Interaction Information Along Lifespan of the Resting Brain Dynamics Reveals a Major Redundant Role of the Default Mode Network

Camino-Pontes, Borja; Díez, Ibai; Jiménez-Marín, Antonio; Rasero, Javier; Erramuzpe, Asier; Bonifazi, P.; Stramaglia, Sebastiano; Swinnen, Stephan P.; Cortés, Jesús M.

doi:10.3390/e20100742

Cited by 17 publications

(14 citation statements)

References 56 publications

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“…Here we are describing in the connectome an organization that cannot be explained only in terms of pairwise node-to-node relationships. Interactions between more than a pair of nodes (high-order interdependencies) are described using information theory tools [42,43], giving rise to phenomena like redundancy and synergy that appear in the brain activity. These cannot be understood nor measured if only pairwise relationships are quantified.…”

Section: Discussionmentioning

confidence: 99%

Cortical ignition dynamics is tightly linked to the core organisation of the human connectome

et al. 2020

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Section: Discussionmentioning

confidence: 99%

Cortical ignition dynamics is tightly linked to the core organisation of the human connectome

et al. 2020

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“…Functional data were preprocessed using FSL (FMRIB Software Library, version 5.0) and AFNI, following a procedure similar to previous work (Diez et al, 2017; Rasero et al, 2017, 2019; Stramaglia et al, 2017; Bonifazi et al, 2018; Camino-Pontes et al, 2018). First, slice-time correction was applied to the fMRI.…”

Section: Methodsmentioning

confidence: 99%

Metastable Resting State Brain Dynamics

Graben

Jiménez-Marín

Diez

et al. 2019

Front. Comput. Neurosci.

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Metastability refers to the fact that the state of a dynamical system spends a large amount of time in a restricted region of its available phase space before a transition takes place, bringing the system into another state from where it might recur into the previous one. beim Graben and Hutt (2013) suggested to use the recurrence plot (RP) technique introduced by Eckmann et al. (1987) for the segmentation of system's trajectories into metastable states using recurrence grammars. Here, we apply this recurrence structure analysis (RSA) for the first time to resting-state brain dynamics obtained from functional magnetic resonance imaging (fMRI). Brain regions are defined according to the brain hierarchical atlas (BHA) developed by Diez et al. (2015), and as a consequence, regions present high-connectivity in both structure (obtained from diffusion tensor imaging) and function (from the blood-level dependent-oxygenation—BOLD—signal). Remarkably, regions observed by Diez et al. were completely time-invariant. Here, in order to compare this static picture with the metastable systems dynamics obtained from the RSA segmentation, we determine the number of metastable states as a measure of complexity for all subjects and for region numbers varying from 3 to 100. We find RSA convergence toward an optimal segmentation of 40 metastable states for normalized BOLD signals, averaged over BHA modules. Next, we build a bistable dynamics at population level by pooling 30 subjects after Hausdorff clustering. In link with this finding, we reflect on the different modeling frameworks that can allow for such scenarios: heteroclinic dynamics, dynamics with riddled basins of attraction, multiple-timescale dynamics. Finally, we characterize the metastable states both functionally and structurally, using templates for resting state networks (RSNs) and the automated anatomical labeling (AAL) atlas, respectively.

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“…A first study on high-order interactions and aging was reported in Ref. [20], which showed significant changes in synergies and redundancies in triple interactions along the lifespan, and a redundant role of the default mode network. The effect of aging on interactions beyond triple relationships is, to the best of our knowledge, still an unexplored territory.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we build upon Ref. [20] and study the effects of aging on the high-order interactions in the human brain, with a special focus on interdependencies between four or more brain regions. To this end, we employ the recently proposed O-Information [21], which can be considered to be revision of the measure of neural complexity proposed by Tononi, Sporns and Edelman [22] under the light of Partial Information Decomposition [23].…”

Section: Introductionmentioning

confidence: 99%

High-Order Interdependencies in the Aging Brain

et al. 2021

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Brain interdependencies can be studied either from a structural/anatomical perspective ("structural connectivity", SC) or by considering statistical interdependencies ("functional connectivity", FC). Interestingly, while SC is typically pairwise (white-matter fibers start in a certain region and arrive at another), FC is not; however, most FC analyses focus only on pairwise statistics and neglect highorder interactions. A promising tool to study high-order interdependencies is the recently proposed O-Information, which can quantify the intrinsic statistical synergy and redundancy in groups of three or more interacting variables. In this paper we used the O-Information to investigate how high-order statistical interdependencies are affected by age. For this, we analised functional magnetic resonance imaging (fMRI) data at rest obtained from 164 healthy participants, ranging from 10 to 80 years old. Our results show that older subjects (age ranging from 60 to 80 years) exhibit a higher predominance of redundant dependencies than younger subjects; moreover, this effect seems to be pervasive, taking place at all interaction orders. Additionally, we found that these effects are highly heterogeneous across brain regions, and suggest the existence of a "redundancy core" formed by the prefrontal and motor cortices -thus involving functions such as working memory, executive and motor functions. Our methodology to assess high-order interdependencies in fMRI data has unlimited applications. The code to calculate these metrics is freely available.

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Interaction Information Along Lifespan of the Resting Brain Dynamics Reveals a Major Redundant Role of the Default Mode Network

Cited by 17 publications

References 56 publications

Cortical ignition dynamics is tightly linked to the core organisation of the human connectome

Cortical ignition dynamics is tightly linked to the core organisation of the human connectome

Metastable Resting State Brain Dynamics

High-Order Interdependencies in the Aging Brain

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