Specificities of Cortical Processing of Visual Information in Subjects with Hearing Deprivation (Congenital Deafness)

In 30 healthy men (age 19–25 years) with normal hearing and 30 men of the same age suffering from complete congenital deafness, we examined peculiarities of the cortical visual evoked potentials, VEPs (photostimulation of the right and left eye by LED flashes, recording from loci O1 and O2). It was found that subjects with auditory deprivation demonstrated significantly shorter (P < 0.05–0.001) peak latencies of the early VEP components (P1, N2, and P2), while peak latencies of the late waves (N2 and P3) were greater (P < 0.05) than the corresponding indices in the control group. Peak-to-peak amplitudes of all VEP components in deaf subjects were about two to three times lower than those in subjects with normal hearing (P < 0.05–0.001). The mean total duration of the VEPs in deaf persons was significantly greater than in the control group (P < 0.05). Therefore, loss of the auditory function in deaf subjects results, due to cross-modal transformations, in substantial modifications of the potentials reflecting perception of the visual signals.

It is recognized that the internal mechanisms for visual information processing are based on semantic inferences where visual information is represented and processed as visual semantic objects rather than direct images or episode pictures in the long-term memory. This article presents a cognitive informatics theory of visual information and knowledge processing in the brain. A set of cognitive principles of visual perception is reviewed particularly the classic gestalt principles, the cognitive informatics principles, and the hypercolumn theory. A visual frame theory is developed to explain the visual information processing mechanisms of human vision, where the size of a unit visual frame is tested and calibrated based on vision experiments. The framework of human visual information processing is established in order to elaborate mechanisms of visual information processing and the compatibility of internal representations between visual and abstract information and knowledge in the brain.

It is recognized that the internal mechanisms for visual information processing are based on semantic inferences where visual information is represented and processed as visual semantic objects rather than direct images or episode pictures in the long-term memory. This article presents a cognitive informatics theory of visual information and knowledge processing in the brain. A set of cognitive principles of visual perception is reviewed particularly the classic gestalt principles, the cognitive informatics principles, and the hypercolumn theory. A visual frame theory is developed to explain the visual information processing mechanisms of human vision, where the size of a unit visual frame is tested and calibrated based on vision experiments. The framework of human visual information processing is established in order to elaborate mechanisms of visual information processing and the compatibility of internal representations between visual and abstract information and knowledge in the brain.

In visual perception and information processing, a cascade of associations is hypothesized to flow from the structure of the visual stimulus to neural activity along the retinogeniculostriate visual system to behavior and action. Do visual perception and information processing adhere to this cascade near the beginning of life? To date, this three-stage hypothetical cascade has not been comprehensively tested in infants. In two related experiments, we attempted to expose this cascade in 6-month-old infants. Specifically, we presented infants with two levels of visual stimulus intensity, we measured electrical activity at the infant cortex, and we assessed infants’ preferential looking behavior. Chromatic saturation provided a convenient stimulus dimension to test the cascade because greater saturation is known to excite increased activity in the primate visual system and is generally hypothesized to stimulate visual preference. Experiment 1 revealed that infants prefer (look longer) at the more saturated of two colors otherwise matched in hue and brightness. Experiment 2 showed increased aggregate neural cortical excitation in infants (and adults) to the more saturated of the same pair of colors. Thus, experiments 1 and 2 taken together confirm a cascade: Visual stimulation of relatively greater intensity evokes relatively greater levels of bioelectrical cortical activity which in turn is associated with relatively greater visual attention. As this cascade obtains near the beginning of life, it helps to account for early visual preferences and visual information processing.

This study explored whether benzodiazepines selectively affect aspects of attention and/or visual information processing, as they do memory. A cued visual-search paradigm was employed, using normal volunteers and a single dose of triazolam. This paradigm provided for a detailed examination of two aspects of visual attention and information processing: 1) controlled versus automatic attention allocation (via central and peripheral cues), and 2) the extent to which processing an item in a non-cued location affects performance (via cue-validity). Triazolam, compared to placebo, significantly increased response time, and Drug Condition interacted with Cue-Validity but not Cue-Type. Based on these data, we argue that triazolam does not affect attention allocation but does affect attentional disengagement and/or attention switching mechanisms.

Information processing and reading competencies in hydrocephalic children

This paper presents a cognitive informatics theory of visual information and knowledge processing in the brain and natural intelligence. A set of cognitive principles of visual perception is reviewed, such as the gestalt principles, the cognitive informatics principles, and the hypercolumn theory. A visual frame theory is developed to explain the visual information processing mechanisms of human vision, where the size of a unit visual frame is tested and calibrated based on vision experiments. Then, the framework of human visual information processing is established. Based on it, the mechanisms of visual information processing and the compatibility of internal representations between visual and abstract information and knowledge are elaborated.

Semantic grasping escapes Weber's law

In previous studies of human information processing, the visual separate system and the auditory separate system have been frequently studied. However, human related characteristic between visual and auditory systems has not been investigated substantially. If the mechanisms of human visual and auditory parallel information processing are elucidated, the finding will contribute to improving technical systems. In our previous studies, human related characteristic between visual search and speech perception is studied. The results showed the mutual effect between visual information processing and auditory information processing in the visual and the auditory parallel information processing. However, to clarify the cause of many car accidents lies in the use of car-phone on driving, it is necessary to use the same kind of visual and auditory stimuli in psychological experiments. In this paper, characteristic of reaction time in parallel information processing of human visual and auditory system is measured by using the same kind of stimuli. The experimental results show the factors that influence the visual and the auditory reaction time are the difficulty of the visual and the auditory stimuli and the timing of the visual and the auditory inputs. The experimental results also suggest that one of the causes of car accidents (to use car-phone while driving) is that the human visual information processing is affected by the auditory information.

