Ideal current dipoles are appropriate source representations for simulating neurons for intracranial recordings. (January 2023)
- Record Type:
- Journal Article
- Title:
- Ideal current dipoles are appropriate source representations for simulating neurons for intracranial recordings. (January 2023)
- Main Title:
- Ideal current dipoles are appropriate source representations for simulating neurons for intracranial recordings
- Authors:
- Thio, Brandon J.
Aberra, Aman S.
Dessert, Grace E.
Grill, Warren M. - Abstract:
- Highlights: Spatiotemporal voltage distributions from dipoles match realistic model neurons. Multiple dipoles are required to represent extended regions (cm 2 ) of active cortex. Minimal localization error using dipoles to represent neural sources for sEEG. Abstract: Objective: To determine whether dipoles are an appropriate simplified representation of neural sources for stereo-EEG (sEEG). Methods: We compared the distributions of voltages generated by a dipole, biophysically realistic cortical neuron models, and extended regions of cortex to determine how well a dipole represented neural sources at different spatial scales and at electrode to neuron distances relevant for sEEG. We also quantified errors introduced by the dipole approximation of neural sources in sEEG source localization using standardized low-resolution electrotomography (sLORETA). Results: For pyramidal neurons, the coefficient of correlation between voltages generated by a dipole and neuron model were > 0.9 for distances > 1 mm. For small regions of cortex (∼0.1 cm 2 ), the error in voltages between a dipole and region was < 100 µV for all distances. However, larger regions of active cortex (>5 cm 2 ) yielded > 50 µV errors within 1.5 cm of an electrode when compared to single dipoles. Finally, source localization errors were < 5 mm when using dipoles to represent realistic neural sources. Conclusions: Single dipoles are an appropriate source model to represent both single neurons and small regions ofHighlights: Spatiotemporal voltage distributions from dipoles match realistic model neurons. Multiple dipoles are required to represent extended regions (cm 2 ) of active cortex. Minimal localization error using dipoles to represent neural sources for sEEG. Abstract: Objective: To determine whether dipoles are an appropriate simplified representation of neural sources for stereo-EEG (sEEG). Methods: We compared the distributions of voltages generated by a dipole, biophysically realistic cortical neuron models, and extended regions of cortex to determine how well a dipole represented neural sources at different spatial scales and at electrode to neuron distances relevant for sEEG. We also quantified errors introduced by the dipole approximation of neural sources in sEEG source localization using standardized low-resolution electrotomography (sLORETA). Results: For pyramidal neurons, the coefficient of correlation between voltages generated by a dipole and neuron model were > 0.9 for distances > 1 mm. For small regions of cortex (∼0.1 cm 2 ), the error in voltages between a dipole and region was < 100 µV for all distances. However, larger regions of active cortex (>5 cm 2 ) yielded > 50 µV errors within 1.5 cm of an electrode when compared to single dipoles. Finally, source localization errors were < 5 mm when using dipoles to represent realistic neural sources. Conclusions: Single dipoles are an appropriate source model to represent both single neurons and small regions of active cortex, while multiple dipoles are required to represent large regions of cortex. Significance: Dipoles are computationally tractable and valid source models for sEEG. … (more)
- Is Part Of:
- Clinical neurophysiology. Volume 145(2023)
- Journal:
- Clinical neurophysiology
- Issue:
- Volume 145(2023)
- Issue Display:
- Volume 145, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 145
- Issue:
- 2023
- Issue Sort Value:
- 2023-0145-2023-0000
- Page Start:
- 26
- Page End:
- 35
- Publication Date:
- 2023-01
- Subjects:
- Dipole -- Source localization -- Intracranial EEG -- Computational modeling -- Inverse problem
Neurophysiology -- Periodicals
Electroencephalography -- Periodicals
Electromyography -- Periodicals
Neurology -- Periodicals
612.8 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13882457 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.clinph.2022.11.002 ↗
- Languages:
- English
- ISSNs:
- 1388-2457
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3286.310645
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24695.xml