Neural Engineering: Computation, Representation, and Dynamics in Neurobiological Systems. Computational Neuroscience. By Chris  Eliasmithand , Charles H  Anderson. A Bradford Book. Cambridge (Massachusetts): MIT Press. $49.95. xx + 356 p; ill.; index. ISBN: 0–262–05071–4. 2003.

2004 ◽  
Vol 79 (3) ◽  
pp. 333-333
Author(s):  
Allen Selverston
Keyword(s):  
Computational Neuroscience ◽  
Neural Engineering ◽  
Engineering Computation

Perception

2018 ◽  
Author(s):  
Joel Z. Leibo ◽  
Tomaso Poggio
Keyword(s):  
Computational Neuroscience ◽  
Feature Detection ◽  
Pedestrian Detection ◽  
Detection Systems ◽  
Catching Up ◽  
Feature Detectors ◽  
Recognition Systems ◽  
Engineered Systems ◽  
Perceptual Systems ◽  
The Brain

This chapter provides an overview of biological perceptual systems and their underlying computational principles focusing on the sensory sheets of the retina and cochlea and exploring how complex feature detection emerges by combining simple feature detectors in a hierarchical fashion. We also explore how the microcircuits of the neocortex implement such schemes pointing out similarities to progress in the field of machine vision driven deep learning algorithms. We see signs that engineered systems are catching up with the brain. For example, vision-based pedestrian detection systems are now accurate enough to be installed as safety devices in (for now) human-driven vehicles and the speech recognition systems embedded in smartphones have become increasingly impressive. While not being entirely biologically based, we note that computational neuroscience, as described in this chapter, makes up a considerable portion of such systems’ intellectual pedigree.

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