Download Methods 1a

Methods of Studying the Nervous System
Hebb, D.O. (1949). The organization of
behavior: A neuropsychological theory.
New York: John Wiley & Sons Inc.
“when an axon of cell A is near enough to
excite a cell B and repeatedly or
persistently takes part in firing it, some
growth process or metabolic change takes
place in one or both cells such that A’s
efficiency, as one of the cells firing B, is
increased.” (p. 62)
In other words:
“cells that fire together, wire together.”
Wikipedia states - …although this is an oversimplification of
the nervous system not to be taken literally, as well as not
accurately representing Hebb's original statement on cell
connectivity strength changes. …simultaneous activation of
cells leads to pronounced increases in synaptic strength.
Such learning is known as Hebbian learning.
If Wikipedia suggests caution, well…
Hebbian Learning
“What has become known as
‘Hebb’s synapse’ or ‘learning
postulate’ is one of the few
aspects of the theory he did
not consider completely
original. Something like it had
been proposed by many
psychologists, including Freud
in his early years as a
neurobiologist.” (Milner, 1993)
Lack of novelty aside, the theory had an even bigger problems because
current technology rendered it untestable. Then, in 1973…
A hundred or so rapid high frequency stimulations of the PP resulted in
LTP at the recording site. LTP is the increased synaptic strength that
lasted for months or even longer, theoretically as long as a memory trace
may exist.
Here is a modern electrophysiological
recording apparatus that can both
stimulate and record electrical signals
from a 400 micron thick slice of the rat
hippocampus.
Just what you need to measure LTP.
Biopsychological research
often dependends on
advances in technology
• Brain imaging
• recording neural activity
• lesion technology
Standard X-ray techniques are good for visualizing bone in flesh (or
metal in flesh given unfortunate circumstances)
Such techniques are not very useful for visualizing brain structures
because X-rays primarily pass through soft tissue.
So this is a fake pic from someone
trying to belittle Homer Simpson
Contrast X ray techniques
Use of X ray technology with other features that enhance
contrast to visualize aspects of brain anatomy
Pneumoencephalography
Angiography
Methods of visualizing the human brain
Computerized Axial Tomography (CAT)
CAT is a 3-D X-ray constructed of a series of
photographs representing horizontal sections through
the brain.
Methods of visualizing the human brain
Computerized Axial Tomography (CAT)
The X-ray tube and detector rotate in opposition
around the brain at one level taking a series of
measurements from which an image of one section is
constructed.
Methods of visualizing the human brain
Magnetic Resonance Imaging (MRI)
Provides high resolution 3-D images
of the brain.
Methods of visualizing the human brain
Magnetic Resonance Imaging (MRI)
Measures the waves emitted by
hydrogen atoms when they are
activated by radio-frequency
waves in a magnetic field.
II. Methods of visualizing the human brain
D. Positron Emission Tomography (PET)
Provides information
about the metabolic
activity of the brain.
Methods of visualizing the human brain
Positron Emission Tomography (PET)
The patient is
injected with
radioactive 2deoxyglucose (2DG) which is taken
up rapidly by active
neurons.
Methods of visualizing the human brain
Positron Emission Tomography (PET)
Because 2-DG cannot be
metabolized, it temporarily
accumulates in active
(energy consuming)
neurons and will indicate
the brain regions that are
active during performance
of some test.
Methods of visualizing the human brain
Given the following images, what is your diagnosis of the patient?
CAT scan
MRI scan
PET scan
No metabolic
activity
Methods of visualizing the human brain
Functional MRI*
Provides information about increases
in oxygen (blood) flow to brain regions
that are active during performance of
a task.
The BOLD signal - magnetic
resonance of blood changes when
oxygenated.
Methods of visualizing the human brain
Functional MRI*
Advantages over PET:
1) Noninvasive
2) Shows both structure and function
3) Spatial resolution is better
4) Can produce 3D images of activity
over the entire brain
magnetoencephalogram (MEG) - the
magnetic fields produced by
electrical brain activity.
electroencephalogram (EEG) - the
associated scalp potentials.
