Evidence map›Paper›PMID 20359885›Full record

ReviewCurrent opinion in neurobiology2010

Neural correlations, decisions, and actions.

Bijan Pesaran

Abstract readReview
In one paragraph

Review in Current opinion in neurobiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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  8. Multi-scale neural decoding and analysis.Journal of neural engineering · 2021
    Review
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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

1 author.

Bijan PesaranCenter for Neural Science, New York University, 4 Washington Pl., New York, NY 10003, USA. bijan@nyu.edu

Funding

CRCNS: Reinforcement learning in multi-dimensional action spacesR01MH087882 · NIMH · NEW YORK UNIVERSITY · PI DAW, NATHANIEL DOUGLASS · 2009 to 2013
$1.8M
NIMH NIH HHS R01 MH087882
6 · The paper itself

Abstract

Multielectrode recording experiments let us measure correlations between the activity of individual neurons and the neural circuits in which they are embedded. Recently, multielectrode studies have been emphasizing how correlated neuronal activity is linked with behavior. Decisions are fundamental to voluntary behavior. Here, we discuss computations necessary to turn a decision into an action and review progress in studying correlated neural activity in areas of the brain which link sensory and motor representations. The themes that emerge are that correlated patterns of activity in populations of neurons can be revealed by measurements of field potential fluctuations and that these measurements can relate the activity of individual neurons to the activity of populations of neurons distributed across different regions of the brain. Investigations into patterns of neuronal correlation are helping us to understand how decisions and other cognitive processes result from the interactions between different brain systems that are responsible for controlling and regulating our behavior.

Indexed as

Action PotentialsAnimalsBrainComputer SimulationDecision MakingElectrophysiologyExecutive FunctionHumansMovementNerve NetNeuronsPsychomotor Performance

Identifiers

PMID20359885
PMCPMC2862782

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.