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Simulating biophysically-detailed neuron models is a computationally expensive but effective method for studying local neural circuits. Recent innovations have shown that artificial neural networks (ANNs) can accurately predict the behavior of these detailed models in terms of spikes, electrical potentials, and optical readouts. While these methods have the potential to accelerate large network simulations by several orders of magnitude compared to conventional differential equation based modelling, they currently only predict voltage outputs for the soma or a select few neuron compartments. Our novel approach, based on enhanced state-of-the-art architectures for multitask learning (MTL), allows for the simultaneous prediction of membrane potentials in each compartment of a neuron model, at a speed of up to two orders of magnitude faster than classical simulation methods. By predicting all membrane potentials together, our approach not only allows for comparison of model output with a wider range of experimental recordings (patch-electrode, voltage-sensitive dye imaging), it also provides the first stepping stone towards predicting local field potentials (LFPs), electroencephalogram (EEG) signals, and magnetoencephalography (MEG) signals from ANN-based simulations. While LFP and EEG are an important downstream application, the main focus of this paper lies in predicting dendritic voltages within each compartment to capture the entire electrophysiology of a biophysically-detailed neuron model. It further presents a challenging benchmark for MTL architectures due to the large amount of data involved, the presence of correlations between neighbouring compartments, and the non-Gaussian distribution of membrane potentials.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1011728","type":"journal-article","created":{"date-parts":[[2024,7,31]],"date-time":"2024-07-31T16:04:06Z","timestamp":1722441846000},"page":"e1011728","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multitask learning of a biophysically-detailed neuron model"],"prefix":"10.1371","volume":"20","author":[{"given":"Jonas","family":"Verhellen","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7764-3763","authenticated-orcid":true,"given":"Kosio","family":"Beshkov","sequence":"additional","affiliation":[]},{"given":"Sebastian","family":"Amundsen","sequence":"additional","affiliation":[]},{"given":"Torbj\u00f8rn V.","family":"Ness","sequence":"additional","affiliation":[]},{"given":"Gaute T.","family":"Einevoll","sequence":"additional","affiliation":[]}],"member":"340","published-online":{"date-parts":[[2024,7,31]]},"reference":[{"issue":"4","key":"pcbi.1011728.ref001","doi-asserted-by":"crossref","first-page":"424","DOI":"10.1113\/jphysiol.1952.sp004716","article-title":"Measurement of current-voltage relations in the membrane of the giant axon of Loligo","volume":"116","author":"AL Hodgkin","year":"1952","journal-title":"The Journal of physiology"},{"issue":"4","key":"pcbi.1011728.ref002","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1113\/jphysiol.1952.sp004717","article-title":"Currents carried by sodium and potassium ions through the membrane of the giant axon of Loligo","volume":"116","author":"AL Hodgkin","year":"1952","journal-title":"The Journal of physiology"},{"issue":"4","key":"pcbi.1011728.ref003","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1113\/jphysiol.1952.sp004718","article-title":"The components of membrane conductance in the giant axon of Loligo","volume":"116","author":"AL Hodgkin","year":"1952","journal-title":"The Journal of physiology"},{"issue":"4","key":"pcbi.1011728.ref004","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1113\/jphysiol.1952.sp004719","article-title":"The dual effect of membrane potential on sodium conductance in the giant axon of Loligo","volume":"116","author":"AL Hodgkin","year":"1952","journal-title":"The Journal of physiology"},{"issue":"4","key":"pcbi.1011728.ref005","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1113\/jphysiol.1952.sp004764","article-title":"A quantitative description of membrane current and its application to conduction and excitation in nerve","volume":"117","author":"AL Hodgkin","year":"1952","journal-title":"The Journal of physiology"},{"issue":"11","key":"pcbi.1011728.ref006","doi-asserted-by":"crossref","first-page":"1165","DOI":"10.1038\/81426","article-title":"The Hodgkin-Huxley theory of the action potential","volume":"3","author":"M H\u00e4usser","year":"2000","journal-title":"Nature neuroscience"},{"key":"pcbi.1011728.ref007","doi-asserted-by":"crossref","unstructured":"Brown A. 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