Abstract
INTRODUCTION Conceptual knowledge allows us to comprehend the multisensory stimulation impinging on our senses. Its representation in the anterior temporal lobe is the subject of considerable debate, with the "enigmatic" temporal pole (TP) being at the center of that debate. The controversial models of the organization of knowledge representation in the TP range from a unilateral/left specialization to a fully unified bilateral TP representational system. METHODS To address these contrasting options, we developed a novel cross-modal approach in a brain imaging study of Braille Reading of descriptions of objects, faces and scenes vs Tactile Exploration of raised-line drawings of these, which were then expressed through either Braille Writing or Non-Visual Drawing guided solely by memory of the respective verbal or pictorial domain inputs. RESULTS The results revealed two functional subdivisions within TP. Remarkably, each subdivision showed previously unreported anti-symmetries such as reciprocal inter-hemispheric suppression for within-domain tasks (i.e., when both reception and expression are verbal as in Braille-Writing from reading, or pictorial, as in Drawing from haptic image-exploration). Across-domain tasks, however (such as Drawing from Braille Reading), showed symmetrical bilateral activation, implying transformation of the conceptual information from the receptive format into the format of the expressive domain (e.g., from verbal into pictorial), before the expressive performance itself. Granger causality analysis differentiated the respective source and target networks involved. CONCLUSIONS Considering the two main knowledge domains (language-mediated vs pictorial/sensory-motor), and the two main knowledge processing modes (receptive and expressive), allowed us to reveal for the first time a system of complementary symmetries, asymmetries and unexpected anti-symmetries in the TP functional organization, concerning left vs right hemisphere, activation vs suppression, cooperation vs competition. We show how, taken together these results provide a unifying explanation for the conflicting models in previous research for knowledge representation.
Meeting abstract presented at VSS 2016