Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Stereotype Content Model02:16

Stereotype Content Model

14.9K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.9K
Control Systems01:10

Control Systems

1.5K
Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
1.5K
Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

26
Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
26
Machines: Problem Solving II01:30

Machines: Problem Solving II

434
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
434
Theory of Attribution I: Correspondent Inference Theory01:15

Theory of Attribution I: Correspondent Inference Theory

44
Correspondent inference theory, proposed by Jones and Davis in 1965, seeks to explain how individuals infer stable personality traits from observed behaviors. It suggests that people attribute actions to underlying dispositions rather than external circumstances, particularly when the behavior appears intentional and socially significant.Voluntary Behavior and Dispositional AttributionAccording to this theory, individuals are more likely to attribute behavior to personal traits when it appears...
44
Observational Learning01:12

Observational Learning

379
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
379

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Using chills-inducing music to augment self-transcendence, emotional breakthrough, and psychological insight during mindfulness and loving kindness meditation.

Frontiers in psychology·2026
Same author

Editorial: Agency in posttraumatic stress disorder: theoretical approach and therapeutic perspectives.

Frontiers in integrative neuroscience·2026
Same author

Contrasting cognitive, behavioral, and physiological responses to breathwork vs. naturalistic stimuli in reflective chamber and VR headset environments.

PLOS mental health·2026
Same author

Self-transcendence accompanies aesthetic chills.

PLOS mental health·2026
Same author

Gesture sonification for enhancing agency: an exploratory study on healthy participants.

Frontiers in psychology·2025
Same author

Research Priorities for Autonomous Sensory Meridian Response: An Interdisciplinary Delphi Study.

Multisensory research·2024
Same journal

Treadmill exercise rescues motor deficits in parkinsonian mice by modulating striatal D2-MSN activity: evidence from calcium imaging and chemogenetics.

Frontiers in systems neuroscience·2026
Same journal

Transfer learning for EEG-based BCIs: a comparative evaluation and optimization of data alignment methods.

Frontiers in systems neuroscience·2026
Same journal

The volatile anesthetic isoflurane causes global suppression of neuronal activity, disrupting hub neuron function in <i>Caenorhabditis elegans</i>.

Frontiers in systems neuroscience·2026
Same journal

Associative emotional memory encoding: insights from network stability analysis of an fMRI-driven bilinear dynamics.

Frontiers in systems neuroscience·2026
Same journal

The neurobiological basis of the awe experience in affective disorders: an exploratory EEG study.

Frontiers in systems neuroscience·2026
Same journal

Exploring the spiking neural autoencoder: from hyperexcitability to noise-driven compensation.

Frontiers in systems neuroscience·2026
See all related articles

Related Experiment Video

Updated: Oct 14, 2025

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
05:21

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Published on: January 7, 2019

8.1K

Trust as Extended Control: Human-Machine Interactions as Active Inference.

Felix Schoeller1,2, Mark Miller3,4, Roy Salomon2

  • 1Massachusetts Institute of Technology, Cambridge, MA, United States.

Frontiers in Systems Neuroscience
|November 1, 2021
PubMed
Summary
This summary is machine-generated.

Trust in human-robot collaboration (HRC) is essential for seamless interaction. This paper proposes a new model of trust based on active inference, viewing it as virtual control and emphasizing the role of user feedback for reliable human-robot systems.

Keywords:
active inferencecoboticscontrolextended mind hypothesishuman computer interactionhuman-robot interactiontrust

More Related Videos

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.7K
Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation
06:53

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Published on: March 1, 2017

13.5K

Related Experiment Videos

Last Updated: Oct 14, 2025

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
05:21

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Published on: January 7, 2019

8.1K
Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.7K
Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation
06:53

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Published on: March 1, 2017

13.5K

Area of Science:

  • Cognitive Neuroscience
  • Human-Robot Interaction
  • Human Factors Engineering

Background:

  • Trust is crucial for effective human-robot collaboration (HRC), yet its development remains poorly understood.
  • Existing models of trust often focus on competence and benevolence, with human-to-human interaction studies highlighting shared behavior and mutual knowledge.
  • Understanding trust is vital for designing user-centered robotic systems and improving human-robot interaction.

Purpose of the Study:

  • To review existing literature on trust in the context of human-robot interaction and collaboration.
  • To introduce a novel model of trust based on active inference and cognitive neuroscience principles.
  • To explore the implications of this model for understanding and designing HRC systems.

Main Methods:

  • Literature review of trust, human-robot interaction, and HRC.
  • Introduction of a theoretical model of trust grounded in active inference and cognitive neuroscience.
  • Analysis of trust determinants (benevolence, competence, vulnerability) through the lens of the proposed model.

Main Results:

  • Trust in HRC can be conceptualized as an agent's best explanation for reliable sensory exchange, akin to virtual control over a partner.
  • Interactive feedback is essential for extending the user's perception-action cycle and building trust.
  • The model reinterprets traditional trust factors (competence, benevolence, vulnerability) within an active inference framework and highlights the role of user feedback, with boredom and surprise as potential indicators of reliance.

Conclusions:

  • The proposed model offers a neuroscientific basis for understanding trust in HRC, framing it as virtual control.
  • User feedback and shared behavior are critical for trust development and influence the design and acceptability of collaborative robotic systems.
  • This framework advances human-centered technology design by grounding human factors in cognitive neuroscience principles.