Bridging circuit modeling and signal analysis to understand the risk of crosstalk contamination in brain recordings
Abstract Advancements in the field of implantable neurotechnologies have enabled the integration of hundreds of microelectrodes on ultra-thin and flexible substrates. Besides implantable components, also connectors, headstages and cables have to comply with the high-count demand, resulting in a comp...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-05-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-59391-0 |
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| author | Maria F. Porto Cruz Elena Zucchini Maria Vomero Aldo Pastore Ioana G. Vasilaș Emanuela Delfino Michele Di Lauro Maria Asplund Luciano Fadiga Thomas Stieglitz |
| author_facet | Maria F. Porto Cruz Elena Zucchini Maria Vomero Aldo Pastore Ioana G. Vasilaș Emanuela Delfino Michele Di Lauro Maria Asplund Luciano Fadiga Thomas Stieglitz |
| author_sort | Maria F. Porto Cruz |
| collection | DOAJ |
| description | Abstract Advancements in the field of implantable neurotechnologies have enabled the integration of hundreds of microelectrodes on ultra-thin and flexible substrates. Besides implantable components, also connectors, headstages and cables have to comply with the high-count demand, resulting in a complex and compact chain with reduced line spacing and smaller safety margins. Here, we show that epicortical recordings acquired from anesthetized rat brains with a state-of-art neural acquisition system are undoubtedly compromised by crosstalk, with signal coherence maps exhibiting a strong dependency to the routing layout. A crosstalk back-correction algorithm is developed, allowing to infer on how signals would look like under a zero-crosstalk scenario. We found that signal coherence between closely routed channels effectively drops after correction, corroborating crosstalk contamination. Our work stresses the importance of validating recorded data against the routing layout as a crucial step of data quality control, helping to come closer to ground truth data. |
| format | Article |
| id | doaj-art-ea374cb5f76540b18315537f0dc50ce6 |
| institution | DOAJ |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-ea374cb5f76540b18315537f0dc50ce62025-08-20T03:08:43ZengNature PortfolioNature Communications2041-17232025-05-0116111310.1038/s41467-025-59391-0Bridging circuit modeling and signal analysis to understand the risk of crosstalk contamination in brain recordingsMaria F. Porto Cruz0Elena Zucchini1Maria Vomero2Aldo Pastore3Ioana G. Vasilaș4Emanuela Delfino5Michele Di Lauro6Maria Asplund7Luciano Fadiga8Thomas Stieglitz9Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering (IMTEK), University of FreiburgDepartment of Neuroscience and Rehabilitation, University of FerraraLaboratory for Biomedical Microtechnology, Department of Microsystems Engineering (IMTEK), University of FreiburgDepartment of Neuroscience and Rehabilitation, University of FerraraLaboratory for Biomedical Microtechnology, Department of Microsystems Engineering (IMTEK), University of FreiburgDepartment of Neuroscience and Rehabilitation, University of FerraraCenter for Translational Neurophysiology of Speech and Communication, Istituto Italiano di TecnologiaBrainLinks-BrainTools Center, University of FreiburgDepartment of Neuroscience and Rehabilitation, University of FerraraLaboratory for Biomedical Microtechnology, Department of Microsystems Engineering (IMTEK), University of FreiburgAbstract Advancements in the field of implantable neurotechnologies have enabled the integration of hundreds of microelectrodes on ultra-thin and flexible substrates. Besides implantable components, also connectors, headstages and cables have to comply with the high-count demand, resulting in a complex and compact chain with reduced line spacing and smaller safety margins. Here, we show that epicortical recordings acquired from anesthetized rat brains with a state-of-art neural acquisition system are undoubtedly compromised by crosstalk, with signal coherence maps exhibiting a strong dependency to the routing layout. A crosstalk back-correction algorithm is developed, allowing to infer on how signals would look like under a zero-crosstalk scenario. We found that signal coherence between closely routed channels effectively drops after correction, corroborating crosstalk contamination. Our work stresses the importance of validating recorded data against the routing layout as a crucial step of data quality control, helping to come closer to ground truth data.https://doi.org/10.1038/s41467-025-59391-0 |
| spellingShingle | Maria F. Porto Cruz Elena Zucchini Maria Vomero Aldo Pastore Ioana G. Vasilaș Emanuela Delfino Michele Di Lauro Maria Asplund Luciano Fadiga Thomas Stieglitz Bridging circuit modeling and signal analysis to understand the risk of crosstalk contamination in brain recordings Nature Communications |
| title | Bridging circuit modeling and signal analysis to understand the risk of crosstalk contamination in brain recordings |
| title_full | Bridging circuit modeling and signal analysis to understand the risk of crosstalk contamination in brain recordings |
| title_fullStr | Bridging circuit modeling and signal analysis to understand the risk of crosstalk contamination in brain recordings |
| title_full_unstemmed | Bridging circuit modeling and signal analysis to understand the risk of crosstalk contamination in brain recordings |
| title_short | Bridging circuit modeling and signal analysis to understand the risk of crosstalk contamination in brain recordings |
| title_sort | bridging circuit modeling and signal analysis to understand the risk of crosstalk contamination in brain recordings |
| url | https://doi.org/10.1038/s41467-025-59391-0 |
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