FUNCTIONAL-ANALYSIS OF THE SENSORY-MOTOR PATHWAY OF RESISTANCE REFLEXIN CRAYFISH - II - INTEGRATION OF SENSORY INPUTS IN MOTOR-NEURONS

The in vitro preparation of the fifth thoracic ganglion of the crayfis h was used to analyze the connections supporting the monosynaptic refl ex responses recorded from the depressor motor neurons (Dep MNs). Dep MNs are directly connected by the release-sensitive afferents from a p roprioceptor, the coxo-basipodite chordotonal organ (CBCO), which is r eleased by upward movements of the leg. Sine-wave movements, applied t o the CBCO strand from the most released position, allowed us to stimu late the greatest part of release-sensitive CBCO fibers. Systematic in tracellular recordings from all Dep MNs performed in high divalent cat ion saline allowed us to determine the connections between CBCO affere nts and their postsynaptic Dep MNs: it highlighted the sequential acti vation of the different Dep MNs involved in the monosynaptic reflex. T he convergence of different sensory afferents onto a given Dep MN, and the divergence of a given sensory afferent onto several Dep MNs illus trates the complexity of the sensory-motor reflex loops involved in th e control of locomotion and posture. Electrophysiological experiments and simulations were performed to analyze the mechanisms by which Dep MNs integrate the large amount of sensory input that they receive. Pai red intracellular recording experiments demonstrated that postsynaptic response shapes characteristic of both phasic and phase-tonic afferen ts could be induced by varying the presynaptic firing frequency, whate ver the postsynaptic Dep MN. Compartment model simulations were used t o analyze the role of the sensory-motor synapse characteristics in the summation properties of postsynaptic MN. They demonstrated the import ance of the postsynaptic compartment geometry, because large postsynap tic compartments allowed to generate greater excitatory postsynaptic p otential (EPSP) summations than small ones. The results presented show that velocity information is the most effective to elicit large compo und EPSPs in MNs. We therefore suggest that the negative feedback refl ex is mainly based on the detection of leg movements.