Functional Brain Imaging (cont’d)

MEG

Ling 411 – 10

Functional Brain Imaging Techniques

Electroencephalography (EEG) Positron Emission Tomography (PET) Functional Magnetic Resonance Imaging (fMRI) Magnetoencephalography (MEG)

• Magnetic source imaging (MSI) Combines MEG with MRI

REVIEW

Magnetoencephalography (MEG)

MEG (MagnetoEncephaloGraphy) measures the magnetic field around the head

Compare EEG: Measures voltage changes on the scalp

MSI (Magnetic Source Imaging) is MEG coupled to MRI

Magnetoencephalography

magnetic brain

pictureproduction of

Magnetoencephalography (MEG)

MEG (MagnetoEncephaloGraphy) measures the magnetic field around the head

Compare EEG: Measures voltage changes on the scalp

MSI (Magnetic Source Imaging) is MEG coupled to MRI

Intra-Cranial Sources

Papanicolaou 1998:31

Dipole (source current)

How MEG works

Records the magnetic flux or the magnetic fields that arise from the source current

A current is always associated with a magnetic field perpendicular to its direction

Magnetic flux lines are not distorted as they pass through the brain tissue because biological tissues offer practically no resistance to them (cf. EEG)

Magnetoencephalography (MEG)

Records the magnetic flux or the magnetic fields that arise from the source current

A current is always associated with a magnetic field perpendicular to its direction

Magnetic flux lines are not distorted as they pass through the brain tissue because biological tissues offer practically no resistance to them (cf. EEG)

A dipole is a small current source

Dipole generates a magnetic field

Dendritic current from apical dendrites of pyramidal neurons

At least 10,000 neighboring neurons firing “simultaneously” for MEG to detect

Recording of the Magnetic Flux

Recorded by special sensors called magnetometers A magnetometer is a loop of wire placed parallel to

the head surface The strength (density) of the magnetic flux at a

certain point determines the strength of the current produced in the magnetometer

If a number of magnetometers are placed at regular intervals across the head surface, the shape of the entire distribution by a brain activity source can be determined (in theory)

Magnetic flux from source currents

Source current

Magnetic flux Magnetometer

Recording of Magnetic Signals

An MRI Machine

Recording of the Magnetic Flux

Present day machines have 248 magnetometers The magnetic fields that reach the head surface are

extremely small Approximately one million times weaker than the

ambient magnetic field of the earth Because the magnetic fields are extremely small, the

magnetometers must be superconductive (have extremely low resistance)

Resistance in wires is lowered when the wires are cooled to extremely low temperatures

Recording of the Magnetic Flux

When the temperature of the wires approaches absolute zero, the wires become superconductive

The magnetometer wires are housed in a thermally insulated drum (dewar) filled with liquid helium

The liquid helium keeps the wires at a temperature of about 4 degrees Kelvin

The magnetometers are superconductive at this temperature

Recording of the Magnetic Flux

The currents produced in the magnetometers are also extremely weak and must be amplified

Superconductive Quantum Interference Devices (SQUIDS) The magnetometers and their SQUIDS are kept in a dewar,

which is filled with liquid helium to keep them at an extremely low temperature

How a MEG Recording is Made

The MEG machine is located in a magnetically shielded room• Subjects cannot wear any

metal because it affects the recording

Digitization process After digitization, the task

is run and the recording is made

The Digitization Process

Needed for co-registration with MRI• MRI scan is done later• Provides images• MSI – Magnetic Source Imaging

Method • 5 points

3 electrodes on forehead 2 earpieces

• Subjects must remain extremely still during the digitization process

After digitization, the task is run and the recording is made

Dipolar Distribution of the Magnetic Flux

In the following figure, one set of concentric circles represents the magnetic flux exiting the head and the other represents the re-entering flux

This is called a dipolar distribution

The two points where the recorded flux has the highest value are called extrema

The flux density diminishes progressively, forming iso-field contours

Surface distribution of magnetic signals

Extrema

Dipolar Distribution of the Magnetic Flux

From the dipolar distributions, we can determine some characteristics of the source

1. The source is below the mid-point between the extrema (points where recorded flux has highest value)

2. The source is at a depth proportional to the distance between the extrema

• Extrema that are close together indicate a source close to the surface of the brain

• A source deeper in the brain produces extrema that are further apart

3. The source’s strength is reflected in the intensity of the recorded flux

4. The orientation of the extrema on the head surface indicates the orientation of the source

Co-registration of MEG and MRI space

MEG scan co-registered with MRI scanusing fiducial markers

Result of co-registration

Event-related brain responses: EEG & MEG

Both types of signals come from the same type of event: active dipoles• Different directions from the dipoles• Detected by different devices

