**Neuroeconomics and Aging**

Palo Alto, California

March 31--April 1, 2006

**WORKSHOP SUMMARY**

National Institute on Aging

Behavioral and Social Research Program

**For Administrative Use**

Prepared by:

Rose Li and Associates, Inc.

April 2006

**National Institute on Aging**

**Workshop on Neuroeconomics and Aging**

**March 31--April 1, 2006**

**Executive Summary**

There has been a noticeable trend in the growing number and complexity
of economically relevant decisions being faced by middle-aged and older
adults, especially regarding pension and benefit issues, portfolio
investment choices, health management, pharmaceuticals, and health
insurance options. These can be cognitively challenging decisions, and
the dizzying array of options faced by the decision maker can -- at any
age -- adversely affect people's abilities to absorb, process, and weigh
information. Meanwhile, the choices people make with regard to savings,
investment, and health care can have a profound impact on their well
being in later life. This trend, therefore, motivates the need for a
greater understanding of how cognitive, motivational, and emotional
processes in decision making influence economic behavior at different
life stages, and particularly in middle to late adulthood when many of
these decisions are made. Our current understanding of how changes in
emotional, cognitive, and physical capacities at different life stages,
in combination with life course changes in motivation and goals, impact
economic behaviors at different life stages remains limited. Even less
is known about changes in the neurobiological underpinnings of these
interactions.

Recent efforts in neuroeconomics, that apply the theories and
methodologies of behavioral economics, game theory, psychology, and
cognitive, social and affective neuroscience to the study of economic
behaviors, are beginning to shed light on the neurobiological basis of
these kinds of complex decision making processes. Neuroeconomics has the
goal of understanding the psychological mechanisms that guide economic
behaviors and the neurobiological mechanisms that underlie them. Fueled
by methodological advances in neuroscience, including the development of
neuroimaging technologies such as functional Magnetic Resonance Imaging
(fMRI), the neuroeconomics approach provides opportunities for a
systematic investigation of the neurobiological mechanisms involved in a
wide array of economically relevant behaviors such as reward processing,
temporal discounting, subjective and objective valuation,
overconfidence, delay of gratification, decision-making under risk and
uncertainty, and affective influences on choice. Recent neuroeconomic
research has also focused on social phenomena involved in the motivation
of economic behavior including altruistic punishment, cooperation,
competition, fairness, persuasion, trust and reciprocity. These
functions implicate the involvement of neural mechanisms associated with
reward processing, motivation, affect, and social cognition.

To date, there has been little investigation of these phenomena in the
context of aging, despite the rapid accumulation of knowledge about
age-related changes in the cognitive, motivational and affective
processes believed to influence economic behavior. It is therefore not
surprising that understanding age-related changes in motivation and
socioemotional influences on decision making are among the top research
priorities identified in a recent National Research Council report
commissioned by BSR from the Committee on Aging Frontiers in Social
Psychology, Personality, and Adult Developmental Psychology, entitled
"When I'm 64", (Carstensen & Hartel, 2006). The present workshop is
motivated by the desire to extend the neuroeconomics approach to
behavioral and social research on aging, creating the opportunity to
explore how the neurobiological changes associated with aging influence
or are influenced by these social, emotional, cognitive, and
motivational factors, and to improve our predictive models of life
course economic behavior by revealing the neurobiological mechanisms
involved. 

Within this context, the Behavioral and Social Research (BSR) Program of
the National Institute on Aging (NIA) convened an exploratory workshop
to share ideas about neuroeconomics and aging around a set of defined
workshop goals. Presentations from experts in aging research in areas of
social, cognitive, and personality psychology; cognitive and affective
neuroscience; decision-making; and health and retirement economics
framed the discussion of how the neuroeconomics perspective can be
applied most fruitfully to issues of relevance to aging. Specifically,
how can collaborative work on the neuroeconomics of aging develop across
the disciplines of psychology, economics and neuroscience? What are the
research gaps and opportunities for advancing neuroeconomics research on
aging, as well as methodological challenges and potential solutions? Are
there longitudinal studies that should be initiated or lifecourse
neuroeconomic models that should be applied to aging issues? How can BSR
define program goals for neuroeconomics of aging research to facilitate
development of better lifecourse economic models, psychological
theories, and applications to targeted aging issues?

The workshop presentations highlighted the importance of affect and
motivation on judgments, probability perception, and decision-making,
and they underscored the potential contributions that behavioral
scientists could make to improve the measurement of utility (an abstract
concept representing subjective well-being or satisfaction used by
economists) and cognitive functioning in large population surveys.
Insight on methodological and interpretive issues involved in
neuroimaging of older adults was provided, and there was discussion of
how to forge links between the neuroscience laboratory and field-based
population research. Findings related to health care and retirement
economics and aging were highlighted. These presentations and
discussions are summarized below. A list of recommended readings
provided by presenters is included as Attachment B.

**Emerging Themes**

Several underlying themes permeated the discussion, including the
following:

*Age differences in affect/emotion*

Affect, a valenced feeling that gives meaning to information, may be an
internal "common currency" used to assess the relative value of choice
options. Affective information may become more salient as we age. The
role of emotion and affective information in guiding economic decision
making was the focus of several presentations at the workshop
(Carstensen, Slovic, Mather), and understanding the role of emotion or
affect in choice is an important emerging theme at the interface of
psychology, economics and neuroscience.

