If I've understood it correctly, a recent paper by Aaron Winder
and colleagues (Article Weak correlations between hemodynamic signals and ongoing ne...
) shows that in mice altered cerebral blood volume in Resting State is poorly correlated with neural activity, and is more likely to refelct some neurovascular activity.If the findings get replicated, they might contradict the widespread belief that resting state networks might indicate some psychological process (although a yet-to-be-identitied one).
Wouldn't that downplay all the 'hype' with Resting State Network, at least as far as they're taken to reveal some 'essential function' of the brain? Which implications might there be from such a reframing?
Well, that would be a bummer...
Seriously, I think it is a difficult question to tackle and there has been some debate about the origin of slow synchronized hemodynamic activity in the brain since the 90's. Some works provide evidence for a neural origin of the resting-state signal. For instance, these 2 papers:
Du, C., Volkow, N. D., Koretsky, A. P., & Pan, Y. (2014). Low-frequency calcium oscillations accompany deoxyhemoglobin oscillations in rat somatosensory cortex. Proceedings of the National Academy of Sciences of the United States of America, 111(43), E4677-4686. https://doi.org/10.1073/pnas.1410800111
and
Ma, Y., Shaik, M. A., Kozberg, M. G., Kim, S. H., Portes, J. P., Timerman, D., & Hillman, E. M. C. (2016). Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons. Proceedings of the National Academy of Sciences, 201525369. https://doi.org/10.1073/pnas.1525369113 show a coupling between neural and hemodynamic activity.
I think this issue will continue to be debatable, specially if the papers on both sides suffer from small sample size problems (n=12,13), until a large-scale study finally settles the question.
some potential physiolog processes have been idenfi e.g. motion or fluctuations in ETCO2 e.g. Wise et al 2004.ed
Wise, R. G., Ide, K., Poulin, M. J., & Tracey, I. (2004). Resting fluctuations in arterial carbon dioxide induce significant low frequency variations in BOLD signal. NeuroImage, 21(4), 1652–1664. http://doi.org/10.1016/j.neuroimage.2003.11.025edi
I agree with Edgar, the debate is not over, as evidenced by the Winder et al. paper. But this paper that was published last month comes down strongly on the side of there being a neuronal component.
Article Entrainment of Arteriole Vasomotor Fluctuations by Neural Ac...
In the following work we present evidence that intrinsic connectivity has neurocomponents data which I interpret as evidence beyond "artifacts". Of course, by definition, BOLD looks at haemodynamics which the brain adapts to metabolic need in a clever way. However, differential sets of brain activity regions co-act differently e.g. as a function of sleep stage while the anatomy does not change (e.g. Neuron). Then, there are EEG oscillations correlated with BOLD functional connectivity changes (Frontiers)e.g. - you would neet to question the origin of EEG oscillations next, then... Finally, signal properties change in a meaningful manner in different ICN unlikely benot in line with a physio noise source (e.g. PNAS).d
1: Haimovici A, Tagliazucchi E, Balenzuela P, Laufs H. On wakefulness fluctuations as a source of BOLD functional connectivity dynamics. Sci Rep. 2017 Jul 19;7(1):5908. doi: 10.1038/s41598-017-06389-4. PubMed PMID: 28724928; PubMed Central PMCID: PMC5517577. 2: Tagliazucchi E, Laufs H. Decoding wakefulness levels from typical fMRI resting-state data reveals reliable drifts between wakefulness and sleep. Neuron. 2014 May 7;82(3):695-708. doi: 10.1016/j.neuron.2014.03.020. PubMed PMID: 24811386. 3: Tagliazucchi E, von Wegner F, Morzelewski A, Brodbeck V, Jahnke K, Laufs H. Breakdown of long-range temporal dependence in default mode and attention networks during deep sleep. Proc Natl Acad Sci U S A. 2013 Sep 17;110(38):15419-24. doi: 10.1073/pnas.1312848110. Epub 2013 Sep 3. PubMed PMID: 24003146; PubMed Central PMCID: PMC3780893. 4: Tagliazucchi E, von Wegner F, Morzelewski A, Brodbeck V, Laufs H. Dynamic BOLD functional connectivity in humans and its electrophysiological correlates. Front Hum Neurosci. 2012 Dec 28;6:339. doi: 10.3389/fnhum.2012.00339. eCollection 2012. PubMed PMID: 23293596; PubMed Central PMCID: PMC3531919.
In my recent research, we studied the impact of HRF variability (the non-neural component of fMRI) on resting-state fMRI functional connectivity (FC). We found that HRF variability causes a mean error of about 15% in FC estimates. This implies that about 85% of the information contained in resting-state FC, on average, is driven by neural activity, implying that an overwhelmingly large share of the fMRI signal still represents neural activity. Here's the paper:
doi.org/10.1002/mrm.27146
Rangaprakash et. al. (2018) Hemodynamic response function (HRF) variability confounds resting-state fMRI functional connectivity. Magnetic Resonance in Medicine