Probabilistic functional tractography of the human cortex
revisited

J 2018

Probabilistic functional tractography of the human cortex revisited

TREBAUL, Lena; Pierre DEMAN; Viateur TUYISENGE; Maciej JEDYNAK; Etienne HUGUES et al.

Základní údaje

Originální název

Probabilistic functional tractography of the human cortex revisited

Autoři

TREBAUL, Lena; Pierre DEMAN; Viateur TUYISENGE; Maciej JEDYNAK; Etienne HUGUES; David RUDRAUF; Manik BHATTACHARJEE; Francois TADEL; Blandine CHANTELOUP-FORET; Caroline SAUBAT; Gina Catalina Reyes MEJIA; Claude ADAM; Anca NICA; Martin PAIL; Francois DUBEAU; Sylvain RHEIMS; Agnes TREBUCHON; Haixiang WANG; Sinclair LIU; Thomas BLAUWBLOMME; Mercedes GARCES; Luca DE PALMA; Antonio VALENTIN; Eeva-Liisa METSAHONKALA; Ana Maria PETRESCU; Elizabeth LANDRE; William SZURHAJ; Edouard HIRSCH; Luc VALTON; Rodrigo ROCAMORA; Andreas SCHULZE-BONHAGE; Ioana MINDRUTA; Stefano FRANCIONE; Louis MAILLARD; Delphine TAUSSIG; Philippe KAHANE a Olivier DAVID

Vydání

Neuroimage, San Diego, ACADEMIC PRESS INC ELSEVIER SCIENCE, 2018, 1053-8119

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30103 Neurosciences

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Impakt faktor

Impact factor: 5.812

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14110/18:00104225

Organizační jednotka

Lékařská fakulta

Klíčová slova anglicky

Brain atlas; Epilepsy; Intracranial electroencephalogram; Cortico-cortical evoked potentials; Connectivity mapping

Štítky

14110127, rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 10. 2. 2019 18:03, Soňa Böhmová

Anotace

V originále

In patients with pharmaco-resistant focal epilepsies investigated with intracranial electroencephalography (iEEG), direct electrical stimulations of a cortical region induce cortico-cortical evoked potentials (CCEP) in distant cerebral cortex, which properties can be used to infer large scale brain connectivity. In 2013, we proposed a new probabilistic functional tractography methodology to study human brain connectivity. We have now been revisiting this method in the F-TRACT project (f-tract.eu) by developing a large multicenter CCEP database of several thousand stimulation runs performed in several hundred patients, and associated processing tools to create a probabilistic atlas of human cortico-cortical connections. Here, we wish to present a snapshot of the methods and data of F-TRACT using a pool of 213 epilepsy patients, all studied by stereo-encephalography with intracerebral depth electrodes. The CCEPs were processed using an automated pipeline with the following consecutive steps: detection of each stimulation run from stimulation artifacts in raw intracranial EEG (iEEG) files, bad channels detection with a machine learning approach, model-based stimulation artifact correction, robust averaging over stimulation pulses. Effective connectivity between the stimulated and recording areas is then inferred from the properties of the first CCEP component, i.e. onset and peak latency, amplitude, duration and integral of the significant part. Finally, group statistics of CCEP features are implemented for each brain parcel explored by iEEG electrodes. The localization (coordinates, white/gray matter relative positioning) of electrode contacts were obtained from imaging data (anatomical MRI or CT scans before and after electrodes implantation). The iEEG contacts were repositioned in different brain parcellations from the segmentation of patients' anatomical MRI or from templates in the MNI coordinate system. The F-TRACT database using the first pool of 213 patients provided connectivity probability values for 95% of possible intrahemispheric and 56% of interhemispheric connections and CCEP features for 78% of intrahemisheric and 14% of interhemispheric connections. In this report, we show some examples of anatomo-functional connectivity matrices, and associated directional maps. We also indicate how CCEP features, especially latencies, are related to spatial distances, and allow estimating the velocity distribution of neuronal signals at a large scale. Finally, we describe the impact on the estimated connectivity of the stimulation charge and of the contact localization according to the white or gray matter. The most relevant maps for the scientific community are available for download on f-tract. eu (David et al., 2017) and will be regularly updated during the following months with the addition of more data in the F-TRACT database. This will provide an unprecedented knowledge on the dynamical properties of large fiber tracts in human.

