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Related Experiment Video

Updated: May 6, 2026

Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study

Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study

Published on: July 21, 2021

UltraFast Layer-Resolved Encoding (uFLARE) functional MRI deciphers bidirectional signaling from spontaneous

Joana Carvalho^1,2, Francisca F Fernandes³, Mafalda Valente³

¹Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal. joana.carvalho@fpce.uc.pt.

Nature Communications

|May 4, 2026

Summary

This summary is machine-generated.

New brain imaging technique uFLARE distinguishes bottom-up and top-down signals. It reveals distinct layer-specific connectivity patterns, showing bottom-up signals are not solely stimulus-driven and identifying injury-induced network changes.

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Area of Science:

Neuroscience
Brain Imaging
Systems Neuroscience

Background:

Understanding information flow directionality in cortical circuits is crucial for brain dynamics, learning, and neuroplasticity.
Current noninvasive methods struggle to differentiate bottom-up from top-down signals across extensive brain networks, including deep regions.

Purpose of the Study:

To introduce UltraFast Layer-Resolved Encoding (uFLARE), a novel method combining ultrafast-fMRI and a Layer-based Connective Field (lCF) model.
To disentangle bottom-up from top-down signaling in the brain using the developed uFLARE technique.
To investigate layer-specific connectivity patterns and their role in information integration during spontaneous brain activity.

Main Methods:

Utilized ultrafast-fMRI combined with a Layer-based Connective Field (lCF) model.
Analyzed layer-specific connectivity patterns to differentiate signal directionality.
Examined spontaneous brain activity and its layer-specific organization.

Main Results:

The lCF size, an indicator of information integration, effectively differentiates bottom-up and top-down activity.
Distinct layer-specific connectivity profiles were identified: bottom-up follows an inverted U-shape (peaking in layer IV), while top-down exhibits a U-shape (peaking in layers I and VI).
These findings challenge the notion that bottom-up signals are exclusively stimulus-driven and reveal injury-induced reorganization, such as LGN bypassing V1.

Conclusions:

uFLARE successfully disentangles bottom-up and top-down signaling, offering new insights into brain dynamics.
Layer-specific connectivity patterns during spontaneous activity reveal distinct bottom-up and top-down information flow.
The study highlights potential network reorganization after injury and provides a powerful tool for future neuroscience research.