Morphological development of thick-tufted layer V pyramidal cells in the rat somatosensory cortex

• ¹ Blue Brain Project, École Polytechnique FÉdÉrale de Lausanne, Lausanne, Switzerland
• ² School of Optometry and Ophthalmology, Wenzhou Medical College, Wenzhou, Zhejiang, People’s Republic of China
• ³ Neurology Research, Caritas St. Elizabeth’s Medical Center, Tufts University, Boston, MA, USA
• ⁴ School of Biomedical Sciences, University of Nottingham, Nottingham, UK

The thick-tufted layer V pyramidal (TTL5) neuron is a key neuron providing output from the neocortex. Although it has been extensively studied, principles governing its dendritic and axonal arborization during development are still not fully quantified. Using 3-D model neurons reconstructed from biocytin-labeled cells in the rat somatosensory cortex, this study provides a detailed morphological analysis of TTL5 cells at postnatal day (P) 7, 14, 21, 36, and 60. Three developmental periods were revealed, which were characterized by distinct growing rates and properties of alterations in different compartments. From P7 to P14, almost all compartments grew fast, and filopodia-like segments along apical dendrite disappeared; From P14 to P21, the growth was localized on specified segments of each compartment, and the densities of spines and boutons were significantly increased; From P21 to P60, the number of basal dendritic segments was significantly increased at specified branch orders, and some basal and oblique dendritic segments were lengthened or thickened. Development changes were therefore seen in two modes: the fast overall growth during the first period and the slow localized growth (thickening mainly on intermediates or lengthening mainly on terminals) at the subsequent stages. The lengthening may be accompanied by the retraction on different segments. These results reveal a differential regulation in the arborization of neuronal compartments during development, supporting the notion of functional compartmental development. This quantification provides new insight into the potential value of the TTL5 morphology for information processing, and for other purposes as well.