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Monitoring and enhancing visual features (movement, color) as a method for
predicting brain activity level - in terms of the perception of pain sensation

Final project by

Noam Roth

Rothn@post.bgu.ac.il


Introduction

We conducted a feasibility study to determine if it is possible to infer pain perception
from the level of brain activity (blood flow). The evaluation of the blood flow to the
brain was deduced from a video signal by using a computational vision tools to amplify
and reveal very small motions and slight changes of color. Should this method be found
to correlate with the subjective 'feeling' of pain (direct report), it may offer a new
alternative simple and low cost method to quantify the subjective perception of pain,
and may be used as an effective and useful research tool in studying pain perception.

Approach and Method

Eulerian motion magnification

Adelson et al. (1984) offered a variety of Pyramid methods for image representation.
An important characteristic of these methods is that it is possible to reconstruct
perfectly the original image from its pyramid representation (Adelson et al., 1984).
Having a method of image analysis that transforms an input image to a representation
space and a complementary method for synthesis from the representation space to an
image facilitates developing schemes of the type analysis-modify-synthesis.

MIT and Cambridge researchers, developed a method that takes a video signal as input,
decomposing each frame using a Pyramid representation (spatial decomposition), followed
by applying temporal filtering on the sequence of decomposed frames, lastly synthesizing
the output video from the sum of the Pyramid decomposition and the temporal processing.

Through this Eulerian spatio-temporal processing, which takes temporal changes of a
sequence of frames and uses them to exaggerate the motion or the color changes in the
frame sequence, we can reveal nearly invisible changes with only a standard monocular
video sequences (Wu, et al., 2012).

An Implementation of the Algorithm

"Pain is a conscious experience, an interpretation of the nociceptive input influenced
by memories, emotional, pathological, genetic, and cognitive factors" (Tracey, 2008).
In other words, pain is a subjective experience, and as such it is difficult to evaluate
objectively.

Most of the research in this field focuses on the regions and structures of the brain
that activates while it occurs. Tracey and Mantyh (2007) define this cerebral activation
as "pain signature" of individualized neural activation while experiencing pain. Other
researches define it as general 'pain matrix' include 'lateral components'- sensory-
discriminatinatory areas (S1, S2, thalamus, and posterior parts of the insula), and
'medial components'- affective-cognitive-evaluative (anterior parts of insula, ACC,
and prefrontal cortex) (Tracey, 2008).

This research focuses on the perception of pain sensation, i.e. what the subject
eventually feels, and suggests a way of assessing that feeling. While perceiving a
painful stimulus, the system is getting into hyper activity. As a result, the brain needs
more oxygen thereby increasing the blood flow towards the regions that worked
intensively, the cognitive, somatosensory and emotional networks. Monitoring the
changes in the blood flow, may give us schematic but robust prediction for the level
of activity in the brain. This, in turn, may help us to conclude upon complex or
decentralized processes such as pain.

The Eulerian magnification algorithm, as described above, will be used to monitor and
amplify the blood flow through the patient's faces (i.e. the redness of the face) and
the blood flow through the main arteries to the brain (i.e. the vibrating of the Anterior
and Posterior circulations main arteries). The more blood will flow through the arteries
per time unit (mili-seconds) will imply that more blood supply was needed by the brain
(i.e. more oxygen needed), thus indicating higher level of brain activity.

From this indication of the brain activity, we will try to infer the perception of pain
sensation of the patient. Therefore, this research may yield a method to a relative
simple and low-cost indication for 'feeling' pain, and as such, could be efficient for
pain related researches.

The Current Study

In this experiment, the subjects will be exposed for two pain inflicting stimuli. Their
responses will be measured using the Eulerian motion magnification method before
and after the stimuli. After the completion of the first stimulus the subject will perform
a short meditation course that aims to regulate their perceived pain level scale.

Method

In this experiment we will attempt to measure changes in the blood flow to the brain
and the subjective perception of pain sensation ('feeling') as a result of a noxious
stimulation.

