publication . Article . 2017

Semi-automated Anatomical Labeling and Inter-subject Warping of High-Density Intracranial Recording Electrodes in Electrocorticography.

Hamilton, Liberty S.; Chang, David L.; Lee, Morgan B.; Chang, Edward F.;
Open Access
  • Published: 31 Oct 2017
  • Publisher: eScholarship, University of California
  • Country: United States
Abstract
In this article, we introduce img_pipe, our open source python package for preprocessing of imaging data for use in intracranial electrocorticography (ECoG) and intracranial stereo-EEG analyses. The process of electrode localization, labeling, and warping for use in ECoG currently varies widely across laboratories, and it is usually performed with custom, lab-specific code. This python package aims to provide a standardized interface for these procedures, as well as code to plot and display results on 3D cortical surface meshes. It gives the user an easy interface to create anatomically labeled electrodes that can also be warped to an atlas brain, starting with ...
Subjects
ACM Computing Classification System: ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
free text keywords: electrocorticography, electrode localization, epilepsy, image coregistration, intracranial recordings, open science, subdural electrodes, surgery, Artificial intelligence, business.industry, business, Computer vision, High density, Data mining, computer.software_genre, computer, Computed tomography, medicine.diagnostic_test, medicine, Software, Preprocessor, Computer science, Neuroscience, Polygon mesh, Python (programming language), computer.programming_language, Image warping, Protocols
Funded by
NIH| The spatiotemporal dynamics of cortical speech representation
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1F32DC014192-01
  • Funding stream: NATIONAL INSTITUTE ON DEAFNESS AND OTHER COMMUNICATION DISORDERS
,
NIH| Functional organization of the superior temporal gyrus for speech perception
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1R01DC012379-01
  • Funding stream: NATIONAL INSTITUTE ON DEAFNESS AND OTHER COMMUNICATION DISORDERS
Communities
Neuroinformatics
22 references, page 1 of 2

Ashburner J.Friston K. J. (1997). Spatial transformation of images. Hum. Brain Funct. 43–58.

Chang E. F. (2015). Towards large-scale, human-based, mesoscopic neurotechnologies. Neuron 86, 68–78. 10.1016/j.neuron.2015.03.037 25856487 [OpenAIRE] [PubMed] [DOI]

Dalal S. S.Edwards E.Kirsch H. E.Barbaro N. M.Knight R. T.Nagarajan S. S. (2008). Localization of neurosurgically implanted electrodes via photograph-MRI-radiograph coregistration. J. Neurosci. Methods 174, 106–115. 10.1016/j.jneumeth.2008.06.028 18657573 [OpenAIRE] [PubMed] [DOI]

Desikan R. S.Ségonne F.Fischl B.Quinn B. T.Dickerson B. C.Blacker D.. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31, 968–980. 10.1016/j.neuroimage.2006.01.021 16530430 [OpenAIRE] [PubMed] [DOI]

Dichter B. K.Bouchard K. E.Chang E. F. (2016). Dynamic structure of neural variability in the cortical re presentation of speech sounds. J. Neurosci. 36, 7453–7463. 10.1523/JNEUROSCI.0156-16.2016 27413155 [OpenAIRE] [PubMed] [DOI]

Dykstra A. R.Chan A. M.Quinn B. T.Zepeda R.Keller C. J.Cormier J.. (2012). Individualized localization and cortical surface-based registration of intracranial electrodes. Neuroimage 59, 3563–3570. 10.1016/j.neuroimage.2011.11.046 22155045 [OpenAIRE] [PubMed] [DOI]

Fischl B.Van Der Kouwe A.Destrieux C.Halgren E.Ségonne F.Salat D. H.. (2004). Automatically parcellating the human cerebral cortex. Cereb. Cortex 14, 11–22. 10.1093/cercor/bhg087 14654453 [OpenAIRE] [PubMed] [DOI]

Groppe D. M.Bickel S.Dykstra A.Wang X.Megevand P.Mercier M.. (2016). iELVis: an open source MATLAB toolbox for localizing and visualizing human intracranial electrode data. bioRxiv 1–20. 10.1101/069179 28192130 [OpenAIRE] [PubMed] [DOI]

Hamilton L. S.Edwards E.Chang E. F. (2016). Parallel streams define the temporal dynamics of speech processing across human auditory cortex. bioRxiv. 10.1101/097485 [OpenAIRE] [DOI]

