Hemodynamic neuroimaging Flashcards

1
Q

What is the history behind hemodynamic neuroimaging?

A

• Temperature of brain goes up during mental exercise
• Case study: auditory noise made by blood flow in an arteriovenous malformation correlated with effortful visual processing
• Hemodynamic imaging: neuroscience hype since the 1990’s
• Hemodynamic imaging to assess neural activity still not without criticism

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2
Q

What are 3 criticisms of hemodynamic neuroimaging?

A

• Indirect measure of neural activity

• Complex relationship between neural activity & hemodynamics
• Complex = cannot be trusted?
• Deep understanding allows discriminating (in)valid ways of using it

• Complexity of methods and analysis

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2
Q

What are 3 criticisms of hemodynamic neuroimaging?

A

• Indirect measure of neural activity

• Complex relationship between neural activity & hemodynamics
• Complex = cannot be trusted?
• Deep understanding allows discriminating (in)valid ways of using it

• Complexity of methods and analysis

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3
Q

What is the relation between hemodynamics and neural activity?

A

• Neurons require continuous supply of glucose and oxygen to function –> blood circulation
• Blood comes in through arteries and arterioles
• Exchange of glucose and oxygen in capillaries
• Oxygen removed from hemoglobin = deoxyhemoglobin
• To venules and to larger veins to leave the brain
• Energy = adenosine triphosphate (ATP), from glucose
• Neural activity –> hemodynamic response function (HRF)

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4
Q

What happens when neural activity occurs?

A

• Slightly delayed local increase in oxygen and glucose consumption
• Ratio oxygenated and deoxygenated hemoglobin (blood oxygenation) decreases
• Signal through neurovascular coupling mechanism, triggering increase in supply of blood
• Accompanied by marked increase in blood oxygenation
• Peak increase in blood oxygenation several seconds after initial oxygen consumption
• Blood volume and oxygenation decay again (negative overshoot to below baseline levels)
• Expand across larger territory than region of neural activity

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5
Q

What are the 3 components of HRF?

A

• Initial dip: Decrease in blood oxygenation and measured signal
• Primary (strongest) response: Influx oxygenated blood –> strong increase in signal
• Negative overshoot: signal decreases

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6
Q

What are 3 factors that influence hemodynamic signal?

A

• Which process and parameter dominates the measurement
• E.g. Blood volume instead of oxygenation: no initial dip

• Whether measurement very near to site of neuronal activity or average across a larger area
• Across larger area:
• No initial dip
• Only positive peak and negative overshoot

• Additivity assumption: in case of multiple stimuli, total hemodynamic
response (HR) is sum of HRF’s to individual stimuli

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7
Q

What is the relation between HR and electrical potential changes?

A

• Measure action potentials = measure output of a neuron
• Measure HR of a region, not sure whether it represents overall action potential output of that region
• Situations possible where energy consumption increases, while output of neuron stays the same
• Inhibitory input, energy consumption increases but output decreases or stays the same

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8
Q

What does the HR represent?

A

• Relation HR and other electrophysiological measures
• Multi-Unit Activity (MUA): number of action potentials
• Local Field Potentials (LFP): synaptic input of neurons (slow changes in post-synaptic membrane potential)
• Typical situation = everything correlates: HR, MUA, LFP
• When partially dissociated, e.g. through long stimulation: HR (in fMRI) slightly more correlated with LFP than with MUA

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9
Q

What is fMRI?

A

• Blood-oxygenation-level dependent (BOLD) signal
• Deoxygenated hemoglobin: magnetic momentum (paramagnetic)
• Alters spin-spin interactions –> faster T2 decay
• Increase in oxygenation –> increased fMRI signal
• More macroscopic side effects of paramagnetic particles:
• Field inhomogeneity
• Tissue susceptibility
–> Total dephasing = T2* decay

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10
Q

What is the relevance of fMRI?

A

• Decade of the brain
• Has pinpointed the neural basis of a range of mental processes
• Beyond mere localization of function
• Effects sometimes overestimated
• Group differences often not consistent enough between subjects to allow prediction at individual subject level

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11
Q

What is PET?

A

• 1980’s: dominant hemodynamic imaging method
• Unique contribution relative to fMRI:
• Measuring metabolism
• Detection of biomarkers and neurotransmitter concentrations
• Positron emission: involves injection of radioactive tracers
• Injection not of isolated isotope, but attached to a molecule with specific biological action
• Molecule and site of injection determines spread of the tracer
• Radionuclides: short half-life = positron emission decay

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12
Q

How does PET work?

A

• Positron is positively charged –> interacts with negatively charged electron –> annihilation
• Pair of photons travelling in opposite directions
• Detected by photo-sensitive tubes or diodes
• Original position of annihilation localized along a straight line
• 2 such photons have to be detected at the same time (coincidence detection)
• Production of radionuclides near the PET requires a cyclotron

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13
Q

How can we use PET to measure neural activity?

