A single parameter model of cortical organization
Jeudi 18 septembre 2014 11:30
- Duree : 1 heure
Lieu : Amphithéâtre Serge Kampf, Grenoble Institut des Neurosciences (GIN) - Bât. Edmond J. Safra, Chemin Fortune Ferrini CHU, La Tronche
Orateur : Kenneth KNOBLAUCH (Inserm U846, Stem Cell and Brain Research Institute, Bron)
The current most prevalent model of the cortico-cortical network is based on sparse data sets of the binary connectivity between areas. These data have led to a Small World (SW) characterization of the network structure with power law dependence of degree distributions that in turn leads to a set of hub areas that are highly inter-connected resulting in a rich club. Over the last 15 years, we have amassed a quantitative and consistent data base of the weighted, inter-areal connectivity among 29 areas distributed across the macaque cortex, using highly sensitive, retrograde tract tracing. We find that the inter-areal connectivity is denser than previously estimated, rendering the SW model less interesting. Instead, we find that a simple principle characterizes the network : connection weights decay exponentially with distance. This Exponential Distance Rule (EDR) can be shown to predict a surprising number of features : 1) the log-normal distribution of input weights to an area, 2) the distribution of reciprocal and non-reciprocal connections, 3) global and local weight-based communication efficiencies, the existence of a network core composed of a large number of cliques (completely interconnected areas) and overall wire-length minimization.
Markov NT, Vezoli J, Chameau P, Falchier A, Quilodran R, Huissoud C, Lamy C, Misery P, Giroud P, Ullman S, Barone P, Dehay C, Knoblauch K, Kennedy H. (2014) Anatomy of hierarchy : Feedforward and feedback pathways in macaque visual cortex J Comp neurol 522 (1) : 225 - 59.
Markov N.T., Ercsey-Ravasz M., Lamy C., Ribeiro-Gomes A.R., Magrou L., Misery P., Giroud P. Barone P., Dehay C., Toroczkai Z., Knoblauch, K., Van Essen D.C., Kennedy H. (2013) The role of long-range connections on the specificity of the macaque interareal cortical network Proceedings of the National Academy of Science, 110(13):5187-92
Kennedy H, Knoblauch K, Toroczkai Z (2013) Why data coherence and quality is critical for understanding interareal cortical network ? Neuroimage 80 : (37-45)
Ercsey-Ravasz M, Markov NT, Lamy C, Van Essen DC, Knoblauch K, Toroczkai Z, Kennedy H (2013) A Predictive Network Model of Cerebral Cortical Connectivity Based on a Distance Rule Neuron 80(1) : 184-97
Markov NT, Ercsey-Ravasz M, Van Essen DC, Knoblauch K, Toroczkai Z, Kennedy H. (2013) Cortical high-density counter-stream architectures Science 342(6158)
Contact : Michel.Dojat@ujf-grenoble.fr
Discipline évènement : (Biologie / Chimie)
Entité organisatrice : (GIN)
Nature évènement : (Séminaire)
Evènement répétitif : (Séminaire Grenoblois de Neurosciences)
Site de l'évènement : Pôle Santé / La Tronche
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