The level of brain activity will be presented as the amount of blood flow, which will
be monitored and calculated in two ways. First, by the color of the subjects' face: the
redness of the subject's face, in comparison to the resting state. Second, by the
motion: the vibration of the two main arteries carrying blood to the brain. The
subjective 'feeling' of the pain will be concluded by the subject's direct report.

At first we will assess the level of blood flow of the subject at resting state.
Afterwards, the painful stimulus will occur as the experimenter will moderately prick
the subject. The subject then will be asked to report the intensity of the pain that
the pricking cause, using the scale to estimate the level of perceived pain.

Manipulation: The next step is 15 minutes of constructed meditation (i.e. mindfulness
practice). In contrast, the control group will be asked to drink a glass of water and
will wait 15 minutes.

Then the final step is to once again execute the pain stimulus (i.e. the pricking) and to
monitor the blood flow reaction and the subjective direct report.

Each subject will be monitored as mentioned during the whole time of the experiment.

Results

By using the Eulerian magnification algorithm, the movement of the arteries is
clearer. As speculated, it seems to be clear different in the vibration between the
points of time before/after painful stimulus (between both baseline-pain
measurements).

However, as opposed to what was speculated, there seem to be little or no difference
between the response before and after the manipulation, although there has been a
change between the subjective estimation (first stimulus- 3, second stimulus- 1),
but due to the small number of participants the correlation is meaningless.

Moreover, for the color analysis due to the illumination used in the experiment
(fluorescent-type) we came across a noise problem (light source flicker), that
prevented us from assessing the changes in the color of the subject's face.

Conclusions

The main goal of this feasibility study was to determine if it is possible to infer pain
perception from measuring color changes or artery vibration using a computational
vision tools. This is an indirect measurement as the hypothesis is that pain sensation
causes increased brain activity which in turn requires increased blood flow to the
brain. It was proposed that the evaluation of the blood flow to the brain be measured
from a video signal by using a computational vision tools to amplify and reveal very
small motions and slight changes of color. In other words, to try and find the
existence of an initial link between usually unseen changes in blood flow toward the
brain and the activity of the system as a result of perception of pain sensation.

We've found hints that such a connection between slight changes of face color and
artery motions with pain perception may be possible but the results are clearly not
decisive. Therefore, follow up studies in this direction should further explore this
approach. If such connection be found, the Eulerian magnification algorithm may be
employed in low cost instruments to research processes of the brain, by the level of
blood flow to the brain.

Additional Information

References

1. E.H. Adelson, C.H. Anderson, J.R. Bergen, P.J. Burt, J.M. Ogden, Pyramid Methods in Image Processing, RCA Engineer, 1984.
2. A. Chiesa, P. Malinowski, Mindfulness-based approaches: Are they all the same? Journal of Clinical Psychology, 67, 404-424, 2011.
3. J. Nolte, The Human Brain. An Introduction to its Functional Anatomy. Mosby Year Book, 6th edition, 2009.
4. R. Peyron, B. Laurent, L. Garcia-Laerrea, Functional Imaging of Brain Responses to Pain. A review and Meta-Analysis, Neurophysiol Clin 30: 263-88, Elsevier, 2000.
5. S.L. Shapiro, L.E Carlson, The Art and Science of Mindfulness: Integrating Mindfulness into Psychology and the Helping Professions, (pp. 75-79). Washington, DC, US: American Psychological Association, 2009.
6. R. Szeliski, Computer Vision: Algorithms and Applications, electronic draft, September 2010 ( http://szeliski.org/Book/)
7. I. Tracey, P.W. Mantyh, The Cerebral Signature for Pain Perception and It's Modulation, Neuron 55, 2007.
8. I. Tracey, Imaging Pain, British Journal of Anesthesia 101(1): 32-9, 2008.
9. H.Y Wu, M. Rubinstein, E. Shih, J. Guttag, F. Durand, W. Freeman, Eulerian Video Magnification for Revealing Subtle Changes in the World, MIT CSAIL and Quanta Research Cambridge Inc., Nov 2012.