Multiple event segmentation mechanisms in the human brain.

Overview

1. Psychological and Brain Sciences, Washington University in St. Louis Saint Louis United States

Abstract

The human brain segments continuous experience into discrete events, with theoretical accounts proposing two distinct mechanisms: creating boundaries at points of high prediction error (mismatch between expected and observed information) and high prediction uncertainty (reduced precision in predictions). Using fMRI and computational modeling, we investigated the neural correlates of error-driven and uncertainty-driven boundaries. We developed computational models that generate boundaries based on prediction error or prediction uncertainty, and examined how both types of boundaries, and human-identified boundaries, related to fMRI pattern shifts and evoked responses. Multivariate analysis revealed a specific temporal sequence of neural pattern changes around human boundaries: early pattern shifts in anterior temporal regions (–11.9 s), followed by shifts in parietal areas (–4.5 s), and subsequent whole-brain pattern stabilization (+11.8 s). The core of this dynamic response was associated with both error-driven and uncertainty-driven boundaries. Critically, both error- and uncertainty-driven boundaries were associated with unique pattern shifts. Error-driven boundaries were associated with early pattern shifts in ventrolateral prefrontal areas, followed by pattern stabilization in prefrontal and temporal areas. Uncertainty-driven boundaries were linked to shifts in parietal regions within the dorsal attention network, with minimal subsequent stabilization. In addition, within the core regions responsive to both types of boundaries, the timing differed significantly. These findings provide evidence for two overlapping brain networks that maintain and update representations of the environment, controlled by two distinct prediction quality signals: prediction error and prediction uncertainty.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

The paper links to its data and to no code of its authors: see the Data section.

The paper's code and data availability statement is in the Data section.

Tracing map

A tracing map links a paper to the code its authors published: this paper has none, so it has no map.

Data

Datasets cited

• openneuro:ds005551, at OpenNeuro; found in “Data availability”

Data availability

BIDS data for this project can be found at https://openneuro.org/datasets/ds005551 under sub <participant_id> directories. All the data and analysis scripts used for this project can be found at https://openneuro.org/datasets/ds005551 under derivatives/scripts/ directory .

The following dataset was generated:

BezdekM ZacksJ NguyenTT EtzelJ 2025Testing neural mechanisms of event segmentation with fMRIOpenNeurods005551

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 4 authors, 4 keywords, 11 MeSH terms, 2 funders, 65 references, 8 RRIDs.

Cite

This paper

Nguyen, T. T., Etzel, J. A., Bezdek, M. A., & Zacks, J. M. (2026). Multiple event segmentation mechanisms in the human brain. eLife, 14, RP107955. https://doi.org/10.7554/elife.107955

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:10.1162/imag_a_00432 [code]

The neural basis of event segmentation: Stable features in the environment are reflected by neural states.

Journal: Imaging neuroscience (Cambridge, Mass.)

In common: 15 references

[2] doi:10.1093/cercor/bhaf114 [code]

Neural state changes during movie watching relate to episodic memory in younger and older adults.

Journal: Cerebral cortex (New York, N.Y. : 1991)

In common: 14 references

[3] doi:10.1038/s41467-023-36805-5 [code]

Flexible reuse of cortico-hippocampal representations during encoding and recall of naturalistic events.

Journal: Nature communications

In common: 17 references

[4] doi:10.7554/elife.77430 [code]

A partially nested cortical hierarchy of neural states underlies event segmentation in the human brain.

Journal: eLife

In common: 12 references

[5] doi:10.1371/journal.pbio.3002934 [code]

Distinct patterns of connectivity with the motor cortex reflect different components of sensorimotor learning.

Journal: PLoS biology

In common: 17 references

[6] doi:10.1093/cercor/bhad106 [code]

Individual differences in neural event segmentation of continuous experiences.

Journal: Cerebral cortex (New York, N.Y. : 1991)

In common: 12 references

[7] doi:10.1523/eneuro.0385-25.2025

Neural Signatures of Engagement and Event Segmentation during Story Listening in Background Noise.

Journal: eNeuro

In common: 12 references

[8] doi:10.1016/j.celrep.2026.117033 [code]

Human superior colliculus pathways represent the form and motion of looming objects.

Journal: Cell reports

In common: 16 references

[9] doi:10.1016/j.neuroimage.2022.119670 [code]

L-DOPA enhances neural direction signals in younger and older adults.

Journal: NeuroImage

In common: 16 references

[10] doi:10.1016/j.neuroimage.2023.120109 [code]

Benchmarking explanation methods for mental state decoding with deep learning models.

Journal: NeuroImage

In common: 16 references

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion: code errors and mismatches between the code and the paper about this paper and its code, from readers and its authors, beside the paper and its tracing map.

Reproductions: reports from readers who ran the authors' code and did not get the paper's result, what they ran, with which environment, commit and data.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.