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

Inferring neural activity from BOLD signals through nonlinear optimization.

Vasily A Vakorin1, Olga O Krakovska, Ron Borowsky

  • 1Rotman Research Institute of Baycrest, Canada. vasily.vakorin@usask.ca

Neuroimage
|September 11, 2007
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

Exploring the interaction of reading and attention through connectivity with the frontal-eye-field.

Neuroscience·2025
Same author

Extreme signal amplitude events in neuromagnetic oscillations reveal brain aging processing across adulthood.

Frontiers in aging neuroscience·2025
Same author

Learning to build low-field MRIs for remote northern communities.

Frontiers in neuroimaging·2025
Same author

Effects of central vs. peripheral attentional-oculomotor exercise on lexical processing.

Quarterly journal of experimental psychology (2006)·2024
Same author

Atypical Brain Connectivity During Pragmatic and Semantic Language Processing in Children with Autism.

Brain sciences·2024
Same author

Musculoskeletal perturbations of deep space radiation: Assessment using a Gateway MRI.

Life sciences in space research·2024
Same journal

Segmentation of the parasagittal dura mater on multi-center 3D-FLAIR MRI.

NeuroImage·2026
Same journal

Spatial frequency channels implement a mental ruler in spatial vision.

NeuroImage·2026
Same journal

Exploring the Link Between Intravoxel Incoherent Motion Measured Brain Diffusivity During Wakefulness and Sleep Macrostructure in the Elderly.

NeuroImage·2026
Same journal

Closed-loop adaptation of transcranial magnetic stimulation intensity with electroencephalography feedback.

NeuroImage·2026
Same journal

Volumetric postmortem MRI of the medial temporal lobe in Alzheimer's disease and related disorders: methodological advances and implications for in vivo biomarker development.

NeuroImage·2026
Same journal

Neural responses to equity and inequity when receiving vicarious rewards for self and charity during adolescence.

NeuroImage·2026
See all related articles

Researchers developed an optimization method to estimate neural activity from blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals. This advanced technique accurately reconstructs neural dynamics and physiological variables from BOLD responses.

Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Biophysics

Background:

  • The blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal is an indirect measure of neural activity, posing challenges for data interpretation.
  • Mathematical models are crucial for bridging the gap between neural activity and the BOLD response, enabling the estimation of underlying neural dynamics.
  • Existing methods like local linearization (LL) filtering can be limited by linearization assumptions and may converge to suboptimal solutions.

Purpose of the Study:

  • To develop and apply an optimization-based framework for accurately estimating neural activity dynamics from BOLD fMRI signals.
  • To investigate the extended 'balloon' model for describing the biophysical processes linking neural activity to the BOLD response.
  • To compare the proposed global optimization approach with traditional linearization methods for improved accuracy and robustness.

Related Experiment Videos

Main Methods:

  • Utilized an extended 'balloon' model to simulate the conversion of neural signals into BOLD responses, incorporating hemodynamic variables.
  • Applied global optimization techniques to identify neural activity and/or biophysical parameters that minimize the discrepancy between model predictions and experimental BOLD data.
  • Explored the use of smooth basis functions to model local field potential (LFP) solutions as an alternative to spiking neural activity.

Main Results:

  • The optimization method successfully reconstructed the dynamics of neural signals, physiological variables, and biophysical parameters from BOLD responses.
  • Spiking neural activity patterns emerged as a natural mathematical solution within the model framework.
  • The inclusion of smooth basis functions enabled the modeling of local field potential (LFP) signals, offering a more generalized representation.

Conclusions:

  • Global optimization provides a robust and effective alternative to linearization for estimating neural activity from BOLD fMRI data.
  • The extended 'balloon' model, combined with optimization, accurately captures the complex relationship between neural activity and hemodynamic responses.
  • The framework offers flexibility in modeling neural activity, accommodating both spiking dynamics and smoothed representations like LFPs.