Citovat

@article{1456217,
   author = {Trebaul, Lena and Deman, Pierre and Tuyisenge, Viateur and Jedynak, Maciej and Hugues, Etienne and Rudrauf, David and Bhattacharjee, Manik and Tadel, Francois and ChanteloupandForet, Blandine and Saubat, Caroline and Mejia, Gina Catalina Reyes and Adam, Claude and Nica, Anca and Pail, Martin and Dubeau, Francois and Rheims, Sylvain and Trebuchon, Agnes and Wang, Haixiang and Liu, Sinclair and Blauwblomme, Thomas and Garces, Mercedes and De Palma, Luca and Valentin, Antonio and Metsahonkala, EevaandLiisa and Petrescu, Ana Maria and Landre, Elizabeth and Szurhaj, William and Hirsch, Edouard and Valton, Luc and Rocamora, Rodrigo and SchulzeandBonhage, Andreas and Mindruta, Ioana and Francione, Stefano and Maillard, Louis and Taussig, Delphine and Kahane, Philippe and David, Olivier},
   article_location = {San Diego},
   article_number = {NOV 1 2018},
   doi = {https://doi.org/10.1016/j.neuroimage.2018.07.039},
   keywords = {Brain atlas; Epilepsy; Intracranial electroencephalogram; Cortico-cortical evoked potentials; Connectivity mapping},
   language = {eng},
   issn = {1053-8119},
   journal = {Neuroimage},
   title = {Probabilistic functional tractography of the human cortex revisited},
   volume = {181},
   year = {2018}
}

TY  - JOUR
ID  - 1456217
AU  - Trebaul, Lena - Deman, Pierre - Tuyisenge, Viateur - Jedynak, Maciej - Hugues, Etienne - Rudrauf, David - Bhattacharjee, Manik - Tadel, Francois - Chanteloup-Foret, Blandine - Saubat, Caroline - Mejia, Gina Catalina Reyes - Adam, Claude - Nica, Anca - Pail, Martin - Dubeau, Francois - Rheims, Sylvain - Trebuchon, Agnes - Wang, Haixiang - Liu, Sinclair - Blauwblomme, Thomas - Garces, Mercedes - De Palma, Luca - Valentin, Antonio - Metsahonkala, Eeva-Liisa - Petrescu, Ana Maria - Landre, Elizabeth - Szurhaj, William - Hirsch, Edouard - Valton, Luc - Rocamora, Rodrigo - Schulze-Bonhage, Andreas - Mindruta, Ioana - Francione, Stefano - Maillard, Louis - Taussig, Delphine - Kahane, Philippe - David, Olivier
PY  - 2018
TI  - Probabilistic functional tractography of the human cortex revisited
JF  - Neuroimage
VL  - 181
IS  - NOV 1 2018
SP  - 414-429
EP  - 414-429
PB  - ACADEMIC PRESS INC ELSEVIER SCIENCE
SN  - 10538119
KW  - Brain atlas
KW  - Epilepsy
KW  - Intracranial electroencephalogram
KW  - Cortico-cortical evoked potentials
KW  - Connectivity mapping
N2  - In patients with pharmaco-resistant focal epilepsies investigated with intracranial electroencephalography (iEEG), direct electrical stimulations of a cortical region induce cortico-cortical evoked potentials (CCEP) in distant cerebral cortex, which properties can be used to infer large scale brain connectivity. In 2013, we proposed a new probabilistic functional tractography methodology to study human brain connectivity. We have now been revisiting this method in the F-TRACT project (f-tract.eu) by developing a large multicenter CCEP database of several thousand stimulation runs performed in several hundred patients, and associated processing tools to create a probabilistic atlas of human cortico-cortical connections. Here, we wish to present a snapshot of the methods and data of F-TRACT using a pool of 213 epilepsy patients, all studied by stereo-encephalography with intracerebral depth electrodes. The CCEPs were processed using an automated pipeline with the following consecutive steps: detection of each stimulation run from stimulation artifacts in raw intracranial EEG (iEEG) files, bad channels detection with a machine learning approach, model-based stimulation artifact correction, robust averaging over stimulation pulses. Effective connectivity between the stimulated and recording areas is then inferred from the properties of the first CCEP component, i.e. onset and peak latency, amplitude, duration and integral of the significant part. Finally, group statistics of CCEP features are implemented for each brain parcel explored by iEEG electrodes. The localization (coordinates, white/gray matter relative positioning) of electrode contacts were obtained from imaging data (anatomical MRI or CT scans before and after electrodes implantation). The iEEG contacts were repositioned in different brain parcellations from the segmentation of patients' anatomical MRI or from templates in the MNI coordinate system. The F-TRACT database using the first pool of 213 patients provided connectivity probability values for 95% of possible intrahemispheric and 56% of interhemispheric connections and CCEP features for 78% of intrahemisheric and 14% of interhemispheric connections. In this report, we show some examples of anatomo-functional connectivity matrices, and associated directional maps. We also indicate how CCEP features, especially latencies, are related to spatial distances, and allow estimating the velocity distribution of neuronal signals at a large scale. Finally, we describe the impact on the estimated connectivity of the stimulation charge and of the contact localization according to the white or gray matter. The most relevant maps for the scientific community are available for download on f-tract. eu (David et al., 2017) and will be regularly updated during the following months with the addition of more data in the F-TRACT database. This will provide an unprecedented knowledge on the dynamical properties of large fiber tracts in human.
ER  -

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