A

• Oxygen-15
• Short half-life of 2 minutes
• Distribution: linear relationship to incoming blood volume
• Total amount of oxygen in a brain region: indication of local neural activity
• Because of over-supply of oxygenated blood following neural activity

• Typical PET experiment
• Low number of conditions (4-8)
• Conditions are typically tested in blocks of around 1 minute
• Often only 2 blocks per condition
• In between blocks: short waiting period with new injection

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14
Q

What are 2 advantages and 3 disadvantages of PET?

A

+ Ability to measure blood volume quantitatively
+ Confronted with less unknown parameters when we try to relate measured signal to neural activity

  • Injecting radionuclides
    • Need for cyclotron
    • Health risks of radioactivity
  • Poorer spatial resolution, about 1 cm
    • Combination with (simultaneous) MRI helps to some extent
  • Poorer temporal resolution: minutes
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15
Q

What are 4 unique contributions of PET?

A

• Metabolism: tracer fluorine-18 (half live 110 minutes) attached to glucose = fluorodeoxyglucose (FDG)

• Diagnose cancer

• Diagnose brain diseases
• Hypometabolism of temporoparietal region in Alzheimer’s disease
• 11C Pittsburgh B PET for beta-amyloid deposits

• Target specific neurotransmitter system
• Tracer attached to molecule with concentration related to activity of one specific neurotransmitter
• Dopamine: 6-(18F)-fluoro-L-DOPA

16
Q

What should we do before we start an experiment?

A

Think before you start an experiment
• Hard work
• Is it worth the effort?
• Know the methods and the theories
• Formulate relevant hypotheses
• Design study to provide evidence for or against some hypothesis
• Expensive machines do not think for you

17
Q

How do we determine which conditions to include in our experiment?

A

• Subtraction method: comparison of two conditions that only differ in one mental process of interest
• Related to behavioural method of Donders: mental chronometry
• fMRI: subtract brain activation
• Multiple extensions:
• Multiple conditions, compared pairwise
• Factorial design
• Parametric design

18
Q

What is the assumption of additivity?

A

• Also known as pure insertion
• The addition of a new mental process does not affect other processes
• If not correct, then comparison between conditions is confounded
• Empirically, violations of this assumption can be visible through interaction effects in the case of a factorial design

19
Q

What are 3 ways to present the conditions?

A

• HRF peak delayed with 6s, total duration more than 12s from onset before at baseline again –> overlapping HRFs
• Option A: ISI of 16s; –> Inefficient!
• Option B: ISI of 2s; signal reaches asymptotic level –> low sensitivity for differences between conditions
• Option C: Block design: trials are blocked per condition

20
Q

What is the block design?

A

• Alternate blocks of different conditions
• Within blocks: strong HRF because of additivity signal
• After a block: signal goes down again (possibly to baseline) before next block
• Condition-associated ups and downs in BOLD signal are large
• Large power and sensitivity to detect changes in BOLD signal
• Very efficient
• Many trials can be presented per unit of time
• No long waiting time between trials

21
Q

What are 3 drawbacks of the block design?

A

• Predictability of conditions (tendency to prepare)
• Unwanted cognitive processes could confound the one process assumed to differ between conditions
• Can be boring to participants in comparison to less predictable situation
• Impossible for some experimental questions
• Impossible to estimate single-trial response function
• Effect that was elicited by one trial
• Possible if one makes strong assumptions about shape of HRF and additivity
• These assumptions are often invalid, e.g. exact form of HRF differs between regions

22
Q

How does the block design work in practice? (5)

A

• Block length
• Short: 6-12s
• Intermediate: 12-21s
• Long: up to 30s or more
• Can vary between blocks

• Period of rest between blocks = rest interval
• Allows signal to go back to baseline
• Increases onset time asynchrony of successive blocks –> increases signal changes
• Less presentations of conditions of interest
• Only if interested in estimating the response to a block of trials

• Counterbalancing condition order to avoid that signal of condition X is predominantly biased by the condition that always precedes it
• One-back counterbalancing

• Number of blocks: 16-20 intermediate-length blocks sufficient for large effects; more needed for smaller effects

• Period of continuous data acquisition = runs
• Typically duration of 4-10 minutes
• Each condition in each run, for at least 2 blocks if possible

23
Q

What is the event related design?

