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tomoki_slides2 - 1 Agenda Efficient Coding Hypothesis...

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2 Agenda ! Efficient Coding Hypothesis ! Response Function and Optimal Stimulus Ensemble ! Firing-Rate Code ! Spike-Timing Code ! OSE vs Natural Stimuli ! Conclusion
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3 Efficient Coding Hypothesis ! “[Sensory systems] recode sensory messages, extracting signals of high relative entropy from the highly redundant sensory input” (Barlow, 1961) ! Neurons should encode information to match the statistics of natural stimuli ! Use fewer bits (and higher resolution) for common stimuli ! Is this true? ! What are the “natural stimuli?” ! Behavioral relevance should be considered ! “Supernatural” stimuli sometimes drive neurons best
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4 Agenda ! Efficient Coding Hypothesis ! Response Function and Optimal Stimulus Ensemble ! Firing-Rate Code ! Spike-Timing Code ! OSE vs Natural Stimuli ! Conclusions
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5 Response and OSE ! Stimulus and response ! Neural system = “channel” ! Channel capacity: maximum mutual information between signal and response ! Optimal stimulus ensemble: stimulus ensemble that saturates the channel capacity.
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6 Response and OSE ! When there is no noise, best RF is the integral (cdf) of the stimulus distribution. ! Conversely, we can calculate the stimulus distribution for which the RF is optimal – “OSE.” ! Is OSE = Natural stimulus ensemble?
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7 ! With noisy responses, OSE changes ! OSE avoids response regions that are noisy ! Still contains most of the probability at 25-55 dB SPL (most useful region) Response and OSE
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8 Response and OSE ! This result is from constant intensity stimuli ! What about time-varying stimuli? ! What if information is encoded in spike timing?
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This note was uploaded on 09/15/2011 for the course COGS 1 taught by Professor Lewis during the Spring '08 term at UCSD.

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tomoki_slides2 - 1 Agenda Efficient Coding Hypothesis...

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