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Updated: May 14, 2026
08:08
Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
Published on: June 24, 2015
A superposable silicon synapse with programmable reversal potential.
Ben V Benjamin1, John V Arthur, Peiran Gao
1Electrical Engineering and P. Gao and K. Boahen are with Bioengineering, Stanford University, Stanford, CA, USA. benvb@stanford.edu
Summary
We developed a novel silicon synapse that mimics biological functions, offering programmable control for neural networks. This advancement enables more robust neuronal synchronization and network-level control.
Area of Science:
- Neuroscience
- Electrical Engineering
- Computer Science
Background:
- Biological synapses exhibit complex dynamics crucial for neural computation.
- Existing silicon synapses often lack the flexibility to emulate diverse biological synaptic behaviors.
- Log-domain circuits offer efficient analog computation for neuromorphic systems.
Purpose of the Study:
- To introduce a novel log-domain silicon synapse capable of emulating biological synaptic interactions.
- To implement a programmable reversal potential in a silicon synapse for enhanced functionality.
- To demonstrate the scalability and network implications of the proposed silicon synapse design.
Main Methods:
- Designed a subthreshold analog silicon synapse circuit operating in the log-domain.
- Emulated neurotransmitter release-reuptake and receptor binding-unbinding dynamics.
- Fabricated an array of 64K silicon neurons with superposable synapse circuits using 180nm CMOS technology.
- Investigated network-level effects by configuring synapses as shunts in a recurrent neural network.
Main Results:
- The silicon synapse successfully emulated biological synaptic interactions with superposable functionality.
- Achieved programmable reversal potential, a first for log-domain synapses, enabling both excitatory and inhibitory behavior.
- Demonstrated scalability with a 64K neuron array, each synapse occupying minimal area.
- Shunting synapses, utilizing programmable reversal potentials, enhanced neuronal spiking synchronization in recurrent networks.
Conclusions:
- The novel log-domain silicon synapse provides a versatile platform for neuromorphic engineering.
- Programmable reversal potentials offer significant advantages for controlling network dynamics and function.
- This design represents a significant step towards more biologically realistic and scalable artificial neural systems.
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