Human Systems Neuroscience
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Our mission
We aim to understand how the human brain works by following electrophysiological and hemodynamic changes by means of noninvasive imaging: magnetoencephalography (MEG) to track brain dynamics at millisecond scale and functional magnetic resonance imaging (fMRI) to spot the active brain areas with millimeter precision. This systems neuroscience approach suits well for merging information from many fields of science interested in human behavior: neuroscience, psychology, social psychology, neurology, psychiatry, and even economics.
Research interests
Brain basis of social interaction
Humans are tuned for and shaped by social interaction. Inherently, studies of the brain basis of social interaction are utmost challenging because the stimuli (gestures, postures, facial expressions, etc) are highly variable, and the brain responses depend in an unpredictable manner on the context, emotional state, and even on reactions of the interacting subject him/herself. Such studies are strongly motivated by the high number of disorders of social interaction, such as autism.
We are interested in socially relevant motor and sensory interaction systems that are activated during the subjects own actions or sensory percepts as well as when the subject observes another person performing a similar motor act or experiencing a similar sensory event. Such "mirroring systems" likely form the basis for intersubjective understanding.
We also aim to develop new setups and analysis methods for as naturalistic experimental conditions as possible, trying to bring the social life to the imaging laboratory. We have started to use eye tracking data as an additional source of information about the subject's focus of interest. Social decision making is studied in the context of financial games. Our goal is to move towards real "two-person neuroscience", both experimentally and conceptually (see Hari and Kujala, Physiol Reviews 2009).
Sensory systems
Touch as the most intime sense has lacked proper natural stimulators that we are now trying to develop and test. We are studying whether frequency tagging might unravel brain mechanisms of bistable visual percepts. In multisensory perception, we have recently focused on audiotactile interactions.
Acute and chronic pain
Chronic pain is a devastating disease that causes considerable human suffering and also has a major economical impact as loss of productivity and costs of treatment. Although acute pain is an ecologically useful warning sign of a threatening tissue damage, changes in the peripheral and/or central nervous system may turn these initially beneficial signals into a disease so that the pain becomes chronic.
To properly understand the complex pathophysiological mechanisms underlying chronic pain, we study how healthy nervous system reacts to acute pain. Following tissue injury, pain impulses are transmitted to the central nervous system by the myelinated fast conducting Aδ-fibers that mediate sharp and pin-prick-like “first” pain and the unmyelinated slow C-fibers that mediate dull, long-lasting and burning “second” pain. As the two pain fiber types differ clearly in their function, they are likely to be differentially involved in various pain disorders; for example, the C-fiber system may be inappropriately active in chronic pain, whereas the Aδ-fiber system is dampened.
We have dveloped methods to selectively stimulate the two nociceptive afferent systems. We currently study groups of well-specified patients suffering from chronic pain, with the aim to clarify whether, and how, one or both of the pain afferent systems (or even the tactile afferent system) are affected. We are also interested in defining the possible modification of the pain–motor cortex connection in pain patients.
Methodological development
Diffusion-tensor imaging (DTI) of white-matter tracts is a new—and presently the only—method for non-invasive visualization of fiber tracts within the living human brain. DTI is based on monitoring of diffusion of water molecules, which within a tight fiber bundle (such as a white-matter tract in the brain) is less limited along the fibers than perpendicular to them. Such imaging is especially important because the tract strengths and course can be correlated with individual skills, pathology, or functional connectivity revealed by e.g. MEG and fMRI. We are currently applying DTI to the study of peripehral nerves.
A new visualization tool is under development to combine anatomical and functional volume data with equivalent current dipoles from MEG analysis. Also, other information such as fiber tracts from DTI can be incorporated. The tool allows the use of both volume rendering and surface rendering methods, benefiting from the hardware acceleration of modern graphics boards. A previously developed texture-mapping method [Seppä & Hämäläinen, Neuroimage 2005] for image generation has been applied for fast and realistic-looking surface visualizations.
People
Hari Riitta, MD PhD, Academy professor; Director of BRU, CoE, and aivoAALTO
Forss Nina, MD PhD, docent, neurologist; senior scientist, Head of CliniMEG (part time)
Jousmäki Veikko, PhD, docent, senior scientist; Director of MEG Centre
Nummenmaa Lauri, PhD, docent, senior scientist @ aivoAALTO
Pihko Elina, PhD, docent, senior scientist; Coordinator of aivoAALTO
Baess Pamela, PhD, postdoctoral scientist
Kirveskari Erika, MD PhD, clinical neurophysiologist, postdoctoral scientist (part time)
Koskinen Miika, DrTech, postdoctoral scientist
Malinen Sanna, DrTech, postdoctoral scientist (on leave)
Nangini Catherine, PhD, postdoctoral scientist
Pannasch Sebastian, PhD, postdoctoral scientist
Piitulainen Harri, PhD, postdoctoral scientist
Renvall Ville, DrTech, postdoctoral scientist
Seppä Mika, DrTech, postdoctoral scientist
Hiltunen Jaana, PhLic, hospital physicist, PhD student; Techn. director of AMI Centre (on leave)
Hirvenkari Lotta, MSc, PhD student (biology)
Hotta Jaakko, MD, PhD student (neurology; part time)
Laaksonen Kristina, MD, PhD student (neurology; part time)
Lamminmäki Satu, MD, PhD student (medicine)
Mandel Anne, PhD student (cognitive science)
Pamilo Siina, MSc(Tech), PhD student (cognitive technology)
Ramkumar Pavan, MSc(Tech), PhD student (signal processing)
Saarinen Veli-Matti, MSc(Tech); eye-traking engineer
Helokunnas Siiri, undergrad student (cognitive science)
Kaksonen Marika, undergrad student (medicine)
Kumar Kranthi, undergrad student (signal analysis)
Keitaanniemi Mariia, undergrad student (physics)
Mäntykangas Mika undergrad student (physics)
Smeds Eero, undergrad student (medicine)
Suppanen Emma undergrad student (physics)
Tiainen Mikko undergrad student (psychology)
Current collaborations
- FINLAND Aalto University
- Signal analysis (e.g. ICA and source modelling)
- Neuroeconomics (effect of competition)
- Selective hearing
- FINLAND Elekta-Neuromag Oy
- Research agreement (validation, consultation, education)
- FINLAND Finnish Institute of Occupational Health
- Face processing
- Eye tracking
- FINLAND Helsinki University Central Hospital (HUS)
- Diffusion tensor imaging
- Pain research
- Radiological development
- Psychiatric imaging
- Clinical MEG recordings
- FINLAND University of Helsinki
- Collaboration with the Neuroscience Research Center (Viikki)
- FRANCE Paul Sabatier University, Tolouse
- Embodied cognition
- GERMANY Research Center Juelich & Univ Hospital Aachen
- Brain basis of agency (touch)
- GERMANY Technische Universität, Dresden
- Eye tracking
- ITALY Universita di Verona, Verona
- MEG source modelling (mathematical methods)
- JAPAN Fujita Neurological Clinic, Higashi-Osaka
- Mirror-neuron system
- JAPAN Kyoto University Graduate School of Medicine
- Human cortical auditory function
- NETHERLANDS University Medical Center Groningen
- Eye tracking
- UNITED KINGDOM University of Nottingham
- Social neuroscience, neuroeconomics
- UNITED KINGDOM Oxford University
- Frequency tagging of visual stimuli (and cortical processing)
- USA Massachusetts General Hospital & Massachusetts Institute of Technology (MIT)
- Modelling and visualization of MEG signals
- USA Washington University in St. Louis
- “Resting-state networks"