My Cosyne 2019 abstract clearly describes a fundamentally new principle for how spikes transmit information. I'm therefore compelled to keep it visible on this website even though it was rejected. Here are the reviews on which that rejection was based. The reader can judge the review quality for himself/herself.

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* Overall: 3 * Confidence: 1 * Comments: The authors compare different types of population code, where sensory inputs are encoded via different combinations of spiking activity within a small temporal window. They first consider a (population) rate code, where all that matters is the fraction of neurons that fire together in a single time window. They then compare this to combinatorial codes, where different combinations of neurons firing carry different meaning. They propose a ‘fixed-size combinatorial’ code that they claim is able to encode a probability distributions. However, despite much effort, I found their explanation and accompanying figure very unclear. As a result, I don’t feel I was able to meaningfully evaluate their model, and see how it advances on previous work.

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* Overall: 3 * Confidence: 3 * Comments: Interesting concepts and example presented in the Abstract. Appears purely theoretical, as the methods and summarized results do not seem to indicate what questions are asked and answered by this work, or the extent of the work that would be presented at the meeting.

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* Overall: 1 * Confidence: 4 * Comments: The abstract is of particularly difficult interpretation. The author introduces new concepts as "temporal" and "atemporal coding" without a stringent definition, moreover he uses the more classical term of temporal (referred by the author as "latency") and rate coding in a misleading way. I suggest a more clear formalisation of the used concepts and a more accurate jargon when referring to physiological phenomena.