Haziq Rabbani, Ipsita Das, Ayan S Mandal, Thomas Nelson, Peter Hadar, Brian Hsueh, Roberto Ciordia, Brian F Coughlin, Emory Peng, Daniel R Cleary, Kelly L Collins, Ahmed M T Raslan, Ziv M Williams, Bryan D Choi, Garth Rees Cosgrove, Shadi A Dayeh, Pamela S Jones, Harmanpreet K Tiwana, Gavin P Dunn, R Mark Richardson, Wenya Linda Bi, Steven Tobochnik, Sydney S Cash, Daniel P Cahill, Angelique C Paulk
{"title":"A modular and flexible pipeline for intraoperative electrode reconstruction and localization in patients with brain lesions.","authors":"Haziq Rabbani, Ipsita Das, Ayan S Mandal, Thomas Nelson, Peter Hadar, Brian Hsueh, Roberto Ciordia, Brian F Coughlin, Emory Peng, Daniel R Cleary, Kelly L Collins, Ahmed M T Raslan, Ziv M Williams, Bryan D Choi, Garth Rees Cosgrove, Shadi A Dayeh, Pamela S Jones, Harmanpreet K Tiwana, Gavin P Dunn, R Mark Richardson, Wenya Linda Bi, Steven Tobochnik, Sydney S Cash, Daniel P Cahill, Angelique C Paulk","doi":"10.3389/fncir.2026.1814667","DOIUrl":null,"url":null,"abstract":"<p><p>Intraoperative intracranial electrophysiological recordings provide unique access to human cortical dynamics but remain difficult to translate across patients due to inconsistent localization of transient surface electrodes. Unlike chronic implantations, intraoperative electrodes are placed transiently, rarely visible on imaging, and often inconsistently documented. We present an open-source imaging pipeline, ALIGNER (Advanced Localization and Imaging Guidance for Neurosurgical Electrode Recording), designed to reconstruct intraoperative surface electrode array placements and quantitatively map neural activity to individualized anatomical and pathological substrates. By enabling anatomical localization of these electrodes, this framework supports systematic analysis of spatial gradients in neural activity relative to pathological tissue. We developed a multimodal reconstruction framework integrating pre- and postoperative MRI and CT, cortical surface modeling, semi-automated pathology segmentation, intraoperative photographs or videos when available, and physics-based electrode modeling. To improve robustness in cases with distorted anatomy, artificial intelligence tools such as SynthSR were used to enable reliable cortical surface reconstruction prior to FreeSurfer processing. A monocular depth-estimation network was incorporated to constrain electrode placement in conjunction with Blender cloth-physics simulation when photographic images were available, while atlas- and note-guided inference supported reconstruction otherwise. The pipeline was applied to 38 neurosurgical patients across drug-resistant epilepsy resection (<i>n</i> = 24), malformation (<i>n</i> = 1), brain tumor (<i>n</i> = 11), and deep brain stimulation (<i>n</i> = 2) cases, achieving some type of reconstruction and electrode localization in all participants. By exporting electrode coordinates for quantitative spatial analyses, including distance-based mapping relative to lesions and resection cavities, ALIGNER enables anatomically grounded and reproducible analysis of intraoperative electrophysiology. This open-source framework provides foundational infrastructure for cancer neuroscience studies of tumor-neuron interactions and establishes a scalable platform for future neurostimulation, implantable neurodevice, and brain-computer interface applications requiring precise anatomical localization.</p>","PeriodicalId":12498,"journal":{"name":"Frontiers in Neural Circuits","volume":"20 ","pages":"1814667"},"PeriodicalIF":2.9000,"publicationDate":"2026-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13290761/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Neural Circuits","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fncir.2026.1814667","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Intraoperative intracranial electrophysiological recordings provide unique access to human cortical dynamics but remain difficult to translate across patients due to inconsistent localization of transient surface electrodes. Unlike chronic implantations, intraoperative electrodes are placed transiently, rarely visible on imaging, and often inconsistently documented. We present an open-source imaging pipeline, ALIGNER (Advanced Localization and Imaging Guidance for Neurosurgical Electrode Recording), designed to reconstruct intraoperative surface electrode array placements and quantitatively map neural activity to individualized anatomical and pathological substrates. By enabling anatomical localization of these electrodes, this framework supports systematic analysis of spatial gradients in neural activity relative to pathological tissue. We developed a multimodal reconstruction framework integrating pre- and postoperative MRI and CT, cortical surface modeling, semi-automated pathology segmentation, intraoperative photographs or videos when available, and physics-based electrode modeling. To improve robustness in cases with distorted anatomy, artificial intelligence tools such as SynthSR were used to enable reliable cortical surface reconstruction prior to FreeSurfer processing. A monocular depth-estimation network was incorporated to constrain electrode placement in conjunction with Blender cloth-physics simulation when photographic images were available, while atlas- and note-guided inference supported reconstruction otherwise. The pipeline was applied to 38 neurosurgical patients across drug-resistant epilepsy resection (n = 24), malformation (n = 1), brain tumor (n = 11), and deep brain stimulation (n = 2) cases, achieving some type of reconstruction and electrode localization in all participants. By exporting electrode coordinates for quantitative spatial analyses, including distance-based mapping relative to lesions and resection cavities, ALIGNER enables anatomically grounded and reproducible analysis of intraoperative electrophysiology. This open-source framework provides foundational infrastructure for cancer neuroscience studies of tumor-neuron interactions and establishes a scalable platform for future neurostimulation, implantable neurodevice, and brain-computer interface applications requiring precise anatomical localization.
期刊介绍:
Frontiers in Neural Circuits publishes rigorously peer-reviewed research on the emergent properties of neural circuits - the elementary modules of the brain. Specialty Chief Editors Takao K. Hensch and Edward Ruthazer at Harvard University and McGill University respectively, are supported by an outstanding Editorial Board of international experts. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics and the public worldwide.
Frontiers in Neural Circuits launched in 2011 with great success and remains a "central watering hole" for research in neural circuits, serving the community worldwide to share data, ideas and inspiration. Articles revealing the anatomy, physiology, development or function of any neural circuitry in any species (from sponges to humans) are welcome. Our common thread seeks the computational strategies used by different circuits to link their structure with function (perceptual, motor, or internal), the general rules by which they operate, and how their particular designs lead to the emergence of complex properties and behaviors. Submissions focused on synaptic, cellular and connectivity principles in neural microcircuits using multidisciplinary approaches, especially newer molecular, developmental and genetic tools, are encouraged. Studies with an evolutionary perspective to better understand how circuit design and capabilities evolved to produce progressively more complex properties and behaviors are especially welcome. The journal is further interested in research revealing how plasticity shapes the structural and functional architecture of neural circuits.