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Multisensory Encoding, Decoding, and Identification

机译:多思考编码,解码和识别

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We investigate a spiking neuron model of multisensory integration. Multiple stimuli from different sensory modalities are encoded by a single neural circuit comprised of a multisensory bank of receptive fields in cascade with a population of biophysical spike generators. We demonstrate that stimuli of different dimensions can be faithfully multiplexed and encoded in the spike domain and derive tractable algorithms for decoding each stimulus from the common pool of spikes. We also show that the identification of multisensory processing in a single neuron is dual to the recovery of stimuli encoded with a population of multisensory neurons, and prove that only a projection of the circuit onto input stimuli can be identified. We provide an example of multisensory integration using natural audio and video and discuss the performance of the proposed decoding and identification algorithms.
机译:我们调查了一种多思科集成的尖峰神经元模型。来自不同感官模型的多种刺激由单个神经电路编码,包括在级联的级联的多师的接收领域,其中级联具有生物物理尖峰发电机群。我们证明了不同尺寸的刺激可以忠实地复用并在尖峰域中进行编码,并导出易于解码来自公共尖峰池的每个刺激的算法。我们还表明,在单个神经元中的多福音统计学识别是双重以恢复具有多扰神经元群编码的刺激,并且证明只能识别电路到输入刺激上的投影。我们提供了一种使用自然音频和视频的多师范学集成的示例,并讨论所提出的解码和识别算法的性能。

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