Functional representation of vision within the mind: A visual consciousness model based in 3D default space

The human eyes and brain, which have finite boundaries, create a ‘‘virtual’’ space within our central nervous system that interprets and perceives a space that appears boundless and infinite. Using insights from studies on the visual system, we propose a novel fast processing mechanism involving the eyes, visual pathways, and cortex where external vision is imperceptibly processed in our brain in real time creating an internal representation of external space that appears as an external view. We introduce the existence of a three-dimension default space consisting of intrapersonal body space that serves as the framework where visual and non-visual sensory information is sensed and experienced. We propose that the thalamus integrates processed information from corticothalamic feedback loops and fills-in the neural component of 3D default space with an internal visual representation of external space, leading to the experience of visual consciousness. This visual space inherently evades perception so we have introduced three easy clinical tests that can assist in experiencing this visual space. We also review visual neuroanatomical pathways, binocular vision, neurological disorders, and visual phenomenon to elucidate how the representation of external visible space is recreated within the mind

New evidence of visual space anisotropy with autostereograms

Postprint (published version

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Laminar fMRI: applications for cognitive neuroscience

The cortex is a massively recurrent network, characterized by feedforward and feedback connections between brain areas as well as lateral connections within an area. Feedforward, horizontal and feedback responses largely activate separate layers of a cortical unit, meaning they can be dissociated by lamina-resolved neurophysiological techniques. Such techniques are invasive and are therefore rarely used in humans. However, recent developments in high spatial resolution fMRI allow for non-invasive, in vivo measurements of brain responses specific to separate cortical layers. This provides an important opportunity to dissociate between feedforward and feedback brain responses, and investigate communication between brain areas at a more fine- grained level than previously possible in the human species. In this review, we highlight recent studies that successfully used laminar fMRI to isolate layer-specific feedback responses in human sensory cortex. In addition, we review several areas of cognitive neuroscience that stand to benefit from this new technological development, highlighting contemporary hypotheses that yield testable predictions for laminar fMRI. We hope to encourage researchers with the opportunity to embrace this development in fMRI research, as we expect that many future advancements in our current understanding of human brain function will be gained from measuring lamina-specific brain responses

A Contrast- and Luminance-Driven Multiscale Netowrk Model of Brightness Perception

A neural network model of brightness perception is developed to account for a wide variety of data, including the classical phenomenon of Mach bands, low- and high-contrast missing fundamental, luminance staircases, and non-linear contrast effects associated with sinusoidal waveforms. The model builds upon previous work on filling-in models that produce brightness profiles through the interaction of boundary and feature signals. Boundary computations that are sensitive to luminance steps and to continuous lumi- nance gradients are presented. A new interpretation of feature signals through the explicit representation of contrast-driven and luminance-driven information is provided and directly addresses the issue of brightness "anchoring." Computer simulations illustrate the model's competencies.Air Force Office of Scientific Research (F49620-92-J-0334); Northeast Consortium for Engineering Education (NCEE-A303-21-93); Office of Naval Research (N00014-91-J-4100); German BMFT grant (413-5839-01 1N 101 C/1); CNPq and NUTES/UFRJ, Brazi