Photoreceptors of the vertebrate retina are known to release the neurotransmitter in the dark and decrease the rate of neurotransmitter release during the graded hyperpolarization in response to the light. To transmit such graded signal to the second order neurons, intracellular Ca2+ concentration ([Ca2+]i) of the photoreceptor terminal is considered to be regulated with the level of hyperpolarization. The purpose of the present study is to elucidate how [Ca2+]i of the cone photoreceptor terminal is regulated by the Ca2+ conductance and the plasma membrane calcium ATPase (PMCA) with the aid of computer simulations. Physiologically realistic models of the Ca2+ conductance and the PMCA of the mammalian cone photoreceptor inner segment were reconstructed from the voltage clamp and Ca2+ imaging experiments which were carried out on the isolated photoreceptor inner segments in previous studies. The physiological ranges of parameters of the model equations describing the voltage-gated calcium channels were estimated by referring to previous experiments. The parameters of the model equation describing the PMCA were estimated by assuming steady levels of [Ca2+]i. Dynamical change of [Ca2+]i at the terminal region was calculated using the estimated parameters. When the conductance and PMCA are evenly distributed in entire model terminal, [Ca2+]i was reduced from 1-2µM to 30nM in response to a voltage change from -45mV to -55mV which is relevant to the light-induced hyperpolarization to moderate light. The model of physiological mechanisms developed in the present study can be used to elucidate the underlying mechanisms of the light-induced response of the cone photoreceptor terminal in situ.
An associative memory model is useful not only for application of information science but for brain's model. In this paper, an associative memory model is employed to elucidate the mechanisms of neuronal responses in the inferior-temporal (IT) cortex. The behavior of the model qualitatively coincides with the responses of IT neurons. Furthermore, we propose three physiological experiments and predict the results from our model. If the results obtained by actual physiological experiments coincide with our predicted results, the associative memory model might be the mechanisms producing the responses of the IT neurons.
Associative memory in neural-neural network systems has long been described by dynamical systems with discrete attractors. Recent neurophysiological findings of graded persistent activity, however, suggest that memory retrieval in the brain is more likely to be described by dynamical systems with continuous attractors. This paper briefly reviews experimental studies of graded persistent activity and computational studies for modelling its neural mechanisms by continuous attractor dynamics. Furthermore, their implications for associative memory are discussed.