With EEG• ERP – event-related potential

With MEG• ERF – event-related (magnetic) field• Addition from 100 or more trials for each tested

condition needed to get measurable data

The inverse problem

A problem for EEG and MEG Locating the dipole(s) based on signals reaching surface of

scalp Problem: Multiple solutions are possible

• Cf. solving x + y = 24 Computer uses iterative procedure to come up with best

fit The problem is compounded by the fact that the brain is a

parallel processor• Many dipoles at each temporal sampling point

MSI before neurosurgery

MSI is preferred because mapping by cortical stimulation increases the patients’ susceptibility to infections as a result of lengthened surgery durations

MSI can be performed prior to the scheduled surgery so that the surgeons can plan the best way to remove the damaged area while avoiding language areas as best they can

Temporal Resolution of MEG

Excellent – unlike fMRI and PET The temporal order of activation of areas in a pattern can

be discerned The time course of the activation can be followed MEG has potential to detect the activation of several brain

regions as they become active from moment to moment during a complex function such as recognition

Temporal Resolution of MEG

Only with MEG can we detect the activation of several brain regions as they become active from moment to moment during a complex function such as recognition

But it is (at present state of the art) virtually impossible to achieve precision

Time course of activation

We can follow the activation of a source across time The magnetic fields recorded in MEG are evoked Activation at each point in time is recorded (millisecond

sensitivity) Sources of early components of Evoked Fields circumscribe

the modality-specific sensory areas Sources of late components circumscribe different sets of

brain regions (mostly association cortex)• These activation patterns are function- (or task-) specific

Spatial limitation of MEG

Magnetic flux is perpendicular to direction of electrical current flow

Flux is therefore relatively easy to detect if dendrites are parallel to surface of skull• i.e., for pyramidal neurons along the sides of sulci

But hard or impossible to detect if vertical• i.e., for pyramidal neurons at tops of gyri or at bottoms

of sulci

The challenge of MSI

The cortex is a parallel processor• Hundreds or thousands of dipoles can be active

simultaneously Multiple dipoles make comprehensive inverse dipole

modeling virtually impossible Hence, compromises are necessary

• Sample larger time spans (up to 500 ms)• Sample larger areas (up to several sq cm)

Other limitations of MEG and EEG

Problem: orientation of dipoles For MEG

• Activity in some areas is practically undetectable Dipoles at tops of gyri Dipoles at bottoms of sulci

For EEG• Dipoles on sides of sulci are hard to detect

Some MEG/MSI Findings

Speech recognition: MEG results

Hemispheric Asymmetry Wernicke's Area

Variability in location of Wernicke’s area(different subjects)

From MEG lab, UT Houston

Wernicke’s area in bilinguals

From MEG lab, UT Houston

Localization of phonemes:The claim of Obleser et al.

Different locations (in temporal lobe) for different vowels

The anterior-posterior axis corresponds to the backness of a vowel – the more back the vowel, the more posterior the source location

The superior-inferior axis corresponds to the height of a vowel (inverse relationship) – the higher the vowel, the more inferior the source location of that vowel

From: Ladefoged, P. (2001). Vowels and Consonants: An Introduction to the Sounds of Languages. Malden, Massachusetts: Blackwell Publishers, Inc.

Distinguishing features of vowels

Tongue height corresponds to F1 (first formant)

Front-back dimension corresponds to F2 (2nd)

The formants are detected in auditory processing (upper temporal lobe)

Tongue positions are controlled by motor cortex (frontal lobe) and monitored in parietal lobe

From: Ladefoged, P. (2001). Vowels and Consonants: An Introduction to the Sounds of Languages. Malden, Massachusetts: Blackwell Publishers, Inc.

Tongue positions

MEG and localization of phonemes

Wernicke’s area may be organized phonemotopically

The anterior-posterior axis corresponds to the backness of a vowel – the more back the vowel, the more posterior the source location

The superior-inferior axis corresponds to the height of a vowel (inverse relationship) – the higher the vowel, the more inferior the source location of that vowel

From: Ladefoged, P. (2001). Vowels and Consonants: An Introduction to the Sounds of Languages. Malden, Massachusetts: Blackwell Publishers, Inc.

MEG and localization of phonemes

Results: The relative positions of neural representations for vowels in Wernicke’s area correlate with the relative positions of the vowels in articulatory space• Obleser, Elbert, Lahiri, & Eulitz, 2003• Obleser, Lahiri, & Eulitz, 2004• Obleser, Elbert, & Eulitz, 2004• Eulitz, Obleser, & Lahiri, 2004

Can this finding be replicated?• Finding supported by different lab!• Shestakova, Brattico, Soloviev, Klucharec, & Huotilainen, 2004!

Shestakova et al. experiment (2004)

Done in Helsinki, Russian vowels [i a u]• Obleser et al. in Germany, German vowels [i a u]

Results similar to those of Obleser et al.• Higher cortical location for [a]• Front-back cortical location corresponds to articulatory

positions They go two steps further:

• Input from different speakers (all male)• Similar findings in both LH and RH

An MEG study from Max Planck Institute

Naming animals from visual (picture) input

LH

RH

More information on MEG

The University of Texas Health Science Center at Houston Division of Clinical Neurosciences MEG Lab:• http://www.uth.tmc.edu/clinicalneuro/

Papanicolaou, A. (1998). Fundamentals of Functional Brain Imaging: A Guide to the Methods and their Applications to Psychology and Behavioral Neuroscience.Lisse: Swets & Zeitlinger.

