Evidence map›Paper›PMID 30923480›Full record

ReviewThe Yale journal of biology and medicine2019

Attention: The Messy Reality.

John K Tsotsos

Abstract readReview
In one paragraph

Review in The Yale journal of biology and medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

John K TsotsosDepartment of Electrical Engineering and Computer Science, York University, Toronto, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The human capability to attend has been both considered as easy and as impossible to understand by philosophers and scientists through the centuries. Much has been written by brain, cognitive, and philosophical scientists trying to explain attention as it applies to sensory and reasoning processes, let alone consciousness. It has been only in the last few decades that computational scientists have entered the picture adding a new language with which to express attentional behavior and function. This new perspective has produced some progress to the centuries-old goal, but there is still far to go. Although a central belief in many scientific disciplines has been to seek a unifying explanatory principle for natural observations, it may be that we need to put this aside as it applies to attention and accept the fact that attention is really an integrated set of mechanisms, too messy to cleanly and parsimoniously express with a single principle. These mechanisms are claimed to be critical to enable functional generalization of brain processes and thus an integrative perspective is important. Here we present first steps towards a theoretical and algorithmic view on how the many different attentional mechanisms may be deployed, coordinated, synchronized, and effectively utilized. A hierarchy of dynamically defined closed-loop control processes is proposed, each with its own optimization objective, which is extensible to multiple layers. Although mostly speculative, simulation and experimental work support important components.

Indexed as

AttentionExecutive FunctionHumansTask Performance and AnalysisVisual Perceptionattentionexecutive controlSelective Tuningvision

Identifiers

PMID30923480
PMCPMC6430176

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.