Age differences in affective/experiential and deliberative processes
have important theoretical implications for judgment and decision theory
and important pragmatic implications for older-adult economic
decision-making. In some situations, age-related adaptive processes,
including motivated selectivity in the use of deliberative capacity, an
increased focus on emotional goals, and greater experience, may moderate
age-related cognitive declines and possibly produce better decisions for
older adults. Indeed, it has been shown that healthy older adults report
greater emotional control, experience the same or greater well-being,
and demonstrate greater emotional understanding and refinement than
their younger counterparts. However, the dynamic range of physiological
response to emotionally evocative stimuli declines with age,
particularly in the cardiovascular system. If visceral sensations also
lessen with age, this may reduce the impact affective signals that
convey important information for decision making. Evidence also exists
that older adults use their cognitive resources to regulate their
emotions. There is some evidence of a "positivity effect," with
chronological age associated with heightened attention to emotional
gratification and the emotional aspects of life, and with accentuated
attention and memory for positive information. Yet older age is also a
time when cognitive processes are declining in efficiency. It remains an
open question how these factors interact in complex domains such as
economic decision-making.

[]{.mark}

*Neuroimaging the aging brain*

While standard observational experiments lend insight to cognitive
processes in old age, advances in neuroimaging, including diffusion
tensor imaging and fMRI, have become increasingly valuable tools for the
study of the neurobiological correlates of these processes. Neuroimaging
studies of cognition indicate that older and younger adults show
different activation patterns when performing the same cognitive tasks,
including task-specific under-activation of some brain areas,
recruitment of additional brain areas, and bilateral rather than
unilateral activation in older compared to younger adults. These kinds
of findings have variously been cited as evidence of either age-related
decline or of compensation and plasticity in the aging brain.^1^ As
neuroimaging results continue to shed light on our understanding of the
cognitive changes associated with normal aging, a growing appreciation
of the challenges that neuroimaging techniques pose for research on
aging is emerging. Of particular importance is the need to understand
how age-related differences in vascular properties influence properties
of the MR signal. In addition, practical issues, such as age-related
differences in head motion and tolerance for time in the scanner, have
the potential to influence neuroimaging data. It is important to
consider the implications of these and related problems for neuroimaging
investigations in older adults, and it is especially important to
distinguish age-related changes in neuroimaging measurement from
age-related changes in underlying brain function.

[]{.mark}

***The need for cross-disciplinary fertilization***

To best enable cross-disciplinary work, it was felt that researchers
need to examine what neuroeconomics can contribute to aging studies and,
likewise, what aging studies can contribute to neuroeconomics.
Neuroeconomics can offer a characterization of the processes involved in
economic behavior and a set of tools for studying how these processes
change over the life cycle. As a complement to this, research on aging
offers insights into age differences in the underlying cognitive,
affective and motivational processes that impact economic decision
making, and can provide a menu of life-cycle economic behaviors that
need to be understood. Development of a common language can be advanced
by improving our understanding how economic decision-making is coded and
processed in the brain, by testing computational models of these
processes, and by increasing our knowledge of age differences in
performance on a wide variety of behavioral economic, game theoretic,
and social exchange tasks. Appreciation by economists of the many facets
and dimensions of the emotional response and of the variety of possible
affective influences on economic behavior, on the one hand, and
appreciation by psychologists and neuroscientists of the details of
economic models and the structure of economic institutions, on the other
hand, would help to advance the discussion.

***The need for external validity***

Two types of external validity---population validity and task
validity---are required to ensure high-quality data. The limitations of
current studies include the focus on relatively high-functioning older
adults who are not a representative sample of the population; also,
there are confounding effects with individual differences that may be
overcome with a larger sample. Large surveys such as Health and
Retirement Study, which has an excellent longitudinal sample on whom a
variety of cognitive measures have been taken, and for whom a wealth of
information about actual economic behaviors exists, could be a valuable
resource for investigators in neuroeconomics. In addition, an identified
battery of tasks to be studied is crucial to understanding how
decision-making processes change over the life cycle and how this
affects economic behavior. Are there any "golden standards" that should
be followed at the intersection of neuroeconomics and aging, without
which data will not be valid? For example, if a cash incentive is not
used, it is likely that the cognitive process will not represent a real
economic transaction. Workshop participants agreed that this is critical
to the justification of the research.

Based on the group discussion, potential areas of study included the
effect of manipulation of time horizon on such activities as
spending/savings behavior; the addition of affective categories to
information displays to add meaning and enable older adults to process
information more easily; and how "institutions" can be manipulated to
facilitate or otherwise influence decision processes. The complexity of
many real world economic decisions was emphasized (the recent Medicare
Part D website served as one example), and research was encouraged to
understand how the presentation of economic choices impacts the
decision-making of older adults.

^1^ Reuter-Lorenz, P.A. (2002). New visions of the aging mind and brain.
*Trends in Cognitive Sciences*, 6 (9), 394-400.

