Volume 92, Issue 2, Pages (October 2016)

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Volume 92, Issue 2, Pages 275-277 (October 2016) Probability by Time Xaq Pitkow Neuron Volume 92, Issue 2, Pages 275-277 (October 2016) DOI: 10.1016/j.neuron.2016.10.007 Copyright © 2016 Elsevier Inc. Terms and Conditions

Figure 1 Cartoon of the Sampling Hypothesis The sensory input (A) is explained or interpreted as superpositions of visual features (B). Each neuron specifies one feature, and its membrane voltage determines the amplitude of that feature. In the illustration, feature amplitude is depicted by opacity and time by color (C). Different interpretations of the image are sampled sequentially and appear as feature amplitudes—or equivalently in this sampling model, voltages—that change over time. The set of possible interpretations determines the posterior probabilities (D) both over multiple features jointly (top) and over individual features (bottom). Photo credit: Xaq Pitkow. Neuron 2016 92, 275-277DOI: (10.1016/j.neuron.2016.10.007) Copyright © 2016 Elsevier Inc. Terms and Conditions