Thursday, 5th of December 2019, 12:00 – 1:00

Biologically inspired visual-auditory processing – from brain-like computation to neuromorphic algorithms

SR1, ICT Building,
Technikerstraße 21a, 6020 Innsbruck

Heiko Neumann
Ulm University, Inst. of Neural Information Processing


A fundamental task of sensory processing is to detect and integrate feature items to group them into perceptual units segregating them from other objects and the background. A framework is discussed which explains how perceptual grouping at early as well as higher-level cognitive stages may be implemented in cortex. Different grouping mechanisms are implemented which are attuned to basic features and feature combinations and mainly evaluated along the forward sweep of stimulus processing. However, due to limitations of local feature detection mechanisms and inherent ambiguities, top-down feedback is required to deliver contextual information helping to disambiguate initial measurements. Feedback of contextual information is demonstrated to improve object recognition performance, stabilize learning of object categories, and integrate multi-sensory representations.

The canonical principles of neural computation define a set of core operations to implement above-mentioned mechanisms of perceptual and cognitive inference. These operations can be mapped, in a simplified form, onto neuromorphic platforms to emulate brain-like computation. It is demonstrated that an architecture composed of canonical circuit mechanisms can be mapped onto neuromorphic chip technology facilitating low-energy non-von Neumann computation.



Work supported by DFG & Baden-Württemberg Foundation


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