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

Decision Making: Traditional Method01:14

Decision Making: Traditional Method

5.6K
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
5.6K
Association Areas of the Cortex01:21

Association Areas of the Cortex

9.9K
Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...
9.9K
Decision Making01:20

Decision Making

1.1K
Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
1.1K
Reason and Intuition01:37

Reason and Intuition

7.6K
The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
7.6K
Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

284
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...
284
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

441
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
441

You might also read

Related Articles

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

Sort by
Same author

Amine-functionalized oyster shell waste for hexavalent chromium removal and phosphate recovery.

Bioresource technology·2026
Same author

Neural Spelling: A Spell-Based BCI System for Language Neural Decoding.

IEEE transactions on bio-medical engineering·2026
Same author

Solvent-assisted sensing ability of <sup>19</sup>F reporter in simultaneous discrimination and quantification of proline and 4-hydroxyproline isomers.

Talanta·2026
Same author

Deciphering Uncoupling Proteins in Cellular Homeostasis and Metabolic Health.

International journal of biological sciences·2026
Same author

A Hybrid Covert Attention-Augmented Motor Imagery Paradigm for Brain-Computer Interfaces.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026
Same author

Requirements for Human Cerebral Organoids.

Cell proliferation·2026
Same journal

Synaptic micromechanics and brain softening as a mechanobiological hypothesis for Alzheimer's disease.

Frontiers in neuroscience·2026
Same journal

The relationship between healthy sleep patterns and the risk of scoliosis: a large prospective cohort study.

Frontiers in neuroscience·2026
Same journal

Dynamic functional reorganization in post-stroke aphasia: a state-of-the-art fMRI review from disease evolution to intervention.

Frontiers in neuroscience·2026
Same journal

Correction: Case Report: A possible novel adult-onset, progressive MAO-A hypofunction.

Frontiers in neuroscience·2026
Same journal

Respiratory modulation of neurophysiology and symptoms in athletes with sports-related concussion: a randomized crossover trial.

Frontiers in neuroscience·2026
Same journal

Impact of C-reactive protein-triglyceride-glucose and systemic immune-inflammation indices on obstructive sleep apnea in older adults with depression.

Frontiers in neuroscience·2026
See all related articles

Related Experiment Video

Updated: Feb 27, 2026

High-definition Transcranial Direct Current Stimulation over Right Dorsolateral Prefrontal Cortex to Enhance Metacognitive Sensitivity
06:11

High-definition Transcranial Direct Current Stimulation over Right Dorsolateral Prefrontal Cortex to Enhance Metacognitive Sensitivity

Published on: September 26, 2025

1.1K

Fuzzy Decision-Making Fuser (FDMF) for Integrating Human-Machine Autonomous (HMA) Systems with Adaptive Evidence

Yu-Ting Liu1, Nikhil R Pal2, Amar R Marathe3

  • 1Faculty of Engineering and Information Technology, Center for Artificial Intelligence, University of Technology SydneySydney, NSW, Australia.

Frontiers in Neuroscience
|July 6, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces a human-machine autonomous system that combines brain-computer interface (BCI) and computer vision for enhanced target recognition. The system effectively fuses human and machine decisions, improving performance in rapid serial visual presentation tasks.

Keywords:
Brain-Computer Interface (BCI)Dempster-Shafer TheoryFuzzy Decision-Making Fuser (FDMF)Human-Machine Autonomous (HMA) SystemInformation Fusion

More Related Videos

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

1.7K

Related Experiment Videos

Last Updated: Feb 27, 2026

High-definition Transcranial Direct Current Stimulation over Right Dorsolateral Prefrontal Cortex to Enhance Metacognitive Sensitivity
06:11

High-definition Transcranial Direct Current Stimulation over Right Dorsolateral Prefrontal Cortex to Enhance Metacognitive Sensitivity

Published on: September 26, 2025

1.1K
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

1.7K

Area of Science:

  • Neuroscience
  • Artificial Intelligence
  • Human-Computer Interaction

Background:

  • Brain-computer interfaces (BCIs) are evolving from restorative patient-oriented systems to auxiliary tools augmenting human capabilities.
  • Human variability (fatigue, stress) presents a significant challenge for BCI performance.
  • Autonomous systems offer potential to enhance BCI performance and mitigate human variability.

Purpose of the Study:

  • To propose and evaluate a human-machine autonomous (HMA) system for augmenting human capabilities.
  • To integrate a rapid serial visual presentation (RSVP) BCI with computer vision for improved target recognition.
  • To address human variability by dynamically aggregating human and machine decisions under uncertainty.

Main Methods:

  • Developed a human-machine autonomous (HMA) system integrating an RSVP BCI with computer vision.
  • Employed a fuzzy decision-making fuser (FDMF) for adaptive, evidence-based inference.
  • Aggregated decisions from human brain activity and autonomous computer vision agents, incorporating uncertainty.

Main Results:

  • The HMA system effectively fused decisions from human brain activity and computer vision techniques.
  • Experimental results demonstrated improved overall performance on the RSVP recognition task.
  • The FDMF provided a natural adaptive framework for integrating uncertain evidence.

Conclusions:

  • The proposed HMA system with FDMF successfully enhances target recognition in RSVP tasks.
  • Integrating autonomous systems with BCIs offers significant potential for augmenting human performance.
  • Collaborative decision-making in HMA systems can achieve superior and more efficient outcomes than individual agents.