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Habituation in Spirostomum ambiguum

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Title: Habituation in Spirostomum ambiguum


1
Habituation in Spirostomum ambiguum
  • Habituation A response decrement to repetitive
    stimulation
  • Spirostomum is a ciliated protozoa

2
Habituation in Spirostomum ambiguum
  • Are multiple cells required for learning
  • Chemical bases of learning

3
Habituation in Spirostomum ambiguum
  • Place individuals on a slide
  • Tap slide with a mechanical stimulus each 4
    seconds
  • Animal shows a response decrement (habituation)
    after 12 to 15 stimuli
  • Other studies show that Spirostomum can remember
    for a least 10 minutes

4
Ivan Pavlov
  • A Russian physiologist
  • Discovered the conditioned reflex by chance

5
E. B. Twitmyer
  • A Beauty Never to See Flower
  • A discoverer of the conditioned reflex

6
Pavlovs Basic Procedure
  • Present the CS without the US-The UR is observed
  • Pair the CS with the US for a number of trials
  • The CR is observed just prior to the US onset

7
Stages Of Pavlovian Conditioning
8
Mowers Bell and Pad
Pavlovian procedure used to treat enuresis
9
Taste Aversion
Pavlovian procedure causes people to avoid
certain foods
10
E. L. Thorndikes Puzzle Box
Law of Effect
11
B. F. Skinner and Operant Conditioning
  1. My introduction to B.F. Skinner
  2. Skinner and society

12
Operant Conditioning
13
Four Critical Definitions
Positive Reinforcement-The application of a
stimulus that increases the probability of the
response it follows. Negative Reinforcement-The
withdrawal of a stimulus that increases the
probability of the response it follows. Punishment
-Reinforcement-The application of a stimulus that
decreases the probability of the response it
follows. Extinction-The withdrawal of a stimulus
that decreases the probability of the response it
follows.
14
Some Negative Side Effects Of Punishment
  1. Person who is punished avoids the punisher.
  2. Punishment may model inappropriate aggressive
    behavior.
  3. Punishment can reduce self-esteem.
  4. Punishment teaches you what not to do but not
    what to do.
  5. Punishment teaches people to do the minimum.
  6. The use of aversive stimuli are hard to control.

15
Abu Graib
16
Schedules of Reinforcement
17
Caswell Center
Caswell Center
18
A New Orleans Story
19
Goal Of Behavior Therapy And A Few Definitions
Goal To provide the individual with better
control over themselves or their
environment. Baseline Behavior prior to
intervention. Shaping Reinforcing successive
approximations of the desired behavior. Prompt
A stimulus used to increase the probability of a
correct response. Fading Gradual removal of a
prompt. Chaining Reinforcing the last behavior
in the sequence, the next to last behavior, etc.
20
Four Types Of Prompts
Physical Assistance Moving an individual through
the desired responses. Modeling Imitating the
desired behavior. Pointing Designating a
location. Verbal Instruction Describing how to
perform a particular behavior.
21
Goal of Behavior Therapy
To give the individuals increased control over
their lives and/or environment.
22
Mary Cover Jones Counterconditioning
Greg and the empty toilet paper roll
23
What Is Automation ?
Any sensing, detection, information-processing,
decision-making, or control action that could be
performed by humans but is actually performed by
a machine (Moray, Inagaki, Itoh,
2000) Automation is usually viewed as a
continuum, ranging from manual control to full
automation.
24
Some Quotes About Technology
But lo!! Men have become the tools of their
tools. - Henry David Thoreau
25
Some Quotes About Technology
It has become appallingly obvious that our
technology has exceeded our humanity. - Albert
Einstein
26
Some Quotes About Technology
We live in a time when automation is ushering in
a second industrial revolution. - Adlai E.
Stephenson
27
Some Quotes About Technology
The first rule of a technology used in a business
is that automation applied to an efficient
operation will magnify efficiency. The second is
that automation applied to an inefficient
operation will magnify inefficiency. - Bill Gates
28
Four Generations of Artificial Environments
(AEs)
Where we have been, where we are, and where we
are going
29
First Generation
Unidirectional Communication-Information moves
from the machine to the person but not the person
to the machine.
Perform the actions necessary to accomplish the
objective via automated or manual control.
30
Second Generation
Bidirectional Communication-Information moves
from the machine to the person and from the
person to the machine.
Perform the actions necessary to accomplish the
objective via automated or manual control.
31
Third Generation
Virtual Reality-Information moves from the
machine to the person and from the person to the
machine. Ideally, the synthetic environment is
indistinguishable from the actual environment.
Perform the actions necessary to accomplish the
objective via automated or manual control.
32
Fourth Generation
Life Simulation-The synthetic and actual
environments are indistinguishable and the person
does not know whether they are in an actual or
synthetic world.
Perform the actions necessary to accomplish the
objective via automated or manual control.
33
Automation Usage Decisions (AUDs)
AUDs Choices in which a human operator has the
option of using manual control or one or more
levels of automation (LOAs) to perform a task.
34
Some AUDs Are Commonplace
Checkbooks may be balanced with a calculator or
by mental computation Automobiles can be set to
cruise control or the driver may operate the
accelerator pedal Stock purchases may be based
on the output of software programs or investors
may depend upon their subjective assessment of
the market
35
Some AUDs Have Historic Consequences
Casey Jones Pearl Harbor Three
Mile Island
36
Some AUDs Have Historic Consequences
USS Greenville
2000 Election
37
Types of Automation
  • Static Level of automation is set a the design
    stage
  • Adaptive Level of automation varies depending
    upon the situation

