Evidence map›Paper›PMID 36811348›Full record

ArticleeLife2023

Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making.

Carmen Kohl, Michelle X M Wong, Jing Jun Wong, Matthew F S Rushworth, Bolton K H Chau

Abstract read
In one paragraph

Article in eLife, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
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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

5 authors.

Carmen KohlDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China.
Michelle X M WongDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China.
Jing Jun WongDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China.ORCID 0000-0001-5241-6997
Matthew F S RushworthDepartment of Experimental Psychology, University of Oxford, Oxford, United Kingdom.
Bolton K H ChauDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China.ORCID 0000-0002-6854-5176

Funding

Medical Research Council MR/P024955/1Wellcome Trust 221794/Z/20/Z
6 · The paper itself

Abstract

There has been debate about whether addition of an irrelevant distractor option to an otherwise binary decision influences which of the two choices is taken. We show that disparate views on this question are reconciled if distractors exert two opposing but not mutually exclusive effects. Each effect predominates in a different part of decision space: (1) a positive distractor effect predicts high-value distractors improve decision-making; (2) a negative distractor effect, of the type associated with divisive normalisation models, entails decreased accuracy with increased distractor values. Here, we demonstrate both distractor effects coexist in human decision making but in different parts of a decision space defined by the choice values. We show disruption of the medial intraparietal area (MIP) by transcranial magnetic stimulation (TMS) increases positive distractor effects at the expense of negative distractor effects. Furthermore, individuals with larger MIP volumes are also less susceptible to the disruption induced by TMS. These findings also demonstrate a causal link between MIP and the impact of distractors on decision-making via divisive normalisation.

Indexed as

AttentionTranscranial Magnetic StimulationHumansPhotic StimulationReaction Timedecision makingdevelopmental biologydistractordivisive normalizationhumanneuroscienceparietal cortextranscranial magnetic stimulation

Identifiers

PMID36811348
PMCPMC9946441

What OpenQuestion holds

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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.