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Human vision is determined based on information theory.

ABSTRACT: It is commonly accepted that the evolution of the human eye has been driven by the maximum intensity of the radiation emitted by the Sun. However, the interpretation of the surrounding environment is constrained not only by the amount of energy received but also by the information content of the radiation. Information is related to entropy rather than energy. The human brain follows Bayesian statistical inference for the interpretation of visual space. The maximization of information occurs in the process of maximizing the entropy. Here, we show that the photopic and scotopic vision absorption peaks in humans are determined not only by the intensity but also by the entropy of radiation. We suggest that through the course of evolution, the human eye has not adapted only to the maximum intensity or to the maximum information but to the optimal wavelength for obtaining information. On Earth, the optimal wavelengths for photopic and scotopic vision are 555?nm and 508?nm, respectively, as inferred experimentally. These optimal wavelengths are determined by the temperature of the star (in this case, the Sun) and by the atmospheric composition.

SUBMITTER: Delgado-Bonal A

PROVIDER: S-EPMC5093619 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Human vision is determined based on information theory.

Delgado-Bonal Alfonso A Martín-Torres Javier J

Scientific reports 20161103

It is commonly accepted that the evolution of the human eye has been driven by the maximum intensity of the radiation emitted by the Sun. However, the interpretation of the surrounding environment is constrained not only by the amount of energy received but also by the information content of the radiation. Information is related to entropy rather than energy. The human brain follows Bayesian statistical inference for the interpretation of visual space. The maximization of information occurs in t ...[more]

PMID: 27808236

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Project description:Many lines of evidence point to a tight linkage between the perceptual and motoric representations of actions. Numerous demonstrations show how the visual perception of an action engages compatible activity in the observer's motor system. This is seen for both intransitive actions (e.g., in the case of unconscious postural imitation) and transitive actions (e.g., grasping an object). Although the discovery of "mirror neurons" in macaques has inspired explanations of these processes in human action behaviors, the evidence for areas in the human brain that similarly form a crossmodal visual/motor representation of actions remains incomplete. To address this, in the present study, participants performed and observed hand actions while being scanned with functional MRI. We took a data-driven approach by applying whole-brain information mapping using a multivoxel pattern analysis (MVPA) classifier, performed on reconstructed representations of the cortical surface. The aim was to identify regions in which local voxelwise patterns of activity can distinguish among different actions, across the visual and motor domains. Experiment 1 tested intransitive, meaningless hand movements, whereas experiment 2 tested object-directed actions (all right-handed). Our analyses of both experiments revealed crossmodal action regions in the lateral occipitotemporal cortex (bilaterally) and in the left postcentral gyrus/anterior parietal cortex. Furthermore, in experiment 2 we identified a gradient of bias in the patterns of information in the left hemisphere postcentral/parietal region. The postcentral gyrus carried more information about the effectors used to carry out the action (fingers vs. whole hand), whereas anterior parietal regions carried more information about the goal of the action (lift vs. punch). Taken together, these results provide evidence for common neural coding in these areas of the visual and motor aspects of actions, and demonstrate further how MVPA can contribute to our understanding of the nature of distributed neural representations.

Dataset Information

Human vision is determined based on information theory.

Publications

Human vision is determined based on information theory.

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