Evidence map›Paper›PMID 29971940›Full record

ReviewWiley interdisciplinary reviews. Cognitive science2019

Clarifying cognitive control and the controllable connectome.

John D Medaglia

Open access · greenAbstract readReview
In one paragraph

Review in Wiley interdisciplinary reviews. Cognitive science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
0.5field-weighted citation impact, top 28% of its field
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

19 citing papers in PubMed, 4 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. On the control of recurrent neural networks using constant inputs.IEEE transactions on automatic control · 2026
    Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. The missing role of gray matter in studying brain controllability.Network neuroscience (Cambridge, Mass.) · 2021
    Article
  15. Article
  16. Article
  17. Implementing a concept network model.Behavior research methods · 2019
    Article
  18. Review
  19. Article
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

1 author at 1 institution in 1 country.

John D MedagliaDepartment of Psychology, Drexel University, Philadelphia, Pennsylvania.
University of Pennsylvania · US

Funding

Contributions of spared brain structures and connections to aphasia recoveryR01DC014960 · NIDCD · GEORGETOWN UNIVERSITY · PI TURKELTAUB, PETER ETHAN · 2017 to 2021
$4.0M
Dynamic Network Neuroscience and Control Theory: Toward Interventions for Cognitive Control DysfunctionDP5OD021352 · OD · UNIVERSITY OF PENNSYLVANIA · PI MEDAGLIA, JOHN · 2015 to 2019
$2.0M
NIDCD NIH HHS R01 DC014960NIDCR NIH HHS R01-DC014960NIH HHS DP5 OD021352NIH HHS DP5-OD021352
6 · The paper itself

Abstract

Cognitive control researchers aim to describe the processes that support adaptive cognition to achieve specific goals. Control theorists consider how to influence the state of systems to reach certain user-defined goals. In brain networks, some conceptual and lexical similarities between cognitive control and control theory offer appealing avenues for scientific discovery. However, these opportunities also come with the risk of conceptual confusion. Here, I suggest that each field of inquiry continues to produce novel and distinct insights. Then, I describe opportunities for synergistic research at the intersection of these subdisciplines with a critical stance that reduces the risk of conceptual confusion. Through this exercise, we can observe that both cognitive neuroscience and systems engineering have much to contribute to cognitive control research in human brain networks. This article is categorized under: Neuroscience > Cognition Computer Science > Neural Networks Neuroscience > Clinical Neuroscience.

Indexed as

ConnectomeExecutive FunctionNerve NetBrainHumansNeurosciencescognitive controlcontrol theorydiffusion imagingfMRIneural networks

Identifiers

PMID29971940
PMCPMC6642819
OpenAlexW2784528425

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.