Abstract
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.
Highlights
Developing interfaces between brain activity and electrical circuits could bring new perspectives for basic research and medical applications, as therapeutic brain stimulation or neuroprosthetics
We show that due to the tight coupling, it is feasible to implement a control circuit which reads the activity of one network while providing stimulation to the other
The circuit is comprised of the following steps: Sampling the activity of the hardware by a subset of 60 neurons, to the recording of the culture activity; This activity is sent to a PI controller algorithm, which calculates the appropriate stimulation amplitude to be applied ; This stimulation is provided to the biological network
Summary
Developing interfaces between brain activity and electrical circuits could bring new perspectives for basic research and medical applications, as therapeutic brain stimulation or neuroprosthetics. The development of such interfaces involves multiple challenges and expertise, spanning the fields of neurobiology, electrophysiology, bioengineering, computational neuroscience, and neuromorphic electrical engineering. Novel neurotherapeutic devices [see Greenwald et al (2016) for review], use neural stimulation to help with epilepsy (Vagus Nerve Stimulation Study Group, 1995; Fisher and Velasco, 2014), chronic pain (Kumar et al, 2007), and rehabilitation following spinal cord injury (Harkema et al, 2011; Angeli et al, 2014). Other studies use bidirectional stimulation to develop motoric feedback interfaces (O’Doherty et al, 2011; Vato et al, 2012), or to reinstate the input
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