Transcript Methods in Neuroscience

Methods in Neuroscience
CHAPTER 4
(YES, WE SKIPPED- WE WILL BE BACK!)
Research, Theory and Science
 Relies on EMPIRICAL DATA as its means of
acquiring knowledge
 Relies on SCIENTIFIC METHOD
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hypothesis testing and theories
operational definitions
systematic observations
 Common sense and folklore may or may not be “true”
 Science differs from folklore and tradition because it uses
empirical method
Science (and thus neuroscience) is Tentative
 Conclusions based on current information
 New information always being acquired
 This creates a problem: what was true yesterday is probably not true
today, and what is true today is probably not true tomorrow!
 Science is evolving, rapidly changing, and ambiguous
 Relies on theories:
 Integrative interpretation of diverse observations
 Attempt to explain some phenomenon
 Based on evidence
 Conclusions pulled together logically
 Explains current facts
 Suggests new hypotheses and experiments to constantly test and refine
the theory
Methods of Research
 Rules for conducting research
 Scientific
 Ethical
 Many techniques
 Two main methods:
 correlational
 experimental method
 sub-areas of these, as well
Correlational method
 NON experimental
 looking at relation between two variables
 effect of X on Y
 Correlation DOES NOT IMPLY CAUSATION
 values of -1.0 to 0 to +1.0
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closer to 1.0 is stronger relationship
if value is close to 0, little relationship
Two types of correlations
 Positive correlation: 0 to 1.0
 as X goes up so does Y
 rate of waterskiing and outside temperature
 Negative correlation: 0 to -1.0
 as X goes up, Y goes down
 rate of hot chocolate intake and outside temperature
Examples of correlations
Experimental Method
 Allows us to conclude causation
 Uses general experimental method
 hypothesis to test
 uses INDEPENDENT and DEPENDENT variables
Conducting an Experiment
 Need independent and dependent variables
 Variable = any characteristic or condition which is subject to
change
 Independent variable: what the experimenter manipulates or
changes
 Dependent variable: what the experimenter measures, what was
changed by the I.V.
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Experimenter manipulates IV, measures DV
 WAY that the IV is manipulated is important:
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assumes using a random sample
control for extraneous (extra or outside) variables
use systematic observations
Types of Groups of IV
 Experimental group: gets the treatment
 Control group:
 does not get the “treatment”, but otherwise equal to the
experimental group
 Placebo Group:
 a control group
 “thinks” they got the treatment
Many Research Techniques in Neuroscience
 Which are correlational?
 No random assignment to groups
 Linking or relating A to B
 Which are causal?
 Random assignment
 Researcher manipulates independent variable
 Does it make a difference?
Thinking in Salmon
 (DEAD salmon)
 Dr. Craig Bennet:
 purchased a whole Atlantic salmon
 put it into an fMRI machine used to study the brain.
 was to be the lab’s test object as they worked out some new methods.
 As the fish sat in the scanner:
 showed it “a series of photographs depicting human individuals in social
situations.”
 To maintain the rigor of the protocol and, just like a human test subject,
salmon “was asked to determine what emotion the individual in the
photo must have been experiencing.”
 The salmon “was not alive at the time of scanning.”
Dead Salmon Can THINK!
 When analyzed the voxel (think: 3-D
or “volumetric” pixel) data, the voxels
representing the area where the
salmon’s tiny brain sat showed
evidence of activity.
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looked like the dead salmon was
actually thinking about the pictures
it had been shown.
 “By complete, random chance, we
found some voxels that were
significant that just happened to be
in the fish’s brain,” Bennett said.
“And if I were a ridiculous
researcher, I’d say, ‘A dead salmon
perceiving humans can tell their
emotional state.'”
What does this mean?
 The result is completely nuts — but that’s actually exactly the point.
 Bennett & Wolford wrote up the work as a warning about the
dangers of false positives in fMRI data.
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wanted to call attention to ways the field could improve its statistical methods.
Researchers get up to 130,000 voxels from each set of scans
Must comb all that data for signals that indicate something is happening in a
particular region of the brain.
The fMRI data has a lot of natural noise,
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LARGE amounts of data generated
 Statistical chance thus can play some tricks. BE CAREFUL HOW
YOU INTERPRET YOUR RESULTS!