Hermes D.Miller K. J.Noordmans H. J.Vansteensel M. J.Ramsey N. F. (2010). Automated electrocorticographic electrode localization on individually rendered brain surfaces. J. Neurosci. Methods 185, 293–298. 10.1016/j.jneumeth.2009.10.005 19836416 [OpenAIRE] [PubMed] [DOI]

Kovalev D.Spreer J.Honegger J.Zentner J.Schulze-Bonhage A.Huppertz H.-J. (2005). Rapid and fully automated visualization of subdural electrodes in the presurgical evaluation of epilepsy patients. Am. J. Neuroradiol. 26, 1078–1083. Available on line at: http://www.ajnr.org/content/26/5/1078/tab-article-info 15891163 [PubMed]

LaPlante R. A.Tang W.Peled N.Vallejo D. I.Borzello M.Dougherty D. D.. (2016). The interactive electrode localization utility: software for automatic sorting and labeling of intracranial subdural electrodes. Int. J. Comput. Assist. Radiol. Surg. 12, 1829–1837. 10.1007/s11548-016-1504-2 27915398 [OpenAIRE] [PubMed] [DOI]

Leonard M. K.Baud M. O.Sjerps M. J.Chang E. F. (2016). Perceptual restoration of masked speech in human cortex. Nat. Commun. 7:13619. 10.1038/ncomms13619 27996973 [OpenAIRE] [PubMed] [DOI]

Miller K. J.Makeig S.Hebb A. O.Rao R. P. N.denNijs M.Ojemann J. G. (2007). Cortical electrode localization from X-rays and simple mapping for electrocorticographic research: The “Location on Cortex” (LOC) package for MATLAB. J. Neurosci. Methods 162, 303–308. 10.1016/j.jneumeth.2007.01.019 17343918 [OpenAIRE] [PubMed] [DOI]

Moses D. A.Mesgarani N.Leonard M. K.Chang E. F. (2016). Neural speech recognition: continuous phoneme decoding using spatiotemporal representations of human cortical activity. J. Neural Eng. 13, 1–19. 10.1088/1741-2560/13/5/056004 27484713 [OpenAIRE] [PubMed] [DOI]

22 references, page 1 of 2
Abstract
In this article, we introduce img_pipe, our open source python package for preprocessing of imaging data for use in intracranial electrocorticography (ECoG) and intracranial stereo-EEG analyses. The process of electrode localization, labeling, and warping for use in ECoG currently varies widely across laboratories, and it is usually performed with custom, lab-specific code. This python package aims to provide a standardized interface for these procedures, as well as code to plot and display results on 3D cortical surface meshes. It gives the user an easy interface to create anatomically labeled electrodes that can also be warped to an atlas brain, starting with ...
Subjects
ACM Computing Classification System: ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
free text keywords: electrocorticography, electrode localization, epilepsy, image coregistration, intracranial recordings, open science, subdural electrodes, surgery, Artificial intelligence, business.industry, business, Computer vision, High density, Data mining, computer.software_genre, computer, Computed tomography, medicine.diagnostic_test, medicine, Software, Preprocessor, Computer science, Neuroscience, Polygon mesh, Python (programming language), computer.programming_language, Image warping, Protocols
Funded by
NIH| The spatiotemporal dynamics of cortical speech representation
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1F32DC014192-01
  • Funding stream: NATIONAL INSTITUTE ON DEAFNESS AND OTHER COMMUNICATION DISORDERS
,
NIH| Functional organization of the superior temporal gyrus for speech perception
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1R01DC012379-01
  • Funding stream: NATIONAL INSTITUTE ON DEAFNESS AND OTHER COMMUNICATION DISORDERS
Communities
Neuroinformatics
22 references, page 1 of 2

Ashburner J.Friston K. J. (1997). Spatial transformation of images. Hum. Brain Funct. 43–58.

