Evidence map›Paper›PMID 30215030›Full record

ArticleNetwork neuroscience (Cambridge, Mass.)2018

The network architecture of value learning.

Marcelo G Mattar, Sharon L Thompson-Schill, Danielle S Bassett

Abstract read
In one paragraph

Article in Network neuroscience (Cambridge, Mass.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Social network analysis for social neuroscientists.Social cognitive and affective neuroscience · 2021
    Article
  6. Article
  7. Media content sharing as a value-based decision.Current opinion in psychology · 2020
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. The network architecture of value learning.Network neuroscience (Cambridge, Mass.) · 2018
    Article
  13. Editorial: New Trends in Connectomics.Network neuroscience (Cambridge, Mass.) · 2018
    Article
  14. Review
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

3 authors.

Marcelo G MattarDepartment of Psychology, University of Pennsylvania, Philadelphia, PA, USA.
Sharon L Thompson-SchillDepartment of Psychology, University of Pennsylvania, Philadelphia, PA, USA.
Danielle S BassettDepartment of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.

Funding

Linguistic and NonLinguistic Functions of Frontal CortexR01DC009209 · NIDCD · UNIVERSITY OF PENNSYLVANIA · PI THOMPSONSCHILL, SHARON L · 2008 to 2018
$5.2M
Conceptual CombinationR01DC015359 · NIDCD · UNIVERSITY OF PENNSYLVANIA · PI THOMPSONSCHILL, SHARON L · 2016 to 2020
$2.5M
Object ConceptsR01EY021717 · NEI · UNIVERSITY OF PENNSYLVANIA · PI THOMPSONSCHILL, SHARON L · 2011 to 2014
$1.6M
CRCNS: US-France Modeling & Predicting BCI Learning from Dynamic NetworksR01HD086888 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI BASSETT, DANIELLE SMITH · 2015 to 2018
$506k
NEI NIH HHS R01 EY021717NICHD NIH HHS R01 HD086888NIDCD NIH HHS R01 DC009209NIDCD NIH HHS R01 DC015359
6 · The paper itself

Abstract

Value guides behavior. With knowledge of stimulus values and action consequences, behaviors that maximize expected reward can be selected. Prior work has identified several brain structures critical for representing both stimuli and their values. Yet, it remains unclear how these structures interact with one another and with other regions of the brain to support the dynamic acquisition of value-related knowledge. Here, we use a network neuroscience approach to examine how BOLD functional networks change as 20 healthy human subjects learn the values of novel visual stimuli over the course of four consecutive days. We show that connections between regions of the visual, frontal, and cingulate cortices become stronger as learning progresses, with some of these changes being specific to the type of feedback received during learning. These results demonstrate that functional networks dynamically track behavioral improvement in value judgments, and that interactions between network communities form predictive biomarkers of learning.

Indexed as

Behavioral adaptabilityBrain networksCognitive systemsFunctional connectivityReinforcement learningValuation system

Identifiers

PMID30215030
PMCPMC6130435

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.