Evidence map›Paper›PMID 36059768›Full record

ArticleFrontiers in psychology2022

Interactive neurorobotics: Behavioral and neural dynamics of agent interactions.

Eric J Leonardis, Leo Breston, Rhiannon Lucero-Moore, Leigh Sena, Raunit Kohli, Luisa Schuster, Lacha Barton-Gluzman, Laleh K Quinn, Janet Wiles, Andrea A Chiba

Abstract read
In one paragraph

Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Eric J LeonardisDepartment of Cognitive Science, University of California, San Diego, San Diego, CA, United States.
Leo BrestonDepartment of Cognitive Science, University of California, San Diego, San Diego, CA, United States.
Rhiannon Lucero-MooreDepartment of Cognitive Science, University of California, San Diego, San Diego, CA, United States.
Leigh SenaDepartment of Cognitive Science, University of California, San Diego, San Diego, CA, United States.
Raunit KohliDepartment of Cognitive Science, University of California, San Diego, San Diego, CA, United States.
Luisa SchusterCenter for Neural Science, New York University, New York, NY, United States.
Lacha Barton-GluzmanDepartment of Cognitive Science, University of California, San Diego, San Diego, CA, United States.
Laleh K QuinnDepartment of Cognitive Science, University of California, San Diego, San Diego, CA, United States.
Janet WilesSchool of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD, Australia.
Andrea A ChibaDepartment of Cognitive Science, University of California, San Diego, San Diego, CA, United States.

Funding

Neurosciences Graduate Training ProgramT32NS061847 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Brenda L Bloodgood · 2008 to 2026
$7.7M
Behavioral, Physiological, and Quantitative Models of Pro-Social BehaviorR01MH110514 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CHIBA, ANDREA ANGELIDES, COLEMAN, TODD P · 2016 to 2018
$1.4M
NIMH NIH HHS R01 MH110514NINDS NIH HHS T32 NS061847
6 · The paper itself

Abstract

Interactive neurorobotics is a subfield which characterizes brain responses evoked during interaction with a robot, and their relationship with the behavioral responses. Gathering rich neural and behavioral data from humans or animals responding to agents can act as a scaffold for the design process of future social robots. This research seeks to study how organisms respond to artificial agents in contrast to biological or inanimate ones. This experiment uses the novel affordances of the robotic platforms to investigate complex dynamics during minimally structured interactions that would be difficult to capture with classical experimental setups. We then propose a general framework for such experiments that emphasizes naturalistic interactions combined with multimodal observations and complementary analysis pipelines that are necessary to render a holistic picture of the data for the purpose of informing robotic design principles. Finally, we demonstrate this approach with an exemplar rat-robot social interaction task which included simultaneous multi-agent tracking and neural recordings.

Indexed as

amygdalahippocampusimmobility behaviorinteractionlocal field potentialolfactory bulbrobotsocial robotics

Identifiers

PMID36059768
PMCPMC9431369

What OpenQuestion holds

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LicenceCC BY
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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.