  Analog neuromorphic computing systems emulate the parallelism and
connectivity of the human brain, promising greater expressivity and energy
efficiency compared to digital systems. Though many devices have emerged as
candidates for artificial neurons and artificial synapses, there have been few
device candidates for artificial dendrites. In this work, we report on
biocompatible graphene-based artificial dendrites (GrADs) that can implement
dendritic processing. By using a dual side-gate configuration, current applied
through a Nafion membrane can be used to control device conductance across a
trilayer graphene channel, showing spatiotemporal responses of leaky recurrent,
alpha, and gaussian dendritic potentials. The devices can be variably connected
to enable higher order neuronal responses, and we show through data-driven
spiking neural network classification simulations that overall spiking activity
is reduced by up to 15% without accuracy loss while low frequency operation is
stabilized. This positions the GrADs as strong candidates for energy efficient
bio-interfaced spiking neural networks.