Clusters of thousands of synchronously
activated pyramidal cortical neurons are
believed to be the main generators of MEG
and EEG signals.
provide unique insights into the dynamic behavior of the human brain as they
are able to follow changes in neural activity on a millisecond time-scale
Transcranial Magnetic
Stimulation
• Disrupts activity in an area of cortex by
creating a magnetic field under a coil
positioned next to the skull.
The God helmet
Parallel and Interactive Memory
Systems in the Human Brain
and
the limitations of fMRI studies
Probabilistic Classification Task
In this learning game you are the weather forecaster.
You will learn how to predict rain or shine using a deck of four
cards:
Knowlton, B.J., Mangels, J.A., & Squire, L.R. (1996) Science, 273, 1399-1402.
(A) Performance on the probabilistic classification tasks by controls (CON, n = 15),
amnesic patients (AMN, n = 12), patients with Parkinson’s disease (PD, n = 20), and a
subgroup of PD patients with the most severe symptoms (PD*, n = 10). (B)
Performance on the declarative memory task. Both PD and PD* groups exhibited
entirely normal declarative memory for facts about the testing episode, despite their poor
performance on the task itself. In contrast, amnesic patients exhibited a severe
impairment in declarative memory for the testing episode but normal performance on the
classification test.
Probabilistic Classification Tasks for fMRI Studies
a. Activation for FB compared to baseline (yellow = increase, blue = decrease); b.
Activation for PA compared to baseline; c. Regions exhibiting significant differences
between FB and PA tasks; d. Plot of task related signal change from the MTL region
exhibiting maximal task-dependent differences against a region in the right caudate that
exhibited significant negative correlation with the MTL in functional connectivity analysis.
Each data point represents a single subject.
Poldrack, R.A., Clark, J., Paré-Blagoev, E.J., Shohamy, D., Moyano, J.C., Myers, C., & Gluck, M.A. (2001). Nature, 414, 546-550.
Results from event-related FMRI
study of FB category learning
(experiment 2). a, Regions
exhibiting significant evoked
activation (yellow) or deactivation
(blue) for classification trials. Yellow
arrow highlights region of caudate
activation, white arrow highlights
region of MTL deactivation. b, c,
Depiction of parametric change in
modelled evoked haemodynamic
response across the initial 450-s
scanning run (averaged across
subjects) in b, left body of caudate
nucleus (-12, 3, 21), and c, left MTL
(-24, -3, -24). Red indicates positive,
event-related response, blue
indicates negative event-related
response.
Poldrack, et al. (2001). Interactive memory systems in the human
brain. Nature, 414, 546-550.
Left body of caudate nucleus
Left medial temporal lobe
Put on the critical thinking caps (save the God helmet for later)
What can/should we conclude from this study? The
authors state that the results:
“…provide the first substantive evidence, to our knowledge, for
competition between memory systems in the human brain …the
present study provides direct evidence for competition at the neural
level by demonstrating three essential features of the MTL-striatum
interaction. First, it shows that engagement of MTL and striatum is
modulated by whether the task encourages the use of declarative
versus nondeclarative memory processes or strategies. Second, it
demonstrates that engagement of these regions is negatively
correlated across subjects. Third, it demonstrates rapid reciprocal
changes in the engagement of these regions. These data are
concordant with animal lesion studies demonstrating that the memory
systems based on the MTL and striatum can compete with one
another during learning.”
Poldrack, R.A., Clark, J., Paré-Blagoev, E.J., Shohamy, D., Moyano, J.C., Myers, C., & Gluck, M.A. (2001). Nature, 414, 546-550.
However, the authors also
state that their
computational theory:
“…interprets both the earlier animal data and
the present human imaging data as implying an
interaction between the hippocampus and other
brain structures, in which the hippocampus has
a modulatory role in learning by developing
new stimulus representations during early
phases of training which are used by the
striatum to develop complex stimulus-response
associations.”
Poldrack, R.A., Clark, J., Paré-Blagoev, E.J., Shohamy, D., Moyano, J.C., Myers, C., & Gluck, M.A. (2001). Nature, 414, 546-550.