Author

A. Nummenmaa

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioengineering· 4

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:electrophysiology· 2 Approach:experimental assay· 2 Organism:human· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Assay:imaging· 1

Frequent Co-Authors

S. N. Makarov· 4 shared A. T. Htet· 2 shared E. H. Burnham· 2 shared G. M. Noetscher· 2 shared M. Daneshzand· 2 shared W. A. Wartman· 2 shared G. B. Saturnino· 1 shared K. Fujimoto· 1 shared

Activity by Year

2018-2020 · peak 2/yr

Co-Author Collaboration Network

9 top collaborators · 20 mutual co-author links

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4 shared papersBioengineering

S. N. Makarov

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Author profile →

4 papers

Recent·Most cited

A Note about the Individualized TMS Focality

S. N. Makarov, W. A. Wartman, M. Daneshzand, A. Nummenmaa

The paper presents a method to improve the focality of transcranial magnetic stimulation by optimizing coil position and orientation, reducing field deviation and increasing stability.

bioRxiv · Feb 10, 2020 · PreprintBioengineering

A Software Toolkit for TMS Electric-Field Modeling with Boundary Element Fast Multipole Method: An Efficient MATLAB Implementation

S. N. Makarov, W. A. Wartman, M. Daneshzand, K. Fujimoto, T. Raij, A. Nummenmaa

The paper introduces a MATLAB-based software toolkit for TMS electric-field modeling using BEM-FMM, achieving threefold faster computation with similar accuracy.

bioRxiv · Feb 9, 2020Bioengineering

Comparative Performance of the Finite Element Method and the Boundary Element Fast Multipole Method for Problems Mimicking Transcranial Magnetic Stimulation (TMS)

A. T. Htet, G. B. Saturnino, E. H. Burnham, G. M. Noetscher, A. Nummenmaa, S. N. Makarov

This paper compares the finite element method and boundary element fast multipole method for transcranial magnetic stimulation simulations, finding BEM-FMM offers lower error and faster performance for high-resolution models.

bioRxiv · Dec 21, 2018Bioengineering

Collection of Sixteen High-Quality Human Head CAD Models Generated with SimNIBS 2.1 Using Connectome Subject Data within MATLAB(R) Platform

A. T. Htet, G. M. Noetscher, E. H. Burnham, A. Nummenmaa, S. N. Makarov

The paper introduces sixteen high-resolution human head CAD models for electromagnetic and acoustic simulations, generated from HCP MRI data using SimNIBS 2.1 in MATLAB.

bioRxiv · Nov 29, 2018 · PreprintBioengineering