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Author Notes:

S.D. Keilholz, 101 Woodruff Circle, Suite 2001, Atlanta, GA 30322, USA. Phone number: +1 404-727-2433, Fax: +1 404-727-9873. shella.keilholz@bme.gatech.edu

The authors would like to acknowledge Alessio Medda, Martha Willis, Jacob Billings, Sadia Shakil and Rui Tang for their helpful comments; Jeremy Edgerton and Collin Lobb for their assistance with rodent electrophysiology; and Wendy Hu for proofreading.

The authors would also like to thank the anonymous reviewers for their helpful comments, which resulted in the addition of Tables I and IV; Figure 5; and Supplemental Figures S1 through S4.

Subjects:

Research Funding:

Funding was provided by the National Institute of Health, 1R21NS072810-01A1 and 1R21NS057718-01; and the Scholarly Inquiry and Research at Emory graduate fellowship.

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Neurosciences
  • Neuroimaging
  • Radiology, Nuclear Medicine & Medical Imaging
  • Neurosciences & Neurology
  • Functional connectivity
  • Neural basis
  • Sliding window
  • Dynamic
  • Time varying
  • Global signal
  • FREQUENCY BOLD FLUCTUATIONS
  • DEFAULT-MODE NETWORK
  • SPATIOTEMPORAL DYNAMICS
  • ALZHEIMERS-DISEASE
  • HUMAN BRAIN
  • FMRI
  • CORTEX
  • ISOFLURANE
  • SIGNAL
  • AMPLITUDE

Neural correlates of time-varying functional connectivity in the rat

Journal Title:

NeuroImage

Volume:

Volume 83

Publisher:

, Pages 826-836

Type of Work:

Article | Post-print: After Peer Review

Abstract:

Functional connectivity between brain regions, measured with resting state functional magnetic resonance imaging, holds great potential for understanding the basis of behavior and neuropsychiatric diseases. Recently it has become clear that correlations between the blood oxygenation level dependent (BOLD) signals from different areas vary over the course of a typical scan (6-10. min in length), though the changes are obscured by standard methods of analysis that assume the relationships are stationary. Unfortunately, because similar variability is observed in signals that share no temporal information, it is unclear which dynamic changes are related to underlying neural events. To examine this question, BOLD data were recorded simultaneously with local field potentials (LFP) from interhemispheric primary somatosensory cortex (SI) in anesthetized rats. LFP signals were converted into band-limited power (BLP) signals including delta, theta, alpha, beta and gamma. Correlation between signals from interhemispheric SI was performed in sliding windows to produce signals of correlation over time for BOLD and each BLP band. Both BOLD and BLP signals showed large changes in correlation over time and the changes in BOLD were significantly correlated to the changes in BLP. The strongest relationship was seen when using the theta, beta and gamma bands. Interestingly, while steady-state BOLD and BLP correlate with the global fMRI signal, dynamic BOLD becomes more like dynamic BLP after the global signal is regressed. As BOLD sliding window connectivity is partially reflecting underlying LFP changes, the present study suggests it may be a valuable method of studying dynamic changes in brain states.

Copyright information:

© 2013 Elsevier Inc.

This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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