Structure and function relationship in the abdominal stretch receptor organs of the crayfish


Purali N.

JOURNAL OF COMPARATIVE NEUROLOGY, cilt.488, sa.4, ss.369-383, 2005 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 488 Sayı: 4
  • Basım Tarihi: 2005
  • Doi Numarası: 10.1002/cne.20590
  • Dergi Adı: JOURNAL OF COMPARATIVE NEUROLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.369-383
  • Hacettepe Üniversitesi Adresli: Evet

Özet

The structure/function relationship in the rapidly and slowly adapting stretch receptor organs of the crayfish (Astacus leptodactylus) was investigated using confocal microscopy and neuronal modeling methods. Both receptor muscles were single muscle fibers with structural properties closely related to the function of the receptors. Dendrites of the rapidly adapting neuron terminated in a common pile of nerve endings going in all directions. Dendrites of the slowly adapting neuron terminated in a characteristic T shape in multiple regions of the receptor muscle. The slowly adapting main dendrite, which was on average 2.1 times longer and 21% thinner than the rapidly adapting main dendrite, induced larger voltage attenuation. The somal surface area of the slowly adapting neuron was on average 51% larger than that of the rapidly adapting neuron. Variation in the neuronal geometry was greatest among the slowly adapting neurons. A computational model of a neuron pair demonstrated. that the rapidly and the slowly adapting neurons attenuated the dendritic receptor potential like low-pass filters with cut-off frequencies at 100 and 20 Hz, respectively. Recurrent dendrites were observed mostly in the slowly adapting neurons. Voltage signals were calculated to be propagated 23% faster in the rapidly adapting axon, which is 51% thicker than the slowly adapting axon. The present findings support the idea that the morphology of the rapidly and the slowly adapting neurons evolved to optimally sense the dynamic and the static features of the mechanical stimulus, respectively. (c) 2005 Wiley-Liss, Inc.