In many biological systems, evolution has found solutions that balance function and structure with metabolic expense. This certainly seems to be the case in the energetically expensive locomotor system, and so maybe similar efficiency optimisations exist in the central nervous system which is also energy expensive. This notion is tested against three sensory coding systems which have been well characterised, these are monochromatic and chromatic sensitive neurons in the early visual system and sound sensitive neurons of the auditory system. Simple linear models are constructed to make predictions of the optimal receptive fields that balance information coding with energy efficiency. More specifically, synaptic energy efficiency is examined and is found to predict many aspects of luminance and spatiochromatic as well as auditory coding. This approach is extended from the neural level to the higher-level domain of statistical inference where organisms build models of their environment. Balancing predictive power with explanatory simplicity results in superior descriptions of the world
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:402672 |
| Date | January 2004 |
| Creators | Vincent, Benjamin Thomas |
| Publisher | University of Sussex |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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