The World in Your Head: A Gestalt View of the Mechanism of Conscious Experience

The World in Your Head: A Gestalt View of the Mechanism of Conscious Experience

The World in Your Head: A Gestalt View of the Mechanism of Conscious Experience

The World in Your Head: A Gestalt View of the Mechanism of Conscious Experience


The World In Your Head: A Gestalt View of the Mechanism of Conscious Experience represents a bold assault on one of the greatest unsolved mysteries in science: the nature of consciousness and the human mind.

Rather than examining the brain and nervous system to see what they tell us about the mind, this book begins with an examination of conscious experience to see what it can tell us about the brain.

Through this analysis, the first and most obvious observation is that consciousness appears as a volumetric spatial void, containing colored objects and surfaces. This reveals that the representation in the brain takes the form of an explicit volumetric spatial model of external reality. The world we see around us therefore is not the real world itself, but merely a miniature virtual-reality replica of that world in an internal representation. In fact the phenomena of dreams and hallucinations clearly demonstrate the capacity of the brain to construct complete virtual worlds even in the absence of sensory input. Perception is therefore somewhat like a guided hallucination, based on sensory stimulation.

This insight allows us to examine the world of visual experience not as scientists exploring the external world, but as perceptual scientists examining a rich and complex internal representation. This unique approach to investigating mental function has implications in a wide variety of related fields, including the nature of language and abstract thought, motor control and behavior, as well as to the world of music, art, and dance, showing how the patterns of regularity and periodicity in space and time apparent in those aesthetic domains reflects the periodic basis set of theunderlying harmonic resonance representation in the brain.


The workings of the human mind and brain represents one of the last great frontiers in human knowledge. For our understanding of the brain today is in a state where physics was before Newton, or astronomy before Galileo. For many years I have felt a strong attraction to this field of knowledge because unlike other branches of science, this one remains wide open to armchair philosophy and novel theoretical approaches. I have always suspected that introspection can offer useful insights into the workings of the brain. How could it possibly be otherwise? Curiously, I was to discover that this is very much a minority view, most experts in the field today seem to think that perception gives us knowledge of the world, rather than of the brain, and that observations made introspectively are somehow suspect, being hopelessly subjective and impossible to verify. My first entry into this field was by way of image processing and artificial intelligence. There is no better introduction to the problems of natural vision than attempting to solve the problem with computers. For the computer has, in the digital image, all of the information in that image in the form of explicit numerical data. And yet the problem of extracting useful information from that data turns out to be extraordinarily difficult. For although the computer can detect simple features easily enough, such as image edges, an edge detection algorithm tends to find thousands of edges in a typical natural scene, most of which are spurious, either texture lines, or shadows, or irregular fragmented surfaces that are hopelessly confused. Furthermore, many of the most significant edges are often missing, being occluded by foreground objects, or having insufficient contrast with the background, and many significant edges contain gaps, kinks, multiple contours, contrast reversals, etc. The next step of making sense of configurations of edges remains largely an unsolved problem except in the most controlled visual environments. In my experience with image processing I began to get the impression that the farther we progress with complex algorithms designed to analyze the image data with ever more sophisticated strategies, the more brittle and rigid and cantankerous our algorithms seem to become. I began to see that there is a fundamental difference between the properties of natural vision, as exhibited even by the lowly house fly, and the rigid deterministic approach to vision represented by the digital computer. The little fly, with its tiny pinpoint of a brain, dodging effortlessly between the tangled branches of a shrub in dappled sunlight and in gusty cross-winds, seems to thumb its nose at our lofty algorithms and expensive hardware that can, at best, guide a van loaded with the latest in computer equipment at a snail's pace down a clearly demarcated road, even then occasionally running astray. It became clear to me that nature was hiding some very simple elegant secret in biological vision, whose operational principles are entirely different from digital computation.

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