{"title":"A holistic perspective on noninvasive brain-computer interfaces.","authors":"Yidan Ding, Joshua Kosnoff, Bin He","doi":"10.1016/j.tins.2026.04.009","DOIUrl":null,"url":null,"abstract":"<p><p>Brain-computer interfaces (BCIs) decode neural activity to enable direct communication with external devices. This process consists of three modules: signal acquisition, signal processing, and output translation. While invasive BCIs have demonstrated sophisticated and intuitive capabilities, their reliance on surgical implantation limits widespread use. Noninvasive BCIs, in contrast, are more broadly applicable but have traditionally been constrained by low spatial resolution and suboptimal signal quality. Emerging methodological advances are beginning to overcome these limitations. In this review, we examine recent progress in noninvasive BCIs, focusing on neuromodulation-paired BCIs for signal enhancement, deep neural network-based signal processing approaches, and expanded applications through robotic integration. Together, these parallel developments are driving the emergence of more robust, intuitive, and adaptive BCI systems for human use.</p>","PeriodicalId":23325,"journal":{"name":"Trends in Neurosciences","volume":" ","pages":"566-581"},"PeriodicalIF":15.7000,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13232709/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trends in Neurosciences","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.tins.2026.04.009","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/5/25 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Brain-computer interfaces (BCIs) decode neural activity to enable direct communication with external devices. This process consists of three modules: signal acquisition, signal processing, and output translation. While invasive BCIs have demonstrated sophisticated and intuitive capabilities, their reliance on surgical implantation limits widespread use. Noninvasive BCIs, in contrast, are more broadly applicable but have traditionally been constrained by low spatial resolution and suboptimal signal quality. Emerging methodological advances are beginning to overcome these limitations. In this review, we examine recent progress in noninvasive BCIs, focusing on neuromodulation-paired BCIs for signal enhancement, deep neural network-based signal processing approaches, and expanded applications through robotic integration. Together, these parallel developments are driving the emergence of more robust, intuitive, and adaptive BCI systems for human use.
期刊介绍:
For over four decades, Trends in Neurosciences (TINS) has been a prominent source of inspiring reviews and commentaries across all disciplines of neuroscience. TINS is a monthly, peer-reviewed journal, and its articles are curated by the Editor and authored by leading researchers in their respective fields. The journal communicates exciting advances in brain research, serves as a voice for the global neuroscience community, and highlights the contribution of neuroscientific research to medicine and society.