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

Assessment of Diffusion and Perfusion

Assessment of Diffusion and Perfusion

Understanding and evaluating diffusion and perfusion is critical in assessing a patient's respiratory and circulatory health. These processes play key roles in maintaining the body's internal environment, ensuring that tissues receive adequate oxygen while waste products are efficiently removed.
The Role of Diffusion in Respiration
Diffusion is the process by which molecules move from an area of higher concentration to an area of lower concentration. In the respiratory system, this principle...

You might also read

Related Articles

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

Sort by

Same author

Flexible Prescribed-Time Optimal Control With Adaptive State-Input Constraint Bounds via Actor-Critic Learning.

IEEE transactions on neural networks and learning systems·2026

Same author

Toward Comprehensive Information-Theoretic Multi-View Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same author

Functional connectivity-based classification and subtyping of major depression for precision mental health: An ensemble graph neural network approach.

PLOS digital health·2026

Same author

DAMind: Zero-Shot Visual Cross-Domain Alignment and Representation for EEG Decoding.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same author

Beyond depression symptoms: the default mode network as a predictor of antidepressant response.

Npj mental health research·2026

Same author

Fast Multi-view Discrete Clustering via Spectral Embedding Fusion.

IEEE transactions on pattern analysis and machine intelligence·2025

Same journal

CLASH-CTTA: Class-Wise Shift-Aware Hierarchical Continual Test-Time Adaptation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same journal

Voxel-based Point Cloud Geometry Compression with Space-to-Channel Context.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same journal

RIGI: Rectifying Image-to-3D Generation Inconsistency via Uncertainty-Aware Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same journal

DA-Cal: Towards Cross-Domain Calibration in Semantic Segmentation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same journal

Multi-Dimensional Quality Assessment for Single-Image-to-3D Contents: Dataset and Model.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same journal

Enhancing Underwater Light Field Images via Global Geometry-Aware Diffusion Process.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 11, 2026

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

NeuralDiffuser: Neuroscience-inspired Diffusion Guidance for fMRI Visual Reconstruction.

Haoyu Li, Hao Wu, Badong Chen

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|March 3, 2025

Summary

This summary is machine-generated.

This study introduces NeuralDiffuser, a new method for reconstructing visual stimuli from brain activity (fMRI). It improves image detail and consistency, overcoming limitations of current diffusion models.

More Related Videos

DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions

DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions

Published on: August 26, 2014

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

Published on: August 11, 2016

Related Experiment Videos

Last Updated: May 11, 2026

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions

DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions

Published on: August 26, 2014

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

Published on: August 11, 2016

Area of Science:

Neuroscience
Computer Vision
Machine Learning

Background:

Reconstructing visual stimuli from functional Magnetic Resonance Imaging (fMRI) offers insights into brain activity.
Current stable diffusion models struggle with accurate reconstruction of fine details and exhibit output variability.

Purpose of the Study:

To develop a novel method that enhances the fidelity and consistency of visual stimuli reconstruction from fMRI data.
To address the limitations of top-down processing in diffusion models by incorporating bottom-up perceptual cues.

Main Methods:

Proposed NeuralDiffuser, integrating primary visual feature guidance (gradients) into diffusion models.
Developed a novel guidance strategy for consistent reconstruction aligned with original images.
Utilized the Natural Senses Dataset (NSD) for extensive experimental validation.

Main Results:

NeuralDiffuser achieves superior semantic coherence and detail fidelity compared to baseline and state-of-the-art methods.
The proposed guidance strategy ensures consistent outputs, reducing variability.
Qualitative and quantitative results demonstrate significant advancements.

Conclusions:

NeuralDiffuser effectively reconstructs visual stimuli from fMRI with improved detail and consistency.
The integration of bottom-up perception enhances the capabilities of diffusion models for neuroscientific applications.
This work advances the field of brain activity decoding and visual reconstruction.