Dynamic reconfiguration of frontal brain networks during executive cognition in humans

In the paper

“First, the frontoparietal module was composed of more medial structures in the 0-back condition, and more lateral structures in the 2-back condition;”

In the paper

“In contrast to a control condition, in which dynamic changes in cortical networks were spread evenly across systems, the effortful working-memory condition was characterized by a reconfiguration of frontoparietal and frontotemporal networks.”

In the paper

“In the current study, we demonstrate that brain network flexibility and its relationship to cognitive demand can be tracked continuously on the order of minutes and undergoes specific and repetitive changes even within a given task.”

In the paper

“we observe that the module that we have referred to as the “parietal module” contains a large portion of higher-order association areas that were classified as part of the visual system in Power et al. (36) (i.e., 85% of nodes in our parietal module were assigned to Power et al.’s “visual module”)”

What the sources say

• Not checked yetcites [36] Power JD, et al. Functional network organization of the human brain. Neuron. 2011;72(4):665–678. doi: 10.1016/j.neuron.2011.09.006. [DOI] [PMC free article] [PubMed] [Google Scholar] source

In the paper

“Third, we observed that the decomposition of the module allegiance matrices into network modules was replicable.”

In the paper

“Despite the conservation of whole-brain flexibility across working-memory load, we did observe a redistribution of flexibility across cognitive systems.”

In the paper

“We robustly observe that network flexibility oscillates across task performance”

In the paper

“We provide evidence that the amount of reorganization in the modular structure and specifically the amount of interaction between modules is behaviorally relevant to working-memory performance and cognitive flexibility.”

In the paper

“The identified network modules map well to biologically meaningful systems of intrinsic connectivity (36) and specifically systems commonly engaged during working-memory performance (14, 38, 39)”

What the sources say

• Not checked yetcites [36] Power JD, et al. Functional network organization of the human brain. Neuron. 2011;72(4):665–678. doi: 10.1016/j.neuron.2011.09.006. [DOI] [PMC free article] [PubMed] [Google Scholar] source
• Not checked yetcites [14] Ginestet CE, Simmons A. Statistical parametric network analysis of functional connectivity dynamics during a working memory task. Neuroimage. 2011;55(2):688–704. doi: 10.1016/j.neuroimage.2010.11.030. [DOI] [PubMed] [Google Scholar] source
• Not checked yetcites [38] Hampson M, Driesen NR, Skudlarski P, Gore JC, Constable RT. Brain connectivity related to working memory performance. J Neurosci. 2006;26(51):13338–13343. doi: 10.1523/JNEUROSCI.3408-06.2006. [DOI] [PMC free article] [PubMed] [Google Scholar] source

In the paper

“In the present study, we have provided evidence that the functional connectivity during a working-memory task is dynamically organized into adapting modules and that this adapting modular structure relates to cognitive demands.”

In the paper

“We found 46% of the mapped nodes belonging to the frontoparietal module identified by us, whereas 27% belonged to the somatomotor module and 12% belonged to the frontal module.”

What the sources say

• Not checked yetcites [39] Owen AM, McMillan KM, Laird AR, Bullmore E. N-back working memory paradigm: A meta-analysis of normative functional neuroimaging studies. Hum Brain Mapp. 2005;25(1):46–59. doi: 10.1002/hbm.20131. [DOI] [PMC free article] [PubMed] [Google Scholar] source

In the paper

“Fourth, we observed a significant difference in flexibility between 0-back and 2-back [repeated-measures ANOVA with task and frontal vs. nonfrontal as categorical factors, main effect of task: F(1,343) = 21.8, P < 0.001], which was a trend in the results based on coherence.”

In the paper

“Critically, we observe that network modules differ in their degree of integration with other network modules: stable core-like modules including visual and somatomotor systems show relatively weak integration with other modules, whereas frontal and frontal-mediated modules show relatively strong integration with other modules (Fig. 2D).”

In the paper

“Finally, the behavioral correlations we observed are small and some fail to reach statistical significance under Bonferroni correction, and therefore should be interpreted with caution and validated in future studies.”

In the paper

“Due to the heuristic nature of the algorithm and to the near degeneracy of the optimization landscape of the multilayer modularity quality function, each independent run of the algorithm provided slightly different partitions of network nodes into communities across the 114 time slices (or network layers).”

In the paper

“The clustering coefficient is highest between task blocks and lowest within task blocks, whereas the path length is longest between task blocks and shortest within task blocks.”

In the paper

“The clustering coefficient is highest between task blocks and lowest within task blocks, whereas the path length is longest between task blocks and shortest within task blocks.”

In the paper

“Theoretical frameworks for working memory call on the interplay of distinct components (12) and their integration in broader cognitive circuits (1).”

What the sources say

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In the paper

“Working memory lies at the interface of perception and action (7) and requires the integration of large-scale neural circuits (8–11).”

What the sources say

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In the paper

“emerging evidence indicates that many so-called “domain-general” areas engage in multiple functions, differing from “domain-specific” areas such as primary visual cortex that perform a very specific function (1, 2).”

