Hierarchical order in the cortex.

Julien Vezoli (1) , Marie-Alice Gariel (1, 2) , Nikola Markov (1) , John C. Anderson (3) , Rodney Douglas (3) , Kevan A.C. Martin (3) , Kenneth Knoblauch (1) , Henry Kennedy (1)

1 SBRI - Institut cellule souche et cerveau
2 Netherlands Institute for Neuroscience
3 Institute for Neuroinformatics

Strong regularities of early visual areas interconnections led to the suggestion that rostral directed connections are feedforward (FF) pathways channelling information from lower to higher order areas, while caudal directed connections constitute feedback (FB) pathways (Rockland and Pandya, 1979). Analysis of these pathways in primate enabled the identification of a hierarchical organization (Felleman and Van Essen, 1991), providing a major conceptual framework for understanding structure-function relationships of the cortex. Because previous description of cortical topology have been restricted to binary connectivity leading to strong indeterminacy (Hilgetag et al., 1996), we re-examined network description of cortex structure by making retrograde tracer injections in areas spanning all cortical lobes. We used quantitative tools to estimate hierarchical distance and relative weights of connections (Barone et al., 2000, Vezoli et al., 2004) and used computational modeling analysis to analyse the underlying hierarchical structure of cortical networks. Comparing weighted and unweighted analyses, we demonstrated a significant hierarchical tendency in the pattern of laminar relations between cortical areas. Further, we evidenced a highly parallel system with high degree of reciprocity and found that rare pairs of areas are reciprocally connected by FF connections, constituting unexpected descending paths (Crick and Koch, 1998) in an otherwise surprisingly hierarchical system of cortical areas.

Mots clés: Connectionnist models; Others

Domaines: Neurosciences [q-bio.NC]; Neurosciences

Julien Vezoli, Marie-Alice Gariel, Nikola Markov, John C. Anderson, Rodney Douglas, et al.. Hierarchical order in the cortex.. Cinquième conférence plénière française de Neurosciences Computationnelles, "Neurocomp'10", Aug 2010, Lyon, France. ⟨hal-00553406⟩