[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-446129-105":59,"doc-detail-446129-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","criticality-and-increased-intrinsic-neural-timescales-in-stroke","Criticality and increased intrinsic neural timescales in stroke","","Stroke disrupts brain function beyond focal lesions, reshaping multiscale temporal dynamics required for information processing. The study examined intrinsic neural timescales (INT) and long-range temporal correlations using longitudinal fMRI from 15 ischemic stroke patients over six months, compared with age-matched controls. Results show prolonged INT across multiple cortical regions, persisting through recovery and stronger in patients with poor outcomes, notably in cognitive control networks. Computational modeling links INT prolongation to heightened neuronal excitability and a shift toward criticality, supporting INT and long-range correlations as biomarkers for functional recovery and guiding targeted neurorehabilitation.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/criticality-and-increased-intrinsic-neural-timescales-in-stroke/446129/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/criticality-and-increased-intrinsic-neural-timescales-in-stroke/446129.png","ImageObject",300,407,{"name":92,"@type":93},"Jordan Avery","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-30","2026-09-29",true,{"@type":102,"interactionType":103,"userInteractionCount":39},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What does the paper investigate in relation to stroke?","Question",{"text":112,"@type":113},"It investigates intrinsic neural timescales (INT) and long-range temporal correlations after ischemic stroke, focusing on how stroke alters temporal dynamics across recovery.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were INT and related dynamics measured?",{"text":117,"@type":113},"INT was derived from the autocorrelation function of neural signals, using decay properties to quantify temporal integration windows and relate them to criticality concepts.",{"name":119,"@type":110,"acceptedAnswer":120},"What were the main findings about INT in stroke patients?",{"text":121,"@type":113},"Stroke patients showed significantly prolonged INT in multiple cortical regions, and these dynamic changes persisted through recovery, with stronger effects in patients with poor outcomes, especially in cognitive control networks.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},446129,1790857424,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":39,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},1099523882367,"https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc","npj | systems biology and applications Article  \nPublished in partnership with the Systems Biology Institute  \n[https://doi.org/10.1038/s41540-025-00626-7](https://doi.org/10.1038/s41540-025-00626-7)  \nCriticality and increased intrinsic neural timescales in stroke  \n Check for updates  \n\n| Kaichao Wu1,2, Beth Jelfs3, Qiang Fang4  & Leonardo L. Gollo1,2  |  |\n| --- | --- |\n| Stroke disrupts brain function beyond focal lesions, altering multiscale temporal dynamics essential for information processing. We investigated intrinsic neural timescales (INT) and other properties of long-range temporal correlations, using longitudinal fMRI data from 15 ischemic stroke patients across 6 months, and compared them to age-matched controls. Results show that stroke patients exhibited significantly prolonged INT in multiple cortical regions, reflecting slowed temporal dynamicsand disrupted hierarchy. These dynamic changes persisted through recovery and were more pronounced in patients with poor outcomes, especially within cognitive control networks. Computational modeling suggested that stroke-induced INT prolongation driven by heightened neuronal excitability reflects a dynamic shift towards criticality. Our findings position long-range temporal correlations and INT as potential biomarkers for monitoring and predicting functional recovery. This framework provides a novel perspective on stroke-induced brain changes and suggests avenues for targeted neurorehabilitation using interventions aiming at restoring intrinsic temporal dynamics. |  |\n| The human brain operates through complex dynamics that enable flexible cognition, efficient information processing, and adaptive responses to the environment1–5. These dynamics emerge from interactions between neural populations and are crucial for maintaining a balance between stability and flexibility in brain function6. As a fundamental property of the dynamics of brain regions, intrinsic neural timescales(INT)reflect the temporal window over which neural activity is integrated2,3,7,8. Alterations in INT have been observed across various conditions, including temporal lobe epilepsy9, 10, Alzheimer’s disease11, and Parkinson’s disease12, highlighting its potential asa biomarker for disrupted neural dynamics and functional impairments. INT provides valuable insights into how neural architecture shapes functional behavior and information processing8, 13, and represents a critical dynamical feature linking brain structure and function. Altered INT are often related14 or caused by alterations in gray matter volume15, reflecting structural and functional changes in the brain, thereby serving as a bridge between anatomical alterations and dynamic neural processes.\u003Cbr>Despite these recent advancesin our understanding ofINT indifferent conditions, its role in stroke remains unexplored. As stroke typically causes substantial structural damage to the brain, INT can be a relevant tool to reveal critical changes in brain dynamics. Stroke can result in localized lesions and disruptions to white matter integrity, leading to widespread functional impairments, including deficits in motor control, cognitive | processes, and sensory integration16–18. While significant progress has been made in understanding post-stroke atypical temporal dynamics in neural activity through studies of network reorganization19–21, functional connectivity22–24, and network efficiency25, the specific impact of stroke lesions on INT and their role in brain function and recovery remains unclear.\u003Cbr>Furthermore, INT is derived from the autocorrelation function (ACF) ofa neural signal and is measured by its decayproperties3, 15,26,27. Aslow decay of ACF typically occurs at a critical point and is known in the literature as critical slowing down6,28–31. In practical terms, this means that INT is maximizedata critical point15 andvarious computational properties are also optimized around the critical state6,28. This concept of criticality provides a powerful f","cbCaivBV7n8ZuSeR","https://ap.wps.com/l/cbCaivBV7n8ZuSeR","pdf",2989385,13,"English","# Introduction\n## Intrinsic neural timescales (INT) and criticality\n## Post-stroke temporal dynamics and the gap\n## Measuring INT via autocorrelation and linking to critical points\n# Methods\n## Participants and clinical information\n## fMRI design and longitudinal assessment","[{\"question\":\"What does the paper investigate in relation to stroke?\",\"answer\":\"It investigates intrinsic neural timescales (INT) and long-range temporal correlations after ischemic stroke, focusing on how stroke alters temporal dynamics across recovery.\"},{\"question\":\"How were INT and related dynamics measured?\",\"answer\":\"INT was derived from the autocorrelation function of neural signals, using decay properties to quantify temporal integration windows and relate them to criticality concepts.\"},{\"question\":\"What were the main findings about INT in stroke patients?\",\"answer\":\"Stroke patients showed significantly prolonged INT in multiple cortical regions, and these dynamic changes persisted through recovery, with stronger effects in patients with poor outcomes, especially in cognitive control networks.\"}]","Criticality and increased intrinsic neural timescales in stroke | PDF",1790714240,33]