What the sources say

• Not checked yetcites [1] Shohamy D, Turk-Browne NB. Mechanisms for widespread hippocampal involvement in cognition. J Exp Psychol Gen. 2013;142(4):1159–1170. doi: 10.1037/a0034461. [DOI] [PMC free article] [PubMed] [Google Scholar] source
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In the paper

“The empirical neuroimaging literature has bolstered these conceptualizations by identifying several distinct sets of brain areas underlying working-memory performance (13–17).”

What the sources say

• Not checked yetcites [13] Baddeley A. Working memory: Looking back and looking forward. Nat Rev Neurosci. 2003;4(10):829–839. doi: 10.1038/nrn1201. [DOI] [PubMed] [Google Scholar] source
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• Not checked yetcites [15] Collette F, Van der Linden M. Brain imaging of the central executive component of working memory. Neurosci Biobehav Rev. 2002;26(2):105–125. doi: 10.1016/s0149-7634(01)00063-x. [DOI] [PubMed] [Google Scholar] source
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In the paper

“Working memory lies at the interface of perception and action (7)”

What the sources say

• Not checked yetcites [7] Linden DE. The working memory networks of the human brain. Neuroscientist. 2007;13(3):257–267. doi: 10.1177/1073858406298480. [DOI] [PubMed] [Google Scholar] source

In the paper

“These results suggest that dynamic network reorganization is taking place predominately in frontal systems and is driven by a constant readaptation and interaction of frontal systems with each other.”

In the paper

“Based on the cognitive load of the 2-back condition (20–22)”

What the sources say

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In the paper

“This analysis confirms our previous results are not due to noise and finite data length, but show task-specific variations.”

In the paper

“Therefore, identical solutions that are obtained from diverse initial conditions actually indicate important replicable features of the landscape, which should be accounted for in subsequent analysis.”

In the paper

“However, as of today, a common method for dealing with this degeneracy is to examine statistics averaged over the 100 repetitions of the optimization, with equal weight being placed on each solution, rather than just on the unique solutions.”

What the sources say

• Not checked yetcites [25] Bassett DS, et al. Robust detection of dynamic community structure in networks. Chaos. 2013;23(1):013142. doi: 10.1063/1.4790830. [DOI] [PMC free article] [PubMed] [Google Scholar] source
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In the paper

“As a complex system, the human brain is intrinsically organized into modules, creating a high degree of flexibility and adaptability of the system without fundamentally altering underlying structure (29, 30).”

What the sources say

• Not checked yetcites [29] Kirschner M, Gerhart J. Evolvability. Proc Natl Acad Sci USA. 1998;95(15):8420–8427. doi: 10.1073/pnas.95.15.8420. [DOI] [PMC free article] [PubMed] [Google Scholar] source
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In the paper

“This indicates that the dynamic reconfiguration of frontal systems for working-memory function may not be limited to the n-back working-memory paradigm but may be essential for the manipulation of stored information across tasks.”

In the paper

“It is intuitively plausible that the strong integration of frontal systems with other network modules forms a physiological basis for cognitive flexibility (15, 41), enabling task switching and cognitive control during demanding tasks (21, 42).”

What the sources say

• Not checked yetcites [15] Collette F, Van der Linden M. Brain imaging of the central executive component of working memory. Neurosci Biobehav Rev. 2002;26(2):105–125. doi: 10.1016/s0149-7634(01)00063-x. [DOI] [PubMed] [Google Scholar] source
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In the paper

“Mathematically, the wavelet-based measures provide significant denoising to the signal, enhancing signal-to-noise ratio in subsequent analyses.”

In the paper

“due to heuristics in the algorithm and challenges inherent to fMRI data, the assignment of nodes to communities on the individual subject level remains a statistical process, accompanied by some degree of uncertainty.”

In the paper

“maximizing the modularity quality function is NP-hard, and we therefore use a Louvain-like locally greedy heuristic algorithm (50) to seek the optimal modularity index Q.”

What the sources say

• Not checked yetcites [50] Jutla I, Jeub L, Mucha P. 2011. A generalized Louvain method for community detection implemented in MATLAB (computer program). Available at netwiki.amath.unc.edu. Accessed September 1, 2014.

In the paper

“we remain limited by the temporal resolution of fMRI data, making it likely that the modular changes and behavioral associations we observed might be further resolved in time if electrophysiological data were used.”

In the paper

“In a recent paper from Van De Ville and colleague (49), the authors demonstrate the optimality of a 30-s time window for quantifying dynamic reconfiguration of networks in the frequency range 0.08–0.15 Hz.”

What the sources say

• Not checked yetcites [49] Leonardi N, Van De Ville D. On spurious and real fluctuations of dynamic functional connectivity during rest. Neuroimage. 2015;104:430–436. doi: 10.1016/j.neuroimage.2014.09.007. [DOI] [PubMed] [Google Scholar] source

In the paper

“flexibility can be driven by transient interactions between modules: the more transient module–module interactions, the more likely regions are to flexibly alter their allegiance to cognitive systems—an aspect of reconfiguration that we capture by integration.”

