1 / 15

PSYC 4380 Rhythms of the Brain Cycle 4: Methods

Functional Magnetic Resonance Imaging. PSYC 4380 Rhythms of the Brain Cycle 4: Methods. Physics behind MRI . All subatomic particles possess a property called ‘spin’ i.e. like a planet rotating on it’s axis Magnetic fields can perturb and align these axes of rotation. Physics behind MRI .

lok
Télécharger la présentation

PSYC 4380 Rhythms of the Brain Cycle 4: Methods

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Functional Magnetic Resonance Imaging PSYC 4380 Rhythms of the BrainCycle 4: Methods

  2. Physics behind MRI • All subatomic particles possess a property called ‘spin’ • i.e. like a planet rotating on it’s axis • Magnetic fields can perturb and align these axes of rotation

  3. Physics behind MRI • The central component of an MRI scanner is a very powerful magnet • The earth’s magnetic field is 1/20,000 T • Scanner magnets are typically ~3T (60,000x stronger than earth’s field)

  4. MRI – Basic Principles • Use powerful magnet to align hydrogen atoms in biological tissue • Transmit radio-frequency (RF) pulses to perturb the rotational axes of protons • Record RFs emitted by protons as they return the orientation imposed by large magnet, and use this to calculate H+ density

  5. MRI – Basic Principles • H+ density varies in different types of biological tissue, and MRI has sufficient sensitivity to distinguish different tissue types

  6. MRI – Basic Principles • The proton-emitted RF pulse can be measured in a number of ways: • 1. Measure the rate at which protons are realigned with the magnetic field (‘T1’) • 2. Measure the drop-off in emitted RF pulses from protons as they realign (‘T2’)

  7. Magnetic Properties of HB • Hemoglobin’s magnetic properties depend on whether it is oxygenated (HbO2) or deoxygenated (Hb) • HbO2 is ‘dimagnetic’ and has no net effect on the magnetic field • Hb is ‘paramagnetic’ and thus increases the strength of the local magnetic field when aligned by the scanner magnet

  8. BOLD Signals • BOLD = Blood Oxygen Level Dependent • The change in Hb’s magnetic properties as a function of it’s oxygenation allow us to measure changes in blood oxygenation • Always a relative measure (A-B)

  9. BOLD Signals • What is the relationship of the BOLD signal to electrophysiological signals? from Logothetis, J Neurosci 2003

  10. BOLD Signals • The selectivity of spiking & BOLD signals are not identical • So what is the best electrical correlate of BOLD?

  11. BOLD Signals • Simultaneous recording of action potentials (MUA), local field potentials (LFPs), and BOLD suggest BOLD is more like LFPs than MUA from Logothetis et al., Nature 2001

  12. BOLD Signals • SimultaneousfMRI and electrical recordings reveal widespread BOLD activation for local excitatory stimulation from Lee et al., Nature 2010

  13. BOLD Signals • negative BOLD & neural inhibition from Lee et al., Nature 2010

  14. BOLD Signals • What can you infer from the absence of a BOLD response? • Positive BOLD response? • Negative BOLD response?

  15. Common Pitfalls in fMRI Analysis & Interpretation Group averaged data- smoothing -> blurring of distinct loci of activation- heterogeneity of activation location across subjects can obscure consistent within-subject results Common coordinates- reported centroid of an activated cluster can be misleading about it’s extent [A > C, B !>C ] -> [A > B]- A and B could have same means, different variances “Activation relative to A or deactivation relative to B”- Can never really tell Multiple Hypothesis Testing - lack of / under-correcting can lead to spurious type I errors - parametric over-correction can lead to many type II errors

More Related