Abstract—We present a delay-insensitive (DI) link that provides virtual point-to-point channels between ports at corresponding locations in two-dimensional arrays on separate chips. A communication, or event, on any particular channel is represented by its input port’s address, which the link encodes, conveys, and decodes. Previous work cut pad-count by transmitting row and column addresses sequentially, appending additional column addresses for concurrent communications in the same row, which are read and written in parallel, thereby boosting throughput. However, a non-DI implementation was used offchip (bundled-data), incurring delay and area penalties when interfaced with DI circuitry used on-chip. The link described here avoids these penalties by using a DI implementation both on- and off-chip (1-of-4 codes). We describe the transmitter’s and receiver’s implementation in detail, including refinements made to ensure efficient and robust operation with arrays as large as 320×960, and provide test results from two chips fabricated in a 0.18µm CMOS process.

Abstract—Thalamic relay cells express distinctive response modes based on the state of a low-threshold calcium channel (T-channel). When the channel is fully active (burst mode), the cell responds to inputs with a high-frequency burst of spikes; with the channel inactive (tonic mode), the cell responds at a rate proportional to the input. Due to the T-channel’s dynamics, we expect the cell’s response to become more nonlinear as the channel becomes more active. To test this hypothesis, we study the response of an in silico relay cell to Poisson spike trains. We first validate our model cell by comparing its responses with in vitro responses. To characterize the model cell’s nonlinearity, we calculate Poisson kernels, an approach akin to white noise analysis but using the randomness of Poisson input spikes instead of Gaussian white noise. We find that a relay cell with active T-channels requires at least a third-order system to achieve a characterization as good as a second-order system for a relay cell without T-channels. Index Terms—Neuroengineering, neuromorphic, relay cell model.

With the advent of new experimental evidence showing that dendrites play an active role in processing a neuron’s inputs, we revisit the question of a suitable abstraction for the computing function of a neuron in processing spatiotemporal input patterns. Although the integrative role of a neuron in relation to the spatial clustering of synaptic inputs can be described by a two-layer neural network, no corresponding abstraction has yet been described for how a neuron processes temporal input patterns on the dendrites. We address this void using a real-time aVLSI (analog very-large-scale-integrated) dendritic compartmental model, which incorporates two widely studied classes of regenerative event mechanisms: one is mediated by voltage-gated ion channels and the other by transmitter-gated NMDA channels. From this model, we find that the response of a dendritic compartment can be described as a nonlinear sigmoidal function of both the degree of input temporal synchrony and the synaptic input spatial clustering. We propose that a neuron with active dendrites can be modeled as a multilayer network that selectively amplifies responses to relevant spatiotemporal input spike patterns. 1