1993 …2024

Research activity per year

Personal profile

Artistic and research interests

The main research area of Parkkonen is non-invasive neuroimaging, mainly instrumentation and data analysis methods related to MEG as well as human neuroscience of sensory modalities and cognition. He has contributed to MEG instrumentation and signal processing methods that are currently in active use in over 100 laboratories world-wide. Currently he pursues the use of optically-pumped magnetometers for MEG, exploits real-time feedback of measurements of brain activity to study cognition and plasticity, both for basic neuroscientific research and for clinical applications. He is also coordinating a national consortium to develop a biobank for functional brain-imaging data.

Parkkonen has also contributed to ultra-low-field MRI research and to invasive monitoring of local cortical activity. In cognitive neuroscience, Parkkonen has shed light on the neural mechanisms of sensory processing, particularly conscious visual perception. Recently he has pioneered the emerging field of social neuroscience to uncover brain mechanisms supporting social interaction by using hyperscanning i.e. simultaneous recording of the brain activity of the interacting participants.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Education/Academic qualification

Doctoral degree, Engineering and Technology, Helsinki University of Technology

Award Date: 25 Aug 2009

Master's degree, Engineering and Technology, Helsinki University of Technology

Award Date: 11 Jun 1996


  • Neuroscience
  • Neurotechnology
  • Human brain imaging
  • Medical Technology
  • Brain Research Unit
  • Aalto Brain Centre (ABC)
  • O.V. Lounasmaa Laboratory
  • Department of Biomedical Engineering and Computational Science
  • Signal processing
  • Magnetic resonance imaging
  • Magnetoencephalography
  • Bioelectromagnetism
  • Inverse problems
  • Modeling the brain


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Collaborations and top research areas from the last five years

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