Boahen, Kwabena A
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Publication A silicon implementation of the thalamic low threshold calcium current(2003-09-17) Hynna, Kai M.; Boahen, Kwabena AA silicon model of the thalamic low threshold calcium current is presented. The channel current (IT) is the product of an activation and inactivation current, normalized by their sum. The individual currents are modeled by a simple current-mirror integrator circuit. A modified differential pair controls the threshold of activation while a leak transistor added to the inactivation mirror controls the rate of inactivation and deinactivation. The dynamics of IT are the result of the interaction between the fast activation and slow inactivation currents. By adjusting the base level of the activation current, we can realize a hyperpolarization activated cation current (Ih), responsible for rhythmic bursting in thalamic cells. By attaching the circuit to a constant leak integrate-and-fire neuron, we demonstrate in silicon both burst and tonic firing modes.Publication A burst-mode word-serial address-event link--III: analysis and test results(2004-07-01) Boahen, Kwabena AWe present results for a scalable multiple-access inter-chip link that communicates binary activity between two-dimensional arrays fabricated in deep submicrometer CMOS. Capacity scales with integration density because an entire row is read and written in parallel. Row activity is encoded in a burst: The row address followed by a column address for each active cell. We predict the distribution of burst lengths when transmission is initiated by active cells and access is arbitered using a two-level queuing model. Agreement with the experiment is excellent for loads over 50% but not for lighter loads, where our assumption that service time is exponentially distributed breaks down. We also quantify the throughput–latency tradeoff. The price of an n-fold increase in throughput is an n per Ncol timing error in a cell’s inter-event interval, where Ncol is the number of cells per row. Links implemented in 0.6, 0.4, and 0.25 micrometer are compared; the highest burst-rate achieved was 27.8 M events/s.Publication A linear cochlear model with active bi-directional coupling(2003-09-17) Wen, Bo; Boahen, Kwabena AWe present a linear active cochlear model that includes the outer hair cell (OHC) forces, which are delivered onto upstream and downstream basilar membrane (BM) segments through Deiters' cells (DCs) and their phalangeal processes (PhPs). Due to the longitudinal tilt of the OHC towards the base and the oblique orientation of the PhP towards the apex, each BM segment receives both feed-forward and feed-backward OHC forces. Transverse BM fibers are actively coupled longitudinally through these bi-directional OHC forces, included in a cochlear model for the first time. We present simulation results that demonstrate large amplification and sharp tuning, and we analyze the underlying mechanism.Publication A multi-chip implementation of cortical orientation hypercolumns(2004-05-23) Choi, Thomas Y. W.; Shi, Bertram E.; Boahen, Kwabena AThis paper describes a neuromorphic implementation of the orientation hypercolumns found in the mammalian primary visual cortex. A hypercolumn contains a group of neurons that respond to the same retinal location, but with different orientation preferences. The system consists of a single silicon retina feeding multiple orientation selective chips, each of which contains neurons tuned to the same orientation, but with different receptive field centers and spatial phases. All chips operate in continuous time, and communicate with each other using spikes transmitted by the asynchronous digital Address Event Representation communication protocol. This enables us to implement recurrent interactions between neurons within one hypercolumn, even though they are located on different chips. We demonstrate this by measuring shifts in orientation selectivity due to changes in the feedback.Publication Contrast Adaptation in Subthreshold and Spiking Responses of Mammalian Y-Type Retinal Ganglion Cells(2005-01-26) Zaghloul, Kareem A; Boahen, Kwabena A; Demb, Jonathan BRetinal ganglion cells adapt their responses to the amplitude of fluctuations around the mean light level, or the "contrast." But, in mammalian retina, it is not known whether adaptation arises exclusively at the level of synaptic inputs or whether there is also adaptation in the process of ganglion cell spike generation. Here, we made intracellular recordings from guinea pig Y-type ganglion cells and quantified changes in contrast sensitivity (gain) using a linear-nonlinear analysis. This analysis allowed us to measure adaptation in the presence of nonlinearities, such as the spike threshold, and to compare adaptation in subthreshold and spiking responses. At high contrast (0.30), relative to low contrast (0.10), gain reduced to 0.82 ± 0.016 (mean ± SEM) for the subthreshold response and to 0.61 ± 0.011 for the spiking response. Thus, there was an apparent reduction in gain between the subthreshold and spiking response of 0.74 ± 0.013. Control experiments suggested that the above effects could not be explained by an artifact of the intracellular recording conditions: extracellular recordings showed a gain change of 0.58 ± 0.022. For intracellular recordings, negative current reduced the spike output but did not affect the gain change in the