On Friday 11 March, Professor Tianzi Kiang is poised to present how brain networks correlate with intelligence.
The brain network consists of two basic elements: nodes and connections, which can be defined at different scales and levels. We can study brain networks at microscale by taking neurons as nodes of networks and their synaptic connections as the connections. However, the whole brain networks at this scale are too large to study with current computing capacity because there are about one hundred billion neurons and one hundred trillion of their connections for human brain. Brain networks can be also studied at mesoscale by taking minicolumns as nodes of networks and their connections within them as the connections of the networks. Even at this scale, the whole brain networks are too large to study with current computing capacity because there are about two hundred millions of minicolumns for human brain. Therefore, all studies of brain networks conducted at macroscale, where the nodes and connections of brain networks are the anatomically distinct brain regions and inter-regional pathways.
Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. Here, we present the advance on how brain networks correlate with intelligence. First, we present the evidence obtained with both functional magnetic resonance imaging (fMRI). After that, the issue on how individual differences in intelligence are associated with brain structural organization is addressed and we will demonstrate that higher scores on intelligence tests are related to greater global efficiency of the brain anatomical network. We will also present the evidence obtained with diffusion tensor imaging (DTI), a type of magnetic resonance imaging. In the fourth part, we discuss the genetic basis of intelligence-related brain networks. We try to address the issue on how intelligence-related genes influence intelligence-related neuronal systems. Finally, the future directions in this field will be presented.
Date: Friday 11 March 2011
Time: 12:00 - 1:00PM
Speaker: Professor Tianzi Jiang, Neuroimaging, Queensland Brain Institute and Centre for Advance Imaging, The University of Queensland
Place: Level 7 Auditorium, QBI Building (#79), St.Lucia Campus. Seminars will be followed by a sandwich lunch for all attendees.
For a list of upcoming seminars at QBI, go to www.qbi.uq.edu.au/neuroscience-seminars.