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 Experiment Videos

Frequency change detection in human auditory cortex.

P May1, H Tiitinen, R J Ilmoniemi

  • 1Department of Mathematics, King's College London, Strand, UK. may@cc.helsinki.fi

Journal of Computational Neuroscience
|May 20, 1999
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Observation of a mixed close-packed structure in superionic water.

Nature communications·2025
Same author

Education as Risk Factor of Mild Cognitive Impairment: The Link to the Gut Microbiome.

The journal of prevention of Alzheimer's disease·2024
Same author

Sociodemographic disparities and potential biases in persistent pain estimates: Findings from 5 waves of the Irish Longitudinal Study on Ageing (TILDA).

European journal of pain (London, England)·2023
Same author

Bacteria in the healthy equine vagina during the estrous cycle.

Theriogenology·2023
Same author

Cancer-associated mesothelial cells are regulated by the anti-Müllerian hormone axis.

Cell reports·2023
Same author

Alterations of oral microbiota and impact on the gut microbiome in type 1 diabetes mellitus revealed by integrated multi-omic analyses.

Microbiome·2022
Same journal

Hierarchical learning creates invariant schema within plastic neural networks.

Journal of computational neuroscience·2026
Same journal

Intrinsic chaos control in cortical circuits: A minimal E-I-M rate model for primary visual cortex.

Journal of computational neuroscience·2026
Same journal

Modeling developmental spiking behavior driven by ionic current dynamics of mouse and human inner hair cells using a calcium-enhanced Izhikevich framework.

Journal of computational neuroscience·2026
Same journal

A biophysically grounded model of glutamatergic synaptic transmission integrating glutamate transport, receptor kinetics, and electrotonic effects.

Journal of computational neuroscience·2026
Same journal

When can neuronal activity-dependent homeostatic plasticity maintain circuit-level properties?

Journal of computational neuroscience·2026
Same journal

A charge conservative finite volume discretization of the Hodgkin-Huxley model.

Journal of computational neuroscience·2026
See all related articles

This study models auditory change detection, revealing that post-stimulus inhibition, specifically adaptation and lateral inhibition, explains the mismatch negativity (MMN) response. These findings offer insights into auditory cortex function.

Area of Science:

  • Neuroscience
  • Auditory Perception
  • Computational Neuroscience

Background:

  • Auditory change detection is crucial for navigating complex soundscapes.
  • Mismatch negativity (MMN) is a preattentive electrophysiological response to auditory changes, measured via EEG and MEG.
  • Neural mechanisms underlying MMN and auditory change detection remain incompletely understood, beyond the involvement of the tonotopic auditory cortex.

Purpose of the Study:

  • To propose and test a computational model of auditory change detection.
  • To investigate the roles of post-stimulus inhibition, including adaptation and lateral inhibition, in generating MMN.
  • To explore MMN as a potential probe for stimulus feature mapping in the human auditory cortex.

Main Methods:

  • Development of a computational model of tonotopically organized auditory cortex.

Related Experiment Videos

  • Comparison of adaptation and lateral inhibition effects within the model.
  • Noninvasive electroencephalogram (EEG) and magnetoencephalogram (MEG) recordings in human subjects.
  • Presentation of auditory stimuli with varying frequency differences (small and large) to elicit MMN.

    • Main Results:

    • The model successfully predicted MMN generation based on post-stimulus inhibition.
    • Experimental data supported the model's predictions, indicating that both adaptation and lateral inhibition contribute to MMN.
    • The magnitude of MMN varied with the frequency difference between standard and deviant tones.

    Conclusions:

    • Post-stimulus inhibition, encompassing adaptation and lateral inhibition, is a key neural mechanism underlying MMN.
    • The findings validate a model of auditory change detection in the human cortex.
    • MMN may serve as a valuable tool for investigating how the auditory cortex represents stimulus features.