A data-compressive wired-or readout for massively parallel neural recording
Dante Gabriel Muratore (Stanford University, TU Delft - Bio-Electronics)
Pulkit Tandon (Stanford University)
Mary Wootters (Stanford University)
E.J. Chichilnisky (Stanford University)
Subhasish Mitra (Stanford University)
Boris Murmann (Stanford University)
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Abstract
This paper describes an architecture for the massively parallel digitization of neural action potentials. The scheme achieves simultaneous data compression and channel multiplexing through wired-OR interactions within an array of single-slope A/D converters. The achieved compression is lossy but effective at retaining the critical samples belonging to action potential spikes. Simulation results using ex-vivo experimental data from a 512-channel array show compression rates up to ∼73x while maintaining ≥90% reconstruction coverage for parasol cells in the primate retina.
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