In the paper

“The n-back task has been studied extensively in the context of traditional activation and connectivity analyses (38, 39), identifying a large (executive) working-memory network dominated by frontal and parietal regions.”

What the sources say

• Not checked yetcites [38] Hampson M, Driesen NR, Skudlarski P, Gore JC, Constable RT. Brain connectivity related to working memory performance. J Neurosci. 2006;26(51):13338–13343. doi: 10.1523/JNEUROSCI.3408-06.2006. [DOI] [PMC free article] [PubMed] [Google Scholar] source
• Not checked yetcites [39] Owen AM, McMillan KM, Laird AR, Bullmore E. N-back working memory paradigm: A meta-analysis of normative functional neuroimaging studies. Hum Brain Mapp. 2005;25(1):46–59. doi: 10.1002/hbm.20131. [DOI] [PMC free article] [PubMed] [Google Scholar] source

In the paper

“Third, we use a measure of functional connectivity that does not reflect causal interaction.”

In the paper

“Indeed, connectivity analyses, and more complex measures of the dynamic reconfiguration of networks in face of different task demands, are not competitive with activation studies but provide very complementary insights that directly address the underlying mechanisms of cognitive processes (61).”

What the sources say

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In the paper

“These results support the view that, within task blocks, network reconfiguration mainly takes place between modules, thus resulting in a lower clustering coefficient and an increased path length.”

In the paper

“Thus, the current work can be seen as a direct validation of the role of frontal regions in adaptive behavior, and as clarifying the mechanism of this role as based on dynamic changes in functional connectivity.”

In the paper

“Finally, dynamic community detection methods have further been used in the context of human motor skill learning (3) and lexical processing (59).”

What the sources say

• Not checked yetcites [3] Bassett DS, et al. Dynamic reconfiguration of human brain networks during learning. Proc Natl Acad Sci USA. 2011;108(18):7641–7646. doi: 10.1073/pnas.1018985108. [DOI] [PMC free article] [PubMed] [Google Scholar] source
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In the paper

“In a following methods paper (25), we stringently evaluated the methodological choices required to robustly detect dynamic community structure in simulated and empirical data.”

What the sources say

• Not checked yetcites [25] Bassett DS, et al. Robust detection of dynamic community structure in networks. Chaos. 2013;23(1):013142. doi: 10.1063/1.4790830. [DOI] [PMC free article] [PubMed] [Google Scholar] source

In the paper

“Therefore, although network reconfiguration explains a small amount of variance, it has quantifiable advantages over traditional analyses and here offers complementary insights into the neurobiological basis of working memory.”

In the paper

“Third, the main effect of task was removed from the data to not confound network measures with large-scale block (co)activations, as has been done previously (e.g., see ref. 23).”

What the sources say

• Not checked yetcites ref. 23

In the paper

“To account for noise, only matrix elements whose values were larger than expected in a random network null model were taken into account.”

In the paper

“This procedure can be repeated iteratively, so that repeated optimizations of the modularity quality function of the consensus matrix Tcons return a single optimal consensus partition S, which partitions brain regions into representative putative functional modules that we interpret as cognitive systems (25).”

What the sources say

• Not checked yetcites [25] Bassett DS, et al. Robust detection of dynamic community structure in networks. Chaos. 2013;23(1):013142. doi: 10.1063/1.4790830. [DOI] [PMC free article] [PubMed] [Google Scholar] source

In the paper

“To be conservative, we remove such “noise” from the original nodal association matrix T by setting any element Tij whose value is less than the maximum entry of the random association matrix to 0.”

In the paper

“For example, although classical GLM-based approaches are often interpreted as indicating functional associations between regions, connectivity analyses provide direct evidence of neurophysiological mechanisms defining the roles of brain networks in cognition (2).”

What the sources say

• Not checked yetcites [2] Fedorenko E, Thompson-Schill SL. Reworking the language network. Trends Cogn Sci. 2014;18(3):120–126. doi: 10.1016/j.tics.2013.12.006. [DOI] [PMC free article] [PubMed] [Google Scholar] source

In the paper

“In that paper, we also developed a framework of null model testing for statistical inference in the context of neuroimaging data.”

What the sources say

• Not checked yetcites [25] Bassett DS, et al. Robust detection of dynamic community structure in networks. Chaos. 2013;23(1):013142. doi: 10.1063/1.4790830. [DOI] [PMC free article] [PubMed] [Google Scholar] source

In the paper

“In the original paper (6), the methods were tested on two different kinds of social networks, and results were consistent with prior knowledge regarding these systems.”

What the sources say

• Not checked yetcites [6] Mucha PJ, Richardson T, Macon K, Porter MA, Onnela JP. Community structure in time-dependent, multiscale, and multiplex networks. Science. 2010;328(5980):876–878. doi: 10.1126/science.1184819. [DOI] [PubMed] [Google Scholar] source