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Whatever the underlying mechanisms, the experimentally observed, stimulus-driven and behavior-related modulations of functional coupling form an interesting feature of cortical organization. They are the signature of an ongoing process of dynamical and activity-related 'linking' and 'unlinking' of neurons in the cortical network. This process may have interesting functional implications at different levels of observation. At the single-neuron level, it might explain how even little speciflcity in anatomical connections could be dynamically sorted out to yield the complex functional properties that have been observed for cortical neurons.
Time-consuming Monte Carlo simulations can be avoided by' finding a single locally optimal point in weight space and constructing a full covariance Gaussian approximation to the posterior distribution around that point. The alternative method proposed in this paper is to use a simpler Gaussian approximation (with no off-diagonal terms in the covariance matrix) but to take this distribution into account during the leaming. With one layer of non-linear hidden units, the integration over the Gaussian distribution can be performed exactly and the exact weight derivatives can be computed efficiently.
Proc. Natl. Acad. Sci. USA 87: 7200-7204 49. Sompolinsky H, Golomb D, Kleinfeld D (1991) Cooperative dynamics in visual processing. Physical Rev A 43: 6990-7011 50. Sporns 0, Gally JA, Reeke GN Jr, Edelman GM, (1989) Reentrant signaling among simulated neuronal groups leads to coherency in their oscillatory avtivity. Proc Nat! Acad Sci USA 86: 7265-7269 51. Scbillen TB, Konig P (1991) Stimulus-dependent assembly formation of oscillatory responses. 2: Desynchronisation. Neural Comp 3: 167-178 52.
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