Correction to: Variation in Reported Human Head Tissue Electrical Conductivity Values

Correction to: Brain Topography (2019) 32:825–858 https://doi.org/10.1007/s10548-019-00710-2

The original publication of the article unfortunately contain mistakes. It has been corrected in this correction.

A GitHub Repository has been created to provide continual updates, since publication, for any measurements of human head electrical conductivity values (https://github.com/Head-Conductivity/Human-Head-Conductivity.git). This resource provides information on all values from the current literature, which will be updated as new data arises. We would appreciate any contribution of additional values and encourage authors to contact us if they become aware of further measurements.

Within the published manuscript, it has come to our attention that the inclusion of some research papers were erroneously described as utilising Magnetic Resonance Electrical Imaging Tomography (MREIT). These papers instead employed Magnetic Resonance Electrical Properties Tomography (MREPT) with frequencies above 1 kHz, greater than our included frequency range. These papers are thus to be excluded from the meta-analysis.

Modifications are presented, in order, following this exclusion to various figures, tables and results.

Within the Abstract, 41, rather than 56 papers are now included in the data extraction. The recommended weighted average means for CSF, GM and WM should be altered to 1.736, 0.3787 and 0.1462 S/m respectively. Results for other tissues remain unchanged from the original publication.

Within the 3. Results section, a total of 170 papers were excluded following full text assessment, resulting in a total of 41 studies (341 participants), utilising 4 methodologies; 14 for DAC, 11 for EIT, 8 for E/MEG, 9 for DTI. Of these included, 27 papers measured or estimated conductivity in vivo, 7 in vitro and 8 ex vivo, 28 reported on healthy participants, 10 on epilepsy and one on Parkinson’s Disease, stroke and neurological disorders. The article no longer reports on tissues from the cerebellum or tumours.

The modified Tables 2 and 3, and Figures2, 3, 9, 10, 11, 12 are shown below. Figure 8 is to be retracted from the published article due to insufficient data presented.

Table 2 Summary of papers included in meta-analysis

Table 3 Descriptive statistics for each tissue type

Figure 2

Figure 3

Figure 9

Figure 10

Figure 11

Figure 12

Within the 4. Discussion section, the weighted average mean and standard deviation (in S/m) for CSF, GM and WM has been revised to: CSF = 1.736 ± 0.17, GM = 0.3787 ± 0.16, WM = 0.1462 ± 0.11. All mention and evaluation of papers utilising the excluded MREIT papers are omitted from the discussion section. These relate to the following references which are also to be excluded:

Haacke, E., Petropoulos, L., Nilges, E., & Wu, D. (1991). Extraction of conductivity and permittivity using magnetic resonance imaging. Physics in Medicine & Biology, 36(6), 723.

Voigt, T., Doessel, O., & Katscher, U. (2009). Imaging conductivity and local SAR of the human brain. Paper presented at the Proceedings of the 17th Annual Meeting of ISMRM, Honolulu, Hawaii, USA.

Voigt, T., Katscher, U., & Doessel, O. (2011). Quantitative Conductivity and Permittivity Imaging of the Human Brain Using Electric Properties Tomography. Magnetic Resonance in Medicine, 66(2), 456–466. https://doi.org/10.1002/mrm.22832

Van Lier, A., Hoogduin, J., Polders, D., Boer, V., Hendrikse, J., Robe, P.,... van den Berg, C. (2011). Electrical conductivity imaging of brain tumours. Paper presented at the Proceedings of the 19th Annual Meeting of ISMRM, Montreal, Canada.

van Lier, A., Kolk, A., Brundel, M., Hendriske, J., Luijten, J., Lagendijk, J., & van den Berg, C. (2012). Electrical conductivity in ischemic stroke at 7.0 T: a case study. Paper presented at the Proceedings of the 20th Scientific Meeting of the International Society of Magnetic Resonance in Medicine (ISMRM’12).

