Research‎ > ‎

EEG

We have a fully equipped EEG lab at the Black Dog Institute including a 64-channels 
EEG set with BrainAmp MR Plus amplifier and custom electrode caps. In both healthy subjects and patients with mood disorder we investigate large-scale brain dynamics and functional connectivity in various paradigms, e.g., resting state, visual working memory and vibrotactile stimulation. We use various data analysis techniques and are particularly interested neural synchronization. We developed a method to assess functional connectivity in single-trial data. The obtained connectivity matrices are assessed using graph analysis and related to the connectivity in large-scale models of spiking neurons.


Resting state

Resting state EEG provides a window into the highly structured nature of spontaneous large-scale brain activity. Patterns in functional connectivity can be observed that might specify functionally relevant brain networks. In addition, by studying the temporal fluctuations in power, deviations from purely linear and diffusive dynamics can be observed that provide insight into the organization underlying system. Below an example is shown of a bimodal distribution of alpha activity (Freyer et al, 2009, J Neurosci 29).





Vibrotactile stimulation

The interactions between sensory stimuli and intrinsic cortical dynamics was parametrically investigated by periodic vibrotactile stimulation at different frequencies. A differential response of cortical populations to certain input frequencies may uncover 

characteristics of the neuronal ensemble dynamics

. The cortical population response was assessed through multivariate phase coherence showing 

phase locked oscillatory activity at different ratios of the stimulus frequency 

(see figure below).

These phase locked components were modulated differently across the range of stimulus frequencies 

with most robust responses around 30Hz. 

These results demonstrate n:m phase synchronization between cortical oscillations and an external periodic signal (Langdon et al, 2010, Prog Biophys Mol Bol).