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Inferring occluded projectile motion changes connectivity within a visuo-fronto-parietal network.

Gabrielle Aude Zbären¹, Manu Kapur², Sarah Nadine Meissner³

¹Neural Control of Movement Lab, Department of Health Science and technology, ETH Zurich, Zurich, Switzerland. gabrielle.zbaeren@hest.ethz.ch.

Brain Structure & Function

|June 24, 2024

Summary

This summary is machine-generated.

Predicting object motion involves brain networks. This study reveals functional connections between early visual and frontoparietal areas during physical inference, suggesting top-down control for predicting trajectories.

Keywords:

Dynamic causal modelling Effective connectivity Functional connectivity Physical inference Visual imagery fMRI

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Area of Science:

Cognitive Neuroscience
Neuroimaging
Human Brain Function

Background:

Anticipating moving object behavior is crucial for daily actions, relying on mental simulations.
Previous research implicates frontoparietal and early visual areas in physical inference.
Neural connectivity patterns during intuitive physical inference are not well understood.

Purpose of the Study:

To identify brain regions functionally connected with early visual areas during physical inference.
To investigate changes in effective connectivity within this network during trajectory prediction.

Main Methods:

Functional magnetic resonance imaging (fMRI) was used.
Participants inferred parabolic trajectories of occluded falling objects under Newtonian physics.
Dynamic causal modeling (DCM) analyzed effective connectivity changes.

Main Results:

Early visual areas showed functional connectivity with parietal and premotor regions during occluded trajectory inference.
Dynamic causal modeling revealed altered effective connectivity within a parieto-premotor network.
This network likely drives top-down, internally generated activity in early visual areas.

Conclusions:

Findings illuminate the interaction between early visual and frontoparietal regions in physical inference.
This research advances understanding of the neural mechanisms for predicting physical outcomes.
The parieto-premotor network plays a key role in predictive visual processing.