38
Optimal And Suboptimal AUDs
If it is assumed that the objective is to perform
a task, the optimal AUD is to employ the level of
control, manual through full automation, that
maximizes the likelihood of a successful
outcome. A suboptimal AUD is a choice to use a
level of control that does not maximize the
likelihood of successfully performing a task.
39
Types of Suboptimal AUDs
Misuse is over reliance, employing automation
when manual control or a relatively low LOA has a
greater likelihood of success Disuse is the
under utilization of automation, manually
performing a task that could best be done by a
machine or a higher LOA.
40
Errors Resulting in Misuse and/or Disuse
Recognition Errors-Operator fails to recognize
that an alternative, either automated or manual,
is available. Appraisal Errors-Operator
inaccurately estimates the utilities of the
options. Intent Errors (also called action
errors)-Operator knowingly selects the
alternative that does not maximize the likelihood
of task success.
41
Two Images of an Operator
An operator is a single minded individual whose
sole object is to maximize task performance An
operators decision to rely on automation is
based on a number of contingencies only one of
which is to achieve a successful performance.
42
Intent Errors and Decision Aids Doing It Your
Way When Your Way Is Obviously Wrong
43
Decision Aids And Intent Errors
Probably no area of automation has proved more
problematical than the introduction of decision
aids Beck, Dzindolet and Pierce contended that
much of the disuse of decision aids is due to
intent errors That is, operators refuse advice
from a decision aid that they know would improve
their performance
44
200 Training Trials
Participants viewed a series of slides on the
computer screen, half of which contained a
soldier in camouflage. Machine Absent Pressed
a button to indicate if the soldier was present
or absent Machine Present 1) Pressed a button
to indicate if the soldier was present or absent
and 2) Received the decision aids response
45
100 Test Trials
Participants viewed a series of slides on the
computer screen, half of which contained a
soldier in camouflage. Machine Absent Pressed
a button to indicate if the soldier was present
or absent Machine Present 1) Received the
decision aids recommendation and 2) Pressed a
button to indicate if the soldier was present
or absent
46
Results
47
Operators In Machine Present Condition
48
Machine Present Condition Estimated Accuracies
49
To Shoot Or Not To Shoot
50
To Shoot Or Not To Shoot
Since 1900, 10 to 25 of US war fatalities in
resulted from fratricide
51
Targeting Decisions Possible Outcomes
  • Soldier and CID detect a friend.
  • 2) Soldier and CID fail to detect a friend.
  • 3) Soldier detects a friend and CID fails to
    detect a friend.
  • 4) Soldier fails to detect a friend and CID
    detects a friend.

