Functional Magnetic Resonance Imaging

 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

 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)

 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

 H+ density varies in different types of biological tissue, and MRI has sufficient sensitivity to distinguish different tissue types

 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’) T1 and T2 values at 1.5 T TissueT1 (ms)T2 (ms) Grey Matter White Matter 79092

 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

 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)

 What is the relationship of the BOLD signal to electrophysiological signals? from Logothetis, J Neurosci 2003

 The selectivity of spiking & BOLD signals are not identical  So what is the best electrical correlate of BOLD?

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

 Simultaneous fMRI and electrical recordings reveal widespread BOLD activation for local excitatory stimulation from Lee et al., Nature 2010

 negative BOLD & neural inhibition from Lee et al., Nature 2010

 What can you infer from the absence of a BOLD response?  Positive BOLD response?  Negative BOLD response?

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