Sobczak, F. | bioRxiv Science

bioRxiv2019

Mapping the brain-wide network effects by optogenetic activation of the corpus callosum

The optogenetically driven manipulation of circuit-specific activity enabled functional causality studies in animals, but its global effect on the brain is rarely reported. Here, we applied simultaneous fMRI with calcium recording to map brain-wide activity by optogenetic activation of fibers running in one orientation along the corpus callosum(CC) connecting the barrel cortex(BC). Robust positive BOLD signals were detected in the ipsilateral BC due to antidromic activity, which spread to ipsilateral motor cortex(MC) and posterior thalamus(PO). In the orthodromic target (contralateral barrel cortex), positive BOLD signals were reliably evoked by 2Hz light pulses, whereas 40Hz light pulses led to a reversed sign of BOLD - indicative of CC-mediated inhibition. This presumed optogenetic CC-mediated inhibition was further elucidated by pairing light with peripheral whisker stimulation at varied inter-stimulus intervals. Whisker induced positive BOLD, and calcium signals were reduced at inter-stimulus intervals of 50/100ms. The calcium-amplitude modulation (AM)-based correlation with whole-brain fMRI signal revealed that the inhibitory effects spread to contralateral BC as well as ipsilateral MC and PO. This work raises the need of fMRI to elucidate the brain-wide network activation in response to projection-specific optogenetic stimulation.

neuroscience↗

bioRxiv2019

Predicting the fMRI signal fluctuation with echo-state neural networks trained on vascular network dynamics

Resting-state functional MRI (rs-fMRI) studies have revealed specific low-frequency hemodynamic signal fluctuations (<0.1 Hz) in the brain, which could be related to oscillations in neural activity through several mechanisms. Although the vascular origin of the fMRI signal is well established, the neural correlates of global rs-fMRI signal fluctuations are difficult to separate from other confounding sources. Recently, we reported that single-vessel fMRI slow oscillations are directly coupled to brain state changes. Here, we used an echo-state network (ESN) to predict the future temporal evolution of the rs-fMRI slow oscillatory feature from both rodent and human brains. rs-fMRI signals from individual blood vessels that were strongly correlated with neural calcium oscillations were used to train an ESN to predict brain state-specific rs-fMRI signal fluctuations. The ESN-based prediction model was also applied to recordings from the Human Connectome Project (HCP), which classified variance-independent brain states based on global fluctuations of rs-fMRI features. The ESN revealed brain states with global synchrony and decoupled internal correlations within the default-mode network.

neuroscience↗