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Neuroimaging 1 > Resting State fMRI > Flashcards

Resting State fMRI Flashcards

1
Q

How does the brain use energy?

A

Most energy is used to support cell communication
Task related BOLD activity uses approx 1-2% of energy

Brain is 2% of body mass but uses up to 20% of energy

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2
Q

What was an interesting finding regarding energy consumed in resting state compared to task?

A

In a task dependent group, there is less activation than in resting state in some regions of the brain

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3
Q

What is the default brain network?

A

The brain’s default network is a set of regions more active during passive tasks than tasks demanding focused external attention

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4
Q

What is resting state fMRI?

A

Resting-state fMRI measures spontaneous low-frequency fluctuations in the BOLD signal to investigate the functional architecture of the brain

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5
Q

What has application of resting fMRI allowed for?

A

Application of this technique has allowed the identification of various resting state networks, or spatially distinct areas of the brain that demonstrate synchronous BOLD fluctuations at rest

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6
Q

Why study the brain at rest?

A
  • Resting state fMRI can be used to inform us about the inherent organisation and functioning of the brain - a basic neuroscience aim - and may help us to understand how the brain enables complex information processing and rich sets of behaviour, thoughts and motivations
  • Understanding communication in the brain can help us to understand how things go wrong in a variety of different disorders e.g., ADHD thought to caused by aberrant communication between different regions in the brain
  • Resting state has the potential to be an objective clinical biomarker
  • Quick with relatively no setup or expertise
  • Can be done in any population - no cognitive demands/tasks for the subjects as they are scanning at rest
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7
Q

What is one criticism of resting state fMRI?

A

Rest is an uncharacterised state ==

The brain is not doing ‘nothing’ when at rest (awake but not engaged in a task), the brain can be engaged in a large variety of processes whilst at rest
The subject could be thinking about the loud noise of the scanner, daydreaming, thinking what they are doing next week etc
Therefore, studying the brain in this uncontrolled state, is seen as highly problematic to some - hard to learn something about the brain when we are unsure what it is doing in that period

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8
Q

What is functional connectivity?

A

Functional connectivity refers to the functionally integrated relationship between spatially separated brain regions

The observed temporal correlation between two electro or neurophysiological measurements from different parts of the brain

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9
Q

What is the assumption regarding functional activity?

A

If two regions show similarities in their BOLD signals over time, they are functionally connected

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10
Q

How was functional connectivity discovered?

A

Biswal (1995) scanned subjects both when they were doing a task (finger tapping) and when they were doing nothing at all

To his surprise, even after regressing out the physiological sources of noise from the resting-state data, they did not explain all of the variance in the BOLD response

Observing what appeared to be temporal correlations between different regions of voxels, Biswal extracted the time-series from the left motor cortex and correlated that signal with every other voxels’ time-series

Instead of the random correlations that one would expect if there were no systematic BOLD fluctuations at rest, there was a strong correlation with the time-series of the opposite hemisphere’s motor cortex - suggesting that these two functionally similar regions, although physically distant from each other, generated similar patterns of activity even at rest

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11
Q

What was another clue that pointed towards resting state functional connectivity?

A

Anti-correlation PET study (Shulman et al., 1997)

Nine previous positron emission tomography (PET) studies of human visual information processing were reanalyzed to determine the consistency across experiments of blood flow decreases during active tasks relative to passive viewing of the same stimulus array

Constellation of areas in the cerebral cortex consistently reduced its activity whilst performing various novel, goal-directed tasks, when compared to a control state of quiet repose
(Resting state = eyes closed, task = visual fixation)

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12
Q

What are the three main types of connectivity in the brain?

A

Functional connectivity
Structural connectivity
Effective connectivity

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13
Q

What is effective connectivity?

A

What is the influence of one brain region to another?

Effective connectivity (EC) is defined as the influence that a node exerts over another under a network model of causal dynamics and is inferred from a model of neuronal integration, which defines the mechanisms of neuronal coupling

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14
Q

What is the assumption regarding functional activity?

A

If two regions show similarities in their BOLD signals over time, they are functionally connected

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15
Q

What are the resting state networks?

A

Default mode network
Right fronto-parietal attention
Left fronto-parietal attention
Executive control
Medial visual cortical areas
Lateral visual cortical areas
Auditive system
Sensorimotor cortex

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16
Q

What are two main features of resting state?

A
  1. Resting state data is very replicable - the same networks have been independently verified by other research groups
  2. Resting state networks are very closely related to task-based activation patterns
17
Q

What is a common question asked surrounding resting state networks?

A

Does the fluctuation really reflect synchronized neuronal fluctuation?

== Physiological noise - cardiac, respiration, subject motion
Scanner instabilities, image reconstruction errors

18
Q

What neuronal evidence is there for resting state networks?

A

Cordes et al (2001) - Aim of study was to measure the contributions of low frequencies and physiological noise to cross-correlation maps
- Task-activation functional MRI and resting state data was acquired from healthy subjects
- Calculated the relative amounts of the spectrum that were in the low-frequency (0 to 0.1Hz), respiratory frequency (0.1 to 0.5Hz) and cardiac frequency (0.6 to 1.2Hz)
- For the auditory and visual cortices, the correlation coefficient depended almost exclusively on low frequencies
- For all cortical regions, low frequency fluctuations contributed to more than 90% of the correlation coefficient
- Physiological noise sources contributed to less than 10% of any functional connectivity
- Concluded that functional connectivity in the auditory, visual and sensorimotor cortices is characterised predominantly by frequencies slower than those in the cardiac and respiratory cycles i.e., evidence for neuronal

19
Q

How was EEG used to back up the neuronal evidence of resting state?

