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(1995). Neuronal circuitry of the lower urinary tract : central and peripheral neuronal control of the micturition cycle. Anatomy and Embryology, 192(3), 195-209. DOI: 10.1007 /BF00184744General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Anat Embryol (1995) 192:195-209 9 Springer-Verlag 1995 Abstract A new presentation technique is introduced to describe the neuronal circuitry involved in the control of the uropoEtic system and its control mechanisms during the micturition cycle. This method is based on the preparation of flow charts and is applied to the discussion of four qualitative models which are derived from the literature. Opinions concerning the reflex arcs and supraspinal connections said to be involved in micturition and continence are different and sometimes contradictory. Little is known about how autonomic information from the lower urinary tract is relayed to supraspinal structures. Information about supraspinal (inter)connections and their function in micturition control is still fragmentary. The control mechanisms which terminate voiding are not totally clear. Moreover, the role of the pelvic floor musculature in the control of the lower urinary tract is probably underestimated. The flow charts presented in this paper contribute to the future design of a single complete qualitative model representing the general central and peripheral nervous connections and control mechanisms. Such a model would provide an approach for future research in neuromodulation and neurostimulation of the uropoetic system and a reduced version could be used for quantitative modelling, e.g. in neural network simulations.

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A continuous neural network coupled to a dynamical model of the urinary bladder IS defined. The neural network is trained to control the bladder model to track a prescribed volume fluctuation, by adjusting weights and time constants. The gradients of the error in the output neurons of the neural network are unknown. Therefore, the learning procedure discussed here minimizes the error functional without using gradient descent.