**National Institute on Aging**

**Workshop on Neuroeconomics and Aging**

**March 31--April 1, 2006**

**[Summary of Proceedings]{.smallcaps}**[^1]

# Introduction

The National Institute on Aging (NIA)'s Behavioral and Social Research
(BSR) Program has begun to advance a research agenda on promising
avenues for aging research in the emerging field of neuroeconomics,
particularly interdisciplinary research that addresses interactions
among psychological, physiological, social, and economic factors that
influence how older adults negotiate important life decisions related to
retirement, Medicare, and health care management. A July 2004 seminar,
Decision-Making and Aging, represented the first of an initial round of
discussions on these topics, followed by two teleconferences on
Neuroeconomics and Aging on August 12 and 26, 2005, respectively, that
served as interim steps initiated by the NIA and BSR, and a November 29,
2005, National Academies Workshop on Decision-Making Needs of Older
Adults. The NIA continued this dialogue on March 31, 2006, with an
exploratory workshop on Neuroeconomics and Aging with invited experts
and observers in the areas of decision science, cognitive, affective and
social neuroscience, emotion and personality psychology, and economics,
to stimulate discussion of how to apply a neuroeconomics perspective
fruitfully to issues of relevance to aging. (The list of workshop
participants is included as Appendix A.) The workshop represented an
effort to develop a common language across disciplines, bring to light
differing perspectives on methodology, and foster cross-disciplinary
work. The exploratory workshop participants were asked to consider the
current state of research in the area of neuroeconomics and aging, as
well as opportunities for research advances and how research goals might
best be realized.

The workshop format was informally structured to allow each invited
expert to present his or her own findings and viewpoint in a 40-minute
talk, followed immediately by a 20-minute discussion of each
perspective. The workshop also allowed ample time for discussion of
common themes and future research directions.

Dr. Lis Nielsen, NIA BSR, and Dr. Antonio Rangel, Director of the
Stanford Neuroeconomics Laboratory, co-hosted the workshop and guided
the discussion. [In her opening remarks, Nielsen]{.mark} \[Link to
Nielsen.ppt\] emphasized that the goal of the workshop was to promote
dialogue on identifying fruitful avenues for research in Neuroeconomics
of Aging. Nielsen began the workshop by describing the organizational
structure of the BSR program at the NIA, emphasizing the program's goals
to support collaborative efforts on topics such as Neuroeconomics of
Aging that allow BSR to draw on expertise in a wide range of disciplines
and to promote integration and linkage across disciplines and topical
areas. An overarching goal of workshops such as this is to encourage
greater collaboration and exchange.

The NIA has been engaging in a dialogue with researchers in
neuroeconomics, both formally and informally, to encourage application
of their investigations to issues of relevance to aging. These
initiatives include pilot research in neuroeconomics at NIA Demography
and Roybal centers, the NIA neuroeconomics teleconferences of August
2005, the present Neuroeconomics and Aging Workshop of March 2006, and
the upcoming seminar on Neuroeconomics and Aging in July 2006, which is
part of the National Science Foundation -sponsored Stanford Summer
School on Neuroeconomics. The BSR is holding concurrent workshops on
decision-making and aging and other related initiatives.

Nielsen presented some background, intriguing findings, and
opportunities for aging research in the emerging field of
neuroeconomics. Neuroeconomic investigations have the potential to shed
light on how the biological, social, and psychological changes
associated with normal aging influence complex economic behaviors such
as investment planning, advance directives, susceptibility to fraud,
age-appropriate marketing strategies, and motivation of behavioral
change. Understanding how middle aged and older adults make economic
choices, and the constraints on those choices posed by health status,
social context, and factors associated with chronological age or changes
in time horizons may also have implications for how we evaluate and
promote well-being in older adults. In the long term, advancing our
knowledge of age-related changes in economic behavior and motivation may
ultimately guide the structuring of decision-supportive interventions
and policies affecting the choices that individuals make as they
approach the end of life.

Nielsen identified four research opportunities in the Neuroeconomics of
Aging:

1.  *Age-related change in reward processing.* Are there age-related
    change in reward processing, and what are their implications for
    economic choice and for measurement of subjective well-being in
    older age?

2.  *Discounting and intertemporal choice.* What are the neurobiological
    mechanisms underlying discounting and intertemporal choice, and how
    to they affect savings and planning behaviors?

3.  *Social and contextual factors influencing economic behaviors of
    older adults.* How does age interact with social and contextual
    influences; are there age differences in trust, reciprocity,
    cooperation, and competition?

4.  *Methodological innovations.* The development of techniques for
    measuring economic choices of relevance to older adults in the
    laboratory, field, and neuroimaging environments.

While research on these general themes is ongoing in a variety of
Neuroeconomics laboratories, very little of this work is focusing on
aging.

Nielsen stated that the goals of the workshop were to: (1) Promote
interest in lifespan developmental applications of basic research in
neuroeconomics; (2) develop a common language and collaborations across
the disciplines of economics, psychology, neuroscience, and aging; (3)
identify research gaps and opportunities as well as methodological
challenges and potential solutions; and (4) facilitate development of
better lifecourse economic models, psychological theories, and
applications to targeted aging issues. Interdisciplinary models may
influence social, financial, and health-related decisions affecting the
well-being of adults and the elderly (such as important life decisions
related to retirement, Medicare, and health care management) and inform
the development and refinement of integrative lifespan economic theories
of utility, learning, and strategic choice.

# Invited Perspectives

**Laura L. Carstensen, Ph.D., Stanford University**

***[Emotion, Motivation, and Aging]{.mark} \[Link this to
"Carstensen.ppt"\]***

Motivational changes across the lifespan can have profound implications
for decision-making. According to the socioemotional selectivity theory,
humans are uniquely able to monitor time---including lifetime---and do
so at both conscious and subconscious levels. Goals always are set in
temporal contexts. Because chronological age is associated with time
left in life, goals should change across the lifespan (Carstensen, 1993;
Carstensen et al., 1999). When time is perceived as expansive (as it
typically is in youth), people are interested in acquiring knowledge,
meeting new people, and taking chances; on the other hand, when time is
perceived as being constrained in some way (i.e., as it is for AIDS
patients), people tend to focus on the present, investing in sure
things, deepening relationships, living in the moment, and savoring
life.

