Literature DB >> 29697052

Resting-state functional connectivity analysis of the mouse brain using intrinsic optical signal imaging of cerebral blood volume dynamics.

Yuto Yoshida1, Mitsuyuki Nakao, Norihiro Katayama.   

Abstract

OBJECTIVE: Resting-state functional connectivity (rsFC) of the human brain is closely related with neurological and psychiatric disorders. Mice are widely used to investigate the physiological mechanisms of such disorders, because of the applicability of invasive experimental techniques. Thus, studies on rsFC of the mouse brain are essential to link physiological mechanisms with these disorders in humans. In this study, we investigated the applicability of intrinsic optical signal imaging of cerebral blood volume (IOSI-CBV) for rsFC analysis of the mouse brain. APPROACH: Transcranial IOSI-CBV images were collected from the brains of un-anesthetized wild-type mice with a cooled-CCD camera. The time traces of all pixels were averaged to create a global signal (GS). Marginal and partial correlation analyses were performed to estimate the rsFC based on CBV signals both with and without GS removal. The consistency of the results were confirmed by comparing them with to the rsFCs data reported in the previous studies. MAIN
RESULTS: We confirmed that GS correlated with heart rate fluctuation in the FC frequency band. The marginal correlation coefficient of CBV with GS removal was consistent with measurements using conventional optical imaging methods relying on oxygenated hemoglobin concentration and cerebral blood flow. SIGNIFICANCE: These results suggest the applicability and usefulness of the transcranial IOSI-CBV method to estimate rsFC of the mouse brain.

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Mesh:

Year:  2018        PMID: 29697052     DOI: 10.1088/1361-6579/aac033

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  2 in total

1.  Differential effects of anesthetics on resting state functional connectivity in the mouse.

Authors:  Hongyu Xie; David Y Chung; Sreekanth Kura; Kazutaka Sugimoto; Sanem A Aykan; Yi Wu; Sava Sakadžić; Mohammad A Yaseen; David A Boas; Cenk Ayata
Journal:  J Cereb Blood Flow Metab       Date:  2019-05-15       Impact factor: 6.200

2.  Measuring the Frequency-Specific Functional Connectivity Using Wavelet Coherence Analysis in Stroke Rats Based on Intrinsic Signals.

Authors:  Leila Mohammadzadeh; Hamid Latifi; Sepideh Khaksar; Mohammad-Sadegh Feiz; Fereshteh Motamedi; Amir Asadollahi; Marzieh Ezzatpour
Journal:  Sci Rep       Date:  2020-06-10       Impact factor: 4.379

  2 in total

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