| Popis: |
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 has been studied 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, it remains unclear how such readouts are implemented by the CNS – making this one of the main criticisms of latency codes.Here we suggest a mechanism based on a 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 inputs. We then test the sensitivity of this mechanism to the fine-tuning of its initial conditions, and show that it is robust to a 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. |
