Data analysis Flashcards
(189 cards)
What is the purpose of registration in fMRI data analysis?
Registration is used for moving between different spaces, such
as aligning functional data with structural images, correcting for
motion, and facilitating other statistical analyses.
List the key functions of registration in fMRI data analysis.
- Moving between ‘spaces’ (e.g., from functional to anatomical
space). 2. Motion correction (accounting for head movements). 3.
Structural statistics (comparing functional data with structural
anatomy). 4. Noise reduction and spatial filtering (enhancing
signal quality).
What is the goal of single-session analysis in fMRI studies?
Single-session analysis aims to analyze data collected during a
single fMRI session to identify patterns of brain activity
corresponding to specific stimuli or tasks.
What are the key modelling approaches used in fMRI?
The key modelling approaches in fMRI include multiple
regression, general linear models (GLM), and efficient regressor
design.
What does modelling the response in fMRI entail?
Modelling the response involves characterizing the stimulusinduced
changes in the Blood-Oxygen-Level Dependent (BOLD)
signal, which reflects neuronal activity.
Find which voxels have time series that match that predicted response
*A good match implies brain activation related to the
stimulus predicted response measure timeseries at marked voxel
What kind of design types are utilized in fMRI modelling?
Common design types used in fMRI modelling include event related
designs, block designs, and mixed designs, each catering
to different experimental needs.
What is the significance of outcome measures in fMRI analysis?
Outcome measures are essential for quantifying the response of
the BOLD signal to various stimuli, influencing interpretations of
cognitive and neural processes.
How does multiple regression relate to fMRI analysis?
Multiple regression is used in fMRI analysis to model the relationship between multiple independent variables (e.g.,
different stimuli) and a dependent variable (e.g., BOLD signal) to
assess brain activity.
What are the different approaches to GLM in fMRI analysis?
The general linear model (GLM) in fMRI analysis can include
approaches such as analysis of variance (ANOVA), t-tests for
contrasts, and parametric mapping.
Why is it important to model efficient regressors in fMRI?
Efficient regressors are important in fMRI modelling as they help
improve the statistical power and sensitivity of detecting brain
activity related to specific experimental conditions.
What is the primary objective when analyzing brain activation
during stimuli like words?
The primary objective is to find which voxels have time series that
match the predicted response to the neural stimulation, indicating
brain activation related to the stimulus.
What does a good match of a voxel’s time series indicate?
A good match implies brain activation that is related to the
predicted response for the given stimulus.
In the context of fMRI studies, what is a voxel?
A voxel (volumetric pixel) is the smallest distinguishable cubic
volume element in a 3D space used in imaging. It represents a
building block of the 3D images obtained from fMRI data.
In the example experiment with ‘Jellyfish’, what is the input (noun)
and output (verb)?
The input is ‘Jellyfish’ (noun) and the generated output is a verb
associated with the noun.
What is examined in the example when a ‘Burger’ is presented?
In the example with ‘Burger’, a noun is seen, and a verb is
generated that represents some action related to the noun.
What occurs in the experiment when the verb ‘Swim’ is seen?
When the verb ‘Swim’ is seen, it prompts the repetition of the
verb ‘Swim’ as part of word generation events.
How does the experiment involving ‘Giggle’ differ from ‘Swim’?
In the experiment with ‘Giggle’, the verb is seen and is then
repeated, similar to the ‘Swim’ experiment, focusing on verb
repetition in response to verb presentation.
What is presented during the experiment involving the Crosshair?
The Crosshair is presented on the screen, serving as a fixation
point, which typically indicates the start of a new trial or stimulus
presentation.
What questions do researchers explore regarding word
generation events?
Researchers explore what the predicted responses to word
generation events are and how these responses can be modeled
and measured.
What does building a model involve in terms of predicting
responses?
Building a model involves predicting the expected neural
response to various stimuli, determining how the brain is
expected to react to word generation events.
What is an example of a predicted response to word generation
events?
A predicted response could be a specific pattern of brain activation associated with processing and generating language,
such as specific regions activating upon seeing nouns versus
verbs.
Why is it important to observe time series data in the context of
fMRI studies?
Observing time series data allows researchers to identify patterns of brain activation over time that correspond to specific
stimuli, providing insight into how the brain processes language
and thought.
How can time series data from voxels be interpreted in studies
involving predicted responses?
Time series data from voxels can be interpreted by analyzing the
changes in activation levels over time to assess how closely they align with predicted responses to stimuli, such as nouns or verbs.
What is the predicted response to word generation events in
brain research?
The predicted response to word generation events involves measuring the brain’s activation patterns in response to tasks
related to generating words, often analyzed through neuroimaging techniques such as fMRI.