How Low-Frequency Neural Activity Structures Language in Time.
The 7 matches
- [1] § MATERIALS AND METHODS › Source-Level Analysis ↔ MATLAB/tcrc_sourceReconstruction_fixedOri.m, lines 142–232 · score 0.95 · unit noise gain, depth bias, Hilbert transformed, source reconstruction, source space, LCMV
- [2] § MATERIALS AND METHODS › Source-Level Analysis ↔ MATLAB/tcrc_sourceStatistic_templategrid.m, lines 72–93 · score 0.79 · MNI space, individual space, individual MRI, source reconstruction, warped, template
- [3] § MATERIALS AND METHODS › Sensor-Level Analysis ↔ MATLAB/tcrc_sourceReconstruction_fixedOri.m, lines 142–232 · score 0.70 · inter trial phase, Hilbert transform, coherence, activity, filtered, window
- [4] § MATERIALS AND METHODS › Electrophysiological Analysis ↔ MATLAB/tcrc_artefacts.m, lines 1–48 · score 0.68 · SQUID jump, artifact rejection, segmented, rejected, channel, FieldTrip
- [5] § MATERIALS AND METHODS › Sensor-Level Analysis ↔ R/tcrc_regression_ITPC_ERF.Rmd, lines 76–167 · score 0.64 · baseline model, Bonferroni corrected, intercepts, mixed, timepoint, magnetometers
- [6] § MATERIALS AND METHODS › Source-Level Analysis ↔ MATLAB/tcrc_prepareSouce.m, lines 162–189 · score 0.60 · head surface, MNE, vertices, BEMs, MEG
- [7] § MATERIALS AND METHODS › Sensor-Level Analysis ↔ MATLAB/tcrc_itpc_delta.m, lines 63–90 · score 0.53 · inter trial phase, coherence, signal, duration, ITPC
Paper
Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC
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The authors' code
MATLAB · 232 lines · 9.6 KB · no license · 2 matches
tcrc_sourceReconstruction_fixedOri.m, no license · at the source
Overview
- Max Planck Research Group Language Cycles, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Methods and Development Group Brain Networks, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Phoniatrics and Pediatric Audiology, University Hospital Münster, Münster, Germany
Abstract
The integration of sensory information in humans may be confined to a time window of 2–3 s. In language, this time window constrains the grouping of words into multi-word chunks, required for comprehension. Chunk boundaries are known to elicit a characteristic event-related brain potential, the Closure Positive Shift (CPS). The likelihood of a CPS increases with the duration of the chunk. In the frequency-domain, boundaries have been associated with neural oscillations in the delta band (<4 Hz). Here, we assessed whether the pace for chunking might be imposed by electrophysiological processing cycles of the brain with phase-locking of such activity underlying the CPS. We recorded participants’ magnetoencephalogram while they listened to globally ambiguous sentences allowing for two alternative ways of chunking. Chunking was not externally imposed, but the temporal limits of integration windows influenced chunk termination. Phase-locking of narrow-band low-frequency neural activity (i.e., <4 Hz) at the boundaries of multi-word chunks increased with sentence duration, and covaried with event-related fields. Behavioral data further indicate subtle interindividual differences in the duration of the integration time window. Source localization revealed neural generators in bilateral posterior temporal and right anterior regions. The brain appears to project duration-limited integration windows onto the incoming auditory speech signal, thus structuring language comprehension in time.
Reproduced under the paper's license (CC BY), from the paper cited above.
Repository
Its files are read in the Code ↔ Paper reader above, with 7 matches between paragraphs and lines of code.
OSF h3c9j
Availability: 1 check, the latest on 28 September 2026: the link answers (HTTP 200)
- 28 September 2026: the link answers (HTTP 200)
18 files, to read at the source
This repository has no license: its authors keep all rights. Read it at the source.
- MATLAB/
createConnectivityMatrix — MATLAB, 63 lines, not shown here.m - MATLAB/
tcrc_artefacts.m — MATLAB, 130 lines, 1 match, not shown here - MATLAB/
tcrc_checkArtfRej.m — MATLAB, 77 lines, not shown here - MATLAB/
tcrc_erf_broadband.m — MATLAB, 258 lines, not shown here - MATLAB/
tcrc_erf_delta.m — MATLAB, 245 lines, not shown here - MATLAB/
tcrc_hp.m — MATLAB, 100 lines, not shown here - MATLAB/
tcrc_ica.m — MATLAB, 55 lines, not shown here - MATLAB/
tcrc_ica_rm_comps.m — MATLAB, 95 lines, not shown here - MATLAB/
tcrc_itpc_delta.m — MATLAB, 302 lines, 1 match, not shown here - MATLAB/
tcrc_prepareSouce.m — MATLAB, 234 lines, 1 match, not shown here - MATLAB/
tcrc_removedTrials_acros — MATLAB, 47 lines, not shown heresBlocks.m - MATLAB/
tcrc_secondArtfRemoval.m — MATLAB, 112 lines, not shown here - MATLAB/
tcrc_segmentation.m — MATLAB, 67 lines, not shown here - MATLAB/
tcrc_sourceReconstructio — MATLAB, 232 lines, 2 matches, not shown heren_fixedOri.m - MATLAB/
tcrc_sourceStatistic_tem — MATLAB, 460 lines, 1 match, not shown hereplategrid.m - R/
tcrc_regression_ITPC_ERF — R, 661 lines, 1 match, not shown here.Rmd - R/
tcrc_singleTrialBehav.Rm — R, 71 lines, not shown hered - README.txt — Text, 32 lines, not shown here
The paper's code and data availability statement is in the Data section.
Tracing map
Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.
What the map holds:
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- 7 matches between paragraphs of the paper and lines of the code (method lexical-v1);
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Data
Datasets cited
- zenodo:18742644 — at Zenodo; found in “DATA AVAILABILITY STATEMENT”
Data availability statement
Raw data cannot be made publicly available due to ethical permissions and legal restrictions. Aggregated data to evaluate the conclusions in the paper are available on Zenodo (https://
Reproduced under the paper's license (CC BY), from the paper cited above.
Versions
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Version 1, 28 September 2026: the first record
Recorded: type, language, journal, volume, pages, dates, 3 authors, 5 keywords, 1 funder, 110 references.
Cite
This paper
Henke, L., Maess, B., & Meyer, L. (2026). How Low-Frequency Neural Activity Structures Language in Time. Neurobiology of language (Cambridge, Mass.), 7, NOL.a.249. https://
BibTeX
@article{henke2026how,
author = {Henke, Lena and Maess, Burkhard and Meyer, Lars},
title = {{How Low-Frequency Neural Activity Structures Language in Time}},
journal = {Neurobiology of language (Cambridge, Mass.)},
year = {2026},
month = may,
volume = {7},
pages = {NOL.a.249},
publisher = {MIT Press},
issn = {2641-4368},
doi = {10.1162/
url = {https://
pmid = {42137739},
pmcid = {PMC13171203}
}
RIS
TY - JOUR
AU - Henke, Lena
AU - Maess, Burkhard
AU - Meyer, Lars
TI - How Low-Frequency Neural Activity Structures Language in Time
T2 - Neurobiology of language (Cambridge, Mass.)
J2 - Neurobiol Lang (Camb)
PY - 2026
DA - 2026/
VL - 7
SP - NOL.a.249
SN - 2641-4368
PB - MIT Press
DO - 10.1162/
UR - https://
LA - en
ER -
CSL-JSON
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