Neural correlates of single-vessel haemodynamic responses in vivo.

Abstract

Neural activation increases blood flow locally. This vascular signal is used by functional imaging techniques to infer the location and strength of neural activity1,2. However, the precise spatial scale over which neural and vascular signals are correlated is unknown. Furthermore, the relative role of synaptic and spiking activity in driving hemodynamic signals is controversial3-9. Prior studies recorded local field potentials (LFPs) as a measure of synaptic activity together with spiking activity and low-resolution hemodynamic imaging. Here we used two-photon microscopy to measure sensory-evoked responses of individual blood vessels (dilation, blood velocity) while imaging synaptic and spiking activity in the surrounding tissue using fluorescent glutamate and calcium sensors. In cat primary visual cortex, where neurons are clustered by their preference for stimulus orientation, we discovered new maps for excitatory synaptic activity, which were organized similar to spiking activity but were less selective for stimulus orientation and direction. We generated tuning curves for individual vessel responses for the first time and found that parenchymal vessels in cortical layer 2/3 were orientation selective. Neighboring penetrating arterioles had different orientation preferences. Pial surface arteries in cats, as well as surface arteries and penetrating arterioles in rat visual cortex (where orientation maps do not exist10), responded to visual stimuli but had no orientation selectivity. We integrated synaptic or spiking responses around individual parenchymal vessels in cats and established that the vascular and neural responses had the same orientation preference. However, synaptic and spiking responses were more selective than vascular responses—vessels frequently responded robustly to stimuli that evoked little to no neural activity in the surrounding tissue. Thus, local neural and hemodynamic signals were partly decoupled. Together, these results indicate that intrinsic cortical properties, such as propagation of vascular dilation between neighboring columns, need to be accounted for when decoding hemodynamic signals.