Huhndorf, M., Stehning, C., Rohr, A., Helle, M., Katscher, U., & Jansen, O. (2013). Systematic brain tumor conductivity study with optimized EPT sequence and reconstruction algorithm. Paper presented at the Proc. ISMRM.

Zhang, X., de Moortele, P. F. V., Schmitter, S., & He, B. (2013). Complex B1 mapping and electrical properties imaging of the human brain using a 16‐channel transceiver coil at 7 T. Magnetic resonance in medicine, 69(5), 1285–1296.

Kim, D. H., Choi, N., Gho, S. M., Shin, J., & Liu, C. (2014). Simultaneous imaging of in vivo conductivity and susceptibility. Magnetic resonance in medicine, 71(3), 1144–1150.

Lee, J., Shin, J., & Kim, D. H. (2016). MR‐based conductivity imaging using multiple receiver coils. Magnetic resonance in medicine, 76(2), 530–539.

Lee, S.-K., Bulumulla, S., Wiesinger, F., Sacolick, L., Sun, W., & Hancu, I. (2015). Tissue electrical property mapping from zero echo-time magnetic resonance imaging. IEEE transactions on medical imaging, 34(2), 541–550.

Gurler N., & Ider, Y.Z. (2017). Gradient-based electrical conductivity imagingusing MR phase. Magn Reson Med 77(1):137–150.

Ropella, K. M., & Noll, D. C. (2017) A regularized, model-based approach to phase-based conductivity mapping using MRI. Magnetic resonance in medicine (5), 2011–2021.

Hampe, N., Herrmann, M., Amthor, T., Findeklee, C., Doneva, M., & Katscher, U. (2018). Dictionary‐based electric properties tomography. Magnetic resonance in medicine.

Michel, E., Hernandez, D., & Lee, S. Y. (2017). Electrical conductivity and permittivity maps of brain tissues derived from water content based on T1‐weighted acquisition. Magnetic resonance in medicine, 77(3), 1094–1103.

Tha, K. K., Katscher, U., Yamaguchi, S., Stehning, C., Terasaka, S., Fujima, N.,... Van Cauteren, M. (2018). Noninvasive electrical conductivity measurement by MRI: a test of its validity and the electrical conductivity characteristics of glioma. European radiology, 28(1), 348–355.

Furthermore, after a thorough search of the published article the following errors are present in the references list:

Acar, Z. A., Ortiz-Mantilla, S., Benasich, A., & Makeig, S. (2016, Aug 16–20). High-resolution EEG source imaging of one-year-old children. Paper presented at the 38th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), Orlando, FL.

Should read:

Acar ZA, Ortiz-Mantilla S, Benasich A, Makeig S (2016, August) High-resolution EEG source imaging of one-year-old children. In: Paper presented at the 38th annual international conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), Orlando, FL. IEEE, pp 117–120

Arumugam, E. T., Sergei. Price, Nick Rech, Dennis. Phan Luu, Phan. Tucker, Don. (2017). In-vivo Estimation of the Scalp and Skull Conductivity Using bEIT for Non-invasive Neuroimaging and Stimulation In: Brain Stimulation and Imaging Meeting.

Should read:

Essaki Arumugam EM, Turovets S, Price N, Rech D, Luu P, Tucker D (2017) In-vivo estimation of the scalp and skull conductivity using bEIT for non-invasive neuroimaging and stimulation. In: June 2017 conference: brain stimulation and imaging meeting, Vancouver, BC

Nurul AAL, Mahmood D, Mohd MK, Ibrahim S (2010) A study of frequency effects on conductivity measurements. RnD Seminar 2010: research and Development Seminar 2010, Malaysia.

Should read:

Latif NAiA, Dollah M, Kamaron MK, Ibrahim S (2010) A study of frequency effects on conductivity measurements. In: RnD Seminar 2010: research and development seminar 2010, Malaysia