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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 .

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PSYC 4380 Rhythms of the Brain Cycle 4: Methods

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  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

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