Hemodynamic correlation imaging of the mouse brain for application in unilateral neurodegenerative diseases.

We developed a single-camera two-channel hemodynamic imaging system that uses near-infrared light to monitor the mouse brain in vivo with an exposed, un-thinned, and intact skull to explore the effect of Parkinson's disease on the resting state functional connectivity of the brain. To demonstrate our system's ability to monitor cerebral hemodynamics, we first performed direct electrical stimulation of an anesthetized healthy mouse brain and detected hemodynamic changes localized to the stimulated area. Subsequently, we developed a unilaterally lesioned 6-hydroxydopamine (hemi-parkinsonian) mouse model and detected the differences in functional connectivity between the normal and hemi-parkinsonian mouse brains by comparing the hemispheric hemodynamic correlations during the resting state. Seed-based correlation for the oxy-hemoglobin channel from the left and right hemispheres of healthy mice was much higher and more symmetric than in hemi-parkinsonian mice. Through a k-means clustering of the hemodynamic signals, the healthy mouse brains were segmented according to brain region, but the hemi-parkinsonian mice did not show a similar segmentation. Overall, this study highlights the development of a spatial multiplexing hemodynamic imaging system that reveals the resting state hemodynamic connectivity in healthy and hemi-parkinsonian mice.

[1]  Davide Contini,et al.  Linear regression models and k-means clustering for statistical analysis of fNIRS data. , 2015, Biomedical optics express.

[2]  Ronald Rousseau,et al.  Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient , 2003, J. Assoc. Inf. Sci. Technol..

[3]  Abraham Z. Snyder,et al.  Imaging of Functional Connectivity in the Mouse Brain , 2011, PloS one.

[4]  F. Irani,et al.  Functional Near Infrared Spectroscopy (fNIRS): An Emerging Neuroimaging Technology with Important Applications for the Study of Brain Disorders , 2007, The Clinical neuropsychologist.

[5]  D. Hwang,et al.  A time-course study of behavioral and electrophysiological characteristics in a mouse model of different stages of Parkinson's disease using 6-hydroxydopamine , 2015, Behavioural Brain Research.

[6]  A. Ziehe,et al.  Estimation of Directional Coupling between Cortical Areas Using Near-infrared Spectroscopy (nirs) References and Links , 2022 .

[7]  Karl J. Friston Functional and Effective Connectivity: A Review , 2011, Brain Connect..

[8]  Abraham Z. Snyder,et al.  Resting-state functional connectivity in the human brain revealed with diffuse optical tomography , 2009, NeuroImage.

[9]  J. Pekar,et al.  On the relationship between seed‐based and ICA‐based measures of functional connectivity , 2011, Magnetic resonance in medicine.

[10]  Anuradha Godavarty,et al.  Functional near-infrared imaging reconstruction based on spatiotemporal features: venous occlusion studies , 2015 .

[11]  Chang-Hwan Im,et al.  Depth-dependent cerebral hemodynamic responses following direct cortical electrical stimulation (DCES) revealed by in vivo dual-optical imaging techniques. , 2012, Optics express.

[12]  Kuncheng Li,et al.  Changes of functional connectivity of the motor network in the resting state in Parkinson's disease , 2009, Neuroscience Letters.

[13]  A. Villringer,et al.  Non-invasive optical spectroscopy and imaging of human brain function , 1997, Trends in Neurosciences.

[14]  M. V. D. Heuvel,et al.  Exploring the brain network: A review on resting-state fMRI functional connectivity , 2010, European Neuropsychopharmacology.

[15]  M. T. Pellecchia,et al.  Resting-state brain connectivity in patients with Parkinson's disease and freezing of gait. , 2012, Parkinsonism & related disorders.

[16]  C. Lingard,et al.  Book Review: The Challenge of Red China , 1946 .

[17]  M. Hallett,et al.  Functional connectivity of cortical motor areas in the resting state in Parkinson's disease , 2011, Human brain mapping.

[18]  B. Slotnick Stereotaxic surgical techniques for the mouse. , 1972, Physiology & behavior.

[19]  Katiuscia Sacco,et al.  Functional connectivity of the insula in the resting brain , 2011, NeuroImage.

[20]  Sung-Hyoun Cho,et al.  Effect of Electrical Stimulation on Blood Flow Velocity and Vessel Size , 2017, Open medicine.

[21]  M. Schölvinck,et al.  Subcortical evidence for a contribution of arousal to fMRI studies of brain activity , 2018, Nature Communications.

[22]  B. Ances,et al.  Coupling of Changes in Cerebral Blood Flow with Neural Activity: What Must Initially Dip Must Come Back Up , 2004, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[23]  P. Meriläinen,et al.  Comparison of principal and independent component analysis in removing extracerebral interference from near-infrared spectroscopy signals. , 2009, Journal of biomedical optics.

[24]  Jonathan R Bumstead,et al.  Cerebral functional connectivity and Mayer waves in mice: Phenomena and separability , 2017, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[25]  Claude Messier,et al.  New Techniques in Stereotaxic Surgery and Anesthesia in the Mouse , 1999, Pharmacology Biochemistry and Behavior.

[26]  Xiaoqi Huang,et al.  Reduced functional connectivity in early-stage drug-naive Parkinson's disease: a resting-state fMRI study , 2014, Neurobiology of Aging.

[27]  T. Murphy,et al.  Mesoscale Mapping of Mouse Cortex Reveals Frequency-Dependent Cycling between Distinct Macroscale Functional Modules , 2017, The Journal of Neuroscience.

[28]  Frédéric Lesage,et al.  Optical imaging of resting-state functional connectivity in a novel arterial stiffness model. , 2013, Biomedical optics express.

[29]  D. Javitt,et al.  Functional connectivity fMRI in mouse brain at 7T using isoflurane , 2013, Journal of Neuroscience Methods.

[30]  Maurizio Corbetta,et al.  The human brain is intrinsically organized into dynamic, anticorrelated functional networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[31]  M. P. van den Heuvel,et al.  Exploring the brain network: a review on resting-state fMRI functional connectivity. , 2010, European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology.

[32]  Anil K. Jain Data clustering: 50 years beyond K-means , 2010, Pattern Recognit. Lett..