Neural Models of Bayesian Belief Propagation Rajesh ... - Washington

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262 11 Neural Models of Bayesian Belief Propagation Rajesh P. N. Rao A Up Lt 1 2 3 4 5 Rt Dn 0.8 0.6 0.4 0.2 0 Lt 1 2 3 4 5 Spatial Positions 0.8 0.6 0.4 0.2 0 Rt 1 2 3 4 5 B 0.8 0.6 0.4 0.2 0 1 2 3 4 5 0.8 Up Dn 0.6 0.4 0.2 0 1 2 3 4 5 Figure 11.8 Input Image Configuration and Conditional Probabilities used in the Attention Experiments. (A) Example image locations (labeled 1-5 and Up, Dn, Lt, and Rt for up, down, left, and right) relevant to the experiments discussed in the paper. (B) Each bar plot shows P (Ci|L, F ) for a fixed value of L (= Lt, Rt, Up, or Dn) and for an arbitrary fixed value of F . Each bar represents the probability for the feature-location combination Ci encoding one of the locations 1-5. Response 0.5 0.3 Model V4 Neuron 0.0 −90 −60 −30 0 30 60 90 Orientation (in degrees) A B Figure 11.9 Multiplicative Modulation due to Attention. (A) Orientation tuning curve of a feature coding model neuron with a preferred stimulus orientation of 0 degrees with (filled squares) and without (unfilled circles) attention (from [31]). (B) Orientation tuning curves of a V4 neuron with (filled squares) and without attention (unfilled circles) (from [23]).
11.5 Discussion 263 Normalized Firing Rate 1 0.8 0.6 0.4 0.2 0 0 20 40 60 80 1 0.8 0.6 0.4 0.2 Model V4 Neuron 0 0 20 40 60 80 Time steps A B Figure 11.10 Attentional Response Restoration in the presence of Distractors. (A) (Top Panel) The three line plots represent the vertical feature coding neuron’s response to a vertical bar (“Reference”), a horizontal bar at a different position (“Probe”), and both bars presented simultaneously (“Pair”). In each case, the input lasted 30 time steps, beginning at time step 20. (Bottom Panel) When “attention” (depicted as a white oval) is focused on the vertical bar, the firing rate for the Pair stimulus approximates the firing rate obtained for the Reference alone (from [31]). (B) (Top Panel) Responses from a V4 neuron without attention. (Bottom Panel) Responses from the same neuron when attending to the vertical bar (see condition Pair Att Ref) (from [36]).
Page 1 and 2: 11 Neural Models of Bayesian Belief
Page 3 and 4: 11.2 Bayesian Inference through Bel
Page 5 and 6: 11.2 Bayesian Inference through Bel
Page 7 and 8: 11.3 Neural Implementations of Beli
Page 9 and 10: 11.3 Neural Implementations of Beli
Page 11 and 12: 11.4 Results 245 deviation σ. Figu
Page 13 and 14: 11.4 Results 247 Nonlinear Spiking
Page 15 and 16: 11.4 Results 249 again leaky-integr
Page 17 and 18: 11.4 Results 251 a high value for P
Page 19 and 20: 11.5 Discussion 253 an evidence acc
Page 21 and 22: 11.5 Discussion 255 the neural popu
Page 23 and 24: 11.5 Discussion 257 of various ioni
Page 25 and 26: 11.5 Discussion 259 [28] Pouget A,
Page 27: 11.5 Discussion 261 50% 100% D 0.05
Page 31 and 32: Index acausal, 122 attention, 101 a
Page 33: Index 319 regularization, 11 revers

Neural Models of Bayesian Belief Propagation Rajesh ... - Washington

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