Quantitative separation of arterial and venous cerebral blood volume increases during voluntary locomotion

Abstract

Voluntary locomotion is accompanied by large increases in cortical activity and localized increases in cerebral blood volume (CBV). We sought to quantitatively determine the spatial and temporal dynamics of voluntary locomotion-evoked cerebral hemodynamic changes. We measured single vessel dilations using two-photon microscopy and cortex-wide changes in CBV-related signal using intrinsic optical signal (IOS) imaging in head-fixed mice freely locomoting on a spherical treadmill. During bouts of locomotion, arteries dilated rapidly, while veins distended slightly and recovered slowly. The dynamics of diameter changes of both vessel types could be captured using a simple linear convolution model. Using these single vessel measurements, we developed a novel analysis approach to separate out spatially and temporally distinct arterial and venous components of the location-specific hemodynamic response functions (HRF) for IOS. The HRF of each pixel of was well fit by a sum of a fast arterial and a slow venous component. The HRFs of pixels in the limb representations of somatosensory cortex had a large arterial contribution, while in the frontal cortex the arterial contribution to the HRF was negligible. The venous contribution was much less localized, and was substantial in the frontal cortex. The spatial pattern and amplitude of these HRFs in response to locomotion in the cortex was robust across imaging sessions. Separating the more localized, arterial component from the diffuse venous signals will be useful for dealing with the dynamic signals generated by naturalistic stimuli.

Mechanical restriction of intracortical vessel dilation by brain tissue sculpts the hemodynamic response

“…Voluntary locomotion is a natural sensorimotor behavior that drives a large and robust increase in blood flow and volume (Huo et al 2015) and neural activity (Chapin and Woodward 1981; Dombeck et al 2007; Huo et al 2014) in the limb representations in somatosensory cortex. We imaged a total of 245 arteriole and 124 venule segments in 17 mice through Polished and Reinforced Thin-Skull (PoRTS) windows (Drew et al 2010; Shih, Mateo, et al 2012).…”

“…5), we wanted to test if this size difference could account for difference in dilation amplitude of surface and intracortical vessels. Smaller surface arterioles are known to be more reactive and dilate more in response to sensory stimulation and hypercapnia (Lee et al 2001; Drew et al 2011; Huo et al, 2015), though it is not known if this is the case for intracortical arterioles. We performed a multivariate regression of peak dilation against depth and resting diameter of the arteriole to determine if diameter differences could account for the differences in dilation.…”

“…3D). As venous dilations were very small (typically ~5% at the peak) and slow, taking tens of seconds to reach their peak (Drew et al 2011; Huo et al 2015), we were not able to accurately calculate their onset time. Averaged across all arterioles, the mean onset time was 0.32±0.66 seconds.…”

“…Fluorescence fractional changes (ΔF/F 0 ) were calculated by normalizing to the same average fluorescence intensity during a ~10 second long stationary period. The ΔD/D 0 and ΔF/F 0 time series were first filtered with a five-point median filter, and then low-pass filtered at 3Hz (3rd order Butterworth) (Huo, et al 2015). …”

“…However, all of these experiments were done in anesthetized animals, and anesthesia profoundly decreases the amplitude and slows the dynamics of hemodynamic responses (Martin et al 2006; Goense and Logothetis 2008; Drew et al 2011; Pisauro et al 2013). To better interpret the signals coming from human neuroimaging studies (Gardner 2010; Kriegeskorte et al 2010), it is important to understand the microvascular basis of hemodynamic in awake animals, preferably those performing voluntary behaviors (Huo et al 2014; Huo et al 2015). …”