TY - JOUR
T1 - A biohybrid setup for coupling biological and neuromorphic neural networks
AU - Keren, Hanna
AU - Partzsch, Johannes
AU - Marom, Shimon
AU - Mayr, Christian G.
N1 - Publisher Copyright:
© 2019 Keren, Partzsch, Marom and Mayr.
PY - 2019
Y1 - 2019
N2 - Developing technologies for coupling neural activity and artificial neural components, is key for advancing neural interfaces and neuroprosthetics. We present a biohybrid experimental setting, where the activity of a biological neural network is coupled to a biomimetic hardware network. The implementation of the hardware network (denoted NeuroSoC) exhibits complex dynamics with a multiplicity of time-scales, emulating 2880 neurons and 12.7 M synapses, designed on a VLSI chip. This network is coupled to a neural network in vitro, where the activities of both the biological and the hardware networks can be recorded, processed, and integrated bidirectionally in real-time. This experimental setup enables an adjustable and well-monitored coupling, while providing access to key functional features of neural networks. We demonstrate the feasibility to functionally couple the two networks and to implement control circuits to modify the biohybrid activity. Overall, we provide an experimental model for neuromorphic-neural interfaces, hopefully to advance the capability to interface with neural activity, and with its irregularities in pathology.
AB - Developing technologies for coupling neural activity and artificial neural components, is key for advancing neural interfaces and neuroprosthetics. We present a biohybrid experimental setting, where the activity of a biological neural network is coupled to a biomimetic hardware network. The implementation of the hardware network (denoted NeuroSoC) exhibits complex dynamics with a multiplicity of time-scales, emulating 2880 neurons and 12.7 M synapses, designed on a VLSI chip. This network is coupled to a neural network in vitro, where the activities of both the biological and the hardware networks can be recorded, processed, and integrated bidirectionally in real-time. This experimental setup enables an adjustable and well-monitored coupling, while providing access to key functional features of neural networks. We demonstrate the feasibility to functionally couple the two networks and to implement control circuits to modify the biohybrid activity. Overall, we provide an experimental model for neuromorphic-neural interfaces, hopefully to advance the capability to interface with neural activity, and with its irregularities in pathology.
KW - Brain-machine interfacing
KW - Neural coupling
KW - Neural engineering
KW - Neural networks
KW - Neuromorphic networks
UR - http://www.scopus.com/inward/record.url?scp=85068582694&partnerID=8YFLogxK
U2 - 10.3389/fnins.2019.00432
DO - 10.3389/fnins.2019.00432
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C2 - 31133779
AN - SCOPUS:85068582694
SN - 1662-4548
VL - 13
JO - Frontiers in Neuroscience
JF - Frontiers in Neuroscience
IS - MAY
M1 - 432
ER -