Magnetic Activity of

Brain

Magnets Magnets  are objects that

generate a magnetic field, a force-field that either pulls or repels certain materials, such

as nickel and iron.

Types of magnets

1. Permanent magnets 

2. Temporary magnets 

3. Electromagnets 

• Permanent MagnetsThere are typically four categories of permanent magnets:• Neodymium Iron Boron (NdFeB)

• Samarium Cobalt (SmCo)

• Alnico

• Ceramic or Ferrite

• Temporary Magnets material that behaves like a permanent

magnets when in the presence of a magnetic field. Soft iron devices, such as paper clips, are often temporary magnets.

• Electromagnets 

Electromagnets are made by winding a wire into multiple loops around a core material, this formation is known as a solenoid. 

MEGMagnetoencephalography • is a functional neuroimaging technique to form a map for

brain activity by recording magnetic fields.

• Magnetic fields ,produced by electrical currents that occur naturally in the brain , can be measured using very sensitive magnetometers

Two types magnetometer

- SQUIDs (superconducting quantum interference devices)

• SERF , (spin exchange relaxation-free)

History of MEG:• first ,a copper induction coil used as the detector. and To reduce the

magnetic background noise, the measurements were made in a magnetically shielded room, The coil detector was hardly sensitive enough, resulting in poor, noisy MEG measurements that were difficult to use.

• At first, a single SQUID detector was used to successively measure the magnetic field at a number of points around the subject’s head. and, in the 1980s, MEG manufacturers started to arrange many sensors , to cover a larger area of the head.

The basis of MEG signals:

• Neural cells produce a current that produce a weak magnetic field , that approx. equal to 10 fT (Femto Tesla) of cortical alctivity , and 103 fT for human alpha rhythm.

• according to the Maxwell equation , any electrical current will produce perpendicular oriented magnetic field.

• The axons of neurons located horizontally to the scalp surface, and this bundle located in the sulci, researchers experiment various  methods to detect deep brain (i.e., non-cortical) signal, but no clinically useful method is currently available.

Video

Magnetic shielding:• External signals affect on magnetic of brain as Earth's magnetic field, To

shield the fields by obtain constructing rooms made of aluminium and mu-metal for reducing high-frequency and low-frequency noise, respectively.

• MSR is A magnetically shielded room model that consists of three main layers. Each of these layers is made of a pure aluminium layer, plus a high-permeability ferromagnetic layer.

Source localization• The challenge posed by MEG is to determine the location of

electric activity within the brain from the induced magnetic fields outside the head. There is mane technology to use:

The inverse problem:• It is called an inverse problem because it starts with the results

and then calculates the causes.

The inverse problem:• The source models can be either• 1. over-determined • 2. under-determined.

The inverse problem:• The defects of use the technology :

1.  there are infinite possible "correct" answers.

2. the problem of defining the "best" solution is itself the subject of intensive research.

Magnetic source imaging

• The estimated source locations can be combined with magnetic resonance imaging (MRI) images to create magnetic source images (MSI).

• The problem of use this technique in clinical practice is that it produces colored areas with definite boundaries superimposed upon an MRI scan

Dipole model source localization• A widely accepted source-modeling technique for MEG

involves calculating a set of equivalent current dipoles (ECDs), which assumes the underlying neuronal sources to be focal

Dipole model source localization

Dipole model source localization

• The limitations:• (1) Difficulties in localizing extended sources with ECDs.• (2) Problems with accurately estimating the total number of

dipoles in advance.• (3) Dependency on dipole location, especially depth in the

brain.

Distributed Source Models

• Unlike multiple-dipole modeling, distributed source models divide the source space into a grid containing a large number of dipoles

Distributed Source Models

Independent component analysis (ICA)

• Independent component analysis (ICA) is another signal processing solution that separates different signals that are statistically independent in time

Independent component analysis (ICA)

Birzeit universityPalestine• Areej Abu Hanieh• Sondos Hassouneh• Aseel Omari• Waffa Beiruti • Angelica Avdella

• May/2015