Mihi est from Brythonic to Breton II

Middle Breton (MB) presents an anomaly of pronominal argument coding in imperative and mihi est HAVE constructions: objects can be accusative proclitics only in 1st/2nd person, while unique enclitics appear in 3rd person. Part II traces the history of object coding: Independent > enclitic coding originates in unavailability of accusative object mesoclitics in V1 imperatives by Vendryes’ Restriction in Brythonic, and nonagreement with nominative objects of mihi est in Breton-Cornish. Restriction of enclitics to 3rd person originates with mihi est in typically nonhuman nominative object possessa in Brythonic or Breton-Cornish. It spreads to imperatives through shared enclitic coding in MB, and is circumvented by the MB innovation of accusative proclitics for mesoclitics that allows 1st/2nd person even in V1, as well as the participle in the new HAVE-perfect later in MB. “Innovative” varieties of Breton transition to regular accusative objects with or without losing dative subjects of mihi est. The developments are constrained to familiar patterns of nominative/anomalous subject + accusative/nominative object case combinations, giving rise to the imperative + HAVE construction grouping of Finnish within the history of Breton.

Object manifold geometry across the mouse cortical visual hierarchy

Despite variations in appearance we robustly recognize objects. Neuronal populations responding to objects presented under varying conditions form object manifolds and hierarchically organized visual areas are thought to untangle pixel intensities into linearly decodable object representations. However, the associated changes in the geometry of object manifolds along the cortex remain unknown. Using home cage training we showed that mice are capable of invariant object recognition. We simultaneously recorded the responses of thousands of neurons to measure the information about object identity available across the visual cortex and found that lateral visual areas LM, LI and AL carry more linearly decodable object identity information compared to other visual areas. We applied the theory of linear separability of manifolds, and found that the increase in classification capacity is associated with a decrease in the dimension and radius of the object manifold, identifying features of the population code that enable invariant object coding.