Transformations of sensory information in the brain suggest changing criteria for optimality.
Transformations of sensory information in the brain suggest changing criteria for optimality.
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DOI：
10.1371/journal.pcbi.1011783
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发表时间：
2024-01
影响因子：
4.3
通讯作者：
中科院分区：
文献类型：
--
作者：
整个大脑中的神经元对他们的发射速率进行了响应，以响应感官输入。但是，大脑中的不同区域仍处于起步阶段。一种与从优化的信息制备到优化感知歧视的方式，重点是表示双眼差异（两只眼睛的视网膜图像中的略有差异） ，V2和MT（中间临时）在猕猴中。使用Fisher信息框架。各个区域的调整曲线特征的差异与优化目标的变化一致：V1和V2人口级响应更加一致支持差异歧视的能力。这些结果。在评估神经代码的最优性时，也与行为相关。
神经系统需要将信息从感官器官转变为可用于指导行为的信号。与行为相关的信息。它们如何表示我们的结果。
Neurons throughout the brain modulate their firing rate lawfully in response to sensory input. Theories of neural computation posit that these modulations reflect the outcome of a constrained optimization in which neurons aim to robustly and efficiently represent sensory information. Our understanding of how this optimization varies across different areas in the brain, however, is still in its infancy. Here, we show that neural sensory responses transform along the dorsal stream of the visual system in a manner consistent with a transition from optimizing for information preservation towards optimizing for perceptual discrimination. Focusing on the representation of binocular disparities—the slight differences in the retinal images of the two eyes—we re-analyze measurements characterizing neuronal tuning curves in brain areas V1, V2, and MT (middle temporal) in the macaque monkey. We compare these to measurements of the statistics of binocular disparity typically encountered during natural behaviors using a Fisher Information framework. The differences in tuning curve characteristics across areas are consistent with a shift in optimization goals: V1 and V2 population-level responses are more consistent with maximizing the information encoded about naturally occurring binocular disparities, while MT responses shift towards maximizing the ability to support disparity discrimination. We find that a change towards tuning curves preferring larger disparities is a key driver of this shift. These results provide new insight into previously-identified differences between disparity-selective areas of cortex and suggest these differences play an important role in supporting visually-guided behavior. Our findings emphasize the need to consider not just information preservation and neural resources, but also relevance to behavior, when assessing the optimality of neural codes. The nervous system needs to transform information from the sensory organs into signals that can be used to guide behavior. Neural activity is noisy and can consume large amount of energy, so sensory neurons must optimize their information processing so as to limit energy consumption while maintaining key behaviorally-relevant information. In this report, we re-examine classically-defined brain areas in the visual processing hierarchy, and ask whether neurons in these areas vary lawfully in how they represent sensory information. Our results suggest that neurons in these brain areas shift from being an optimal conduit for conveying sensory information towards prioritizing information that supports key perceptual discriminations during natural tasks.
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