subthreshold response: 0.80 ± 0.051. Thus, adaptation in the subthreshold response did not require spike-dependent conductances. We conclude that the contrast-dependent gain change in the spiking response can be explained by both a synaptic mechanism, as reflected by responses in the subthreshold potential, and an intrinsic mechanism in the ganglion cell related to spike generation.Publication A recurrent model of orientation maps with simple and complex cells(2003-12-09) Merolla, Paul; Boahen, Kwabena AWe describe a neuromorphic chip that utilizes transistor heterogeneity, introduced by the fabrication process, to generate orientation maps similar to those imaged in vivo. Our model consists of a recurrent network of excitatory and inhibitory cells in parallel with a push-pull stage. Similar to a previous model the recurrent network displays hotspots of activity that give rise to visual feature maps. Unlike previous work, however, the map for orientation does not depend on the sign of contrast. Instead, sign-independent cells driven by both ON and OFF channels anchor the map, while push-pull interactions give rise to sign-preserving cells. These two groups of orientation-selective cells are similar to complex and simple cells observed in V1.Publication A retinomorphic chip with parallel pathways : encoding INCREASING, ON, DECREASING, and OFF visual signals(2001-02-12) Boahen, Kwabena ARetinomorphic chips may improve their spike-coding efficiency by emulating the primate retina's parallel pathways. To model the four predominant ganglion-cell types in the cat retina, I morphed outer and inner retina microcircuits into a silicon chip, Visio1. It has 104 x 96 photoreceptors, 4 x 52 x 48 ganglion-cells, a die size of 9.25 x 9.67 mm2 in 1.2 µm 5V CMOS, and consumes 11.5 mW at 5 spikes/second/ganglion-cell. Visio1 includes novel subthreshold current-mode circuits that model horizontal-cell autofeedback, to decouple spatial filtering from local gain control, and model amacrine-cell loop-gain modulation, to adapt temporal filtering to motion. Different ganglion cells respond to motion in a quadrature sequence, making it possible to detect edges of one contrast or the other moving in one direction or the other. I present results from a multichip 2-D motion system, which implements Watson and Ahumada's model of human visual-motion sensing.Publication Self-organized cortical map formation by guiding connections(2005-05-23) Lam, Stanley Y.M.; Shi, Bertram E.; Boahen, Kwabena AWe describe an algorithm for self-organizing connections from a source array to a target array of neurons that is inspired by neural growth cone guidance. Each source neuron projects a Gaussian pattern of connections to the target layer. Learning modifies the pattern center location. The small number of parameters required to specify connectivity has enabled this algorithm's implementation in a neuromorphic silicon system. We demonstrate that this algorithm can lead to topographic feature maps similar to those observed in the visual cortex, and characterize its operation as function maximization, which connects this approach with other models of cortical map formation.Publication Recurrently Connected Silicon Neurons with Active Dendrites for One-Shot Learning(2004-07-25) Arthur, John V.; Boahen, Kwabena AWe describe a neuromorphic chip designed to model active dendrites, recurrent connectivity, and plastic synapses to support one-shot learning. Specifically, it is designed to capture neural firing patterns (short-term memory), memorize individual patterns (long-term memory), and retrive them when primed (associative recall). It consists of a recurrently connected population of excitatory pyramidal cells and a recurrently connected population of inhibitory basket cells. In addition to their recurrent connections, the excitatory and inhibitory populations are reciprocally connected. The model is novel in that it utilizes recurrent connections and active dendrites to maintain short-term memories as well as to store long-term memories.Publication Optic Nerve Signals in a Neuromorphic Chip I: Outer and Inner Retina Models(2004-04-01) Zaghloul, Kareem A.; Boahen, Kwabena AWe present a novel model for the mammalian retina and analyze its behavior. Our outer retina model performs bandpass spatiotemporal filtering. It is comprised of two reciprocally connected resistive grids that model the cone and horizontal cell syncytia. We show analytically that its sensitivity is proportional to the space-constant-ratio of the two grids while its half-max response is set by the local average intensity. Thus, this outer retina model realizes luminance adaptation. Our inner retina model performs high-pass temporal filtering. It features slow negative feedback whose strength is modulated by a locally computed measure of temporal contrast, modeling two kinds of amacrine cells, one narrow-field, the other wide-field.We show analytically that, when the input is spectrally pure, the corner-frequency tracks the input frequency. But when the input is broadband, the corner frequency is proportional to contrast. Thus, this inner retina model realizes temporal frequency adaptation as well as contrast gain control.We present CMOS circuit designs for our retina model in this paper as well. Experimental measurements from the fabricated chip, and validation of our analytical results, are presented in the companion paper [Zaghloul and Boahen (2004)].