Literature DB >> 23106103

Dynamic properties of functional connectivity in the rodent.

Shella D Keilholz1, Matthew E Magnuson, Wen-Ju Pan, Martha Willis, Garth J Thompson.   

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.

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Year:  2013        PMID: 23106103      PMCID: PMC3621313          DOI: 10.1089/brain.2012.0115

Source DB:  PubMed          Journal:  Brain Connect        ISSN: 2158-0014


  22 in total

1.  Comparison of alpha-chloralose, medetomidine and isoflurane anesthesia for functional connectivity mapping in the rat.

Authors:  Kathleen A Williams; Matthew Magnuson; Waqas Majeed; Stephen M LaConte; Scott J Peltier; Xiaoping Hu; Shella D Keilholz
Journal:  Magn Reson Imaging       Date:  2010-04-24       Impact factor: 2.546

2.  Simultaneous FMRI and electrophysiology in the rodent brain.

Authors:  Wen-ju Pan; Garth Thompson; Matthew Magnuson; Waqas Majeed; Dieter Jaeger; Shella Keilholz
Journal:  J Vis Exp       Date:  2010-08-19       Impact factor: 1.355

3.  Spatiotemporal dynamics of low frequency BOLD fluctuations in rats and humans.

Authors:  Waqas Majeed; Matthew Magnuson; Wendy Hasenkamp; Hillary Schwarb; Eric H Schumacher; Lawrence Barsalou; Shella D Keilholz
Journal:  Neuroimage       Date:  2010-08-20       Impact factor: 6.556

4.  Competition between functional brain networks mediates behavioral variability.

Authors:  A M Clare Kelly; Lucina Q Uddin; Bharat B Biswal; F Xavier Castellanos; Michael P Milham
Journal:  Neuroimage       Date:  2007-08-23       Impact factor: 6.556

5.  Functional connectivity in blood oxygenation level-dependent and cerebral blood volume-weighted resting state functional magnetic resonance imaging in the rat brain.

Authors:  Matthew Magnuson; Waqas Majeed; Shella D Keilholz
Journal:  J Magn Reson Imaging       Date:  2010-09       Impact factor: 4.813

6.  Rat brains also have a default mode network.

Authors:  Hanbing Lu; Qihong Zou; Hong Gu; Marcus E Raichle; Elliot A Stein; Yihong Yang
Journal:  Proc Natl Acad Sci U S A       Date:  2012-02-21       Impact factor: 11.205

7.  Time-frequency dynamics of resting-state brain connectivity measured with fMRI.

Authors:  Catie Chang; Gary H Glover
Journal:  Neuroimage       Date:  2009-12-16       Impact factor: 6.556

8.  A protocol for use of medetomidine anesthesia in rats for extended studies using task-induced BOLD contrast and resting-state functional connectivity.

Authors:  Christopher P Pawela; Bharat B Biswal; Anthony G Hudetz; Marie L Schulte; Rupeng Li; Seth R Jones; Younghoon R Cho; Hani S Matloub; James S Hyde
Journal:  Neuroimage       Date:  2009-03-12       Impact factor: 6.556

9.  Spatiotemporal dynamics of low frequency fluctuations in BOLD fMRI of the rat.

Authors:  Waqas Majeed; Matthew Magnuson; Shella D Keilholz
Journal:  J Magn Reson Imaging       Date:  2009-08       Impact factor: 4.813

10.  BOLD study of stimulation-induced neural activity and resting-state connectivity in medetomidine-sedated rat.

Authors:  Fuqiang Zhao; Tiejun Zhao; Lei Zhou; Qiulin Wu; Xiaoping Hu
Journal:  Neuroimage       Date:  2007-08-22       Impact factor: 6.556

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  75 in total

1.  Intracranial Electrophysiology Reveals Reproducible Intrinsic Functional Connectivity within Human Brain Networks.

Authors:  Aaron Kucyi; Jessica Schrouff; Stephan Bickel; Brett L Foster; James M Shine; Josef Parvizi
Journal:  J Neurosci       Date:  2018-04-06       Impact factor: 6.167

2.  Different dynamic resting state fMRI patterns are linked to different frequencies of neural activity.

Authors:  Garth John Thompson; Wen-Ju Pan; Shella Dawn Keilholz
Journal:  J Neurophysiol       Date:  2015-06-03       Impact factor: 2.714

3.  Time-resolved resting-state brain networks.

Authors:  Andrew Zalesky; Alex Fornito; Luca Cocchi; Leonardo L Gollo; Michael Breakspear
Journal:  Proc Natl Acad Sci U S A       Date:  2014-06-30       Impact factor: 11.205

4.  Tracking ongoing cognition in individuals using brief, whole-brain functional connectivity patterns.

Authors:  Javier Gonzalez-Castillo; Colin W Hoy; Daniel A Handwerker; Meghan E Robinson; Laura C Buchanan; Ziad S Saad; Peter A Bandettini
Journal:  Proc Natl Acad Sci U S A       Date:  2015-06-29       Impact factor: 11.205

5.  Introducing co-activation pattern metrics to quantify spontaneous brain network dynamics.

Authors:  Jingyuan E Chen; Catie Chang; Michael D Greicius; Gary H Glover
Journal:  Neuroimage       Date:  2015-02-07       Impact factor: 6.556

Review 6.  Noise and non-neuronal contributions to the BOLD signal: applications to and insights from animal studies.

Authors:  Shella D Keilholz; Wen-Ju Pan; Jacob Billings; Maysam Nezafati; Sadia Shakil
Journal:  Neuroimage       Date:  2016-12-22       Impact factor: 6.556

7.  Infraslow Electroencephalographic and Dynamic Resting State Network Activity.

Authors:  Joshua K Grooms; Garth J Thompson; Wen-Ju Pan; Jacob Billings; Eric H Schumacher; Charles M Epstein; Shella D Keilholz
Journal:  Brain Connect       Date:  2017-06

8.  Dynamic brain connectivity is a better predictor of PTSD than static connectivity.

Authors:  Changfeng Jin; Hao Jia; Pradyumna Lanka; D Rangaprakash; Lingjiang Li; Tianming Liu; Xiaoping Hu; Gopikrishna Deshpande
Journal:  Hum Brain Mapp       Date:  2017-06-12       Impact factor: 5.038

9.  The contribution of electrophysiology to functional connectivity mapping.

Authors:  Marieke L Schölvinck; David A Leopold; Matthew J Brookes; Patrick H Khader
Journal:  Neuroimage       Date:  2013-04-13       Impact factor: 6.556

10.  Evaluation of sliding window correlation performance for characterizing dynamic functional connectivity and brain states.

Authors:  Sadia Shakil; Chin-Hui Lee; Shella Dawn Keilholz
Journal:  Neuroimage       Date:  2016-03-04       Impact factor: 6.556

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