New Aalto Distinguished Professor Riitta Salmelin traces the brain’s own ‘fingerprint’
Riitta Salmelin believes that her field of brain imaging has matured to a stage where questions ignored in the early days can now be addressed
Imaging Language
Our group's work is necessary for a scientific description of language processing in a healthy human brain, but essential in providing the groundwork for an informed and efficient description and treatment of developmental and acquired language disorders.
Research interests and projects
Over the past few decades, real-time tracking of cortical current flow and accurate localisation of blood oxygenation changes have offered complementary windows to the functional architecture of language in the human brain (MEG, fMRI; local activation, connectivity patterns).
The neuroimaging domain has reached its first level of maturity: we now know how to reliably measure and quantify different types of neuroimaging signals, we know that those signals show good intraindividual reproducibility but notable inter-individual variability in language tasks and, phenomenologically, we know what type of group-level functional effects to expect in a large variety of experimental conditions. To reach the next phase in the neuroscience of language, it is essential
- to uncover the neural mechanisms and representations reflected in the neuroimaging signals,
- to advance from group-level descriptions to quantitative model-based individual-level predictions, and
- to bring together the complementary information provided by different neuroimaging metrics in a principled way.
To reach these goals, we combine careful experimental design and data collection and analysis with computationally explicit models and machine learning approaches.
Aalto University, Imaging Language Group Code
Members
Aino Saranpää
Doctoral Researcher
Recent
Difficulty learning nonsense words may indicate a child’s high risk of dyslexia
Studies show disorder is linked to the left cerebral hemisphere and that confidence can help kids overcome difficulties
Artificial intelligence for dementia prevention
AI-Mind is a 5-year project funded by Horizon 2020, with the goal of facilitating a paradigm shift in clinical practice of mild cognitive impairment. A team of Aalto University and HUS Helsinki University Hospital researchers are involved in the project
Can EEG and machine learning predict respiratory difficulties in Covid19 patients?
Researchers are planning to investigate severe respiratory problems in coronavirus patients with EEG and machine learning, to help to predict the need of intensive care treatment of other COVID19 patients.
The human brain tracks speech more closely in time than other sounds
The way that speech processing differs from the processing of other sounds has long been a major open question in human neuroscience.
Brain scans shine light on how we solve clues
Partnered with machine learning, brain scans reveal how people understand objects in our world.
Riitta Salmelin receives Justine & Yves Sergent award
The awards is a well know prestige among international brain imaging researchers