Optical Memory and Neural Networks is an international peer-reviewed journal that covers a wide range of problems in information optics such as optical memory, mechanisms for optical data recording and processing, photosensitive materials, optical, optoelectronic and holographic nanostructures, articles on optics and photonics and many other related topics. Papers on memory systems using holographic and biological structures and concepts of brain operation are also included. The journal pays particular attention to research in the field of neural net systems that may lead to a new generation of computational technologies by endowing them with intelligence. The journal welcomes manuscripts from all countries. PEER REVIEW Optical Memory and Neural Networks is a peer reviewed journal. We use a single blind peer review format. Our team of reviewers includes over 50 experts, both internal and external (90%), from 7 countries. The average period from submission to first decision in 2019 was 35 days, and that from first decision to acceptance was 15 days. The rejection rate for submitted manuscripts in 2019 was 30%. The final decision on the acceptance of an article for publication is made by the Editors-in-Chief. Any invited reviewer who feels unqualified or unable to review the manuscript due to the conflict of interests should promptly notify the editors and decline the invitation. Reviewers should formulate their statements clearly in a sound and reasoned way so that authors can use reviewer’s arguments to improve the manuscript. Personal criticism of the authors must be avoided. Reviewers should indicate in a review (i) any relevant published work that has not been cited by the authors, (ii) anything that has been reported in previous publications and not given appropriate reference or citation, (ii) any substantial similarity or overlap with any other manuscript (published or unpublished) of which they have personal knowledge. Covers a wide range of issues in information optics. Reports on theoretical researches and applications in different fields. Pays particular attention to research in the field of neural net systems that may lead to a new generation of computing devices.