Chang E. F. (2015). Towards large-scale, human-based, mesoscopic neurotechnologies. Neuron 86, 68–78. 10.1016/j.neuron.2015.03.037 25856487 [OpenAIRE] [PubMed] [DOI]

Dalal S. S.Edwards E.Kirsch H. E.Barbaro N. M.Knight R. T.Nagarajan S. S. (2008). Localization of neurosurgically implanted electrodes via photograph-MRI-radiograph coregistration. J. Neurosci. Methods 174, 106–115. 10.1016/j.jneumeth.2008.06.028 18657573 [OpenAIRE] [PubMed] [DOI]

Desikan R. S.Ségonne F.Fischl B.Quinn B. T.Dickerson B. C.Blacker D.. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31, 968–980. 10.1016/j.neuroimage.2006.01.021 16530430 [OpenAIRE] [PubMed] [DOI]

Dichter B. K.Bouchard K. E.Chang E. F. (2016). Dynamic structure of neural variability in the cortical re presentation of speech sounds. J. Neurosci. 36, 7453–7463. 10.1523/JNEUROSCI.0156-16.2016 27413155 [OpenAIRE] [PubMed] [DOI]

Dykstra A. R.Chan A. M.Quinn B. T.Zepeda R.Keller C. J.Cormier J.. (2012). Individualized localization and cortical surface-based registration of intracranial electrodes. Neuroimage 59, 3563–3570. 10.1016/j.neuroimage.2011.11.046 22155045 [OpenAIRE] [PubMed] [DOI]

Fischl B.Van Der Kouwe A.Destrieux C.Halgren E.Ségonne F.Salat D. H.. (2004). Automatically parcellating the human cerebral cortex. Cereb. Cortex 14, 11–22. 10.1093/cercor/bhg087 14654453 [OpenAIRE] [PubMed] [DOI]

Groppe D. M.Bickel S.Dykstra A.Wang X.Megevand P.Mercier M.. (2016). iELVis: an open source MATLAB toolbox for localizing and visualizing human intracranial electrode data. bioRxiv 1–20. 10.1101/069179 28192130 [OpenAIRE] [PubMed] [DOI]

Hamilton L. S.Edwards E.Chang E. F. (2016). Parallel streams define the temporal dynamics of speech processing across human auditory cortex. bioRxiv. 10.1101/097485 [OpenAIRE] [DOI]

Hermes D.Miller K. J.Noordmans H. J.Vansteensel M. J.Ramsey N. F. (2010). Automated electrocorticographic electrode localization on individually rendered brain surfaces. J. Neurosci. Methods 185, 293–298. 10.1016/j.jneumeth.2009.10.005 19836416 [OpenAIRE] [PubMed] [DOI]

Kovalev D.Spreer J.Honegger J.Zentner J.Schulze-Bonhage A.Huppertz H.-J. (2005). Rapid and fully automated visualization of subdural electrodes in the presurgical evaluation of epilepsy patients. Am. J. Neuroradiol. 26, 1078–1083. Available on line at: http://www.ajnr.org/content/26/5/1078/tab-article-info 15891163 [PubMed]

LaPlante R. A.Tang W.Peled N.Vallejo D. I.Borzello M.Dougherty D. D.. (2016). The interactive electrode localization utility: software for automatic sorting and labeling of intracranial subdural electrodes. Int. J. Comput. Assist. Radiol. Surg. 12, 1829–1837. 10.1007/s11548-016-1504-2 27915398 [OpenAIRE] [PubMed] [DOI]

Leonard M. K.Baud M. O.Sjerps M. J.Chang E. F. (2016). Perceptual restoration of masked speech in human cortex. Nat. Commun. 7:13619. 10.1038/ncomms13619 27996973 [OpenAIRE] [PubMed] [DOI]

Miller K. J.Makeig S.Hebb A. O.Rao R. P. N.denNijs M.Ojemann J. G. (2007). Cortical electrode localization from X-rays and simple mapping for electrocorticographic research: The “Location on Cortex” (LOC) package for MATLAB. J. Neurosci. Methods 162, 303–308. 10.1016/j.jneumeth.2007.01.019 17343918 [OpenAIRE] [PubMed] [DOI]

Moses D. A.Mesgarani N.Leonard M. K.Chang E. F. (2016). Neural speech recognition: continuous phoneme decoding using spatiotemporal representations of human cortical activity. J. Neural Eng. 13, 1–19. 10.1088/1741-2560/13/5/056004 27484713 [OpenAIRE] [PubMed] [DOI]

22 references, page 1 of 2
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publication . Article . 2017

Semi-automated Anatomical Labeling and Inter-subject Warping of High-Density Intracranial Recording Electrodes in Electrocorticography.

Hamilton, Liberty S.; Chang, David L.; Lee, Morgan B.; Chang, Edward F.;