Matias Palva group studies the systems-level neuronal mechanisms of emergent neuronal and behavioral dynamics.
Spontaneous brain activity fluctuates in time scales spanning at least across five orders of magnitude. These fluctuations have also been observed on all studied spatial scales and they are statistically governed by spatio-temporal power-laws.
Such a scale-free organization at a macroscopic level is, however, contrasted by salient scale-specific neuronal activities - neuronal oscillations. Our research addresses the functional significance of scale-free and scale-specific brain dynamics in human sensory perception, cognitive performance, and motor output.
We have developed methods for MEG/EEG source reconstruction, optimized cortical parcellations, and quantification of neuronal/behavioral scaling-laws as well as for the mapping of dynamic neuronal interaction networks from invasive and non-invasive electrophysiological recordings of human brain activity. We are also in the process of translating our data management, analysis, and visualization platform into a more easily shareable python package.
Our three main research lines are 1. Assessing the functional roles of brain criticality and connectivity in human cognition by using MEG/EEG and SEEG based connectomes of neuronal couplings and "dynomes" of spatio-temporal dynamics. We are also performing simulations of brain dynamics and utilize several lines of interventional approaches, from electric and magnetic brain stimulation to cognitive training. 2. Identifying the roles of dysconnectivity and dysdynamics in mental disorders such as depression, anxiety, ADHD and schizophrenia, with the major depressive disorder being our main research focus. 3. Developing neuroplasticity-recruiting cognitive training methods for targeted alterations of cortical connectivity and dynamics.
He is currently investigating large-scale synchronized brain networks and trying to disentangle the effects on synchronized neural activity in case of different neurological disorders such as focal epilepsy or Parkinson's disease.
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He joined our group in 2015 and has been analysing the network of functional interactions obtained from human SEEG data in resting state, using methods from graph theory.
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Contact: All group members can be contacted via email at firstname.lastname@example.org.