A number of postulates stem from this theory: (1) perceived constraints
on time motivate people to pursue emotionally meaningful goals; (2)
motivation to pursue emotionally meaningful goals directs cognitive
resources to emotional information; and (3) focusing on emotionally
meaningful goals is good for well-being. Research suggests that it is
likely that emotional functioning improves into late adulthood and is at
least maintained in old age. Indeed, older adults have the lowest rates
of virtually all psychological disorders, as compared to younger adults.
Older people report that they can control their emotions more
effectively, experience more mixed emotions, and feel negative emotions
for shorter durations. Even in the midst of cognitive decline, there
appears to be an improvement in the emotional system, at least in terms
of regulating emotion.

While emotion and cognition cannot be delineated clearly, emotion is
inherent in all cognitive functions as captured in the observation that
"categories exist because some objects and events matter and others
\[do\] not" (Zajonc, 1997). Of particular relevance to the psychology of
aging is the notion that, to the extent that the categories that matter
change with age, we may see systematic changes in cognitive processing
as a function of these motivational factors.

A number of empirical studies demonstrate how emotions may matter. In
one study, Carstensen presented two sets of advertisements that were
identical in terms of their graphic design but differed in terms of the
promises they made---i.e., one set focused on the future, acquiring new
knowledge, and on widening one's horizons, and the other focused on
emotional experiences in the present moment. Whereas the framing of the
ad made no difference for the younger adults, older people clearly
preferred the more emotional ads. They also were able to remember these
slogans better than the knowledge-related slogans and were more likely
to remember the products associated with emotional slogans (Fung &
Carstensen, 2003). In a subsequent experiment, the researchers asked old
and young subjects to imagine that they had just received a phone call
from their physician virtually ensuring them that they will live another
20 years in good health. Based upon this assumption, the groups were
again shown the advertisements; when subject to the new, time-expanded
condition, older subjects no longer significantly preferred the
emotional ads over the knowledge-related ads. Carstensen and her
colleagues concluded the following with regard to time horizons: When
time horizons are manipulated experimentally, preferences change
systematically. Younger people show preferences similar to older people
when time horizons are shortened and older people show preferences
similar to the young when time horizons are expanded. When natural
time-shortening occurrences such as personal illnesses, epidemics,
political upheavals, or terrorism prime endings, preferences of the
young come to resemble those of the old.

In a number of laboratory studies, Carstensen and her colleagues have
found evidence of a "positivity effect," i.e., preference for negative
information in attention and memory in youth shifts; at advanced ages
positive information is relatively accentuated. She noted that she does
not use the term positivity "bias," because the effect is driven as much
by younger people's preference for negative information as older adults'
preference for positive information. In several studies, accuracy is
found to be the same when comparing older and younger adults.

To test the positivity effect, Carstensen and her colleagues presented
subjects with visual stimuli that were positive, negative, and neutral,
and then asked them to recollect the images. Older people were more than
twice as likely to remember positive images over negative images and
they remembered even fewer of the neutral images. Young people
remembered more of the images and were equally likely to remember
negative and positive images. They were less likely to remember neutral
images. Middle-aged people remembered more of the positive images over
any other age group and remembered slightly fewer of the negative images
than the younger age group. Middle-aged people in the study also
remembered fewer of the neutral images than their younger counterparts.
The most common response among older people regarding how to deal with
negative emotional issues is to "just not think about it." Studies of
amygdala activity appear to confirm this phenomenon.

In a second study on selective attention, subjects were shown multiple
images (a pair of faces: one positive or negative, and one neutral) at
one time for a duration of one second. A dot then appeared over one of
the faces, and they were asked to identify over which of the faces the
dot appeared. Subjects were faster to respond if they were looking at
the image already when the dot appeared. Data from the study indicated
that older subjects were faster to respond when the dot was above the
positive faces rather than the negative faces, suggesting that older
people most often look toward the positive and away from the negative.

Carstensen then discussed affective working memory studies. Affective
working memory maintains a representation of an emotion in the absence
of the immediate elicitors to form goal-directed behavior. A recent
study examined affective working memory with negatively valenced
information compared to a brightness working memory task (Mikels &
Reuter-Lorenz, 2004). There is some reason to suspect that there may be
distinct neural subsystems underpinning affective working memory versus
working memory for other types of information. The study addressed the
question of whether affective working memory is better for positive
rather than negative information. In the study, participants see an
image; it disappears; there is a retention period; another image
appears; and then the participant is to report which image was the most
intensely negative. In the brightness study, photographs were shown that
varied in brightness. In each task, the participants were asked to hold
the feeling state and then make a comparison with the new information.
Older adults did not perform as well as younger adults on the brightness
trial; however, in the study that compared affective (emotional) images,
there was no main effect of age in working memory. What Carstensen found
more interesting was that in the valence condition, where pairs of
negative and positive images were compared, there was an absolute
advantage of older people over younger people in the positive trials,
while there was an absolute advantage of younger over older people in
the negative trials.

