What is neuronal computation?
The term neural computation is basically synonymous with computational neuroscience.  It is the science of studying how the brain processes information by creating realistic mathematical models. Unlike general study of artificial neural networks (ANNs), neural computation heavily relies on biological accurateness. However, it may use models from ANN research, and vice versa.

Also see this course description of the PhD level course "Neural Computation" at Carnegie Mellon University  (CMU) :  


  Neural Computation is an area of interdisciplinary study that seeks to
  understand how the brain computes to achieve natural intelligence. It
  seeks to understand the computational principles and mechanisms of
  intelligent behaviors and mental abilities -- such as perception,
  language, motor control, and learning -- by building artificial
  systems and computational models with the same capabilities. This
  course explores how neurons encode and process information, adapt and
  learn, communicate and compute at the individual level as well as at
  the levels of networks and systems. It will cover basic concepts in
  computational and neuronal modeling, information theory and coding,
  neural networks and learning, neural data analysis and decoding,
  signal processing and system analysis, statistical learning and
  probabilistic inference.


(Emphasis mine)