fMRI Experimental Design Flashcards

Question

What cognitive strategies can be used to increase blood flow in neural feedback?

Answer 1

'Recall and relive personal memories of situations and events in which you were very physically aroused. These could be pleasant or unpleasant' 'Become aware of the tension of the muscles in your face, or limbs, the sensations created by the noise and vibration of the scanner, heartbeat or breathing rate'

Answer 2

'Count back from 100 in 3s'

Answer 3

A set of methods that analyse neural responses as patterns of activity - looking at the activation of different voxels as a multivariate pattern Motivated by machine learning and AI - enables the advance machine learning techniques such as pattern classifiers Has been proven to be more sensitive and more informative about the functional organisation of the cortex compared to univariate approaches

Answer 4

In univariate analysis the research question asks will there be different areas of activation in response to two different types of stimuli (i.e., face compared to house) In contrast, multivariate pattern analysis uses reverse inference - based on the activated neural pattern, we will be able to predict which visual stimuli the subject perceived

Answer 5

Univariate voxel-wise analysis relates psychological or physical dimensions to the activation of single voxels and thus can fail to map the neural basis of experimental variables and conditions when these variables have a distributed multidimensional effect on activation MVPA measures that take into account information from multiple voxels, may be necessary to answer whether a region codes for a particular psychological dimension or experimental condition

Answer 6

fMRI data is recorded whilst the subject sees a large number of the stimuli to be discriminated The acquired data is then split into a training data set and a testing data set The data from the training set is entered into a pattern classifier which attempts to detect features in the neural patterns that distinguish the two types of trials from one another Next, the classifier is presented with unlabelled data from the testing set and based on the patterns it detected from the training data set, it attributes the most likely label to each of the testing trials For each stimulus the classifier guess is compared to the correct stimulus label and classifier performance is calculated as the percentage of correct guesses The higher the percentage, the higher the indication of consistent differences between the patterns in that brain area (i.e., the two stimuli have been perceived differently)

Answer 7

The two stimuli being compared in MVPA must be completely independent of each other in order to make any conclusions of generalisability

Answer 8

Representational similarity analysis == multivariate method that can be used to extract information about distributed patterns of representations across the brain Responses are placed into a representational similarity matrix (i.e., if you have 3 picture stimuli, they can be placed into a 3x3 matrix to compare each of the stimuli) Pearson's r correlation coefficient is calculated for each of the comparisons of stimuli and the resulting BOLD activation pattern

Answer 9

Used representational similarity analysis to compare activation patterns of faces and houses Computed representational dissimilarity matrices which characterise the information carried by a given representation in a brain or model Pp given an experimental condition - either looking at pictures of a face or a house Record the activity patterns in the brain Compute dissimilarity to create a representational dissimilarity matrix

Answer 10

Created further representational dissimilarity matrices using the following categories: human (body/face), animate (not human, body/face), inanimate (natural/artificial) Look at the BOLD responses and the pattern of activity between different objects presented and then correlated the pattern from every object to every other object Recorded in the human inferior temporal cortex Findings = naturally forms different clusters in the representational dissimilarity matrix Inanimate objects most similar to inanimate objects in the matrix same with human objects most similar with human objects in matrix

Answer 11

Found a very different organisation within the representational dissimilarity matrix - there are no clear clusters of correlation between the same objects

Answer 12

In the early stages of visual processing, the brain is not interested in object categories - it doesn't differentiate objects coming from different categories e.g., animals or humans Brain is more interested in low level features e.g., whether the object is round or if they are the same colour etc

Answer 13

The representational dissimilarity matrix is very similar to the human matrix Surprising considering the neural representation between different brains is very different

Answer 14

Memory impairments in dementia Decreased activation at medial temporal lobe compared to healthy controls Increased activation at medial temporal lobe for high-risk individuals comparing to low risk controls during encoding but decreased activation during recall

Answer 15

Scan areas involved in memory e.g., hippocampus Present two different pictures to the pp during the scan e.g., two different types of houses Record the activity pattern when the two houses are presented Give a delay and then present only one of the houses again Would expect to see an activity pattern more similar to the pattern seen when first presented the same house Hypothesis for pps with dementia is that they would have less reliable episodic reinstatement meaning the activity patterns during the two phases will not be similar

Answer 16

Found no significant difference in recognition memory performance, but Spatial location related episodic memory impairments in family history of dementia

fMRI Experimental Design Flashcards

(40 cards)