A recent study examined the positivity effect in autobiographical memory
by going back to an order of nuns who had completed an extensive
questionnaire 15 years earlier. In 1987, the School Sisters of St.
Francis completed a 26-page questionnaire about their physical, social,
and emotional lives. In 2002, they were re-contacted and asked to
complete the questionnaire again---"as you completed it in 1987." By the
time of the second questionnaire, the ages of the nuns ranged from 52 to
over 100 years. The researchers used a quasi-experimental design to see
if they could eliminate the positivity effect by having the participants
focus either on being accurate, or on how they felt while completing the
survey, or giving no instructions whatsoever. They embedded several
prompts throughout the questionnaire, reminding them to be as accurate
as possible or to pay attention to their feelings. Both older control
participants and participants who were focused on emotional states
showed a tendency to remember the past more positively than they
originally reported in 1987. In contrast, both younger control
participants and participants who were focused on accuracy tended to
remember the past more negatively than originally reported (Kennedy,
Mather & Carstensen 2004).

Carstensen then asked whether such findings have implications for
decisions about health care. Can you improve people's ability to make
decisions about healthcare plans based on their feelings about the plan?
She presented some preliminary data on a study she and her colleagues
have recently begun, asking participants to rely on their feelings to
choose among emotionally valenced health-related statements about two
options from four domains (i.e., health care plans, treatments, primary
care physicians, and home care aides) rather than attempt to remember
all of the information. The task goal was to choose between one of two
weighted alternatives; in each, one was a better option. There were two
between-subject conditions: a remember condition and an affective
condition. Subjects were asked to rate how well they remembered an
option (e.g., HealthNow) or how they felt about that option; then they
were asked to make a choice. Preliminary data from this study suggest
that older people perform better when they are updating how they feel
about the plan rather than focusing on what they remember about the
plan. What Carstensen found notable here is that the age effect
disappears in the condition where the participants focus on feeling.

The findings from these studies have a number of implications for
decision-making. There is suggestive evidence that older people are
deferring decisions that are emotionally charged. Researchers are
concerned that decisions could be influenced by biased recollections of
the past, favoring the positive---which can place older adults at a
disadvantage. In studies in which choice options are presented, older
people tend to look longer at positive, rather than negative, options.
If the emotional system is improving across adulthood and deliberate
cognitive processes are declining in efficiency, it remains an open
question whether older adults can and should be encouraged to rely upon
intuitive, emotional processes to improve their decision-making skills.

In the ensuing discussion, there was speculation that older adults may
recall more positive images simply because it takes longer to process
negative information (as in the dot probe experiment) rather than
because they selectively attend to the positive. Could it be that
negative images are deemed irrelevant or suppressed? According to Dr.
Mara Mather, imaging studies show more frontal and less amygdala
activation in older adults. Carstensen believes that there is something
deliberative about the behavior; that the more automatic the subjects'
attention, the more likely they are to see the dot.

The concept of time horizon and the manipulation of time horizon are
very important in economic policy. Yet, Dr. Michael Hurd observed, no
studies have been done yet to examine the effect of manipulation of time
horizon on spending and savings behavior. If consumption is required for
exploration of the world (the goal preference of younger adults) how do
we encourage savings behavior? Hurd noted that the finding that young
people generally do not plan to save is not a new trend, but a
historically accurate characteristic of younger adults. People in their
50s are better prepared financially than people in any other generation
and save at the highest rates.

Dr. Robert Willis was struck by the parallels of the psychological
models to the human capital theoretical framework that economists use.
An investment in new knowledge and learning provides competence that is
reflected in capital stock accumulation and rewarded in markets,
followed by declining investment rates. He suggested that it may be
worthwhile to look at the two models together.

Dr. Paul Slovic observed a widening of distribution in that some older
people do not decline much in terms of physical performance tasks, while
others decline rapidly. He noted that the subjects in the studies
discussed by Carstensen are relatively high-functioning and may have
greater ability with cognitive tasks too, which may color our sense of
the results. Carstensen stated that the higher-performing people show
the positivity effect more than the lower-performing people. While she
acknowledged that there were relatively high-functioning people in the
studies, the investigators were careful to recruit a mix of two-thirds
white collar and one-third blue collar with minority representation. No
class, race, or gender differences were found. There have been no gender
interactions by age in studies demonstrating the positivity effect.

Experimental economists cautioned that institutional effects can be
subtle; how do these affect factors such as emotional state and
perceptions of time? How does our environment influence how older adults
feel, and how can we create better environments where their lives may be
improved? For example, can rules about how you buy and sell in an
auction-like environment be designed better for the elderly? What kinds
of questions or simple tasks might be incorporated to identify changes
across the population and their influence on motivation? How does the
environment affect a person's perception of time, particularly with
respect to retirement decisions, health care decisions, and so on? It
also was noted that preferences change over time, but people need to
plan or make decisions about their old age at a younger age. One
suggestion for reconciling this was manipulation via a short time
horizon.

Another participant asked whether the positivity effect changes with
cognitive resource changes. Dr. David Laibson suggested that
interventions causing older adults to think emotionally might hinder
rather than help them, if, indeed, negative emotions get ignored in
calculations, resulting in problematic decisions and outcomes. The
decision to "go with your gut" is not always a good decision. Thus, it
may be better to look at other interventions that would undo the bias
about negative emotions.

**Robert W. Levenson, Ph.D., University of California at Berkeley**

***[Social Neuroscience, Psychophysiology, and Aging]{.mark} \[Link this
to Levenson.ppt\]***

Dr. Robert Levenson began by providing some background information on
emotion and the emotional response. A physiological emotional reaction
is brief, and can be observed when an antecedent event, such as loss,
matches a prototype and invokes an emotional response. To capture
emotional responses in the laboratory, Levenson has employed a number of
different techniques including having people relive emotional memories,
using emotionally evocative films to elicit response in people, asking
subjects to make emotional faces, and examining social interactions.

