@misc{10481/69457,
year = {2021},
url = {http://hdl.handle.net/10481/69457},
abstract = {Brain networks can be defined and explored through their connectivity. Here, we analyzed the relationship
between structural connectivity (SC) across 2,514 regions that cover the entire brain and
brainstem, and their dynamic functional connectivity (DFC). To do so, we focused on a combination
of two metrics: the first assesses the degree of SC-DFC similarity –i.e. the extent to which the dynamic
functional correlations can be explained by structural pathways–; and the second is the intrinsic
variability of the DFC networks over time. Overall, we found that cerebellar networks have a smaller
DFC variability than other networks in the brain. Moreover, the internal structure of the cerebellum
could be clearly divided in two distinct posterior and anterior parts, the latter also connected to the
brainstem. The mechanism to maintain small variability of the DFC in the posterior part of the cerebellum
is consistent with another of our findings, namely, that this structure exhibits the highest SC-DFC
similarity relative to the other networks studied, i.e. structure constrains the variation in dynamics. By
contrast, the anterior part of the cerebellum also exhibits small DFC variability but it has the lowest
SC-DFC similarity, suggesting a different mechanism is at play. Because this structure connects to
the brainstem, which regulates sleep cycles, cardiac and respiratory functioning, we suggest that such
critical functionality drives the low variability in the DFC. Overall, the low variability detected in
DFC expands our current knowledge of cerebellar networks, which are extremely rich and complex,
participating in a wide range of cognitive functions, from movement control and coordination to
executive function or emotional regulation. Moreover, the association between such low variability
and structure suggests that differentiated computational principles can be applied in the cerebellum as
opposed to other structures, such as the cerebral cortex.},
organization = {Consejería de Conocimiento},
organization = {Excellence of Science
	30446199},
organization = {Investigación y Universidad, Junta de Andalucía},
organization = {KU Leuven Special Research Fund
	C16/15/070},
organization = {Spanish Ministry},
organization = {Eusko Jaurlaritza

PRE_2019_1_0070},
organization = {Fonds Wetenschappelijk Onderzoek

G089818N	FWO},
organization = {Ikerbasque, Basque Foundation for Science},
organization = {European Regional Development Fund

DPI2016-79874-R,KK-2018/00032,SAF2015-69484-R	ERDF},
organization = {Ministerio de Economía, Industria y Competitividad, Gobierno de España

	MINECO},
organization = {Agencia Estatal de Investigación

FIS2017-84256-P	AEI},
organization = {Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía SOMM17/6105/UGR},
publisher = {Elsevier},
keywords = {Dynamic functional connectivity},
keywords = {Structural connectivity},
keywords = {Anterior Cerebellum},
keywords = {Posterior Cerebellum},
keywords = {Resting-state},
title = {Small variation in dynamic functional connectivity in cerebellar networks},
doi = {10.1016/j.neucom.2020.09.092},
author = {Fernández-Iriondo, Izaro and Muñoz Martínez, Miguel Ángel},
}