Christoph Dinh

Publications

Publications

Journal articles, book chapters, conference contributions, patents and research software. My name is set in darker type in each author list. Where a paper is behind a paywall and a free copy exists, it is linked.

BibTeX fileORCIDGoogle Scholar

Selected

2021

Dinh C, Samuelsson JG, Hunold A, Hämäläinen MS, Khan S. Contextual MEG and EEG source estimates using spatiotemporal LSTM networks. Frontiers in Neuroscience 2021;15:552666.

An LSTM network predicts the next source estimate from the preceding ones; the prediction is used to correct the noise-normalised minimum-norm estimate. Evaluated on simulated epileptiform activity and recorded auditory steady-state responses.

doi:10.3389/fnins.2021.552666Open accessCode

2019

Esch L, Dinh C, Larson E, Engemann D, Jas M, Khan S, Gramfort A, Hämäläinen MS. MNE: Software for acquiring, processing, and visualizing MEG/EEG data. Magnetoencephalography: From Signals to Dynamic Cortical Networks, 2nd ed. (Supek S, Aine CJ, eds.), Springer 2019, pp. 355–371.

Overview of the MNE software for acquiring, processing and visualising MEG and EEG data. It is the reference the MNE-CPP project asks its users to cite.

doi:10.1007/978-3-030-00087-5_59Author manuscript (HAL)

2018

Esch L, Sun L, Klüber V, Lew S, Baumgarten D, Grant PE, Okada Y, Haueisen J, Hämäläinen MS, Dinh C. MNE Scan: Software for real-time processing of electrophysiological data. Journal of Neuroscience Methods 2018;303:55–67.

The acquisition and real-time analysis application built on MNE-CPP, tested in three device-independent use cases: a clinical epilepsy study, real-time source estimation and a brain–computer interface. Senior author.

doi:10.1016/j.jneumeth.2018.03.020Author manuscript (PMC)Code

2016

Okada Y, Hämäläinen M, Pratt K, Mascarenas A, Miller P, Han M, Robles J, Cavallini A, Power B, Sieng K, Sun L, Lew S, Doshi C, Ahtam B, Dinh C, Esch L, Grant E, Nummenmaa A, Paulson D. BabyMEG: A whole-head pediatric magnetoencephalography system for human brain development research. Review of Scientific Instruments 2016;87(9):094301.

Design and performance of a 375-channel MEG system for infants and young children. My contribution was to the acquisition and real-time software.

doi:10.1063/1.4962020

2015

Dinh C, Strohmeier D, Luessi M, Güllmar D, Baumgarten D, Haueisen J, Hämäläinen MS. Real-time MEG source localization using regional clustering. Brain Topography 2015;28(6):771–784.

The source space is reduced with a cortical atlas: each region is represented by a few dipoles found by clustering. With it, dynamic statistical parametric mapping runs in real time and localises an auditory response in the superior temporal gyrus.

doi:10.1007/s10548-015-0431-9Author manuscript (PMC)

Journal articles and book chapters

2017

Sun L, Han M, Pratt K, Paulson D, Dinh C, Esch L, Okada Y, Hämäläinen M. Versatile synchronized real-time MEG hardware controller for large-scale fast data acquisition. Review of Scientific Instruments 2017;88(5):055110.

doi:10.1063/1.4983080

2016

Okada Y, Hämäläinen M, Pratt K, Mascarenas A, Miller P, Han M, Robles J, Cavallini A, Power B, Sieng K, Sun L, Lew S, Doshi C, Ahtam B, Dinh C, Esch L, Grant E, Nummenmaa A, Paulson D. BabyMEG: A whole-head pediatric magnetoencephalography system for human brain development research. Review of Scientific Instruments 2016;87(9):094301.

doi:10.1063/1.4962020

Conference and workshop papers

2025

Ripoll M, Andres MN, Sohrabpour A, Dinh C, Diepold K, Khan S. Signals of decline: Machine learning driven biomarkers for Alzheimer’s disease. NeurIPS 2025 Workshop on Learning from Time Series for Health (TS4H) 2025.

openreview.net/forum?id=GOg6WF6lDS

2015

Beier F, Sattler KU, Dinh C, Baumgarten D. Dataflow programming for big engineering data. Datenbanksysteme für Business, Technologie und Web (BTW 2015), Workshopband 2015, pp. 101–102.

