functional connectivity
We generated connectivity maps from 18 different seeds for each subject and for each of the three different resting state conditions. Fig. 1 displays the group connectivity maps for the left primary visual cortex seed (lVis) for each condition (p-threshold of 1 ∗ 10− 15). A T-test map was generated to assess the differences. Connectivity between the visual seeds was significantly modulated by the resting condition. The EC condition resulted in greater negative connectivity between the left visual
Functional connectivity
Consistent with results from other studies (Fox et al., 2005, Fransson, 2005, Yan et al., 2009), we found that default mode network connectivity maps are largely similar across different resting conditions. That is, in all three of the resting conditions we assessed, the PC has significant positive connectivity to the medial prefrontal cortex and bilateral parietal regions. However, a statistical comparison between resting conditions reveals a decreased connectivity between the PC node of the
Conclusion
This study confirmed the reliability and consistency of the rs-fMRI technique as a tool to observe and characterize functional connectivity of the human brain. Functional connectivity maps were consistent within-subjects and the strength of connectivity within default mode, attention, motor, visual, and auditory networks were reliable across subjects. More particularly, having subjects keep their eyes open (and not asking them to fixate) resulted in the highest reliability in the visual
Acknowledgments
We used an ICC code written by Arash Salarian (MATLAB Central File Exchange. Retrieved August 23, 2012). We thank Rebecca D. Ray, Ricardo Pizarro and Jie Song for assistance with data collection. We also thank Moo K. Chung for his statistical assistance. This study was funded by NIH grant RC1MH090912 and the Health Emotions Research Institute.
Conflict of interest
We have no conflict of interests to report.
References (48)
- et al.
Test–retest reliability of resting-state connectivity network characteristics using fMRI and graph theoretical measures
NeuroImage
(2012) AFNI: software for analysis and visualization of functional magnetic resonance neuroimages
Comput. Biomed. Res.
(1996)- et al.
The precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: evidence from a partial correlation network analysis
NeuroImage
(2008) - et al.
Abnormal neural activities in first-episode, treatment-naive, short-illness-duration, and treatment-response patients with major depressive disorder: a resting-state fMRI study
J. Affect. Disord.
(2011) - et al.
Integration of motion correction and physiological noise regression in fMRI
NeuroImage
(2008) - et al.
The intrinsic functional organization of the brain is altered in autism
NeuroImage
(2008) - et al.
EEG-correlated fMRI of human alpha activity
NeuroImage
(2003) - et al.
Correlates of alpha rhythm in functional magnetic resonance imaging and near infrared spectroscopy
NeuroImage
(2003) - et al.
Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion
NeuroImage
(2012) - et al.
A new method for improving functional-to-structural MRI alignment using local Pearson correlation
NeuroImage
(2009)
Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth
NeuroImage
The thalamus as the generator and modulator of EEG alpha rhythm: a combined PET/EEG study with lorazepam challenge in humans
NeuroImage
Advances in functional and structural MR image analysis and implementation as FSL
NeuroImage
Resting-state fMRI can reliably map neural networks in children
NeuroImage
The influence of head motion on intrinsic functional connectivity MRI
NeuroImage
Bayesian analysis of neuroimaging data in FSL
NeuroImage
Regional homogeneity approach to fMRI data analysis
NeuroImage
Reliable intrinsic connectivity networks: test–retest evaluation using ICA and dual regression approach
NeuroImage
Über das Elektrenkephalogramm des Menschen
Arch. Psychiatr. Nervenkr.
Über das Elektrenkephalogramm des Menschen II
J. Psychol. Neurol.
Functional connectivity in the motor cortex of resting human brain using echo-planar MRI
Magn. Reson. Med.
The brain's default network: anatomy, function, and relevance to disease
Ann. N. Y. Acad. Sci.
Control of goal-directed and stimulus-driven attention in the brain
Nat. Rev. Neurosci.
Cortical and subcortical correlates of electroencephalographic alpha rhythm modulation
J. Neurophysiol.
Cited by (297)
Abnormal spontaneous activity of regions related to mood regulation mediates the effect of childhood emotional neglect on major depressive disorder
2023, Psychiatry Research - NeuroimagingRegional Homogeneity in schizophrenia patients with tardive dyskinesia: a resting-state fMRI study
2023, Psychiatry Research - NeuroimagingImpact of Amplitude and Phase of fMRI time series for Functional Connectivity Analysis
2023, Magnetic Resonance Imaging