Evidence map›Paper›PMID 28919222›Full record

ReviewCortex; a journal devoted to the study of the nervous system and behavior2018

Understanding active sampling strategies: Empirical approaches and implications for attention and decision research.

Jacqueline Gottlieb

Abstract readReview
In one paragraph

Review in Cortex; a journal devoted to the study of the nervous system and behavior, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

21 citing papers in PubMed, 55 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Attentional priority is determined by predicted feature distributions.Journal of experimental psychology. Human perception and performance · 2022
    Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. A physicochemical model of odor sampling.PLoS computational biology · 2021
    Article
  12. Article
  13. The ventral striatum dissociates information expectation, reward anticipation, and reward receipt.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  14. Article
  15. A neural network for information seeking.Nature communications · 2019
    Article
  16. Article
  17. Article
  18. Review
  19. Review
  20. 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.

Jacqueline GottliebDepartment of Neuroscience, Columbia University, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, USA. Electronic address: jg2141@columbia.edu.
Columbia University · US

Funding

Instrumentation, Fabrication, and Design CoreP30EY019007 · NEI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Xin Zhang · 2010 to 2026
$12.9M
Attentional control by uncertainty and reward: parietal and frontal mechanismsR01MH098039 · NIMH · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GOTTLIEB, JACQUELINE · 2012 to 2016
$2.0M
Top-down selection of task-relevant cues: neural mechanisms in the frontal and parietal lobes.R01EY025965 · NEI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GOTTLIEB, JACQUELINE · 2015 to 2019
$2.0M
Neural mechanisms of saccadic information seeking behaviorR03MH115644 · NIMH · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GOTTLIEB, JACQUELINE · 2017 to 2018
$160k
NEI NIH HHS P30 EY019007NEI NIH HHS R01 EY025965NIMH NIH HHS R01 MH098039NIMH NIH HHS R03 MH115644
6 · The paper itself

Abstract

In natural behavior we actively gather information using attention and active sensing behaviors (such as shifts of gaze) to sample relevant cues. However, while attention and decision making are naturally coordinated, in the laboratory they have been dissociated. Attention is studied independently of the actions it serves. Conversely, decision theories make the simplifying assumption that the relevant information is given, and do not attempt to describe how the decision maker may learn and implement active sampling policies. In this paper I review recent studies that address questions of attentional learning, cue validity and information seeking in humans and non-human primates. These studies suggest that learning a sampling policy involves large scale interactions between networks of attention and valuation, which implement these policies based on reward maximization, uncertainty reduction and the intrinsic utility of cognitive states. I discuss the importance of using such paradigms for formalizing the role of attention, as well as devising more realistic theories of decision making that capture a broader range of empirical observations.

Indexed as

AttentionChoice BehaviorDecision MakingEye MovementsHumansLearningRewardActive sensingAttentionDecision makingEye movementsInformation seeking

Identifiers

PMID28919222
PMCPMC5826782
OpenAlexW2750343807

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.