Research

Neural dynamics and brain oscillations have wide spatio-temporal, inter-individual,  and time-dependent variability. Our goal is to uncover complex systems-level mechanisms governing the emergence of oscillations and their network interactions using computational approaches focusing on brain network analysis in the context of brain oscillations and brain criticality frameworks (Palva & Palva 2012, Palva & Palva 2017, Palva & Palva 2018). We further investigate the structural, biological and genetic basis of brain dynamics and their fluctuations. 

Key publications: 

• Arnulfo, G., Wang, S.H., Toselli, B., Myrov, V., Hirvonen, J., Fato, M., Nobili, L., Cardinale, F., Rubino, A., Zhigalov, A., Palva, S., Palva, J.M. (2020) Long-range phase synchronization of high-frequency oscillations in human cortex. Nature Communications. 11:5363.
• Fuscà M, Siebenhühner F, Wang SH, Myrov V, Arnulfo G, Nobili L, Palva JM, Palva S (2023) Brain criticality predicts individual levels of inter-areal synchronization in human electrophysiological data.Nat Commun. 2023;14(1):4736.
• Palva S, Palva JM (2018) Roles of brain criticality and multi-scale oscillations in temporal predictions for sensorimotor processing. Trends Neurosci. 41 (10): 729-743, .
• Siebenhuhner F, Wang SH, Arnulfo G, Lampinen A, Nobili L, Palva JM, Palva S (2020) Resting-state       cross-frequency coupling networks in human electrophysiological recordings Plos Biology 18(5): e3000685.
• Simola J, Siebenhühner  F, Kantojärvi K, Paunio T,  Palva JM, Brattico E & Palva S (2021) Critical synchronization dynamics of human brain oscillations is influenced by COMT and BDNF genetic polymorphisms. iScience. 2022 Aug 18;25(9):104985. . eCollection 2022 Sep 16.

Oscillations are fundamental for cognitive functions by providing a temporal clocking mechanism for neural processing, their interactions reflecting the routing of information in neuronal circuits. Our research aims to understand computational principles carried out by network oscillations in visual cognition.  We focus on understanding how network oscillations could implement top-down control and representation of sensory information in support of visual working memory and visual attention. 

Key Publications:

• Cruz G, Melcón M, Sutandi M, Palva JM, Palva S, Thut G (2024) Oscillatory brain activity in the canonical alpha-band conceals distinct mechanisms in attention. Journal of Neuroscience Oct 15:e0918242024. .
• Lobier M, Palva JM, Palva S (2018) High-alpha band synchronization across frontal, parietal and visual cortex mediates behavioral and neuronal effects of visuospatial attention NeuroImage 23;165:222-237.
• Honkanen R, Wang S, Rouhinen S, Palva JM, Palva S (2015) Gamma oscillations underlie the maintenance of feature specific information and contents of visual working memory Cerebral Cortex 25(10):3788-801. .
• Siebenhühner F, Wang SH, PalvaJM, Palva S (2016) Cross-frequency synchronization connects networks of fast and slow oscillations during visual working memory maintenance. eLife Sep 26;5. pii: e13451. .

We investigate whether deviances of network dynamics from the normative range could lead to brain disorder symptoms. Our overarching goal is to develop novel diagnostic biomarkers for brain disorder subtypes and treatment outcome prediction modeling based on multi-modal brain imaging.  Accurate treatment outcome prediction would allow personalized treatment selection and lead to increased treatment efficacy.  

Key Publications:

Javed E, Suárez-Méndez I, Susi G, Román JV, Palva JM, Maestú F, Palva S (2025) A shift toward supercritical brain dynamics predics Alzheimer's disease progression. J. Neurosci 26:45(9):e0688242024. doi: 10.1523/JNEUROSCI.0688-24.2024

Liu W, Vesterinen M, Andersson A, Partanen P, Knapič S, Juvonen JJ, Siebenhühner F, Salonen A, Renvall H, Ilmoniemi RJ, Castrén E, Isometsä E, Van De Ville D, Palva JM, Palva S. Low-dimensional brain-symptom associations delineate depression phenotypes with distinct connectivity biomarkers and symptom profiles.