title: An automated workflow for the anatomo-functional mapping of the barrel cortex.
abstract: BACKGROUND
  The rodent barrel cortex is a widely used model to study the cortical processing of tactile sensory information. It is notable by the cytoarchitecture of its layer IV, which contains distinguishable structural units called barrels that can be considered as anatomical landmarks of the functional columnar organization of the cerebral cortex. To study sensory integration in the barrel cortex it is therefore essential to map recorded functional data onto the underlying barrel topography, which can be reconstructed from the post hoc alignment of tangential brain slices stained for cytochrome oxidase.
  
  
  METHODS
  This article presents an automated workflow to perform the registration of histological slices of the barrel cortex followed by the 2-D reconstruction of the barrel map from the registered slices. The registration of two successive slices is obtained by computing a rigid transformation to align sets of detected blood vessel cross-sections. This is achieved by using a robust variant of the classical iterative closest point method. A single fused image of the barrel field is then generated by computing a nonlinear merging of the gradients from the registered images.
  
  
  METHODS
  This novel anatomo-functional mapping tool leads to a substantial gain in time and precision compared to conventional manual methods. It provides a flexible interface for the user with only a few parameters to tune.
  
  
  CONCLUSIONS
  We demonstrate here the usefulness of the method for voltage sensitive dye imaging of the mouse barrel cortex. The method could also benefit other experimental approaches and model species.
authors.affiliation: CNRS and Ceremade, Université Paris-Dauphine, Place du Maréchal De Lattre De Tassigny, 75775, Paris Cedex 16, France; Unité de Neurosciences, Information et Complexité, CNRS FRE 3693, 91198 Gif-sur-Yvette Cedex, France.
authors.forename: Lorraine
authors.initials: L
authors.lastname: Perronnet
authors.affiliation: Unité de Neurosciences, Information et Complexité, CNRS FRE 3693, 91198 Gif-sur-Yvette Cedex, France.
authors.forename: María Eugenia
authors.initials: ME
authors.lastname: Vilarchao
authors.affiliation: Unité de Neurosciences, Information et Complexité, CNRS FRE 3693, 91198 Gif-sur-Yvette Cedex, France.
authors.forename: Guillaume
authors.initials: G
authors.lastname: Hucher
authors.affiliation: Unité de Neurosciences, Information et Complexité, CNRS FRE 3693, 91198 Gif-sur-Yvette Cedex, France.
authors.forename: Daniel E
authors.initials: DE
authors.lastname: Shulz
authors.affiliation: CNRS and Ceremade, Université Paris-Dauphine, Place du Maréchal De Lattre De Tassigny, 75775, Paris Cedex 16, France.
authors.forename: Gabriel
authors.initials: G
authors.lastname: Peyré
authors.affiliation: Unité de Neurosciences, Information et Complexité, CNRS FRE 3693, 91198 Gif-sur-Yvette Cedex, France. Electronic address: isabelle.ferezou@unic.cnrs-gif.fr.
authors.forename: Isabelle
authors.initials: I
authors.lastname: Ferezou
mesh_terms: D000818:Animals; D001808:Blood Vessels / Q000033:anatomy & histology; D001931:Brain Mapping; D051379:Mice; D009716:Numerical Analysis, Computer-Assisted; D010812:Physical Stimulation; D013003:Somatosensory Cortex / Q000033:anatomy & histology* / Q000502:physiology*; D014738:Vibrissae / Q000294:innervation; D056969:Voltage-Sensitive Dye Imaging; D057188:Workflow
keywords: Barrel cortex; Blood vessels; Gradient domain fusion; Histological sections; Registration; Robust iterative closest point; Voltage sensitive dye imaging