Abstract
Loss of bladder-control is a common condition after spinal cord injury and in the elderly population that can have devastating effects on the quality of life. Implanted devices that restore voluntary bladder function by peripheral neuromodulation, so called bioelectronic medicines, can be a localized and permanent remedy for the affected individuals. Feedback about the current bladder state, i.e., its fullness, is crucial for the correct function of these devices, and can be obtained by recording and analyzing the afferent innervation of the bladder. In the past, studies have been conducted on both the data-driven decoding of bladder pressure from afferent fibres and the physiology of single units. However, neither has the encoding of bladder-pressure by a population of sensory fibres been thoroughly analyzed, nor have decoders explicitly been tailored to the encoding principles employed by the body. We here investigate how populations of bladder afferents encode pressure by applying information theory to microelectrode-array recordings from the cat sacral dorsal root ganglion. We find an encoding scheme by three main bladder neuron types (slow tonic, phasic, and derivative fibres) that offers reliability through within-type redundancy and high information rates through near-independence of different bladder neuron types. Based on these encoding insights, we propose an adapted decoding strategy from within-type mean responses that is both accurate and robust against cell loss.
