NONLINEAR MODELS OF THE FIRST SYNAPSE IN THE LIGHT-ADAPTED FLY RETINA

1. Randomly modulated light stimuli were used to characterize the nonl inear dynamic properties of the synapse between photoreceptors and lar ge monopolar neurons (LMC) in the fly retina. Membrane potential fluct uations produced by constant variance contrast stimuli were recorded a t eight different levels of background light intensity. 2. Representat ion of the photoreceptor-LMC input-output data in the form of traditio nal characteristic curves indicated that synaptic gain was reduced by light adaptation. However, this representation did not include the tim e-dependent properties of the synaptic function, which are known to be nonlinear. Therefore nonlinear systems analysis was used to character ize the synapse. 3. The responses of photoreceptors and LMCs to random light fluctuations were characterized by second-order Volterra series , with kernel estimation by the parallel cascade method. Photoreceptor responses were approximately linear, but LMC responses were clearly n onlinear. 4. Synaptic input-output relationships were measured by pass ing the light stimuli to LMCs through the measured photoreceptor chara cteristics to obtain an estimate of the synaptic input. The resulting nonlinear synaptic functions were well characterized by second-order V olterra series. They could not be modeled by a linear-nonlinear-linear cascade but were better approximated by a nonlinear-linear-nonlinear cascade. 5. These results support two possible structural models of th e synapse, the first having two parallel paths for signal flow between the photoreceptor and LMC, and the second having two distinct nonline ar operations, occurring before and after chemical transmission. 6. Th e two models were each used to calculate the synaptic gain to a brief change in photoreceptor membrane potential. Both models predicted that synaptic gain is reduced by light adaptation.