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Wondering whether axonal input *drives* fMRI-based functional connectivity? Us too!

Here is what we found using #chemogenetic deconstruction of rsfMRI in the mouse🐁🐭

➡️Cortical silencing results in paradoxical fMRI overconnectivity

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Computational and empirical evidence suggest that structural and functional connectivity are robustly related

➡️ this recent review from @richardfbetzel @misicbata summarizes it all

⚠️A key prediction of structurally based models of fMRI coupling is that *inactivation* of a brain node would result in reduced rsfMRI connectivity with its targets⚠️

But is that really the case?

➡️Seminal computational modelling supports this hypothesis

➡️Chemo-fMRI work in primates does too, as inactivation of the amygdala leads to reduce rsfMRI connectivity as predicted

So this settles the question, right?

Well, as often the case in science, things might be more complicated than they seem

For example intact bilateral networks have been observed in acallosal people

Plus *over-connectivity* is often observed in disorders characterized by loss of cortical function Alzheimer's Stroke..

So there seems to be also evidence arguing AGAINST a purely dyadic relationship between structural and functional connectivity..

...which led us to investigate how inactivation of a cortical region *causally* affects brain-wide fMRI connectivity

➡️We first chronically silenced the 🐭prefrontal cortex via overexpression of a K+ channel. ePhys below shows that this leads to reduced spontaneous firing

Surprisingly, we found that chronic PFC silencing results in *increased* rsfMRI connectivity between the silenced area and its targets within the mouse default mode network (midline thalamus, posterior cingulate - retrosplenial in rodents)

By comparing overconnected regions against a voxel-resolution model of the structural connectome we found that all the affected regions are robustly innervated by the PFC

➡️ these are areas that are directly "communicating" with the PFC

Could this effect reflect homeostatic/neuroadaptive adaptations? What happens if we acutely silence the PFC instead?

To address these questions we designed a chemo-fMRI study in which DREADDs were used to acutely silence the mouse PFC

We found that acute DREADD inhibition of PFC reproduces the same pattern of rsfMRI *overconnectivity*

This means
➡️effect is not manipulation specific
➡️nor a neuroadaptive response to protracted inhibition

Plus, with DREADDs we can now investigate neural mechanism

Using in vivo ePHYS we found that DREADDs robustly and specifically attenuates firing in PFC

This lead to
➡️*reduced* ƴ activity (expected)
➡️*increased* δ power (intriguing!)

Could δ band coupling explain the observed overconnectivity?

Multielectrode recordings suggest so!

➡️ All hyperconnected areas show robustly increased δ power & phase coherence
➡️ δ power is linearly related to mean rsfMRI connectivity in all areas

So δ band coherence is a plausible driver of the observed fMRI over-synchronization

Interestingly, our recordings also showed increased δ coupling between polymodal thalamus and posterior cingulate (retrosplenial in mouse)

➡️If delta is a prominent correlate of rsfMRI over-synchronization, these two regions should then exhibit rsfMRI overconnectivity too

This may be important mechanistically as polymodal thalamus generates and propagates δ activity to cortex
(see below)

If this were the case
➡️ polymodal/unimodal rsfMRI profiles should be segregable
➡️ polymodal thalamus would be "overconnected" with large cortical areas

Using a clustering analysis we show this might be the case

➡️we found distinct poly/unimodal rsfMRI profiles
➡️polymodal (but not unimodal) thalamus exhibits rsfMRI overconnectivity with cortical areas
➡️ these include retrosplenial Ctx as predicted by ePHYS recordings

This leads to a putative model whereby silencing of a cortical region leads to
➡️ reduced "direct" (e.g. ƴ) communication with its targets
➡️ & increased rsfMRI coupling mediated by co-varying slow oscillations (from polymodal thalamus and/or other remote rhythm generators)

These results may have important implications e.g.

for modelling ➡️rsfMRI connectivity is not always a monotonic indicator of interareal communication

for brain disorders ➡️overconnectivity in degenerative disorders may be indirect result of lower cortical output

This is it. Many thanks to twitterless
& freshly graduated 🍾 #Carola_Canella
#Federico_Rocchi, #Stefano_Panzeri, @danielgb_87 @GIurilli and all the collaborators at @IITalk
And to @BBRFoundation and @ERC_Research for generous funding. Comments/suggestions are welcome

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