Evidence map›Paper›PMID 32886673›Full record

ArticlePLoS computational biology2020

Relations between large-scale brain connectivity and effects of regional stimulation depend on collective dynamical state.

Lia Papadopoulos, Christopher W Lynn, Demian Battaglia, Danielle S Bassett

Abstract read
In one paragraph

Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed.

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  6. cuBNM: GPU-Accelerated Brain Network Modeling.bioRxiv : the preprint server for biology · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Lia PapadopoulosDepartment of Physics & Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
Christopher W LynnDepartment of Physics & Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
Demian BattagliaUniversité Aix-Marseille, INSERM UMR 1106, Institut de Neurosciences des Systèmes, F-13005, Marseille, France.ORCID 0000-0003-2021-7920
Danielle S BassettDepartment of Physics & Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.ORCID 0000-0002-6183-4493

Funding

Inter-modal Coupling Image AnalyticsR01MH112847 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Theodore Satterthwaite, Russell Takeshi Shinohara · 2017 to 2026
$5.9M
Linguistic and NonLinguistic Functions of Frontal CortexR01DC009209 · NIDCD · UNIVERSITY OF PENNSYLVANIA · PI THOMPSONSCHILL, SHARON L · 2008 to 2018
$5.2M
Virtual Resection to Treat EpilepsyR01NS099348 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI BASSETT, DANIELLE SMITH, LITT, BRIAN · 2016 to 2019
$2.3M
Multimodal brain maturation indices modulating psychopathology and neurocognitionR01MH107235 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI GUR, RUBEN C. · 2015 to 2017
$1.5M
Nanoparticle-driven systems for tunable local pain reliefR01GM116920 · NIGMS · BOSTON CHILDREN'S HOSPITAL · PI KOHANE, DANIEL S · 2016 to 2019
$1.2M
CRCNS: US-France Modeling & Predicting BCI Learning from Dynamic NetworksR01HD086888 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI BASSETT, DANIELLE SMITH · 2015 to 2018
$506k
NICHD NIH HHS R01 HD086888NIDCD NIH HHS R01 DC009209NIGMS NIH HHS R01 GM116920NIMH NIH HHS R01 MH107235NIMH NIH HHS R01 MH112847NINDS NIH HHS R01 NS099348
6 · The paper itself

Abstract

At the macroscale, the brain operates as a network of interconnected neuronal populations, which display coordinated rhythmic dynamics that support interareal communication. Understanding how stimulation of different brain areas impacts such activity is important for gaining basic insights into brain function and for further developing therapeutic neurmodulation. However, the complexity of brain structure and dynamics hinders predictions regarding the downstream effects of focal stimulation. More specifically, little is known about how the collective oscillatory regime of brain network activity-in concert with network structure-affects the outcomes of perturbations. Here, we combine human connectome data and biophysical modeling to begin filling these gaps. By tuning parameters that control collective system dynamics, we identify distinct states of simulated brain activity and investigate how the distributed effects of stimulation manifest at different dynamical working points. When baseline oscillations are weak, the stimulated area exhibits enhanced power and frequency, and due to network interactions, activity in this excited frequency band propagates to nearby regions. Notably, beyond these linear effects, we further find that focal stimulation causes more distributed modifications to interareal coherence in a band containing regions' baseline oscillation frequencies. Importantly, depending on the dynamical state of the system, these broadband effects can be better predicted by functional rather than structural connectivity, emphasizing a complex interplay between anatomical organization, dynamics, and response to perturbation. In contrast, when the network operates in a regime of strong regional oscillations, stimulation causes only slight shifts in power and frequency, and structural connectivity becomes most predictive of stimulation-induced changes in network activity patterns. In sum, this work builds upon and extends previous computational studies investigating the impacts of stimulation, and underscores the fact that both the stimulation site, and, crucially, the regime of brain network dynamics, can influence the network-wide responses to local perturbations.

Indexed as

ConnectomeModels, NeurologicalBrainHumansNeurons

Identifiers

PMID32886673
PMCPMC7537889

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.