As an important branch of artificial intelligence, computer vision plays a huge role in the rapid development of artificial intelligence. From a biological point of view, in the acquisition and processing of information, vision is much more important than hearing, touch, etc., because 70% of the human cerebral cortex is processing visual information. Therefore, advances in computer vision technology are critical to the development of artificial intelligence that is designed to allow machines to think and handle things like humans. The acquisition and processing of visual information has always been the focus of computer vision research, and it is also difficult. The main problem of traditional computer vision technology in the processing of visual information is that the extracted image features are less discriminative, the generalization ability of image features in complex background scenes is insufficient, and the recognition ability on object recognition is poor. In response to these problems, based on the visual neural mechanism, this paper establishes an appropriate computer model for the neuronal cells in the human primary visual cortex, models the recognition response mechanism of the visual ventral system, and performs image feature extraction on the training samples. And object recognition. The results show that compared with the traditional methods, the proposed method effectively improves the discrimination of image features, and the image features extracted under complex background scenes have good generalization ability. On this basis, the training samples can be effectively recognized. The results show that the model based on the visual neural mechanism, the recognition of the edge, orientation and contour of the training sample show the advantages of the biological vision mechanism in object recognition.

Findings from a study designed to examine differences in ex pert and novice teachers' information processing are pre sented. Specifically, results are described which suggest differ ences in the ways expert, novice, and "postulant" teachers perceive, understand, monitor, and process visual information in classrooms. Expert, novice, and postulant subjects were asked to view a series of slides taken in science and mathema tics classrooms and to discuss their perceptions about and reactions to visual stimuli. Subjects were asked to respond to structured interview questions both orally and in writing; the responses were recorded and transcribed for analysis. Protocols and written responses were analyzed through a multi-step, itera tive process designed to determine patterns, trends, and differ ences in both kind and quantity of responses. Results suggested that experts, novices, and postulants differed with respect to their abilities to perceive and interpret classroom information. Experts appeared better able to weigh the import of one piece of visual information against another, to form connections among pieces of information, and to represent management and instructional situations into meaningful problem units. In general, experts appeared to possess comparatively richer schemata for ascribing meaning to visual classroom information.

Processing of emotional visual information engages cognitive functions and induces arousal. We aimed to examine the modulatory role of emotional valence on brain activations linked to the processing of visual information and those linked to arousal. Participants were scanned and their pupil size was measured while viewing negative and neutral images. The visual noise was added to the images in various proportions to parametrically manipulate the amount of visual information. Pupil size was used as an index of physiological arousal. We show that arousal induced by the negative images, as compared to the neutral ones, is primarily related to greater amygdala activity while increasing visibility of negative content to enhanced activity in the lateral occipital complex (LOC). We argue that more intense visual processing of negative scenes can occur irrespective of the level of arousal. It may suggest that higher areas of the visual stream are fine-tuned to process emotionally relevant objects. Both arousal and processing of emotional visual information modulated activity within the ventromedial prefrontal cortex (vmPFC). Overlapping activations within the vmPFC may reflect the integration of these aspects of emotional processing. Additionally, we show that emotionally-evoked pupil dilations are related to activations in the amygdala, vmPFC, and LOC.

This investigation compared deaf and hearing subjects in the degree of accuracy with which they can perceive visual nonverbal information about people, their short-term recall of visual information and the extent to which they focus on different parts of the body. Subjects were asked to gauge information about relationships between people shown in photographs and later to indicate what they remembered from the photos. Neither group demonstrated a statistically significant advantage in accuracy or recall. When comparing the reasoning processes used by the two groups to arrive at their conclusions it was found that deaf subjects were more than twice as likely as hearing subjects to base their judgments upon hand and arm behavior.

This paper analyzes the parallel and serial information processing structure of visual system and proposes a visual information processing model with three layers: visual receptor layer, visual information conduction and relay layer, and information processing layer of visual information computing and processing area. Based on the analysis, abstraction, and simplification of the biological prototype of each layer in the visual system, a framework model of an artificial neural system corresponding to the visual system is proposed. An artificial neural network model is proposed to simulate the mechanism of visual attention. A network model is formed by introducing the saliency mask map as additional information on the benchmark network, and the selective enhancement operation is performed on the extracted features in different regions according to the mask map. The experimental results show that the visual computing processing network model can effectively improve the classification performance of the network when the appropriate saliency mask is used. The visual information computing and processing model network can work effectively for different data sets and different structures of the benchmark network, which is a universal network model. The complexity of visual information computing and processing model network is very small, and the improvement of network performance is not at the cost of increasing model complexity, but in the way of improving network efficiency. The performance of artificial neural network visual information computation and processing model is directly related to the performance of saliency map used as mask map.

Contrast in visible images is one of the most relevant characteristics of visual signals. Since the pioneering works performed in vision psychology and optics, different definitions have been proposed in the literature. However, for the time being there exist no definition of contrast on which the vision research and visual processing scientific community can agree on. This makes it critical to have a clear view on the notion of contrast and its use in various applications. One issue to consider is how to define and particularly use this important measure in developing image processing and analysis methods. In this article, we present a critical review of contrast measures and associated models developed by the scientific community in vision, optics, and image processing. We also provide learned lessons and guidelines on the use of appropriate contrast measures in selected visual information processing and analysis applications. We discuss challenges and propose research avenues for models enriched by recent findings in the field of human vision research and machine learning. We believe that this work serves as a guideline and can potentially open new research perspectives to the scientific community working on visual information processing and analysis.