@inproceedings{d2da95936225465881b15f73a67c619f,
title = "Transport-Independent Protocols for Universal AER Communications",
abstract = "The emergence of Address-Event Representation (AER) as a general communications method across a large variety of neural devices suggests that they might be made interoperable. If there were a standard AER interface, systems could communicate using native AER signalling, allowing the construction of large-scale, real-time, heterogeneous neural systems. We propose a transport-agnostic AER protocol that permits direct bidirectional event communications between systems over Ethernet, and demonstrate practical implementations that connect a neuromimetic chip: SpiNNaker, both to standard host PCs and to real-time robotic systems. The protocol specifies a header and packet format that supports a variety of different possible packet types while coping with questions of data alignment, time sequencing, and packet compression. Such a model creates a flexible solution either for real-time communications between neural devices or for live spike I/O and visualisation in a host PC. With its standard physical layer and flexible protocol, the specification provides a prototype for AER protocol standardisation that is at once compatible with legacy systems and expressive enough for future very-large-scale neural systems.",
author = "Alexander Rast and Stokes, {Alan B} and Sergio Davies and Adams, {Samantha V} and Himanshu Akolkar and Lester, {David R} and Chiara Bartolozzi and Angelo Cangelosi and Steve Furber",
note = "This work has been partially supported by the European Unionunder grant nos. FP7-604102 (HBP), FP7-287701 (BrainScales-Extension), and ERC-320689 (BIMPC), by EPSRC grant EP/J004561/1 (BABEL) and by EPSRC grantEP/G015740/1 (BIMPA).; 22nd International Conference, ICONIP 2015, Proceedings ; Conference date: 09-11-2015 Through 12-11-2015",
year = "2015",
month = nov,
day = "18",
doi = "10.1007/978-3-319-26561-2_79",
language = "English",
isbn = "978-3-319-26560-5",
volume = "9492",
series = "Lecture Notes in Computer Science",
publisher = "Springer Nature",
pages = "675--684",
booktitle = "Neural Information Processing",
address = "United States",
}