Intelligence Value

The MICrONS program aimed to close the performance gap between human analysts and automated pattern recognition systems by reverse-engineering the algorithms of the brain


The human brain has the remarkable ability to learn patterns from small amounts of data and then recognize novel instances of those patterns despite distortion and noise. Although advances in machine learning algorithms have been weakly informed by the brain since the 1940’s, they do not yet rival human performance.

MICrONS sought to close this performance gap by reverse-engineering the algorithms of the brain. The research leveraged the latest generation of brain mapping tools to reveal and exploit the structure and function of cortical circuits. This will allow the design of algorithms based on biologically inspired data representations, transformations, and learning rules. These algorithms are expected to achieve human-like performance on challenging inference tasks. This will be achieved by using sparse data that allows automated recognition of objects in imagery, even when few training examples exist, or when the objects appear different enough from the training examples that a human would have to infer their similarity. In mid-2019, MICrONS demonstrated the first proof-of-concept that a neurally informed algorithm can outperform the state of the art.

MICrONS assembled the largest (multi-petabyte) extant dataset of co-registered neurophysiological and neuroanatomical data from the mammalian brain, spanning 1 mm3 and encompassing 100,000 neurons. Performers densely mapped synaptic connectivity in this imaging volume and studied how network structure constrains function. At the conclusion of the program, performers delivered pattern recognition algorithms informed by neuroscience that achieved improved robustness to noise on on challenging visual scene analysis problems.

 Browse MICrONS data using the MICrONS Explorer

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Related Publications

To access MICrONS program-related publications, please visit Google Scholar.


Contact Information

Program Manager

Main Office

Related Program(s)

Broad Agency Announcement (BAA)

Link(s) to BAA


Solicitation Status


Proposers' Day Date

July 17, 2014

BAA Release Date

January 8, 2015

BAA Question Period

January 8, 2015 — February 9, 2015

Proposal Due Date

March 13, 2015

Program Summary

Testing and Evaluation Partners

  • Sandia National Laboratories
  • Johns Hopkins University Applied Physics Laboratory

Prime Performers

  • Baylor College of Medicine
  • Allen Institute for Brain Science
  • Princeton University