Magnetoencephalography (MEG) and its role in studying human neurophysiology David Poeppel Cognitive Neuroscience of Language Lab Department of Linguistics and Department of Biology Neuroscience and Cognitive Science Program University of Maryland College Park Additional slides courtesy of: • Kanazawa Institute of Technology/Eagle Technology • Prof. Dr. Kensuke Sekihara, Tokyo • Prof. Dr. Timothy Roberts, Toronto • Prof. Dr. Riitta Salmelin, Helsinki

resonance imaging (fMRI) Positron emission tomography (PET) Excellent spatial resolution (~1-2mm) Limited temporal resolution (~1sec) Hemodynamic techniques Electro-magnetic Functional magnetic resonance imaging (fMRI) Non-invasive recording from human brain (Functional brain imaging) Electro- encephalography (EEG) Limited spatial resolution (~1cm) Excellent temporal resolution (<1msec) Magneto- encephalography (MEG) D. Poeppel , A. Braun et al.

Origin of the signal - noninvasive measurement - direct measurement. skull CSF tissue MEG EEG B orientation of magnetic field recording surface scalp current flow - noninvasive measurement - direct measurement.

requires sensitive detectors (low noise-high gain amplification) How small is the signal? Earth field Intensity of magnetic signal(T) EYE (retina) Steady activity Evoked activity LUNGS Magnetic contaminants LIVER Iron stores FETUS Cardiogram LIMBS Steady ionic current BRAIN (neurons) Spontaneous activity Evoked by sensory stimulation SPINAL COLUMN (neurons) HEART Cardiogram (muscle) Timing signals (His Purkinje system) GI TRACK Stimulus response Magnetic contaminations MUSCLE Under tension Urban noise Contamination at lung Heart QRS Biomagnetism Fetal heart Muscle Spontaneous signal (a-wave) requires sensitive detectors (low noise-high gain amplification) Signal from retina Evoked signal Intrinsic noise of SQUID

Superconducting Quantum Interference Devices (SQUIDS) with differential measurement Magnetometer Gradiometer KIT System CTF System BTi-4D NeuroMag VectorView 50 mm base line Planar type NeuroMag VectorView BTi-4D Magnes Axial type

Superconductivity To construct a highly sensitive detector - Magnetic flux quantization - Josephson effect - Linearization

Capturing the signal For a gradiometer of this type, a signal from cortex looks different between the two coils because of the distance between the two coils. A signal from far away, however, will look similar in size to the two coils. This gradiometer principle can help further with the challenging problem of measuring small source that exist in an electro- magnetic environment with many large source (subways, elevators, computers, etc.). axial gradiometer recording surface neuronal source

In addition to using gradiometers: Noise reduction using reference channels

In addition to using gradiometers and reference channels for noise reduction: Magnetically shielded room (MSR)

High density sensor array front view bottom view

Sensor layout: recording from 160 channels Response peak at 98ms after onset of an auditory stimulus, in the left and right temporal lobes.

Butterfly plot: overlay of the channels over right temporal lobe Response peak at 98ms after onset of an auditory stimulus

Contour plot: distribution of magnetic field at peak response

For better source reconstruction … not so ideal expensive- but closer to ideal …high spatial sampling is crucial.

Magnetic source imaging (MSI): MEG + MRI Dipole fit at response peak, 98ms after onset of stimulus

Somatosensory evoked field (SEF)

Dipole locations subsequent to somatosensory and auditory stimulation SI 40ms SII 160 ms and >300ms AI 100ms Dipole locations subsequent to somatosensory and auditory stimulation (primary and secondary somatosensory as well as primary auditory areas and the time of response peak). Disbrow et al. (2001) J. Neurophysiol.

What is the benefit of using MEG? EEG As high temporal resolution as EEG … … but much easier and quicker to set up (kids, patients) - Sensitivity to within-subjects effects Magnetic fields are not differentially attenuated …. …. easier to get a reasonable estimate of source over time

fMRI (yellow blobs) and MEG (red dots) show remarkably consistent co-localization Roberts & Poeppel, forthcoming

Sanders, Sekihara, Poeppel 2003

MEG is a technique that allows you to (i) record brain activity directly, with excellent temporal resolution (ms) (ii) design within-subjects experiments and evaluate single-subject data (iii) test models of cognitive processes and evaluate how these models map on to the brain.