A

Laufs et al. (2003)
- Used EEG correlated fMRI to identify BOLD signal changes associated with physiological EEG events
- Implemented continuous and simultaneous EEG/fMRI to identify BOLD signal changes related to spontaneous power fluctuations in the alpha rhythm, the dominant EEG pattern during relaxed wakefulness
- At all electrode positions studied, a strong negative correlation of parietal and frontal cortical activity with alpha power was found
- Widespread and strong brain activity changes could be detected when negatively correlating alpha power with the fMRI images over time
- In other words, cortical activity in these areas was higher when alpha band power decreased

20
Q

How is resting state acquired?

A

Subject placed in normal MRI scanner
6-10 minutes scanning time is often enough

21
Q

What are the typical parameters of RS acquisition?

A

T2*-weighted pulse sequence
TE = 35ms
TR = 2600ms
In-plane pixel dimensions = 1.8mm x 1.8mm
Contiguous trans-axial slices thickness of 4mm

22
Q

What software is used in resting state analysis?

A

SPM (CONN toolbox)
FSL

23
Q

What is the standard resting state analysis pipeline?

A
  1. Acquire fMRI data
  2. Pre-processing
  3. Denoising
  4. Post-processing
  5. Network measures/ predefined measures
24
Q

Explain pre processing

A
  1. Realignment - realign the functional data and co-register it to a structural image
  2. Slice timing - shift the time series of each slice to temporally align all slices to a reference time-point
  3. Outlier detection
  4. Functional normalisation - warping data to a template brain
  5. Smoothing - used to increase signal-to-noise ratio (SNR) through noise averaging
25
Q

What is denoising?

A

Noise can be filtered/regressed out of the data prior to analysis

OR

Noise signals can be entered into the analysis models to explain additional variance

26
Q

What are some examples of noise?

A

Head movement
Mean white matter/CSF signals
Cardiac
Respiratory
ETCO2 measures

27
Q

How can we denoise our data?

A

Independent Component Analysis (ICA)-based
- ICA-AROMA = fully automatic but only removes head motion
- ICA-FIX = semi-automatic, requires training data
- Manual = labour-intensive, but best?

Mean-signal-based method
- Global signal
- Mean grey/white matter and/or CSF

Linear regression and temporal band-pass filtering

28
Q

What are the resting state analysis methods?

A

Voxel-based methods (Predefined measures)
Node-based methods (Network measures)

29
Q

What are the different voxel-based methods?

A
  • Seed-based correlation analysis
  • Independent component analysis
  • Amplitude of low frequency fluctuations (ALLF/fALLF)
    -Regional homogeneity (ReHo)
  • Group MVPA
30
Q

What are the different node-based methods?

A
  • Network modelling analysis (FSL nets)
  • Graph theory analysis
  • Dynamic causal modelling
  • Non-stationary methods
  • ROI to ROI
31
Q

What is ICA?

A

Independent component analysis ==
A technique that allows the separation of a mixture of signals into their different sources

  • Multivariate voxel based approach
  • Exploratory ‘model free’ or data driven method
  • Global brain approach

In FSL the fMRI data is represented in a 2D matrix decomposed into the components

32
Q

What is spatial ICA?

A

X = A * S
fMRI data = time course x spatial maps

fMRI data (X) measured is expressed as a set of unknown spatial patterns (S) and the associated time courses (A)

33
Q

What is the pipeline for ICA functional connectivity?

A

Single subject –> Identify interested networks –> Extract connectivity measures –> Group/condition comparison

Group –> Identify interested networks –> Dual regression –> Group/condition comparison

34
Q

What is group wise ICA?

A

Important analysis tool to study specific conditions within or between groups of subjects

Uses the same X = A * S but with multiple data sets

35
Q

What is dual regression?

A

Dual regression is a tool that we can use as part of a group-level resting state analysis to identify the subject-specific contributions to the group level ICA

Spatial Regression: The spatial map is used as a spatial regressor to find the time series associated with the voxels in that map.

Temporal Regression: The time series found by spatial regression is then used as a temporal regressor to find the full set of voxels associated with that time series.

The output of dual regression is a set of subject-specific spatial maps and time courses for each group level component (spatial map) that can be then compared across subjects/groups

36
Q

What is seed based correlation analysis?

A

Based on the time series of a seed voxel (or ROI), connectivity is calculated as the correlation of time series for all other voxels in the brain. The result of SCA is a connectivity map showing Z-scores for each voxel indicating how well its time series correlates with the time series of the seed.

Calculate correlation coefficient between two areas or regions
Localised approach
User specifies the seed or ROI

37
Q

What is the seed based correlation analysis pipeline?

A
  1. Define ROI or seed region
  2. Extract time series
  3. Extract connectivity measures
  4. Group/condition comparison
38
Q

What is the ROI to ROI analysis?

A

ROI-to-ROI connectivity metrics characterise the connectivity between all pairs of ROIs among a pre-defined set of regions

39
Q

What is the ROI to ROI functional connectivity pipeline?

A

Same as seed-based correlation analysis pipeline
1. Define ROI
2. Extract time series
3. Extract connectivity measures
4. Group/condition comparison

Neuroimaging 1 (16 decks)

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