How do the brain and eyes jointly process information?

Table of contents

Introduction

The intricacies of the human eye enable us to interpret light and distinguish colour to produce vision. It is, however, the complexity of the processing in the visual pathway from eye to brain along which this information is interpreted and manifested that allows us to create a representation of the surrounding world, otherwise known as visual perception (Gibson, 1950). Whilst vision begins with the eye and ends with the brain, the way these organs work together and the relative influence each has on our perception is fundamental to producing what we see.

Light is first refracted onto the cornea of the eye before passing to the pupil and lens. An image is then projected onto the retina, resulting in the production of ganglion cells specialised to describe depth, colour, shape, motion, and light intensity (Nelson, 2007). Nerve spikes from the ganglion cells containing this information transmit to the brain’s optic nerve, by which visual information is passed for interpretation in the visual cortex.

The right and left visual cortices comprise part of the occipital lobe of the brain, both receiving information from the opposite hemisphere’s visual field. The estimated 140 million neurons in the primary visual cortex (V1) (Lueba & Kraftsik, 1994) fire when visual stimuli appear within their receptive field, and these fields are tuned to receive stimuli of specific orientations and colours (Kandal et al., 2000). The receptive fields of neurons in more complex visual processing areas are able to detect more intricate stimuli such as faces (Kanwisher, McDermott & Chun, 1997) or direction (Allman et al. 1984). The five identified visual areas (V1-V5) are interconnected with varying strengths, allowing information to be projected forward from one to another and feedback to be given. As the visual information passes through this hierarchy, it is proposed that is processed by two pathways of neural representation. These pathways, named the dorsal and ventral streams, are hypothesised to deal with spatial attention and the recognition and perception of visual stimuli respectively, and involve the passing of visual information and representation further into the brain integrating it with awareness, attention, and memory functions (Ungerleider & Mishkin, 1982).

The process of visual perception, as the eye’s sensory input is interpreted throughout the brain enables us to perceive and construct our own visual world.

Gibson (1966) proposed a direct theory of perception, affording the richness of the sensory input with the construction of the perceived visual outcome. He claimed that a variety of environmental cues, or affordances, aid the interpretation of the visual scene. These include brightness, texture gradient, relative size, and superimposition (where one object blocks another). Gibson believed that when combined with invariants (constancies within the environment ie. parallel lines appearing to converge toward a horizon) and optic flow (the pattern of light movement within a visual scene) this was enough to enable the perceiver to orient themselves and the surrounding environment.

There are, however, complexities to Gibson’s bottom-up theory of visual processing. It may be overly simplistic to underestimate the role of a top-down influence from the brain. Gibson’s theory does not account for times when the visual system is fooled, or becomes subject to an illusion.

Rubin’s Vase (Rubin, 1915) is a classic example of how the human visual system is subject to ambiguity, where one single visual stimulus can be perceived as two distinct images. If the visual system directly processes light into an image, it would follow that a single visual input would lead to a universal and singular output. However, the existence of ambiguity in the perception of a visual stimulus suggests there may be times when the brain cannot decide as to what representation to assign to the visual input.

Further questions are raised when looking at the influence of context, and how this can lead us to misinterpret visual stimuli. The Ebbinghaus Illusion, demonstrates perceptual distortion, highlighting the role of contextual cues, where a circle surrounded by large circles is judged as smaller than the same circle surrounded by small circles (Obonai, 1954). This is suggestive of a higher-level process in which the brain applies context relevant logic to the interpretation of a visual stimuli.

Additionally, experience provides strong influence over the processing of visual information. ‘Impossible illusions‘ such as Escher’s Waterfall, and the Hollow Face Illusion (Gregory, 1997) exploit concepts of experiential perceptual learning, such as knowledge that adjacent edges must join, and human faces are always convex. These illusions demonstrate how the brain aims to perceive coherence in 3D objects to make sense out of its visual environment, creating a captivating paradox between what we know and what we are actually seeing.

Visual perception can be ambiguous, distorted, paradoxical, and even fictitious (Gregory, 1980). It appears to be influenced by context, experience, and expectation, a concept asserted by Richard Gregory (1970) who theorised perception as a top-down process. Deduced from observations of when the human visual system makes errors, Gregory proposed that the brain constructs a visual hypothesis from information processed by the eye based on former experience and knowledge.