Levenson presented a videotape of one experiment, in which a subject
viewed a film of a person working in a woodshop who suffered a serious
accident (the antecedent event). The brevity of the emotional response
was evident in the facial expression of the subject. This short duration
distinguishes an emotional response from moods, emotional traits, or
emotional pathologies, as proposed by Paul Ekman (1986). The emotional
response occurs in waves rather than steady states, and it readily
crosses internal and external boundaries---many of the subject's
reactions occurred after the screen went blank. Stimulation inside the
system activates the emotional response a few seconds after the event
has passed. The psychophysiological approach provides evidence that
emotions are organized rather than chaotic. When we are in an emotional
state, facial behavior is correlated perfectly with peaks of emotion,
sweat gland activity, and heart rate.

Emotions are critically important in aging, helping to establish and
maintain social relationships, which are closely connected to health and
well-being. Emotion is intimately involved in critical psychological
processes that are impacted by age (e.g., memory, learning,
attention/perception), assuming an important role in late-life "wisdom,"
and is altered by many dementing disorders. Unlike many other areas of
human functioning, emotions do not show unrelenting decline with age.
Rather, many aspects of emotional functioning are relatively preserved
in healthy elders, and some aspects may even show improvement in late
life (e.g., use of positive emotion to regulate conflictive social
interaction). Emotional dysfunction is a prominent feature of many
dementing disorders, especially in those aspects that require monitoring
of self, others, and social situations.

There is evidence that older adults experience greater emotional control
(Lawton, et al., 1992); the same or greater well-being (Stacey & Gatz,
1991); greater emotional understanding (Labouvie-Vief, et al., 1989);
and greater emotional refinement (poignancy, reminiscence; Molinari &
Reichlin, 1984) -- all of which counters the "classic" view that old age
is a time of dampened emotionality. Older adults also experience more
sources of pleasure and fewer sources of conflict than their younger
counterparts. In addition, during marital studies on emotion in
problem-area discussions, older couples expressed more affection, while
middle-aged couples expressed more anger, belligerence, and whining.

[]{.mark}

Comparisons of emotional physiology between young (ages 18 through 30)
and old (ages 71 through 83) subjects showed reduced dynamic range in
heart beats per minute with age. Visceral sensations are lessened with
age, relaying fewer signals to react or respond quickly to a dangerous
or important occurrence. A question is whether age-related decisions
could be mediated by these kinds of reductions in visceral response. One
participant questioned the idea that there is less visceral input with
age because for older adults, there is the same percentage of dynamic
range in changing heart rate. Differences in visceral response by age
may be more important in novel contexts as opposed to more familiar
circumstances.

In one study, couples in long-term marriages, newlyweds, recent
divorcees, and pastoral counselors demonstrated greater accuracy in
judging the marital satisfaction and stability of ten couples discussing
a marital problem for 3 minutes than marital researchers and marital
therapists (Ebling & Levenson, 2003). Based on his observations from the
videos, Levenson surmised that the ability to use humor and affection in
discussing problems attenuates conflicts.

[]{.mark}

Levenson next discussed two social neuroscience approaches to studying
emotion and dementia: (1) the "activated brain" approach where brain
scans (e.g., fMRI, EEG, ERP, MEG) of normal subjects reveal regions of
brain activation; and (2) the "damaged brain" approach which enables
examination of behavior in an unconstrained way, usually of patients
with lesions or neurodegeneration, using conventional measures of
behavior, subjective experience, language, and peripheral physiology.
After pointing out the anatomical locations of social brain activity,
Levenson concluded that most action occurs in the fronto-temporal parts
of the brain. It is therefore of interest to understand their functions
by looking at the effects of frontotemporal lobar degeneration (FTLD).

In patients with FTLD, there is a rapid progression of tissue loss. As
the disease progresses, cognitive functioning is relatively preserved,
but patients begin changing emotionally. While they have emotions, they
show a loss of empathy and emotional understanding. Many are
misdiagnosed with depression. Patients with FTLD show a loss of
self-conscious emotion in which no secondary emotion, like embarrassment
or laughter after initial startle response, is observed. Attempts by
FTLD patients to regulate emotion (i.e., minimize or suppress a response
to an acoustic startle) results in an inappropriate response. Different
dementias have different effects on emotion. For example, unlike
patients with FTLD, Alzheimer's Disease patients appear to have intact
emotional processing and to demonstrate a sense of self. FTLD patients
cannot recruit the rational processes needed for making appropriate
decisions.

One participant observed that the relationships among the limbic system,
reward system, and the cortex and frontal lobe in terms of decision
making and pleasure are integrated systems. An interesting research
question is how these relationships might change with age. The
progression of an injury may alter relational systems, although the
change may be subtle. How an imprinted emotional memory, which is stored
differently than temporary memories, changes over time, is another
interesting question.

**Panel on Decision-Making and Aging**

**[Mara Mather, Ph.D]{.mark}., University of California at Santa Cruz
\[Link this to Mather.ppt\]**

Mather focused on aging and emotional goals and implications for risk
seeking. She echoed a theme from earlier presentations that as older
adults' time perspective shifts in old age, they focus more on emotional
goals and that compared with younger adults, older adults show a
positivity effect in attention and memory. Mather is interested in the
mechanism underlying these changes in older adults: Is the positivity
effect the result of goal-directed strategic processes, or is it a
serendipitous side effect of age-related decline? If older adults have
emotional goals, how is it that they will implement them in their
attention and memory? They need executive resources and cognitive
control; they need to be able to inhibit the things they want to inhibit
and selectively attend the positive. The paradox of this is that the
ability to exert executive control declines with age. Mather proposed
that older adults, who exhibit these effects, are likely to be those who
have the highest cognitive control of all groups and are best able to
implement their goals.

