Identifying Common-Source Driven Correlations in Resting-State FMRI Via Laminar-Specific Analysis in the Human Visual Cortex
Jonathan Rizzo Polimeni¹, Thomas Witzel^1,2, Bruce Fischl^1,3, Douglas N. Greve¹, Lawrence L. Wald^1,2
1Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, United States; ²Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States; ³Computer Science and AI Lab (CSAIL), Massachusetts Institute of Technology, Cambridge, MA, United States

High-resolution 7T fMRI together with laminar surface-based analysis is utilized to assess the ability of laminar-specific comparisons to differentiate resting state correlations stemming from direct cortical-to-cortical connections from correlations arising from common-source input. We show that the Layer II/III “outputs” of human V1 are more highly correlated to the Layer IV “inputs” of area MT than to other layers, while each layer of V1 is maximally correlated with the same layer in the V1 of the opposite hemisphere. This suggests that laminar analysis of functional connectivity can help identify correlations that may be attributable to indirect connections through common inputs.

Demonstration of the Central Role of the Subcortex in the Developing Brain by Identifying "hubs" in the Network Organisation of Functional Connectivity
Richard Andrew James Masterton¹, Graeme D. Jackson^1,2
1Brain Research Institute, Florey Neuroscience Institutes, Melbourne, Victoria, Australia; ²Department of Medicine, The University of Melbourne, Melbourne, Victoria, Australia

We describe a new voxel-based analysis technique for characterising the network organisation of functional connectivity in the brain. Results are presented showing that subcortical structures play a more central role in children compared with adults.

Do Neural Oscillations Underlie Haemodynamic Functional Connectivity Measurements?
Joanne Rachel Hale¹, Matthew Brookes¹, Claire Stevenson¹, Johanna Zumer¹, Gareth Barnes², Julia Owen³, Susan Francis¹, Srikantan Nagarajan³, Peter Morris^1
1SPMMRC, University of Nottingham, Nottingham, Nottinghamshire, United Kingdom; ²University College London, London, United Kingdom; ³University of California, San Francisco, San Francisco, CA, United States

Recently, interest has increased in studying resting state fluctuations in BOLD fMRI and work has shown correlation between BOLD signals from spatially separate but functionally related brain regions. Unfortunately, fMRI signals are affected by non-neuronal physiological artifacts which can lead to spurious connectivity measurements. The ability to investigate the neuronal activity underlying BOLD connectivity is therefore important. Here we use MEG and 7T fMRI to measure independently resting state sensorimotor cortex connectivity. We show that beta-band fluctuations are implicated in sensorimotor network connectivity, adding weight to previous EEG/fMRI results implying a neural oscillatory basis to resting state BOLD signals.

The Modulation of 7.0T Spontaneous Blood-Oxygenation-Level-Dependent (BOLD) Signal by the Behavioral State
Manus Joseph Donahue^1,2, Hans Hoogduin³, Stephen M. Smith^1,4, Jeroen CW Siero³, Natalia Petridou³, Peter Jezzard^1,2, Peter Luijten³, Jeroen Hendrikse^3
1Clinical Neurology, Oxford University, Oxford, United Kingdom; ²Physics Division, FMRIB Centre, Oxford, United Kingdom; ³Radiology, University Medical Center Utrecht, Utrecht, Netherlands; ⁴Analysis Division, FMRIB Centre, Oxford, United Kingdom

Although the use of spontaneous BOLD activity is being increasingly exploited for connectivity studies, there is limited information available on how spontaneous BOLD signal is influenced by different behavioural states. Here, we investigate the effect of different behavioural states (eyes closed, eyes open, constant-fist-clench, and finger tapping) on spontaneous BOLD signal in the motor cortex at high field strength (7.0T) and high spatial resolution (1.6x1.6x1.6 mm3). Results show that spontaneous signal coherence and, to a lesser degree, amplitude are both dependent (P<0.05) on behavioural state; implications of this phenomenon on evoked, spontaneous and 7.0T BOLD experiments are discussed.

