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We present an electronic cortical neuron incorporating both active and passive dendritic properties. The circuit is simulated using a carbon nanotube field-effect transistor SPICE model. We demonstrate that our neuron can detect coincident spatiotemporal input, and transform this neural information into a precisely-timed output spike. We also demonstrate that a dendritic spike is key to enhance precisely-timed...
A biomimetic carbon nanotube synapse, the portion of the neuron that receives inputs from other neurons, has been fabricated in the laboratory as an analog circuit. The waveforms input to the synapse and output from the synapse resemble biological waveforms in shape and relative amplitudes and durations. This working circuit is an important first step towards the use of nanotechnology for biomimetic...
Dendritic computations play a major role in the processing that occurs within each cortical neuron. In particular, for many pyramidal neurons, dendritic spiking has a major effect on neural behavior and must be modeled in order to capture nonlinear response of a neuron to its presynaptic inputs. This paper presents electronic circuits for dendritic spiking that demonstrate the global and local reset...
This paper describes a carbon nanotube synapse circuit that exhibits spike-timing dependant plasticity (STDP). These synapses are found in cortical (e.g. pyramidal) neurons. Experiments with the synapse in a neuron circuit demonstrate changes in synaptic potential with pre- and post-spiking timing variations. The circuit design is biomimetic and changes in control voltages representing neurotransmitter...
A cortical neuron with carbon nanotube circuit elements that performs nonlinear dendritic computations with excitatory and inhibitory post-synaptic potentials is presented. An inhibitory synapse with controllable parameters that implement plasticity is described. The circuit design was simulated using carbon nanotube spice models, showing that the neuron fires as long as the inhibitory post-synaptic...
A neural dendritic computational circuit design is presented here. The circuit models the result of action potentials applied to biological synapses on a portion of a dendritic tree. The resultant excitatory post synaptic potentials (EPSPs) are combined in a dendritic tree that demonstrates linear, superlinear and sublinear summation of both spatially and temporally separated EPSPs. The synapse circuit...
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