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A Readout Mechanism for Latency Codes

机译:延迟代码的读取机制

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摘要

Response latency has been suggested as a possible source of information in the central nervous system when fast decisions are required. The accuracy of latency codes was studied in the past using a simplified readout algorithm termed the temporal-winner-take-all (tWTA). The tWTA is a competitive readout algorithm in which populations of neurons with a similar decision preference compete, and the algorithm selects according to the preference of the population that reaches the decision threshold first. It has been shown that this algorithm can account for accurate decisions among a small number of alternatives during short biologically relevant time periods. However, one of the major points of criticism of latency codes has been that it is unclear how can such a readout be implemented by the central nervous system. Here we show that the solution to this long standing puzzle may be rather simple. We suggest a mechanism that is based on reciprocal inhibition architecture, similar to that of the conventional winner-take-all, and show that under a wide range of parameters this mechanism is sufficient to implement the tWTA algorithm. This is done by first analyzing a rate toy model, and demonstrating its ability to discriminate short latency differences between its inputs. We then study the sensitivity of this mechanism to fine-tuning of its initial conditions, and show that it is robust to wide range of noise levels in the initial conditions. These results are then generalized to a Hodgkin-Huxley type of neuron model, using numerical simulations. Latency codes have been criticized for requiring a reliable stimulus-onset detection mechanism as a reference for measuring latency. Here we show that this frequent assumption does not hold, and that, an additional onset estimator is not needed to trigger this simple tWTA mechanism.
机译:当需要快速决策时,建议将反应潜伏期作为中枢神经系统中可能的信息来源。过去,使用称为时间赢家通吃(tWTA)的简化读出算法研究了延迟码的准确性。 tWTA是一种竞争性读出算法,其中具有相似决策偏好的神经元群体竞争,并且该算法根据首先达到决策阈值的群体的偏好进行选择。已经表明,该算法可以在较短的生物学相关时间段内解释少数选择中的准确决策。然而,对延迟码的批评的主要要点之一是目前尚不清楚中枢神经系统如何实现这种读出。在这里,我们证明了解决这一长期难题的方法可能非常简单。我们提出了一种基于倒数抑制结构的机制,类似于传统的“赢家通吃”的机制,并表明在广泛的参数范围内,该机制足以实现tWTA算法。首先要分析速率玩具模型,并证明其辨别其输入之间的短时延差异的能力。然后,我们研究了该机制对其初始条件进行微调的敏感性,并表明它在初始条件下对宽范围的噪声水平均具有鲁棒性。然后,使用数值模拟将这些结果推广到Hodgkin-Huxley型神经元模型。延迟代码已被批评为需要可靠的刺激发作检测机制作为测量延迟的参考。在这里,我们证明了这种频繁的假设并不成立,并且不需要额外的开始估计器来触发这种简单的tWTA机制。

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