Scientists Shed New Light On How The Brain Detects Motion


Ben Taub


Ben Taub

Freelance Writer

Benjamin holds a Master's degree in anthropology from University College London and has worked in the fields of neuroscience research and mental health treatment.

Freelance Writer

3800 Scientists Shed New Light On How The Brain Detects Motion
Scientists have discovered that the neural pathways involved in detecting motion differ depending on whether the moving object is alive or not. Taiga/Shutterstock

If you’ve managed to avoid getting hit by a bus today, you should thank your brain, which is designed to detect motion in order to help us safely navigate the world around us. This ability is so vital for our survival as a species that we’ve even developed the capacity to detect “implied motion,” such as movement that is suggested in still photographs. Yet while most of us take this for granted, scientists have long struggled to understand the neural pathways that control this essential function.

Publishing their findings in the journal NeuroImage, a team of researchers from Dartmouth College have now shed new light on how the brain interprets motion, indicating that the two pathways involved in this process may be more integrated than previously thought. Additionally, their results suggest that motion is processed differently depending on whether the moving object is animate or inanimate.


For over two decades it has been generally accepted that the detection of movement occurs via two separate neural pathways, both originating in the primary visual cortex of the brain, the region concerned with vision. An area called the dorsal stream, which runs to the parietal cortex, is responsible for determining the location of objects, and is therefore known as the “where” pathway, while the ventral stream runs to the temporal cortex, and carries data regarding “what” the object is.

The researchers performed functional magnetic resonance imaging (fMRI) scans on a number of participants as they viewed photographs with varying levels of implied motion, hoping to determine how these two pathways work together. The photographs were divided into four categories, two of which involved animate objects (animals and humans) while the other two were inanimate (objects and scenery). They were also arranged into five levels of motion, with level 0 representing stasis and level 5 representing high speed.

Scientists took fMRI scans of volunteers as they observed a series of images with varying degrees of implied motion and animacy. Zhengang Lu

Interestingly, the scans revealed increased activity in both pathways as implied speed increased in the pictures of inanimate objects, but hardly any increase in activity as speed increased in the pictures of people and animals. This suggests that the ways in which the brain processes motion differs depending on whether the moving item is alive or not. At the same time, the fact that the dorsal pathway was affected by the animate-inanimate distinction seems to imply that it is involved not only in determining location, but also categorizing objects. As a consequence, the study authors conclude that “the two visual pathways may interact with each other instead of being separate from one another when processing implied motion of different stimulus categories.”


While the researchers insist that more work is needed to determine exactly how the two pathways are connected, they have already identified a number of potential implications for their findings. For instance, this new knowledge could contribute to the development of treatments for disorders such as agnosia, whereby complications within the ventral pathway cause an inability to identify objects, faces or places. Similarly, Akinetopsia, which is a disorder of the dorsal pathway, leaves sufferers unable to perceive motion, instead seeing the world as a sequence of disjointed still images.

Furthermore, co-author Zhengang Lu said in a statement that the insights provided by this study could even help to develop motion recognition algorithms that could revolutionize security and surveillance systems. “By analyzing how terrorists would move in public spaces and incorporating this action signature into pattern recognition algorithm, better accuracy of recognition of terrorist suspects may be achieved than with facial-feature based recognition algorithm,” he said.


  • tag
  • brain,

  • movement,

  • motion,

  • neurology,

  • dorsal stream,

  • ventral stream,

  • primary visual cortex,

  • agnosia,

  • akinetopsia