Imaging methods compared

A practical consideration: Cost

Most expensive: MEG• About $2 million for the machine• $1 million for magnetically shielded

room Next most expensive: PET Next: fMRI Cheapest: EEG

Temporal resolution – summary

PET: 40 seconds and up fMRI: 10 seconds or more MEG and EEG: instantaneous

• Theoretically it is possible to do ms by ms tracking, to follow time course of activation

• Commonly used sampling rate for MEG: 4 ms• Practically, such tracking is difficult or impossible

The inverse problem Too many dipoles at each point in time

Spatial Resolution

EEG: Poor PET: Fair – 4-5 mm fMRI: Fair – 4-5 mm

• MRI: Good – 1 mm or less MEG: Fairly good – 3-4 mm or less

• Under good conditions

Sensitivity of Imaging Methods

All of the methods have limited sensitivity MEG

• 10,000 dendrites in close proximity have to be active to detect signal

PET and fMRI• Similar limitations

Any activation that involves fewer numbers goes undetected

Other limitations of MEG and EEG

Problem: orientation of dipoles For MEG

• Activity in some areas is practically undetectable Dipoles at tops of gyri Dipoles at bottoms of sulci

For EEG• Dipoles on sides of sulci are hard to detect

Neuronal Structure and Function

(Pulverműller 2002, Chapter 2)

Neuronal Structure and Function I The Cortex is a Network

Pulvermüller (2002):• The brain is not like a computer“…any hardware computer configuration can realize

almost any computer program or piece of software.” “… it may be that the neuronal structures themselves

teach us about aspects of the computational processes that are laid down in these structures.”

Connectivity as key property

Since it is a network, The cortex operates by means of connections

Grey matter• The functional units are not individual

neurons but clusters of neurons Cortical columns (cf. next slide)

• Horizontal connections to and from neighboring columns Excitatory Inhibitory

White matter• Connections between distant columns

Excitatory only

Gray matter and white matter

Grey matter

White matter

Three views of the gray matter

Different stains show different features

Computers and Brains: Different Structures, Different Skills

Computers• Exact, literal• Rapid calculation• Rapid sorting• Rapid searching• Faultless memory• Do what they are told• Predictable

Brains• Flexible, fault tolerant• Slow processing• Association• Intuition• Adaptability, plasticity• Self-driven activity• Unpredictable • Self-driven learning

Things that brains but not computers can do

Acquire information to varying degrees• “Entrenchment” • How does it work?

Variable connection strength Connections get stronger with repeated use

Perform at varying skill levels• Degrees of alertness, attentiveness• Variation in reaction time• Mechanisms:

Global neurotransmitters (next slide) Variation in blood flow Variation in available nutrients Presence or absence of fatigue Presence or absence of intoxication

Global neurotransmitters

Released into interneural space, has global effect – e.g. serotonin, dopamine

Neuronal Structure and Function:Connectivity

White matter: it’s all connections• Far more voluminous than gray matter• Cortico-cortical connections

The fibers are axons of pyramidal neurons They are all excitatory

• White since the fibers are coated with myelin Myelin: glial cells

There are also grey matter connections• Unmyelinated• Local• Horizontal, through gray matter• Excitatory and inhibitory

Pyramidal neurons and their connections

Connecting fibers• Dendrites (input): length 2mm or less• Axons (output): length up to 10 cm

Synapses• Afferent synapses: up to 50,000

From distant and nearby sources• Distant – to apical dendrite• Local – to basal dendrites or cell body

• Efferent synapses: up to 50,000 On distant and nearby destinations

• Distant – main axon, through white matter• Local – collateral axons, through gray matter

Proportion of pyramidal cells in the cortex

Abeles (1991: 52) says 70% Mountcastle says 70% - 80% (1998: 54)

• Based on information from Feldman (1984) Pulvermüller (2002: 13) says 85%

• Based on information from Braitenburg & Schüz (1998) Some difference comes from how spiny stellate cells are

counted• Pyramidal or not?

No discrete boundary between these categories

Connecting fibers of pyramidal neurons

Apical dendrite

Basal dendrites

Axon

Interconnections of pyramidal neurons

Input from distant cells

Input from neighboring columns

Output to distant cells

Neuronal Structure and Function:Connectivity

Synapses of a typical pyramidal neuron:• Incoming (afferent) – 50,000 (5 x 104) • Outgoing (efferent) – 50,000

Number of synapses in cortex:• 28 billion neurons (Mountcastle’s estimate)

i.e., 28 x 109

Synapses in the cortex (do the math)• 5 x 104 x 28 x 109 = 140 x 1013 = 1.4 x 1015

• Approximately 1,400,000,000,000,000• i.e., over 1 quadrillion

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