Zhen Qi, Gregory M Noetscher, Alton Miles, Konstantin Weise, Thomas R Knösche, Cameron R Cadman, Alina R Potashinsky, Kelu Liu, William A Wartman, Guillermo Nunez Ponasso, Marom Bikson, Hanbing Lu, Zhi-De Deng, Aapo R Nummenmaa, Sergey N Makaroff
{"title":"在显微镜下逼真的大脑中建立电磁模型--对大脑刺激的影响。","authors":"Zhen Qi, Gregory M Noetscher, Alton Miles, Konstantin Weise, Thomas R Knösche, Cameron R Cadman, Alina R Potashinsky, Kelu Liu, William A Wartman, Guillermo Nunez Ponasso, Marom Bikson, Hanbing Lu, Zhi-De Deng, Aapo R Nummenmaa, Sergey N Makaroff","doi":"10.1101/2024.04.04.588004","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Modeling brain stimulation at the microscopic scale may reveal new paradigms for a variety of stimulation modalities.</p><p><strong>Objective: </strong>We present the largest map of distributions of the extracellular electric field to date within a layer L2/L3 mouse primary visual cortex brain sample, which was enabled by automated analysis of serial section electron microscopy images with improved handling of image defects (250×140×90 μm <sup>3</sup> volume).</p><p><strong>Methods: </strong>We used the map to identify microscopic perturbations of the extracellular electric field and their effect on the activating thresholds of individual neurons. Previous relevant studies modeled a macroscopically homogeneous cortical volume. Result: Our immediate result is a reduction of the predicted stimulation field strength necessary for neuronal activation by a factor of approximately 0.7 (or by 30%) on average, due to microscopic perturbations of the extracellular electric field-an electric field \"spatial noise\" with a mean value of zero.</p><p><strong>Conclusion: </strong>Although this result is largely sample-specific, it aligns with experimental data indicating that existing macroscopic theories substantially overestimate the electric fields necessary for brain stimulation.</p><p><strong>Significance statement: </strong>Currently, there is a discrepancy between macroscopic volumetric brain modeling for brain stimulation and experimental results: experiments typically reveal lower electric intensities required for brain stimulation. This study is arguably the first attempt to model brain stimulation at the microscopic scale, enabled by automated analysis of modern scanning electron microscopy images of the brain. The immediate result is a prediction of lower electric field intensities necessary for brain stimulation, with an average reduction factor of 0.7.</p>","PeriodicalId":72407,"journal":{"name":"bioRxiv : the preprint server for biology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11030228/pdf/","citationCount":"0","resultStr":"{\"title\":\"Enabling Electric Field Model of Microscopically Realistic Brain.\",\"authors\":\"Zhen Qi, Gregory M Noetscher, Alton Miles, Konstantin Weise, Thomas R Knösche, Cameron R Cadman, Alina R Potashinsky, Kelu Liu, William A Wartman, Guillermo Nunez Ponasso, Marom Bikson, Hanbing Lu, Zhi-De Deng, Aapo R Nummenmaa, Sergey N Makaroff\",\"doi\":\"10.1101/2024.04.04.588004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Modeling brain stimulation at the microscopic scale may reveal new paradigms for a variety of stimulation modalities.</p><p><strong>Objective: </strong>We present the largest map of distributions of the extracellular electric field to date within a layer L2/L3 mouse primary visual cortex brain sample, which was enabled by automated analysis of serial section electron microscopy images with improved handling of image defects (250×140×90 μm <sup>3</sup> volume).</p><p><strong>Methods: </strong>We used the map to identify microscopic perturbations of the extracellular electric field and their effect on the activating thresholds of individual neurons. Previous relevant studies modeled a macroscopically homogeneous cortical volume. Result: Our immediate result is a reduction of the predicted stimulation field strength necessary for neuronal activation by a factor of approximately 0.7 (or by 30%) on average, due to microscopic perturbations of the extracellular electric field-an electric field \\\"spatial noise\\\" with a mean value of zero.</p><p><strong>Conclusion: </strong>Although this result is largely sample-specific, it aligns with experimental data indicating that existing macroscopic theories substantially overestimate the electric fields necessary for brain stimulation.</p><p><strong>Significance statement: </strong>Currently, there is a discrepancy between macroscopic volumetric brain modeling for brain stimulation and experimental results: experiments typically reveal lower electric intensities required for brain stimulation. This study is arguably the first attempt to model brain stimulation at the microscopic scale, enabled by automated analysis of modern scanning electron microscopy images of the brain. The immediate result is a prediction of lower electric field intensities necessary for brain stimulation, with an average reduction factor of 0.7.</p>\",\"PeriodicalId\":72407,\"journal\":{\"name\":\"bioRxiv : the preprint server for biology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11030228/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"bioRxiv : the preprint server for biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2024.04.04.588004\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"bioRxiv : the preprint server for biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.04.04.588004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enabling Electric Field Model of Microscopically Realistic Brain.
Background: Modeling brain stimulation at the microscopic scale may reveal new paradigms for a variety of stimulation modalities.
Objective: We present the largest map of distributions of the extracellular electric field to date within a layer L2/L3 mouse primary visual cortex brain sample, which was enabled by automated analysis of serial section electron microscopy images with improved handling of image defects (250×140×90 μm 3 volume).
Methods: We used the map to identify microscopic perturbations of the extracellular electric field and their effect on the activating thresholds of individual neurons. Previous relevant studies modeled a macroscopically homogeneous cortical volume. Result: Our immediate result is a reduction of the predicted stimulation field strength necessary for neuronal activation by a factor of approximately 0.7 (or by 30%) on average, due to microscopic perturbations of the extracellular electric field-an electric field "spatial noise" with a mean value of zero.
Conclusion: Although this result is largely sample-specific, it aligns with experimental data indicating that existing macroscopic theories substantially overestimate the electric fields necessary for brain stimulation.
Significance statement: Currently, there is a discrepancy between macroscopic volumetric brain modeling for brain stimulation and experimental results: experiments typically reveal lower electric intensities required for brain stimulation. This study is arguably the first attempt to model brain stimulation at the microscopic scale, enabled by automated analysis of modern scanning electron microscopy images of the brain. The immediate result is a prediction of lower electric field intensities necessary for brain stimulation, with an average reduction factor of 0.7.