If the top-down, constructivist theory holds true, there are implications for the constancy of percepts between individuals. We all have idiosynchratic knowledge and experience. Do differences in internal representation lead individuals to perceive visual stimuli differently from each otherAdditionally, what is to be said for the perception of those that have no knowledge or experienceDoherty et al. (2010) observed an absence of suceptibility to the Ebbinghaus illusion in a number of children under seven years of age, perhaps suggestive that experience and knowledge does have an influence on visual information processing. Without the knowledge base, the children were not affected by the contextual cues.

MacLeod (2007) proposes that top-down theories are based on times when visual conditions are poor, and bottom-up theories are founded in ideal viewing conditions; neither of which is an all encompassing explanation of perception. Recent research highlights the interaction of both constructivist and direct processes (MacLeod, 2007), with the proposal that when bottom-up, sensory information is abundant there is less input from contextual hypotheses, and when there is an absence of stimulus information, the brain draws on its prior knowledge and experience to comprehend the input (Ramachandran, 1994).

It becomes apparent that the study of human perception and how it is influenced by not only the anatomical structure of the visual pathway, but also psychological components such as experience and knowledge will enable us to further understand how the eyes and the brain interact to process visual information.

References:

  1. Allman, J., Miezin, F., McGuinness, E. (1985) ‘Direction- and velocity-specific responses from beyond the classical receptive field in the middle temporal visual area (MT)” Perception, 14(2), pp. 105 – 126.
  2. Doherty, M., Campbell, N., Hiromi, T., and Phillips, W. (2010) ‘The Ebbinghaus illusion deceives adults but not young children’, Developmental Science, 13(5), pp. 714-721.
  3. Gibson, J. (1950). The perception of the visual world. Oxford: Houghton Mifflin.
  4. Gibson, J. (1966). The senses considered as perceptual systems. Oxford: Houghton Mifflin.
  5. Gregory, R. (1970). The Intelligent Eye. London: Weidenfeld and Nicolson.
  6. Gregory RL. (1980) ‘Perceptions as hypotheses’. Philosophical Transactions of the Royal Society of London, vol. 290(B), pp. 181-197.
  7. Gregory, R. (1997) ‘Knowledge in perception and illusion’, Philosophical Transactions of the Royal Society of London B, vol. 352, pp. 1121–1128.
  8. Kandal, E., Schwartz,J., and Jessell, T. (2000). Principles of Neural Science. 4th Ed. New York: McGraw-Hill, Health Professions Division.
  9. Kanwisher, N., McDermott, J., and Chun, M. (1997) ‘The fusiform face area: a module in human extrastriate cortex specialized for face perception’, Journal of Neuroscience, 17, pp. 4302-4311.
  10. Leuba, G., and Kraftsik, R. (1994) ‘Changes in volume, surface estimate, three-dimensional shape and total number of neurons of the human primary visual cortex from midgestation until old age’, Anatomy of Embryology, 190, pp.351-366.
  11. McLeod, S. (2007). Simply Psychology. [online] Available at: <http://www.simplypsychology.org/perception-theories.html> [Accessed 22 February 2012].
  12. Nelson, R. (2007) Visual responses of ganglion cells. In: H. Kolb, E. Fernandez, and R. Nelson (eds.), The Organisation of the Retina and Visual System. Salt Lake City (UT): University of Utah Health Sciences Centre.
  13. Obonai, T., (1954) ‘Induction effects in estimates of extent’, Journal of Experimental Psychology, 47, pp. 57-60.
  14. Ramachandran, V. (1994). In: R. Gregory, and J. Harris, (eds.) The Artful Eye. Oxford: Oxford University Press. pp. 249–267.
  15. Rubin, E. (1915). Synsoplevede Figurer: Studier i psykologisk Analyse. Forste Del’ [Visually experienced figures: Studies in psychological analysis. Part one]. Copenhagen and Christiania: Gyldendalske Boghandel, Nordisk Forlag.
  16. Ungerleider, L., and Mishkin, M. (1982). Two cortical visual systems. In: D. Ingle, M. Goodale, and R. Mansfield, (eds). Analysis of Visual Behavior. Cambridge, MA: MIT Press. pp. 549–586.

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