Visual information about an object is widely distributed over the cortex. The problem of how this information gets reassembled in consciousness is the “binding problem”. It is assumed in this paper that consciousnes...Visual information about an object is widely distributed over the cortex. The problem of how this information gets reassembled in consciousness is the “binding problem”. It is assumed in this paper that consciousness reads the distributed information as a laser reads a barcode;and that this solves the binding problem without resorting to oscillations, or synchronous signals, or any other form of mechanical association. Cortical distributions are made intelligible by consciousness that learns from childhood to recognize cortical arrays of single objects and project them onto the external world. An example shows how consciousness exercises its influence in the case of a well-known line drawing. When an object is constructed by consciousness there is no guarantee that the resulting image will be anything like the original object of observation. However, there is reason to believe that most of the visual images of our surroundings reflect real properties of those surroundings. These images have a constancy about them that is not always conveyed by the sensory input, but consistency in the external world can be learned by consciousness that is able to override the incongruities of the senses.展开更多
The"Binding Problem"is an important problem across many disciplines,including psychology,neuroscience,computational modeling,and even philosophy.In this work,we proposed a novel computational model,Bayesian ...The"Binding Problem"is an important problem across many disciplines,including psychology,neuroscience,computational modeling,and even philosophy.In this work,we proposed a novel computational model,Bayesian Linking Field Model,for feature binding in visual perception,by combining the idea of noisy neuron model,Bayesian method,Linking Field Network and competitive mechanism.Simulation Experiments demonstrated that our model perfectly fulfilled the task of feature binding in visual perception and provided us some enlightening idea for future research.展开更多
文摘Visual information about an object is widely distributed over the cortex. The problem of how this information gets reassembled in consciousness is the “binding problem”. It is assumed in this paper that consciousness reads the distributed information as a laser reads a barcode;and that this solves the binding problem without resorting to oscillations, or synchronous signals, or any other form of mechanical association. Cortical distributions are made intelligible by consciousness that learns from childhood to recognize cortical arrays of single objects and project them onto the external world. An example shows how consciousness exercises its influence in the case of a well-known line drawing. When an object is constructed by consciousness there is no guarantee that the resulting image will be anything like the original object of observation. However, there is reason to believe that most of the visual images of our surroundings reflect real properties of those surroundings. These images have a constancy about them that is not always conveyed by the sensory input, but consistency in the external world can be learned by consciousness that is able to override the incongruities of the senses.
基金the National Natural Science Foundation of China(Grant No.60435010)National High-Tech Program(863 Program)of China(Grant No.2006AA01Z128)National Basic Research Priorities Program of China(Grant No.2007CB311004)
文摘The"Binding Problem"is an important problem across many disciplines,including psychology,neuroscience,computational modeling,and even philosophy.In this work,we proposed a novel computational model,Bayesian Linking Field Model,for feature binding in visual perception,by combining the idea of noisy neuron model,Bayesian method,Linking Field Network and competitive mechanism.Simulation Experiments demonstrated that our model perfectly fulfilled the task of feature binding in visual perception and provided us some enlightening idea for future research.
