A study is presented of a set of coupled nets proposed to function as a global competitive network. One net, of hidden nodes, is composed solely of inhibitory neurons and is excitatorily driven and feeds back in a disinhibitory manner to an input net which itself feeds excitatorily to a (cortical) output net. The manner in which the former input and hidden inhibitory net function so as to enhance outputs as compared with inputs, and the further enhancements when the cortical net is added, are explored both mathematically and by simulation. This is extended to learning on cortical afferent and lateral connections. A global wave structure, arising on the inhibitory net in a similar manner to that of pattern formation in a negative laplacian net, is seen to be important to all of these activities. Simulations are only performed in one dimension, although the global nature of the activity is expected to extend to higher dimensions. Possible implications are briefly discussed.
We consider the generalized bioelectromagnetic inverse problem (the evaluation of expressions for the unknown current densities that give rise ta experimentally measurable iieldlsurfae potential d i n 5 ) . We apply the principle of ccossenVopy minimization to compute new expressions for the expected means and convariances of the c m n t densities. The new expressions are shown by computer simulations to offer betfer results than the existing methds in those cases when only partial information about the source is available. Our expressions are general enough to be equally valid for the biomagnetic, bicelectric or combined bicelechomagnetic inverse problems.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.