2009

Dinh C, Struck M. A new real-time fall detection approach using fuzzy logic and a neural network. Proc. 6th International Workshop on Wearable, Micro and Nano Technologies for Personalized Health (pHealth) 2009, pp. 57–60.

doi:10.1109/PHEALTH.2009.5754822

Conference abstracts in proceedings

2026

Schote D, Behrens J, Kolbitsch C, Winter L, Dinh C. Remote control of portable low-field MRI by a cloud-native acquisition platform. Proc. Annual Meeting of the ISMRM 2026.

2014

Dinh C, Strohmeier D, Esch L, Güllmar D, Baumgarten D, Hämäläinen MS, Haueisen J. Real-time single-trial source localization using RAP-MUSIC and region of interest clustering. Biomedical Engineering / Biomedizinische Technik 2014, 59(S1):S949.

2014

Dinh C, Strohmeier D, Esch L, Baumgarten D, Hämäläinen MS, Haueisen J. Real-time source localization using minimum norm estimation and region of interest clustering. Biomedical Engineering / Biomedizinische Technik 2014, 59(S1):S988.

2013

Dinh C, Luessi M, Sun L, Haueisen J, Hämäläinen MS. MNE-X: MEG/EEG real-time acquisition, real-time processing, and real-time source localization framework. Biomedical Engineering / Biomedizinische Technik 2013, 58(S1).

doi:10.1515/bmt-2013-4184

2012

Dinh C, Strohmeier D, Haueisen J, Güllmar D. Brain atlas based region of interest selection for real-time source localization using K-means lead field clustering and RAP-MUSIC. Biomedical Engineering / Biomedizinische Technik 2012, 57(SI-1).

doi:10.1515/bmt-2012-4316

Thesis and preprint

2019

Dinh C, Samuelsson JGW, Hunold A, Hämäläinen MS, Khan S. Contextual minimum-norm estimates (CMNE): A deep learning method for source estimation in neuronal networks. arXiv 2019, 1909.02636.

Preprint of the 2021 article in Frontiers in Neuroscience.

arxiv.org/abs/1909.02636

Patents

2025

Haeusser P, Ruppersberg P, Dinh C. Systems, devices, components and methods for detecting the locations of sources of cardiac rhythm disorders in a patient’s heart using improved electrographic flow (EGF) methods. US 12,220,199 B2.

Granted 11 February 2025. Filed while at Ablacon; current assignee Boston Scientific Scimed, Inc.

patents.google.com/patent/US12220199B2/en

Research software

Selected talks

  • 2025

    Decoding brain activity: from EEG/MEG source estimations to AI-driven interpretation. International Conference on Basic and Clinical Multimodal Imaging (BaCI), Munich

  • 2021

    Mitigating the inverse problem: contextual MEG and EEG source estimates using spatiotemporal LSTM networks. 5th BaCI conference, held online

  • 2018

    Deep learning for MEG/EEG distributed source estimation: CMNE. 21st International Conference on Biomagnetism (BIOMAG), Philadelphia

  • 2018

    Estimation of neuronal sources with MNE. 8th International Summer School in Biomedical Engineering, Chengdu

  • 2017

    MNE-CPP. Supervised Neural Time Series Workshop, NYU Center for Data Science, New York

  • 2014

    Real-time MEG/EEG source localisation using source-space clustering. Brain Research Unit, Aalto University, Helsinki

  • 2014

    Real-time single-trial source localisation using RAP-MUSIC. 19th BIOMAG, Halifax

  • 2013

    MNE-X: real-time acquisition, processing and source localisation framework. 47th annual conference of the DGBMT, Graz

About this list

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