The Aspirational Neuroscience Memory Decoding Challenge is a $100K prize for the first team to decode a non-trivial memory from a static map of the brain. For example, do a computational analysis of a mapped brain structure and figure out what that organism learned.

Examples that would count include reconstructing a zebra finch's learned song from its brain structure, or figuring out which maze path a rat was trained on just from its mapped brain structure. The key is that the analysis has to recover a learned behavior or memory that couldn't be inferred from trivial features, like muscle size or tissue scarring. 

A full brain emulation that replicates learned behaviors would qualify, but the prize is designed to be achievable without requiring that (in fact, well before that). 

To be clear, this excludes things like inferring disease states from tissue pathology, or detecting environmental exposures from molecular traces. The decoded information has to be something the brain was representing, not just something that happened to it.

The prize has no time limit. This manifold market resolves to the year when 

 (or a successor website, if it is changed) officially announces a winner. If there is no winner by end of 2045, it resolves to the final bucket. 

Each bucket covers a 2-year window ending in that year. '2027' = won by end of 2027 (including 2025-2026). '2029' = won in 2028-2029. '2031' = won in 2030-2031. Etc.

Resolution is based on Aspirational Neuroscience's official announcement, not the publication date of the underlying paper. If Aspirational Neuroscience dissolves without a successor organization and without awarding the prize, this market resolves N/A.