52
Automation Usage Decisions (AUDs)
AUDs- Choices in which a human operator has the
option of relying upon manual control or one or
more levels of automation (LOAs) to perform a
task. Optimal AUD-Soldier relies upon the form
of control that is most likely to result in a
correct decision.
53
Types of Suboptimal AUDs
Misuse is over reliance, soldier employs
automation when manual control or a relatively
low LOA has a greater likelihood of
success Disuse is the under utilization of
automation, soldier manually performs a task that
could best be done by a machine or a higher LOA.
Perform the actions necessary to accomplish the
objective via automated or manual control.
54
Beck, Dzindolet, Pierce (2002)
Appraisal Errors-Soldier misjudges the relative
utilities of the automated (CID) and
non-automated (e.g., view through gun site)
options. Intent Errors-Soldier disregards the
utilities of the alternatives when making AUDs.
55
Intent Errors Two Images of an Operator
An operator is a single-minded individual whose
sole object is to maximize task performance An
operators decision to rely on automation is
based on a number of contingencies only one of
which is to achieve a successful performance.
Perform the actions necessary to accomplish the
objective via automated or manual control.
56
John Henry Effect
John Henry Effect Operators respond to
automation as a challenger, competitor, or
threat Increasing the operators personal
involvement with the non-automated alternative
augments the likelihood of a John Henry Effect.
57
John Henry Effect
Variables that increase the strength of a John
Henry Effect augment operators preference for
the non-automated over the automated
alternative Heightened preference for the
non-automated option should 1) increase disuse
and 2) decrease misuse
58
Design
2 (Operator Self-reliant, Other-reliant) x 2
(Machine Performance Inferior, Superior) x 14
(Trial Blocks) design Dependent Variable
Suboptimal AUDs (Superior Machine Basing credit
point on the operators performance Inferior
Machine Basing credit on the machines
performance)
59
Credit Choice Screen
60
Sample Helicopter Photograph
61
Sample Helicopter Photograph
62
Operator Response Screen
63
CID Response Screen
64
Results Screen
65
Hypotheses
  • Self-reliant operators will be less likely to
    base credit points on the CID than other-reliant
    operators
  • Therefore
  • Disuse will be greater in the self-superior than
    in the other-superior condition
  • Misuse will be higher among other-inferior than
    self-inferior persons

66
Disuse
  • Figure 1. Mean suboptimal automation usage
    decisions (AUDs) as a function of operator and
    trial block for persons working with the superior
    machine.

67
Misuse
  • Figure 2. Mean suboptimal automation usage
    decisions (AUDs) as a function of operator and
    trial block for persons working with the inferior
    machine.

68
Conclusions
1) Self-reliant and other-reliant operators were
yoked. Each had the same information. It seems
reasonable to conclude that the difficulty in
determining the optimal AUD was approximately
equal in both conditions. Thus, the large
differences in suboptimal AUDs were probably due
to intent rather than appraisal
errors. 2)Results support the hypotheses that
factors which augment the degree of personal
involvement or challenge from automated devices
will increase the probability of disuse and
decrease the likelihood of misuse
69
A Few Implications
  1. Operator training programs should attempt to
    attenuate intent as well as appraisal errors.
  2. At least on this task, intent errors were a
    significant source of suboptimal AUDs
  3. Both appraisal and intent errors are sufficient
    to produce suboptimal AUDs although neither is
    necessary
  4. It will be a hollow achievement if advances in
    our knowledge of hardware and software are not
    matched by an equally sophisticated comprehension
    of the causes and control of misuse and disuse.
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