Repeated oesophageal acidification causes lower oesophageal sphincter (LOS) relaxation in the anaesthetized ferret which is mediated by a peripheral neurokinin (NK-1) receptor mechanism. Our aim in this study was to characterize neural pathways in the LOS activated by capsaicin and tachykinin receptor agonists in vitro. Circular muscle strips of LOS (two per animal) from a total of 24 ferrets were maintained in organ baths. Electrical field stimulation (EFS, 50 V, 5-50 Hz) caused frequency-dependent LOS relaxation which was abolished by tetrodotoxin (TTX; 10(-6) M: P < 0.001) and reduced by N(G)-nitro-L-arginine (L-NNA; 10(-4) M: P < 0.01). Substance P and [Sar9, Met (O2)11]-substance P (selective NK-1 agonist) caused dose-dependent relaxation, while the NK-2 receptor agonist [beta-Ala8]-NKA 4-10 evoked excitation. Capsaicin (10(-6) M) caused relaxation and desensitization that was overcome by long recovery periods and substance P dosing (10(-8) M). After pretreatment with the NK-1 receptor antagonist CP 99994 (10(-7) M), substance P (10(-8) M; P < 0.001) and capsaicin (10(-6) M: P < 0.01)-induced relaxations were reduced. In the presence of TTX (10(-6) M), excitation resulted in response to substance P (10(-8) M; P < 0.05) and [Sar9, Met (O2)11]-substance P (10(-8) M; P < 0.001), while the response to [beta-Ala8]-NKA 4-10 (10(-7) M) was unaffected. In the presence of L-NNA (10(-4) M), substance P and [Sar9, Met (O2)11]-substance P-induced relaxations were reduced (10(-8) M; P < 0.01), while the response to [beta-Ala8]-NKA 4-10 (10(-7) M) was unaffected. These results show that functional coupling between capsaicin-sensitive sensory neurones and NANC inhibitory neural pathways occurs via NK-1 receptors in the ferret LOS. NK-2 (and some NK-1) receptors activate non-neural excitatory mechanisms. Substance P and NK-1 receptors coupling sensory and NANC inhibitory neurones may be important in the reflex control of LOS motility.
Staged assimilation is a means of extracting information from a sequence of related images. It is used to develop feature detectors of transformationinvariant properties. It is applied within a hierarchical network, referred to as the bi-panel architecture. Temporal response properties of neurons are used to capture this information.High-level feature detectors arise by grouping sequentially detected low level features into equivalence classes. When the system is exposed to imagery undergoing a continuous transformation, it develops detectors for properties that tend to remain constant over time. This is how it forms invariant feature detectors.This paper explains how the approach derives from studies of the visual cortex and J. J. Gibson's theory of perception. An example is given of how it works and details of the system's operation are discussed. Finally, its relationship to other' learning paradigms and networks is described.
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