Lauri Parkkonen
Institutionen för neurovetenskap och medicinsk teknik

Lauri Parkkonen

Professor (Associate Professor)

Kontakt information

Postadress
Otakaari 3
Mobile phone
+358405089712
Full researcher profile
https://research.aalto.fi/...

Beskrivning

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 has expanded beyond MEG by contributing 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.

Kompetensområden

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

Utmärkelser

Award or honor granted for a specific work
Institutionen för neurovetenskap och medicinsk teknik
Jan 2002

Biomag 2002; Young Investigator Award, First Prize 13th International Conference on Biomagnetism, Young Investigator Committee, saksa

Award or honor granted for academic career
Institutionen för neurovetenskap och medicinsk teknik
Jan 2015

European Research Council (ERC) Starting Grant

Publikationer

Institutionen för neurovetenskap och medicinsk teknik

Adaptive neural network classifier for decoding MEG signals

Publishing year: 2019 NeuroImage
Institutionen för neurovetenskap och medicinsk teknik

On-scalp MEG system utilizing an actively shielded array of optically-pumped magnetometers

Publishing year: 2019 NeuroImage
Institutionen för neurovetenskap och medicinsk teknik

Non-Linear Dynamical Analysis of Resting Tremor for Demand-Driven Deep Brain Stimulation

Publishing year: 2019 Sensors (Basel, Switzerland)
Institutionen för neurovetenskap och medicinsk teknik

The impact of improved MEG–MRI co-registration on MEG connectivity analysis

Publishing year: 2019 NeuroImage
Institutionen för neurovetenskap och medicinsk teknik

Optical Co-registration of MRI and On-scalp MEG

Publishing year: 2019 Scientific Reports
Institutionen för neurovetenskap och medicinsk teknik

Decoding attentional states for neurofeedback

Publishing year: 2019 NeuroImage
Institutionen för neurovetenskap och medicinsk teknik

Across-subject offline decoding of motor imagery from MEG and EEG

Publishing year: 2018 Scientific Reports
Institutionen för neurovetenskap och medicinsk teknik

Requirements for Coregistration Accuracy in On-Scalp MEG

Publishing year: 2018 Brain Topography
Institutionen för neurovetenskap och medicinsk teknik

Evidence for a general performance-monitoring system in the human brain

Publishing year: 2018 Human Brain Mapping
Department of Electrical Engineering and Automation, Institutionen för neurovetenskap och medicinsk teknik, Sensor Informatics and Medical Technology

Tracking of dynamic functional connectivity from MEG data with Kalman filtering

Publishing year: 2018 Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018