Specific Versus Nonspecific Connectivity: A Transition of the Resting Network from Light to Deep Anesthesia
Xiao Liu^1,2, Xiao-Hong Zhu¹, Yi Zhang¹, Wei Chen^1,2
1CMRR, radiology, University of Minnesota, Minneapolis, MN, United States; ²Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States

In this study, we observed that the resting networks covering specific rat cortical regions under light anesthesia (~1.0% isoflurane) merged into a nonspecific network covering wider cortical regions with stronger connectivity under the deep anesthesia (~1.8% isoflurane). This observation is consistent with a previous electrophysiological study, which demonstrated that the deeply anesthetized brain showed global and nonselective responses to external stimuli. They support a new theory in regards to anesthesia: the deep anesthesia can disrupt the repertoire of neural activity patterns and thus reduce the information carried by them, even though the information may still be integrated globally.

Correlation Between Simultaneously Recorded Full-Band EEG and BOLD at Rest
Ahmed Abou Elseoud¹, Tuija Hiltunen¹, Pasi Lepola², Kalervo Suominen², Tuomo Starck¹, Juha Nikkinen¹, Jukka Remes¹, Osmo Tervonen¹, Vesa Kiviniemi^1
1Diagnostic Radiology, Oulu University Hospital, Oulu, Finland; ²Clinical Neurophysiology, Oulu University Hospital, Oulu, Finland

Hypothesizing that low frequency FbEEG recordings correlate to the most active brain network at rest, i.e. default mode network (DMN). We investigated the correlation between the two signals, and we showed how the amplification of vasomotor waves by caffeine alters the resulted correlation. Correlations between FbEEG and resting state BOLD were located in the dorsomedial prefrontal cortex (dMPFC), left superior medial and precentral gyri. Caffeine administration augmented the correlations in dMPFC and more correlating areas were observed in; ventromedial prefrontal cortex (vMPFC), cuneus, lingual, middle occipital, middle temporal gyri and right anterior cingulate. These correlations were reduced after physiological corrections.

Identification of Anti-Correlated Resting-State Networks Using Simultaneous EEG-FMRI and Independent Components Analysis
Chi Wah Wong¹, Valur Olafsson², Hongjian He², Tom Liu^2
1Radiology, University of California - San Diego, La Jolla, CA, United States; ²Radiology, University of California - San Diego, La Jolla, CA, United States

It has been shown with resting-state fMRI that the Default Mode Network (DMN) is anti-correlated with the Task Positive Network (TPN). In this study, we used simultaneous  EEG-fMRI to investigate the relationship of the EEG alpha power time course  with the resting-state BOLD signals in these anti-correlated networks. We found that the relation between the EEG alpha power and BOLD fMRI signals in these networks is stronger  when using independent components (as determined with Independent Components Analysis) as compared to the use of the global alpha power.

Within- And Between-Subject Reproducibility of Matrix-Based Analysis of Resting-State Functional Connectivity Network
Ying-hui Chou¹, Lawrence P. Panych², Chandlee C. Dickey³, Nan-kuei Chen^4
1Fu-Jen Catholic University, Hsin-chung, Taipei, Taiwan; ²Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, United States; ³VA Boston Healthcare System and Harvard Medical School, Boston, MA, United States; ⁴Duke University, Durham, NC, United States

In this study, we assessed the within- and between-subject reproducibility of resting-state functional connectivity measured by a matrix-based analysis (MBA) in six healthy volunteers. The MBA can quantify connectivity strength for the whole brain without a priori model, and can be applied to dissociate clinical populations. Each participant was scanned nine times for more than a one-year period. Our results show that 1) the functional networks measured by the MBA are highly reproducible across nine sessions; and 2) there exists measurable between-subject variance. The MBA-based connectivity mapping should prove useful for monitoring long-term changes in functional networks.

Contribution of Different Sources of Signal Variance to T₂* and S₀ Maps in the Human Brain at Rest: A 7T Study
Marta Bianciardi¹, Masaki Fukunaga¹, Peter van Gelderen¹, Jacco A. de Zwart¹, Jeff H. Duyn^1
1Advanced MRI Section, LFMI/NINDS/NIH, Bethesda, MD, United States

To exploit the increased BOLD-contrast available at 7T for fMRI-studies, it is crucial to identify the various noise-sources and their origin. We determined the contribution of non-thermal noise to fluctuations in BOLD-weighted-, T₂*- and S₀-signals in the visual cortex at 7T during rest. The following noise-sources were considered: low-frequency-drifts, effects related to the phase of physiological cycles and to changes in physiological rates, thermal-noise, and other sources, tentatively attributed to spontaneous-activity. Our findings show that low-frequency-drifts have a physiological-contribution, and that spontaneous-activity has an echo-time dependence. Effects related to physiological-cycles and their rates contributed both to T₂*- and to S₀-images.