Network modularity is a key feature for efficient information processing in
the human brain. This information processing is however dynamic and networks
can reconfigure at very short time period, few hundreds of millisecond. This
requires neuroimaging techniques with sufficient time resolution. Here we use
the dense electroencephalography, EEG, source connectivity methods to identify
cortical networks with excellent time resolution, in the order of millisecond.
We identify functional networks during picture naming task. Two categories of
visual stimuli were presented, meaningful (tools, animals) and meaningless
(scrambled) objects.
In this paper, we report the reconfiguration of brain network modularity for
meaningful and meaningless objects. Results showed mainly that networks of
meaningful objects were more modular than those of meaningless objects.
Networks of the ventral visual pathway were activated in both cases. However a
strong occipitotemporal functional connectivity appeared for meaningful object
but not for meaningless object. We believe that this approach will give new
insights into the dynamic behavior of the brain networks during fast
information processing.Comment: The 3rd Middle East Conference on Biomedical Engineering (MECBME'16