[email protected]
Computational Neuroscience Group

In my ongoing Ph.D. project, titled “Exploring the effective communication of brain network dynamics under different states”, we carried the first research to demonstrate significant brain-wide integration changes during three cognitive tasks using intracranial EEG [1].  In a second study, we provided the first demonstration of a whole-brain model integrating anatomical connectivity, functional activity and neuromodulator receptor density from multimodal imaging of healthy human participants [2], and in a third study, we investigated the relevant timescale for understanding spatiotemporal dynamics across the whole brain. We introduced a novel way to generate whole-brain neural dynamical activity at the millisecond scale from fMRI signals, and using the independent measures of entropy and hierarchy to characterize the richness of the dynamical repertoire, we showed that both methods find a similar optimum at a timescale of around 200 ms in resting state and in task data [3].

1. Cruzat, J., Deco, G., Tauste-Campo, A., Principe, A., Costa, A., Kringelbach, M. L., & Rocamora, R. (2018). The dynamics of human cognition: Increasing global integration coupled with decreasing segregation found using iEEG. NeuroImage, 172, 492-505.

2. Deco, G., Cruzat, J., Cabral, J., Knudsen, G. M., Carhart-Harris, R. L., Whybrow, P. C., ... & Kringelbach, M. L. (2018). Whole-brain multimodal neuroimaging model using serotonin receptor maps explains non-linear functional effects of LSD. Current biology, 28(19), 3065-3074.

3. Deco, G., Cruzat, J., & Kringelbach, M. L. (2019). Brain songs framework used for discovering the relevant timescale of the human brain. Nature communications, 10(1), 583.