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      Information coding via spontaneous oscillations in neural ensembles

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      Physical Review E
      American Physical Society (APS)

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          Entropy and Information in Neural Spike Trains

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            Reproducibility and variability in neural spike trains.

            To provide information about dynamic sensory stimuli, the pattern of action potentials in spiking neurons must be variable. To ensure reliability these variations must be related, reproducibly, to the stimulus. For H1, a motion-sensitive neuron in the fly's visual system, constant-velocity motion produces irregular spike firing patterns, and spike counts typically have a variance comparable to the mean, for cells in the mammalian cortex. But more natural, time-dependent input signals yield patterns of spikes that are much more reproducible, both in terms of timing and of counting precision. Variability and reproducibility are quantified with ideas from information theory, and measured spike sequences in H1 carry more than twice the amount of information they would if they followed the variance-mean relation seen with constant inputs. Thus, models that may accurately account for the neural response to static stimuli can significantly underestimate the reliability of signal transfer under more natural conditions.
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              Coherent 40-Hz oscillation characterizes dream state in humans.

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                Author and article information

                Journal
                PLEEE8
                Physical Review E
                Phys. Rev. E
                American Physical Society (APS)
                1063-651X
                1095-3787
                July 2000
                July 1 2000
                : 62
                : 1
                : 1063-1068
                Article
                10.1103/PhysRevE.62.1063
                beb9de1a-be06-480f-ab89-b5c9452ee2d6
                © 2000

                http://link.aps.org/licenses/aps-default-license

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