Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Auditory Perception

Auditory Perception

The auditory system is essential for sound perception, utilizing various critical structures. When sound waves enter the outer ear, they travel through the ear canal and cause the eardrum to vibrate. These vibrations are then transmitted to the middle ear, where three tiny bones – the malleus, incus, and stapes – amplify the sound. This amplification is crucial, as it ensures that the sound vibrations are strong enough to be conveyed to the inner ear. These vibrations then reach the...

Parallel Processing

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...

Perceiving Loudness, Pitch, and Location

Perceiving Loudness, Pitch, and Location

The human brain perceives pitch through two primary mechanisms reflected in place theory and frequency theory. Each mechanism describes how sound waves are interpreted as specific pitches by the brain, offering insights into the intricate processes of auditory perception.
Place theory, or place coding, suggests that different pitches are heard because various sound waves activate specific locations along the cochlea's basilar membrane. The brain determines the pitch of a sound by...

You might also read

Related Articles

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

Sort by

Same author

Spatiotemporal dynamics of renal distal convoluted tubule dilatation and cyst formation in nephronophthisis type 1 mice.

Renal failure·2026

Same author

Domain-aware domain-class adaptation network for motor execution to motor imagery EEG classification.

Frontiers in neuroscience·2026

Same author

Noise-Driven Feature Enhancement of High-Frequency SSVEP Through Underdamped Second-Order Stochastic Resonance Energy Transfer.

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

Same author

SCGait a novel method for person identification applied to legged robots.

Scientific reports·2026

Same author

Differential neural responses to rhythmic motion and rhythmic static auditory stimuli: An EEG and fNIRS study.

Hearing research·2026

Same author

Nonlinear Characteristics of High-Density Electroencephalography Demonstrate Differences in Neural Processing of Musical Syntax by Musicians and Nonmusicians.

Annals of the New York Academy of Sciences·2026

Search research articles

Related Experiment Video

Updated: Nov 22, 2025

A Method to Study Adaptation to Left-Right Reversed Audition

A Method to Study Adaptation to Left-Right Reversed Audition

Published on: October 29, 2018

Auditory Noise Leads to Increased Visual Brain-Computer Interface Performance: A Cross-Modal Study.

Jun Xie^1,2,3,4, Guozhi Cao¹, Guanghua Xu^1,4

¹School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China.

Frontiers in Neuroscience

|January 8, 2021

Summary

This summary is machine-generated.

Adding moderate auditory noise to visual stimuli enhances brain activity and improves brain-computer interface (BCI) performance. This cross-modal stochastic resonance (SR) boosts visual recognition accuracy and reduces processing time.

Keywords:

auditory noise brain–computer interface (BCI)cross-modal stochastic resonance functional connectivity phase synchronization steady-state motion visual evoked potential (SSMVEP)

More Related Videos

A Two-interval Forced-choice Task for Multisensory Comparisons

A Two-interval Forced-choice Task for Multisensory Comparisons

Published on: November 9, 2018

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

Published on: July 5, 2015

Related Experiment Videos

Last Updated: Nov 22, 2025

A Method to Study Adaptation to Left-Right Reversed Audition

A Method to Study Adaptation to Left-Right Reversed Audition

Published on: October 29, 2018

A Two-interval Forced-choice Task for Multisensory Comparisons

A Two-interval Forced-choice Task for Multisensory Comparisons

Published on: November 9, 2018

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

Published on: July 5, 2015

Area of Science:

Neuroscience
Biomedical Engineering
Signal Processing

Background:

Stochastic resonance (SR) theory explains noise's beneficial role in non-linear systems like the human brain.
Previous research focused on single-modal SR, but cross-modal SR has been observed across sensory systems.
Brain-computer interfaces (BCIs) offer potential for human-computer interaction, with visual BCIs being a key area of development.

Purpose of the Study:

To investigate the phenomenon of cross-modal stochastic resonance (SR) between visual and auditory systems.
To enhance the performance of a visual brain-computer interface (BCI) by applying auditory noise to visual stimuli.
To analyze the impact of auditory noise on neural activity and functional connectivity in the visual cortex.

Main Methods:

A cross-modal SR paradigm was designed by presenting visual stimuli with superimposed auditory noise.
Fast Fourier Transform (FFT) and Canonical Correlation Analysis (CCA) were employed to assess noise effects on visual responses.
Directed Transfer Function (DTF) and weighted Phase Lag Index (wPLI) were utilized to analyze functional connectivity and phase synchronization.

Main Results:

Moderate levels of auditory noise significantly enhanced periodic components in visual evoked potentials.
Auditory noise increased the activation of relevant brain areas, as indicated by flow gain maps.
wPLI analysis revealed enhanced phase synchronization between visual and auditory brain regions under noise conditions.
The cross-modal SR approach led to higher recognition accuracy and a shorter required time window for BCI operation.

Conclusions:

This study provides evidence for cross-modal stochastic resonance between the visual and auditory cortices.
Applying auditory noise to visual stimuli can effectively improve the performance of visual BCIs.
The findings suggest a novel method for optimizing BCI systems by leveraging cross-modal sensory interactions.