A

• Slow event-related design: long ISI (with or without jitter)
• Ideal for estimating HRF function by the event-related response
• Inefficient use of time and boring

24
What is the Rapid counterbalanced event-related design?
• ISI = 0 or not longer than the trial duration • Conditions alternate in pseudo-random order: each condition follows each condition an equal number of times (counterbalancing) • Peak in a difference of signal between conditions when particular condition occurs frequently in short period of time • Reasonable sensitivity and power • > Alternating design and slow design • < Block design • Estimation possible when one of the conditions = rest • < Slow design • Trial order similar to that of most behavioral experiments
25
Is there dichotomy between block and event related designs?
No dichotomy between block and event-related • Distinction = fuzzy • Intermediate approaches • E.g. block length of 4-6 s; manipulation of probability of conditions • Many different designs and extensions developed and used • Condition-rich event-related design: multi-voxel pattern analysis • fMRI adaptation – also known as repetition supppresion
26
What are the tasks and stimuli in the scanner?
• To activate particular mental processes of interest • Task depends on question • Comparing conditions different in both stimuli and task violates subtraction method assumptions • When interested in stimulus effects • No need for a behavioral response, in contrast to behavioural study • Possible tasks without a stimulus-related response: • Passive viewing • Orthogonal task • Very hard to avoid criticism about confounding task effects
27
How can we present the stimuli?
• Few problems for fNIRS • Most problems for fMRI: • Visual stimuli: Goggles, projection on a screen, or screen seen through a mirror • Eye movement control: useful but difficult • Auditory stimuli: noise of scanner (can be 120 dB!), interleaved data acquisition • Verbal responses: interference from scanner noise, confounding head movements during speaking • MRI-compatible equipment = nonmagnetic and certified for use in a strong magnetic field
28
How do we go from design to scanning?
• Programming • Need to synchronize MRI data acquisition with experiment by reading in trigger signal from scanner • Presenting stimuli is more complicated (e.g., specific hardware) • Reading behavioural response: no keyboard, other hardware is needed • Ethical approval takes longer than for behavioral experiment • Good preparation is critical because scanning is costly • Keep detailed logbook of *everything* that happens
29
What are some considerations for participants?
• Safety issues • Practice session in dummy/mock scanner for special populations like children • Handedness • Gender • Number • Depends upon expected effect size and signal to noise ratio • Prior estimate of power is strongly advised, but not easy to determine • Variation in literature between only 3-5 participants (when effect is large, can be demonstrated in single subjects, and data collection per subject is intensive) up to hundreds of participants.
30
What is the role of image preprocessing?
• Pre-processing not or very limited for behavioural data, but very important for imaging data • Pre-processing is not part of statistics (but can strongly influence stats)
31
What does the choice of software package depend on? (4)
• Knowledge/background of the researcher • Flexibility researcher wants • Potential preference for operating system • Expertise in lab of researcher
32
What is the pre-processing step 0?
Quality control • Continuous point of attention • Automatization is efficient, but creates large distance between experimenter and data without good quality control • When starting: cut analysis in small pieces and run step by step • Large problems often already detected during scanning itself • After scanning, image files copied to work station but check them • File names • File sizes (all runs of equal length should be equal size) • Inspect some time points
33
Why to not use data of extensive motion? (3)
• Some displacements cannot be corrected offline • E.g. abrupt motion during TR àlarge shift of all other slices acquired after • Motion decreases image quality due to instabilities in fMRI signal • Alters magnetic field and its inhomogeneities and history of excitation of nuclei • Takes much longer than actual movement to stabilize again • Amount or type of motion can be related to experimental conditions • E.g.: complex movement for a condition --> small head movement • Hard to dissociate neural activity from motion artefacts/ confounds
34
How can we do external quality control?
External quality control through transparency and reproducibility • Questionable research practices and relatively low rate of reproducibility • In fields where statistics play a big role • When effect sizes are small • When many different research groups • Positive: Many neuroimaging key findings have been documented over and over again (e.g., presence of face-selective regions) • Negative: Chance of success to replicate a randomly chosen neuroimaging paper will be lower than it should be • Number from psychology: effect size in replication typically half of effect size in original report
35
What are some causes of low reproductibility?
• Large degree of flexibility and possibility for exploration in analysis • Each choice impacts results • All choices together can have huge influence on final results • Worst case, and not acceptable: some of the choices influenced by knowing about the results obtained with these choices --> circular analyses • Insufficient statistical power • Due to insufficient number of participants given the typical effect size • Increases possibility of false negatives • Increases potential impact of questionable research practices, and thus possibility of false positives • e.g. decision to take out 1 participant because of “bad data” (based on a priori criterion or on circular reasoning) will have more impact with a lower number of participants • Decreases trustworthiness of effect size estimates in studies • Need for a priori power analysis (even though it is difficult, e.g. because effect size is also determined by data quality)
36
What are 4 solutions for the low reproducibility problem?
• Methods sections as complete and transparent as possible • In its asymptote very similar to a preregistered study • Analysis tools and data made available (e.g., Open Science Framework) • More replication efforts necessary • More focus upon meta-analytic approaches and innovative tools to do so • More data sharing