To test this hypothesis, Mather initiated two studies. In the first, two
groups of subjects were asked to watch pictures in a slideshow on a
computer screen. In giving one group a divided-attention task, Mather's
goal was to reduce access to cognitive resources, with the expectation
that doing so would attenuate the positivity effect. Under full
attention (the control condition), there was an age-by-valence
interaction. In the divided-attention group, for younger adults the
divided-attention task did not affect which valence was most memorable,
but the valence of older adults' memories appeared to be affected by the
availability of attentional resources (Mather & Knight, 2005).

The positivity effect actually reversed under reduced availability of
cognitive resources. In the study, dividing attention eliminated younger
adults' negativity effect, while nearly 70 percent of what the older
adults remembered consisted of negative pictures. This may be explained
by the idea of ironic processes and mental control, e.g., if people are
told not to think of white bears, they can do this fairly easily if
their minds are focused on doing so; but when distracted, thoughts of
white bears flood in (Wegner, 1994). Thus, there may be a cost if older
adults are trying to avoid the negative and they are not at that moment
able to implement the goal.

In a second study, Mather and her team used eye-tracking to study
patterns that occur in the moment when the information is encoded.
Subjects were shown pairs of pictures with different valences; e.g.,
negative and neutral images were shown in a block next to positive and
neutral faces. In younger adults, a negativity effect disappeared under
divided attention, which may indicate that younger adults have a goal of
focusing on the negative. This is consistent with previous findings,
based on younger adults, of a perception that "bad" is stronger than
"good" (Baumeister, Bratslavsky, Fickenauer & Vohs, 2001). Older adults
followed the same pattern as in the first study: there was an increased
negativity effect with divided attention. Mather concluded that even
though the first fixation for all age groups is on the emotional picture
(with an attention preference on pictures that represent threat), older
adults use their subsequent attention for different purposes than
younger adults because they have different goals. She contended that the
positivity effect in attention and memory among older adults is the
result of strategic processes.

Mather then discussed potential implications of goal-directed emotion
regulation processes on risky decisions. Previous laboratory studies
reveal few consistent age differences. There is limited evidence of
increased risk aversion on the Iowa Gambling Task (Denberg, et al.,
2001; MacPherson, et al., 2002; Sanfey, et al., 2003; Wood, et al.,
2005). However, one consistent finding is an increase in decision
avoidance (Mather, 2006). Older adults prefer not to make difficult
decisions themselves, and their problem-solving strategies tend to be
more avoidant than those of younger adults.

For most choices, regret or satisfaction with the outcome is where the
emotional action is. Regret is largely determined by the counterfactuals
that are most likely to come to mind. When forecasting future emotions,
sure-thing options provide the most concrete counterfactual. Thus, a
focus on avoiding regret should lead older adults to favor alternatives
with known positive outcomes over alternatives with uncertain positive
or negative outcomes. When presented with "sure-thing" and risky options
with similar expected values, older subjects generally preferred the
sure-thing option, which is consistent with older adults' use of
cognitive resources for emotion regulation purposes in their attention
and memory. This emotion regulation focus may also influence decision
search, variety seeking, and memory for decisions (e.g., Mather &
Johnson, 2000; Mather, Knight, & McCaffrey, 2005). Mather posed three
questions for further study: (1) Can older adults' tendency to choose
the sure-thing option be explained by the affect heuristic or emotion
regulation? (2) How might this tendency affect loss aversion? And (3)
How do age changes relate to changes in the brain? One point of
discussion involved the definition of a goal and the widely held belief
that individuals have subconscious goals.

**[Paul Slovic, Ph.D.]{.mark}, and Ellen Peters, Ph.D., University of
Oregon \[Link this to Slovic.ppt\]**

Dr. Paul Slovic identified three categories of characteristics affecting
decision-making competence, drawn from the Person-Task Fit Framework by
Finucane and Lees (2005): task, decision-maker, and context. Slovic
focused on just a few of these characteristics: framing (task
characteristic); speed of processing, age, and numeracy (decision-maker
characteristics); decision support (context characteristic); and
comprehension and affective fluency (decision-making competence).

According to the Comprehension Index (Hibbard, et al., 2001; Finucane,
et al., 2002), which reflects the number of errors made out of 35
decision tasks involving interpretation of tables and graphs,
comprehension errors increase with age, and there is a high percentage
of error (especially above age 80) among the elderly even for acquiring
information. This finding suggests the need to address the fact that a
high percentage of older patients will not be able to comprehend
information presented in graphical or tabular format. The range of
decision making competence increases with age, making individual
differences particularly important in older adults.

Slovic emphasized Montague's theory of a common internal currency to
assess the relative value of events, like drinking water versus
searching for predators (Montague & Berns, 2002). Recent work has shown
that fluctuations in the delivery of the neurotransmitter dopamine may
represent one such common currency. The dopamine system is well designed
to handle the kinds of decisions that an early human would have
encountered; however, it is grossly inadequate in many situations, such
as drug-abuse situations, that have arisen in modern society.

