Signal and Noise

Question 1

What is the primary concern regarding noise in fMRI studies?

Answer 1

The noise may be synchronous with the signal, causing a multicollinearity problem if not eliminated.

Question 2

In fMRI, what is the significance of understanding the synchronization of stimulus and signal?

Answer 2

It is crucial to eliminate noise; if noise is synchronous with the signal, it leads to a multicollinearity problem.

Question 3

What does the Raw Signal-to-Noise (S/N) Ratio measure in fMRI?

Answer 3

It measures MRI scanner performance by dividing the intensity of the image in the brain by the intensity of the image outside the brain.

Question 4

What information does the Contrast to Noise Ratio (CNR) provide in fMRI?

Answer 4

It describes how easy it is to see differences between two tissues, considering the intensity difference divided by noise.

Question 5

How does Functional SNR (fSNR) differ from CNR in fMRI?

Answer 5

While CNR depends on intensity differences between voxels across space, fSNR depends on intensity differences within a voxel or cluster over time.

Question 6

What is the typical range for Signal-to-Noise Ratio (SNR) in fMRI data?

Answer 6

The total range is 0.1-4.0, with a typical range of 0.2-0.5, considering percent signal change amplitudes.

Question 7

How can experimental power be increased in fMRI studies?

Answer 7

By increasing the number of participants, stimuli per condition, and conditions.

Question 8

What does fSNR represent in fMRI, and where are the largest changes observed?

Answer 8

fSNR represents the ratio between task-related and non-task-related variability. The largest changes occur in primary motor and sensory areas.

Question 9

Why is the selection of stimuli critical for fSNR?

Answer 9

Selecting the right stimuli is crucial to enhance sensitivity in experimental manipulations.

Question 10

What is the primary factor affecting fMRI data when there is lower SNR?

Answer 10

Lower SNR leads to more confounds in simulated data.

Question 11

How is noise distributed across the brain in fMRI studies?

Answer 11

Noise is not equally distributed, with some regions, such as edges and areas close to the eyes, being more affected.

Question 12

What is a major source of noise in fMRI caused by fluctuations in MR signal intensity over space or time?

Answer 12

Thermal noise, caused by the thermal motion of electrons within the sample or scanner hardware.

Question 13

How can head motion artifacts be minimized in fMRI?

Answer 13

By using restraints, such as padding, vacuum packs, head masks, or thermoplastic masks, and providing specific instructions to participants.

Question 14

What is the purpose of Prospective Motion Correction (e.g. Siemens PACE) in fMRI?

Answer 14

It shifts slices on-the-fly to follow motion, improving data quality but preventing the acquisition of raw data.

Question 15

What is the primary solution for mass motion artifacts in fMRI?

Answer 15

Co-registration/realignment steps to correct for bulk head motion and inclusion of movement parameters as regressors of no interest.

Question 16

How can individual subject’s hemodynamic responses be used to address inter-subject variability?

Answer 16

It corrects for differences in latency and shape, requiring appropriate statistical measures like random effects analyses.

Question 17

What is the role of filtering approaches in improving SNR in fMRI?

Answer 17

They reduce power around unwanted frequency variations, such as drift or physiological noise.

Question 18

How does increasing field strength impact raw SNR in fMRI?

Answer 18

Raw signal increases as the square of field strength, leading to a higher BOLD signal change. However, higher field strength also increases thermal and physiological noise.

Question 19

How can physiological artifacts be addressed in fMRI studies?

Answer 19

Co-registration/realignment steps to correct for bulk head motion and including movement parameters as regressors of no interest.

Question 20

What is the premise behind improving (f)SNR with trial averaging in fMRI?

Answer 20

MR data on each trial are composed of constant signal and random noise. Averaging decreases noise and increases SNR.

Question 21

What are the effects of increasing the number of trials in trial averaging?

Answer 21

It increases signal detection, determined by the capacity to locate the signal and the spatial extent of activated voxels.

Question 22

What does signal averaging assume about noise in fMRI?

Answer 22

It assumes noise is uncorrelated over time, and data is the sum of signal and temporally random noise.

Question 23

Why might signal averaging ignore critical information in fMRI?

Answer 23

It may ignore potentially critical information when noise is temporally correlated with the task, such as physiological noise time-locked with the stimulus.

Question 24

How does non-task-related neural variability impact averaging in fMRI?

Answer 24

If unsynchronized, averaging could reduce its impact; what is considered noise in one study may become the focus of another.

Question 25

What factors contribute to behavioral and cognitive variability in fMRI?

Answer 25

Reaction times (RTs), practice/fatigue effects, and the speed-accuracy trade-off, leading to changes in hemodynamic response function (HRF) based on prioritized tasks.

Question 26

What is the issue with reproducibility of fMRI activity across sessions?

Answer 26

High variability in activity, especially in cognitive tasks, poses challenges for subject averaging and drawing inferences at the population level.

Question 27

How can individual subject’s hemodynamic responses be used to address inter-subject variability?

Answer 27

It corrects for differences in latency and shape, requiring appropriate statistical measures like random effects analyses.

Question 28

What are the potential solutions for improving SNR in fMRI?

Answer 28

Filtering approaches, denoising of fMRI time series using techniques like independent component analysis (ICA) and principal component analysis (PCA), and increasing field strength.

Question 29

What is the primary aim of co-registration/realignment steps in fMRI?

Answer 29

To correct for bulk head motion and include movement parameters as regressors of no interest, controlling for their residual effects in statistical results.

Question 30

How does trial averaging impact SNR in fMRI?

Answer 30

Averaging decreases noise and increases SNR by assuming that MR data on each trial consists of a constant signal and random noise.