Mind Science

1802 Submissions

[3] viXra:1802.0275 [pdf] submitted on 2018-02-20 08:37:55

The Brain Wrinkles

Authors: George Rajna
Comments: 42 Pages.

A team of researchers working at the Weizmann Institute of Science has found that organoids can be used to better understand how the human brain wrinkles as it develops. [29] A team of biologists has found an unexpected source for the brain's development, a finding that offers new insights into the building of the nervous system. [28] Researchers discover both the structure of specific brain areas and memory are linked to genetic activity that also play important roles in immune system function. [27] The inner workings of the human brain have always been a subject of great interest. Unfortunately, it is fairly difficult to view brain structures or intricate tissues due to the fact that the skull is not transparent by design. [26] But now there is a technology that enables us to "read the mind" with growing accuracy: functional magnetic resonance imaging (fMRI). [25] Advances in microscopy techniques have often triggered important discoveries in the field of neuroscience, enabling vital insights in understanding the brain and promising new treatments for neurodegenerative diseases such as Alzheimer's and Parkinson's. [24]
Category: Mind Science

[2] viXra:1802.0190 [pdf] submitted on 2018-02-14 21:46:19

Evolution Linked to String Theory

Authors: Mell Lenz, Baz Taylor
Comments: 14 Pages.

The Lenz/Taylor theory is a prediction model derived from human development and suggests that the unification of several sciences including String Theory may be undeniable when placed into a cohesive context. For the purpose of this paper, String Theory was used comparatively for the overall concept and provides for it a more meaningful context. 5 stages of space and 5 stages of awareness... together they equal 10 stages of life and 2 stages of birth and death creating 12 stages (with 1 and 12 representing life and death respectively, in the broader sense of the Universe recycling matter) happening simultaneously. “We looked inside Pandora’s Box and found hope.” Mell Lenz
Category: Mind Science

[1] viXra:1802.0066 [pdf] submitted on 2018-02-06 05:41:09

a Computational Approach to Estimation of Crowding in Natural Images

Authors: Lauri Ahonen
Comments: 83 Pages. Master's thesis

Crowding is a phenomenon where the identification of objects in peripheral vision is deteriorated by the presence of nearby targets. Crowding therefore reduces the extent of visual span, i.e. information intake during a single eye fixation. It is, thus, a limiting factor of many everyday tasks, such as reading. The phenomenon is due to wide area feature integration in the higher levels of visual processing. Despite the critical role of the phenomenon, complex natural images have so far not been used in the research of crowding. The purpose of the present study was to determine how the crowding effect affects object recognition in complex natural images, and whether the magnitude of the crowding could be modelled using methods introduced below. The actual magnitude of the crowding effect was determined experimentally by measuring contrast thresholds for letter targets of different sizes on various natural image backgrounds. The results of the experiments were analyzed to evaluate the developed methods. The methods are based on image statistics and clutter modelling. Clutter models assess the complexity in the image. The image statistics and the clutter models were combined with basic knowledge of the crowding effect. In addition, an early visual system model was incorporated to assess the role of the visual acuity across the visual field. The developed models predicted the induced crowding effect in an arbitrary natural image. The model of the visual system contributed to the results, as well. The differences between the methods for assessing the image properties were, however, negligible. Contrast energy, the simplest measure, can be regarded as the most efficient. Natural images can cause very strong crowding effects. The conclusion is that predicting quantitative dimensions of the crowding effect in an arbitrary image is viable. However further research of the subject is necessary for developing the models. Computational assessment of the crowding effect potentially can be applied to e.g. user interface design, assessing information visualization techniques, and the development of augmented reality applications.
Category: Mind Science