This document summarizes research in neuroscience related to mind reading using fMRI. It discusses how fMRI works and early experiments using fMRI to analyze brain activation patterns in response to images. Studies found consistent patterns across individuals, allowing researchers to predict thoughts. The document raises discussion points about the implications of mind reading for criminal justice, certainty of conclusions, and free will.
2. The Power of Modern Neuroscience
http://www.youtube.com/watch?feature
=player_embedded&v=nsjDnYxJ0bo#!
3. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
4. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
History
First Brain Imaging
Experiment
Angelo Mosso
Italian Physiologist
Major Break through
5. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
How does fMRI work?
What causes an fMRI signal? Is it A or B?
A) fMRI measures the REDUCTION in the
amount of paramagnetic deoxygenated
hemoglobin in neural tissue from a resting
state to an active state.
B) fMRI measures the INCREASE in the amount
of paramagnetic deoxygenated hemoglobin in
neural tissue from a resting state to an active
state.
6. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
How does fMRI work?
Resting State Active State
7. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
Just and Mitchells Methods
fMRI data from 9 healthy college aged
Tom Mitchell participants
Randomly viewed 60 different word-
picture pairs 6x
Signal for each word-picture pair was
Marcel Just recorded and averaged.
Average signal used as baseline and
compared to new fMRI signal from a
new participant
8. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
Repeated for all 9 participants.
9. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
Do different people have the same
type of brain activation patterns?
10. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
NEW participant gets in the fMRI machine and looks at the
same word-pictures
BUT this time the computer does not know what pictures
the participant is looking at, it ONLY sees the brain activity
pattern
11. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
Do different people have the same
type of brain activation?
New participants
brain activity
patterns
12. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
John-Dylan Haynes
Have you been
here before?
13. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
John-Dylan Haynes
14. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
The earliest technique to see unconscious processing.
John-Dylan Haynes Haynes elaborates on this phenomenon.
15. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
Neural decision before conscious
awareness of the decision
John-Dylan Haynes Conscious decision
EEG signals before the feeling of wanting
entered consciousness!
Challenged our concept of free will
16. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
John-Dylan Haynes
17. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
Step 1: decode
John-Dylan Haynes
Step 2: give to
computer to classify
Step 3: predict
18. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
Conclusions
Using fMRI data, software can now accurately
predict what a human is thinking.
fMRI data is incredibly useful and flexible.
Mind Reading is now a reality in laboratories
with fMRI machines.
19. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
Discussion question 1
In the realm of criminal justice, do you think brain pattern
activation is equivocal with physical evidence such as DNA,
semen, etc. or is it equivocal with personal testimony and
protected by the fifth amendment?
20. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
Discussion question 2
Can we be decisive when making conclusions about what a
pattern of brain activity means?
i.e. What if my brain says I love chocolate chip cookies
but I say that I dont like chocolate chip cookies at all.
Can we be CERTAIN?
=
21. 1. Mind Reading 2. Simple thought 3. Familiar 4. Complex thought 5. Conclusions
Summary representation environments representation and Discussion
Discussion question 3
We mentioned Haynes study where Haynes could predict
what decision youre going to make 7 seconds before you
are consciously aware of your own decision. Do you think
this interferes with the notion of free will?
#3: The left clip is a segment of a Hollywood movie trailer that the subject viewed while in the magnet. The right clip shows the reconstruction of this segment from brain activity measured using fMRI. The procedure is as follows:[1] Record brain activity while the subject watches several hours of movie trailers.[2] Build dictionaries (i.e., regression models) that translate between the shapes, edges and motion in the movies and measured brain activity. A separate dictionary is constructed for each of several thousand points at which brain activity was measured.(For experts: The real advance of this study was the construction of a movie-to-brain activity encoding model that accurately predicts brain activity evoked by arbitrary novel movies.)[3] Record brain activity to a new set of movie trailers that will be used to test the quality of the dictionaries and reconstructions.[4] Build a random library of ~18,000,000 seconds (5000 hours) of video downloaded at random from YouTube. (Note these videos have no overlap with the movies that subjects saw in the magnet). Put each of these clips through the dictionaries to generate predictions of brain activity. Select the 100 clips whose predicted activity is most similar to the observed brain activity. Average these clips together. This is the reconstruction.
#7: EXPLANATION: At both the resting state and active state, fMRI measures the amount of paramagnetic deoxygenated hemoglobin in a neural tissue.Logically you would think, active tissue uses more oxygen, expect to see more deoxygenated hemoglobin in neural tissue during an active stateBUT the increased blood flow pushes deoxygenated hemoglobin out of the area so fast that fMRI actually measures a REDUCTION from the resting stateTo the active state.
#10: Learned voxelactivation signatures for3 of the 25 semantic features,for participant P1(top panels) and averagedover all nine participants(bottom panels). Just onehorizontal z slice is shownfor each. The semantic featureassociated with theverb eat predicts substantialactivity in rightpars opercularis, which isbelieved to be part of thegustatory cortex. The semanticfeature associatedwith push activates theright postcentralgyrus,which is believed to beassociated with premotorplanning. The semantic feature for the verb run activates the posterior portion of the right superior temporalsulcus, which is believed to be associated with the perception of biological motion.
#12: How accurate?Learned voxelactivation signatures for3 of the 25 semantic features,for participant P1(top panels) and averagedover all nine participants(bottom panels). Just onehorizontal z slice is shownfor each. The semantic featureassociated with theverb eat predicts substantialactivity in rightpars opercularis, which isbelieved to be part of thegustatory cortex. The semanticfeature associatedwith push activates theright postcentralgyrus,which is believed to beassociated with premotorplanning. The semantic feature for the verb run activates the posterior portion of the right superior temporalsulcus, which is believed to be associated with the perception of biological motion.
#13: http://www.bccn-berlin.de/digitalAssets/0/680_HaveYouBeenHereBefore_Xvid_English_LowResolution.aviThis will take some time 3-4 minutes
#18: Example of voxel selectivity for a representativesearchlight (position with peak decoding accuracy in frontopolar cortex). Thespherical clusters at that position are shown for all 12 subjects. The selectivity foreach voxel for either a left or right decision is colour coded in blue and yellowrespectively. The selectivity profiles clearly indicate that some voxels areactivated stronger preceding either left or right decisions, thus pointing towards adistributed encoding of long-term predictive information.If all three of these brain regions are activated 7 seconds prior, we can
#25: At a resting state, fMRI measures the amount of paramagnetic deoxygenated hemoglobin in a neural tissue.Active State,Increased Blood Flow,Oxygenated blood-paramagnetic,fMRI measures signal difference
#26: Learned voxelactivation signatures for3 of the 25 semantic features,for participant P1(top panels) and averagedover all nine participants(bottom panels). Just onehorizontal z slice is shownfor each. The semantic featureassociated with theverb eat predicts substantialactivity in rightpars opercularis, which isbelieved to be part of thegustatory cortex. The semanticfeature associatedwith push activates theright postcentralgyrus,which is believed to beassociated with premotorplanning. The semantic feature for the verb run activates the posterior portion of the right superior temporalsulcus, which is believed to be associated with the perception of biological motion.
#27: Mental representations of objects vary between people.However, similarities exist.Not a carbon copy, but similar enough.