Ultrastructural characterization of synaptic terminals formed on newly generated neurons in a song control nucleus of the adult canary forebrain

The fine structure of synaptic terminals contacting neurons generated in the forebrain of adult male canaries was investigated by autoradiography and electron microscopy and the procedure for labeling the new neurons included pretreating adult canaries with 3H‐thymidine and sacrificing them 23–45 days later.

Abstract

The fine structure of synaptic terminals contacting neurons generated in the forebrain of adult male canaries was investigated by autoradiography and electron microscopy. The procedure for labeling the new neurons included pretreating adult canaries with 3H-thymidine and sacrificing them 23-45 days later. Neurons were identified as newly generated by the presence of 3H-thymidine in the cell nucleus. The new neurons in the nucleus hyperstriatum ventralis, pars caudalis (HVc) were identified by autoradiography and light microscopy and examined with electron microscopy. Several types of synaptic terminals contacted the cell body and proximal dendrites of the newly formed neurons. Synaptic junctions were formed by terminals that contained spherical, agranular vesicles, large dense-core vesicles and spherical, agranular vesicles, and pleomorphic or flattened synaptic vesicles. Terminals that contained spherical vesicles were most often associated with asymmetric synaptic densities, and terminals that contained pleomorphic or flattened vesicles formed symmetric junctions. New neurons were also contacted by small terminals that contained few vesicles and had little pre- or postsynaptic density associated with the junction; these terminals may be a special type or may be in the process of developing their synaptic contact with the new neuron. In addition, rare terminals that appeared to be degenerating or to contain debris from other degenerating neural elements contacted new neurons. In summary, these data indicate that the new neurons, which are known to be inserted into existing neural networks, receive synaptic input from at least three different sources.