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A brain atlas of axonal and synaptic delays based on modelling of cortico-cortical evoked potentials

Jean-Didier Lemaréchal 1, 2, 3, 4 Maciej Jedynak 2 Lena Trebaul 2 Anthony Boyer 2 François Tadel 2 Manik Bhattacharjee 2 Pierre Deman 2 Viateur Tuyisenge 2 Leila Ayoubian 2 Etienne Hugues 2 Blandine Chanteloup-Forêt 2 Carole Saubat 2 Raouf Zouglech 2 Gina Catalina Reyes Mejia 2 Sébastien Tourbier 5 Patric Hagmann 5 Claude Adam 6 Carmen Barba 7 Fabrice Bartolomei 4 Thomas Blauwblomme 8 Jonathan Curot 9 François Dubeau 10 Stefano Francione Mercedes Garcés 11 Edouard Hirsch 12 Elizabeth Landré 13 Sinclair Liu 14 Louis Maillard 15 Eeva-Liisa Metsähonkala Ioana Mindruta 16 Anca Nica 17, 18, 19 Martin Pail 20 Ana Maria Petrescu 21 Sylvain Rheims 22 Rodrigo Rocamora 23 Andreas Schulze-Bonhage 24 William Szurhaj 25 Delphine Taussig 21 Antonio Valentin 26 Haixiang Wang 27 Philippe Kahane 2 Nathalie George 1, 3 Olivier David 2, * 
Abstract : Epilepsy presurgical investigation may include focal intracortical single-pulse electrical stimulations with depth electrodes, which induce cortico-cortical evoked potentials at distant sites because of white matter connectivity. Cortico-cortical evoked potentials provide a unique window on functional brain networks because they contain sufficient information to infer dynamical properties of large-scale brain connectivity, such as preferred directionality and propagation latencies.  Here, we developed a biologically informed modelling approach to estimate the neural physiological parameters of brain functional networks from the cortico-cortical evoked potentials recorded in a large multicentric database. Specifically, we considered each cortico-cortical evoked potential as the output of a transient stimulus entering the stimulated region, which directly propagated to the recording region. Both regions were modelled as coupled neural mass models, the parameters of which were estimated from the first cortico-cortical evoked potential component, occurring before 80 ms, using dynamic causal modelling and Bayesian model inversion. This methodology was applied to the data of 780 patients with epilepsy from the F-TRACT database, providing a total of 34 354 bipolar stimulations and 774 445 cortico-cortical evoked potentials. The cortical mapping of the local excitatory and inhibitory synaptic time constants and of the axonal conduction delays between cortical regions was obtained at the population level using anatomy-based averaging procedures, based on the Lausanne2008 and the HCP-MMP1 parcellation schemes, containing 130 and 360 parcels, respectively. To rule out brain maturation effects, a separate analysis was performed for older (>15 years) and younger patients (<15 years). In the group of older subjects, we found that the cortico-cortical axonal conduction delays between parcels were globally short (median = 10.2 ms) and only 16% were larger than 20 ms. This was associated to a median velocity of 3.9 m/s. Although a general lengthening of these delays with the distance between the stimulating and recording contacts was observed across the cortex, some regions were less affected by this rule, such as the insula for which almost all efferent and afferent connections were faster than 10 ms. Synaptic time constants were found to be shorter in the sensorimotor, medial occipital and latero-temporal regions, than in other cortical areas. Finally, we found that axonal conduction delays were significantly larger in the group of subjects younger than 15 years, which corroborates that brain maturation increases the speed of brain dynamics. To our knowledge, this study is the first to provide a local estimation of axonal conduction delays and synaptic time constants across the whole human cortex in vivo, based on intracerebral electrophysiological recordings.
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Submitted on : Tuesday, November 30, 2021 - 4:15:46 PM
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Jean-Didier Lemaréchal, Maciej Jedynak, Lena Trebaul, Anthony Boyer, François Tadel, et al.. A brain atlas of axonal and synaptic delays based on modelling of cortico-cortical evoked potentials. Brain - A Journal of Neurology , Oxford University Press (OUP), 2022, 145 (5), pp.1653-1667. ⟨10.1093/brain/awab362⟩. ⟨hal-03457509⟩

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