Current Research

The brain is arguably the most powerful and complex computer in the world, but how does the brain encode information? There are many ways to approach this question, but the visual system is particularly well suited for studying how information about the outside world is coded as patterns of electrical activity in various brain regions, and how this signal changes as it is passed from one stage of analysis to the next. For example, if someone throws a baseball towards you, how are the properties of the ball coded by the spiking activity of neurons in parts of your brain serving vision to enable perception of the ball’s form (“that’s a baseball”) and motion (“it’s coming straight at me”)? Precise and timely calculations to characterize a stimulus are required to initiate an appropriate response (i.e., catch the baseball).

Research in the Dalhousie Visual Neuroscience Lab is focused on examining how the brain codes for the form and motion of objects in the environment. We make use of various experimental techniques including neurophysiology, neuroanatomy, and psychophysics.


Below are a few research topics we are currently interested in:

1. Adaptation in the visual system

The perception and neural processing of a visual stimulus is influenced by the spatial context (what surrounds an object or feature) and the temporal context (what has been observed in the recent past). In other words, the visual system can respond to an identical stimulus in slightly different ways depending on the context this stimulus is seen in. This change in responsiveness is called adaptation. Important questions about adaptation in the visual system include: A) why does the system have this ability; and B) how does the brain implement this ability.

  • Contrast Adaptation: For our purposes, contrast is the relative luminance over space. The visual system adapts to prevailing contrasts while viewing a visual scene. Contrast adaptation is a very robust phenomenon that can be studied at physiological and perceptual levels, but the mechanisms and purpose of contrast adaptation remain open questions.
  • Speed Adaptation: The visual system also adapts to the speed of visual motion. Speed adaptation can improve our ability to discriminate between two similar speeds, but this comes with the cost of poor veridical perception [1,2]. An example of speed adaptation that many motorists experience everyday occurs when a highway transitions to a residential road. Your visual system adapts to high image speeds (~100km/h) as you travel along the highway, but when you slow down to the speed limit of the residential road you perceive that you are moving slower than your actually are. This speed underestimation can cause drivers to exceed the residential speed limit if they use optic-flow information alone without checking their speedometer (a veridical speed measure). We use psychophysics and electrophysiological techniques to study how the visual system codes for image speed from both basic research and applied perspectives.

2. Motion Detection

Photoreceptors in the retina change their membrane potential in response to increments or decrements in luminance. However, a lone photoreceptor cannot tell whether a stimulus is moving or not. The visual system must calculate a motion signal from multiple luminance inputs. The ability to detect motion is a critically important function of all visual systems, but the precise mechanisms for calculating a motion signal require much more investigation to elucidate. The diagram on the right shows a simple correlation-type motion detector [3,4]. This type of circuit is probably a good approximation of how motion detection works in the insect nervous system, but the situation gets more complex in the vertebrate brain.

Motion Detector

References:

  • 1. Bex PJ, Bedingham S, Hammett ST. (1999). JOSA-A, 16: 2817–2824.
  • 2. Clifford CW, Wenderoth P. (1999). Vis Res, 39: 4324–4332.
  • 3. Reichardt W. (1961). In: Sensory Communication, Rosenblith WA ed. New York: Wiley.
  • 4. Crowder NA, Dawson MR, Wylie DR. (2003). J Neurophysiol, 90: 1829-1841.