UCL Institute of Ophthalmology, University College London, London WC1 6BT, UK.
Neuron. 2024 Sep 4;112(17):2854-2868.e1. doi: 10.1016/j.neuron.2024.06.016. Epub 2024 Jul 15.
Logistic classification is a simple way to make choices based on a set of factors: give each factor a weight, sum the results, and use the sum to set the log odds of a random draw. This operation is known to describe human and animal choices based on value (economic decisions). There is increasing evidence that it also describes choices based on sensory inputs (perceptual decisions), presented across sensory modalities (multisensory integration) and combined with non-sensory factors such as prior probability, expected value, overall motivation, and recent actions. Logistic classification can also capture the effects of brain manipulations such as local inactivations. The brain may implement it by thresholding stochastic inputs (as in signal detection theory) acquired over time (as in the drift diffusion model). It is the optimal strategy under certain conditions, and the brain appears to use it as a heuristic in a wider set of conditions.
为每个因素赋予一个权重，将结果相加，并使用总和来确定随机选择的对数几率。这种操作被认为可以根据价值（经济决策）描述人类和动物的选择。越来越多的证据表明，它也可以描述基于感官输入的选择（感知决策），这些选择涉及到各种感觉模式（多感觉整合），并与非感官因素（如先验概率、预期价值、总体动机和最近的行为）相结合。逻辑分类还可以捕捉到大脑操作的影响，如局部失活。大脑可能通过对随时间积累的随机输入进行阈值处理（如在信号检测理论中）来实现这一点（如在漂移扩散模型中）。在某些条件下，它是最优策略，而大脑似乎在更广泛的条件下将其用作启发式。
