Neural Control of Actions Involving Different Coordinate Systems

Sigma-Pi units lend themselves to the task of frame of reference transformations. Multiplicative attentional control can dynamically route information from a region of interest within the visual field to a higher area (Andersen et al, 2004). With an architecture involving Sigma-Pi weights activation patters can be dynamically routed, as we have shown in Fig. 8 b). In a model by Grimes and Rao (2005) the dynamic routing of information is combined with feature extraction. Since the number of hidden units to be activated depends on the inputs, they need an iterative procedure to obtain the hidden code. In our scenario only the position of a stereotyped activation hill is estimated. This allows us to use a simpler, SOM-like algorithm. 7.1 Are Sigma-Pi Units Biologically Realistic? A real neuron is certainly more complex than a standard connectionist neuron which performs a weighted sum of its inputs. For example, there exists input, such as shunting inhibition (Borg-Graham et al., 1998; Mitchell & Silver, 2003), which has a multiplicative effect on the remaining input. However, such potentially multiplicative neural input often targets the cell soma or proximal dendrites (Kandel et al., 1991). Hence, multiplicative neural influence is rather about gain modulation than about individual synaptic modulation. A Sigma-Pi unit model proposes that for each synapse from an input neuron, there is a further input from a third neuron (or even a further "receptive field" from within a third neural layer). There is a debate about potential multiplicative mutual influences between synapses, happening particularly when synapses gather in clusters at the postsynaptic dendrites (Mel, 2006). It is a challenge to implement the transformation of our Sigma-Pi network with more established neuron models, or with biologically faithful models.

@InCollection{WETW07, 
 	 author =  {Weber, Cornelius and Elshaw, Mark I. and Triesch, Jochen and Wermter, Stefan},  
 	 title = {Neural Control of Actions Involving Different Coordinate Systems}, 
 	 booktitle = {Humanoid Robots: Human-like Machines},
 	 number = {},
 	 volume = {},
 	 pages = {577--600},
 	 year = {2007},
 	 month = {Jun},
 	 publisher = {I-Tech Education and Publishing},
 	 doi = {10.5772/4824}, 
 }