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RISS 인기검색어
- 검색키워드
- 저자 : ( Kevin P Murphy ) (검색결과 3 건)
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Murphy, Matthew C.,Poplawsky, Alexander J.,Vazquez, Alberto L.,Chan, Kevin C.,Kim, Seong-Gi,Fukuda, Mitsuhiro Elsevier 2016 NeuroImage Vol.137 No.-
<P><B>Abstract</B></P> <P>Functional MRI (fMRI) is a popular and important tool for noninvasive mapping of neural activity. As fMRI measures the hemodynamic response, the resulting activation maps do not perfectly reflect the underlying neural activity. The purpose of this work was to design a data-driven model to improve the spatial accuracy of fMRI maps in the rat olfactory bulb. This system is an ideal choice for this investigation since the bulb circuit is well characterized, allowing for an accurate definition of activity patterns in order to train the model. We generated models for both cerebral blood volume weighted (CBVw) and blood oxygen level dependent (BOLD) fMRI data. The results indicate that the spatial accuracy of the activation maps is either significantly improved or at worst not significantly different when using the learned models compared to a conventional general linear model approach, particularly for BOLD images and activity patterns involving deep layers of the bulb. Furthermore, the activation maps computed by CBVw and BOLD data show increased agreement when using the learned models, lending more confidence to their accuracy. The models presented here could have an immediate impact on studies of the olfactory bulb, but perhaps more importantly, demonstrate the potential for similar flexible, data-driven models to improve the quality of activation maps calculated using fMRI data.</P> <P><B>Highlights</B></P> <P> <UL> <LI> We applied machine learning to compute activation maps in the rat olfactory bulb. </LI> <LI> Results from learned models were compared to results from general linear models. </LI> <LI> Spatial accuracy of activation maps was significantly improved with learned models. </LI> <LI> CBV and BOLD activation maps showed increased agreement using learned models. </LI> </UL> </P>
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Murphy, Matthew C.,Chan, Kevin C.,Kim, Seong-Gi,Vazquez, Alberto L. Elsevier 2018 NeuroImage Vol.169 No.-
<P><B>Abstract</B></P> <P>Functional imaging of spontaneous activity continues to play an important role in the field of connectomics. The most common imaging signal used for these experiments is the blood-oxygen-level-dependent (BOLD) functional MRI (fMRI) signal, but how this signal relates to spontaneous neuronal activity remains incompletely understood. Genetically encoded calcium indicators represent a promising tool to study this problem, as they can provide brain-wide measurements of neuronal activity compared to point measurements afforded by electrophysiological recordings. However, the relationship between the calcium signal and neurophysiological parameters at the mesoscopic scale requires further systematic characterization. Therefore, we collected simultaneous resting-state measurements of electrophysiology, along with calcium and hemodynamic imaging, in lightly anesthetized mice to investigate two aims. First, we examined the relationship between each imaging signal and the simultaneously recorded electrophysiological signal in a single brain region, finding that both signals are better correlated with multi-unit activity compared to local field potentials, with the calcium signal possessing greater signal-to-noise ratio and regional specificity. Second, we used the resting-state imaging data to model the relationship between the calcium and hemodynamic signals across the brain. We found that this relationship varied across brain regions in a way that is consistent across animals, with delays increasing by600 ms towards posterior cortical regions. Furthermore, while overall functional connectivity (FC) measured by the hemodynamic signal is significantly correlated with FC measured by calcium, the two estimates were found to be significantly different. We hypothesize that these differences arise at least in part from the observed regional variation in the hemodynamic response. In total, this work highlights some of the caveats needed in interpreting hemodynamic-based measurements of FC, as well as the need for improved modeling methods to reduce this potential source of bias.</P> <P><B>Highlights</B></P> <P> <UL> <LI> We acquired simultaneous electrophysiology and imaging in lightly anesthetized mice. </LI> <LI> Both calcium and hemodynamic signals are correlated with neuronal activity. </LI> <LI> Multi-unit activity was the best electrophysiological correlate of both signals. </LI> <LI> The hemodynamic versus calcium relationship varied significantly by brain region. </LI> <LI> Estimates of connectivity derived from two signals were correlated but different. </LI> </UL> </P>
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