Subcellular, cellular, and circuit mechanisms underlying classical conditioning in Hermissenda crassicornis.
A breakthrough for studying the neuronal basis of learning emerged when invertebrates with simple nervous systems, such as the sea slug Hermissenda crassicornis, were shown to exhibit classical conditioning. Hermissenda learns to associate light with turbulence: prior to learning, naive animals move toward light (phototaxis) and contract their foot in response to turbulence; after learning, conditioned animals delay phototaxis in response to light. The photoreceptors of the eye, which receive monosynaptic inputs from statocyst hair cells, are both sensory neurons and the first site of sensory convergence. The memory of light associated with turbulence is stored as changes in intrinsic and synaptic currents in these photoreceptors. The subcellular mechanisms producing these changes include activation of protein kinase C and MAP kinase, which act as coincidence detectors because they are activated by convergent signaling pathways. Pathways of interneurons and motorneurons, where additional changes in excitability and synaptic connections are found, contribute to delayed phototaxis. Bursting activity recorded at several points suggest the existence of small networks that produce complex spatiotemporal firing patterns. Thus, the change in behavior may be produced by a nonlinear transformation of spatiotemporal firing patterns caused by plasticity of synaptic and intrinsic channels. The change in currents and the activation of PKC and MAPK produced by associative learning are similar to those observed in hippocampal and cerebellar neurons after rabbit classical conditioning, suggesting that these represent general mechanisms of memory storage. Thus, the knowledge gained from further study of Hermissenda will continue to illuminate mechanisms of mammalian learning.
Blackwell
Kim T
KT
School of Computational Sciences, and the Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA 22030, USA. avrama@gmu.edu
D000818:Animals; D001245:Association Learning / Q000502:physiology*; D003198:Computer Simulation; D003214:Conditioning, Classical / Q000502:physiology*; D049870:Hermissenda / Q000502:physiology*; D006801:Humans; D007473:Ion Channels / Q000502:physiology; D008027:Light; D008568:Memory; D009474:Neurons / Q000502:physiology; D010786:Photoreceptor Cells / Q000502:physiology; D015398:Signal Transduction; D013569:Synapses
D007473:Ion Channels