{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T07:55:44Z","timestamp":1773820544410,"version":"3.50.1"},"reference-count":52,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T00:00:00Z","timestamp":1773792000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Hum. Neurosci."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Robot-assisted training (RAT) exhibits inconsistent efficacy in post-stroke upper limb rehabilitation, with its underlying neural mechanisms remaining unclear. This study aimed to investigate how different therapy modes modulate cerebral activation strategies in distinct subgroups of stroke patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We utilized functional near-infrared spectroscopy (fNIRS) to investigate differences in cortical activation strategies, specifically the response sensitivity to various robotic training modes, by stratifying forty-one patients based on functional level, disease chronicity, and hemiplegic side. In a single session, each participant underwent four RAT modes (Passive, Assistive-active, Active, and Mirror) while a 48-channel fNIRS system monitored cortical activation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Our results revealed no statistically significant differences in global mean activation intensity between any of the subgroups (\n                      <jats:italic>p<\/jats:italic>\n                      &amp;gt; 0.05). Instead, the core finding was a clear dichotomy in neural strategy: low-function, subacute, and left-hemiplegia groups were highly \u201cmode-sensitive,\u201d exhibiting significant changes in brain activation across different training modes (e.g., Active vs. Mirror,\n                      <jats:italic>p<\/jats:italic>\n                      &amp;lt; 0.05). Conversely, high-function, chronic, and right-hemiplegia groups were \u201cmode-consolidated,\u201d demonstrating a stable activation pattern with almost no significant differences among the active modes.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>We conclude that the core neural mechanism of post-stroke recovery is characterized not by simple changes in activation intensity, but by a strategic evolution from a flexible, cue-dependent \u201cmode-sensitive\u201d state to a more automated \u201cmode-consolidated\u201d state. This distinction provides a robust neurophysiological rationale for personalizing rehabilitation, enabling clinicians to strategically match therapeutic stimuli to a patient's specific neural profile\u2014applying diversified training to \u201cmode-sensitive\u201d patients and high-load challenges to \u201cmode-consolidated\u201d patients\u2014to break through rehabilitation plateaus.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fnhum.2026.1767418","type":"journal-article","created":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T06:56:09Z","timestamp":1773816969000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Modulation of cerebral activation strategies by training mode in stratified stroke cohorts: an fNIRS study"],"prefix":"10.3389","volume":"20","author":[{"given":"Mengjian","family":"Qu","sequence":"first","affiliation":[{"name":"Department of Rehabilitation, Hengyang Medical School, The 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