Computer science experts at Ulster University, in partnership with Trinity College Dublin, used 3D computer modelling of the brain to explore the speed and pathway that visual signals travel from the optical lobe, the part of the brain that first interprets what we see, to the frontal, parietal and temporal lobes, which process more complex cognition such as decision-making.
This University research, published in The Journal of Neuroscience, one of the leading journals in brain sciences, has the potential to identify areas of the brain that are not functioning correctly, or at all, and provide clinicians with crucial information regarding the most appropriate patient treatment.
The University research was carried out using computer models of study participants' brain activity, which was recorded using state-of-the-art, non-invasive brain imaging facilities at Trinity College Dublin. The Ulster University researchers hope to extend this work by investigating other cognitive processing and brain disorders using the recently acquired magnetoencephalography (MEG) system at Ulster University, the only such machine in Ireland.
Lead researcher, Dr KongFatt Wong-Lin from Ulster University said: "This Ulster University research lays an important foundation for better understanding of the human visual system. Due to the generality of the method, it can be used to understand other sensory or cognitive processing. It also provides us with a new, scientific method to identify areas of the brain that are dysfunctional.
"As a potential clinical application, stroke sufferers can have brain functional pathways that are effectively blocked or redirected, and thereby changing their cognitive processing. This method may be used to identify specific pathway alterations of individuals, and hence providing more precise treatments, for example, through specific rehabilitation or neurofeedback.
"Importantly, this research offers insight into the speed that visual signals travel from one part of the brain to the other. Cognitive processing such as decision-making often requires time to integrate information. Hence the method developed in this work, which identifies the timing of signals within the brain, will be crucial for a better understanding of such cognition.
"It could also potentially be used to understand how some elderly people, seemingly for no reason can lose their balance, fall and injure themselves. This may be attributed to slower or poorer integration of multiple types of information over time. Thus, identifying the signal timing and pathways will be useful for prescribing appropriate treatment for elderly groups of people."