Techniques include
 Cell work: study brain cells or slices
 Measuring brain activity in live organisms:
 Scans of functioning brains
 Implanting measurement tools and measuring
 Animal models
 Post-mortem examination
Research techniques in neuroscience:
Staining and imaging neurons
 Golgi stain method:
 randomly stains about 5% of
neurons in slice
 Places them in relief against
background
 Can see patterns
 Myelin stains:
 Stain taken up by fatty
myelin that insulates axon
 Stain helps identify neural
pathways
 Nissl stains:
 Stain taken up by neurons
 Identify cell bodies of
neurons
Research techniques in neuroscience:
Staining and imaging neurons
 Autoradiography
 Use fluorescent dye:
flurogold
 Make neurons stand out
 Importantly: tells which
neurons are active
 Can correlate with behavior
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Also use radioactive tracers:
2-DG (2-deoxyglucose)
Make this sugar radioactive
 Is taken up by neuron
 Can trace where it went
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 Can also stain for
neurotransmitters or other
brain chemicals
Light and Electron Microscopy
 Electron microscope:
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Passes beam of electrons through thin
slice of brain tissue onto photo plate
Different parts of tissue block or pass
electrons at different degrees
Electrons produce image based on this
variance
 Scanning electron microscope:
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Beam of electrons causes specimen to
emit electrons itself
These are captured by photo plate
Not as great of magnification, but image is
3-D
Measuring Brain Activity
 Electroencephalography or EEG
 Hans Berger, 1929
 Recorded from two electrodes on scalp
over area of interest
 Electronic amplifier detects combined
electrical activity of all neurons
between these two neurons
 Can graph activity
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Terrific temporal resolution: 1
millisecond recording
Spatial resolution is poor
 Why use?
 Detecting changes in brain patterns or
arousal
 Can average several readings to obtain
evoked potential
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Signal – background noise
Gives better estimation of patterns
Often used for detecting epilepsy and
other brain disorders, sleep disorders
Stereotaxic techniques:
 Stereotaxic device:
 Allows precise positioning in
brain of electrode or other
device
 Holds head in position
 3-D: height x depth x width
 Use stereotaxic atlas to find
locations
 Brain atlas!
 Several kinds of things
might be put into brain
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Cannula
Electrode
Stereotaxic techniques:
 Allows one to ablate or
lesion precise areas of
brain
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Alter specific area to
determine function
Examine pathways
 Several kinds of measures
 Electrophysiology
 Electrodialysis
 Fast scan cyclic voltammetry
 All allow measurement of
brain electrical and
chemical changes
Brain Imaging
 CT or CAT scan:
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Computed tomography
X ray scanning
Produces series of x rays
taken from different
angles
Combined using computer
to create series of 2-d
horizontal cross sessions
or slices
Presented as series to
make 3-D
Brain Scanning: MRI
 Magnetic Resonance
Imaging or MRI
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Measures radio-frequency
waves emitted by
hydrogen atoms when
they are subjected to
strong magnetic field
Extremely fast
Can scan very small areas
clearly
Brain Scanning: PET
 PET: positron emission
tomography
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Involves injecting radioactive
substance into bloodstream
Is taken up by parts of brain
according to how active each area
is
Often radioactive 2-DG
Use other radioactive tracers to
mark bloodflow, oxygen uptake
 Requires lots of training and
access to cyclotron
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Cyclotron supplies radioactive
substances
 Provides estimates of brain
activity and changes in brain
activity
Brain Scanning: fMRI
 fMRI: functional magnetic
resonance imaging
 Measures brain activation by
detecting increase in oxygen
levels in active neural structures
 Can be used as individual is
engaging in a behavior or
cognitive task
 Can see changes as behavior
changes
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Important: don’t have to ablate or
lesion to determine function
Allows use of human subjects
Studying heritability and genetics
 Family studies:
 Determine how strongly a
characteristic is shared across family
members
 Quantify
 Correlate degree of heritability
 Adoption studies
 Compare adopted and biological
children
 Compare behavior in adoptive vs
biological family
 Twin studies
 Identical vs. fraternal twins
 Concordance rate: frequency with
which relatives are alike in
characteristics
Genetic Engineering
 Genetic engineering:
 Manipulation of organism’s
genes or their functioning
 Knockout technique:
 Nonfunctioning mutation is
introduced into isolated gene
 Altered gene is transferred
into embryo
 Antisense RNA procedure:
 Blocks participation of
messenger RNA in protein
construction
Genetic Engineering
 Gene Transfer:
 Gene is inserted into an
animal’s cells
 Transgenic animal:
 Gene is inserted into animal
embryo
 Embryo now has that trait
 Genetic Engineering
 Manipulate genes to turn
on/off different traits
 Goal is to be of therapeutic
use
Research Ethics
 Regulatory
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Animal research:
IACUC: Institutional animal care and use committee
 5 federal agencies have federal guidelines
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NIH human subjects use
 Problems:
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Plagiarism
Fabrication of data
 Ethical dilemmas
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Gene therapy
Stem cell therapy