At the psychological level, the "common currency" may be affect, a
valenced feeling (e.g., goodness or badness) associated with a stimulus.
Although it may be very faint, it can strongly influence behavior. There
are at least four functions of affect: It acts as a common currency, it
acts as information, it acts as a spotlight, and it acts as a motivator
of action. The meaning of information is closely linked with affective
response. Affect conveys meaning upon information, and without affect,
information lacks meaning and will not be used in judgment and
decision-making. Affect is a key ingredient of rational behavior; it
also sometimes leads to poor decision-making.

Slovic next discussed Epstein's (1994) two modes of thinking associated
respectively with the experiential and analytic systems. Reliance on
feelings appears to increase with innumeracy, cognitive load, stress,
older age, and affect-rich outcomes and images. Affective information
may become more important as we age, according to Carstensen's
Socioemotional Selectivity Theory (1992) and Labouvie-Vief's Dynamic
Integration Theory (2003), which hold that age-related cognitive
limitations cause a shift and that there is an increase in disruptions
from emotionally arousing stimuli, particularly to less
resource-demanding positive information. Affect has been linked to such
activities as evaluating gambles, travel destination preferences, risk
perception, and marketing.

A study on affect, evaluability, and attractiveness of simple gambles
underscores the importance of contextual factors in determining affect
and preference and that meaning, utility, and weighting of even very
familiar and "well-understood" monetary outcomes is not fixed, but
depends greatly on contextual factors, e.g., whether the probability or
the payoff are evaluable.

With respect to numeracy, the ability to understand and use basic
probability and mathematical concepts, studies have found that lower
numeracy is linked with lower comprehension, greater framing effects in
decisions, greater influence of direct (and irrelevant) sources of
affect and emotion in decisions, and the drawing of less meaning from
numbers. The ability to understand numbers influences the precision of
feelings about probabilistic information, the extent to which irrelevant
affect influences choices, the accessibility and influence of nonsalient
frames of the same number, and the degree to which affect is elicited
through a comparison of numbers.

For example, both younger and older people with less ability to
understand numbers, respond differently to the likelihood of an adverse
event expressed as a relative frequency (e.g. "1 out of 100") and the
likelihood expressed as a probability (e.g. a 1 percent chance). The
frequency representation seems riskier to them, perhaps because it
promotes imagery of "the one\...." In contrast, highly numerate people
do not respond differently to the two frames, perhaps because they
translate effortlessly between them.

Judgment and decision skills can be improved by restructuring the task
or environment to correct known biases. Illustrating his point with
examples of visual illusions, Slovic emphasized that perception, as good
as it is, sometimes goes wrong. Decision aids such as coding affect in
information displays may help older adults process information more
effectively; for example, affective categories add meaning to a complex
data display such as a table showing patient satisfaction with doctor
communication. In this example, affective categories influenced choices,
whereas a table with only category lines did not, showing that
highlighting affective elements can help the elderly interpret
information. Participants slower in speed of processing were helped more
by the affective coding on the categories.

Slovic concluded by raising numerous directions for behavioral and
neuroscience researchers to pursue collaboratively. These included
whether neurological techniques can be applied to study evaluability;
the brain response to "10 percent" versus "10 out of 100"; and more
generally, analytic versus affective processes in the brain. How does
brain activity differ in high- versus low-numerate people as they make
judgments and decisions? Some challenges to this area of study include
the need for repetition in fMRI studies and complexities of sampling in
studies of older adults.

From an economic standpoint, Willis observed that the decision reflects
personal preference and the rate could be construed as evidence of what
that probability might be, and so people who are highly numerate seem to
be adept at converting evidence into meaningful pieces for decision
making. For the low numerate, there appears to be more of a
disconnect---in these cases, affect seems to be driving numeracy (or
vice versa). Numeracy may not be the correct label; something else may
be occurring. It also was observed that the notion of affect may play
into some recent neural mechanisms used to describe choice.

Laibson commented that in economics, research methodology requires
consistency and compatibility between incentives and behavior. He
emphasized the need for real incentives and for ensuring that incentives
are introduced at the correct points in the study, and that incentives
are truly motivating risk-averse as opposed to risk-seeking behavior.

**Timothy Salthouse, Ph.D., University of Virginia**

***[Cognitive Research on Aging]{.mark} \[Link this to Salthouse
SHORT.ppt\]***

In his presentation, Dr. Timothy Salthouse intended to achieve two
goals: (1) to provide a brief summary of what is currently known about
the relation between age and cognitive functioning; and (2) to describe
a research strategy designed to ensure cumulative progress by
investigating age differences in new variables and constructs, such as
those concerned with economic decision-making, in the context of what
already has been established. He began by highlighting some of the
common assumptions about aging that have proven to be misperceptions:
That aging primarily affects memory; that only small effects are
observed; that these effects are observed only in some people; and that
they are not longitudinal but cross-sectional. He then proceeded to
address each assumption in turn.

Regarding age effects on memory, Salthouse showed data on a variety of
cognitive tests that were administered in different ways representing
different cognitive abilities (four tasks measured memory/recall of a
removed past experience; matrix reasoning; spatial visualization; and
perceptual speed). Age-related declines in each of the four types of
tests indicate that age affects not just memory. He added that
age-related declines in cognitive abilities do not occur only late in
life. With a large enough sample, a decline in performance on such
variables as speed and vocabulary already can be seen between ages 20
and 25.

It is not only small effects in age declines that are observed.
Nationally representative samples for norms, Wexler studies, and
Woodcock-Johnson tests all show the same downward trends with age in
cross-sectional comparisons. In addition, data on cognitive abilities in
people showed the same slope of decline from ages 8 to 18 as from ages
18 to 80. The annual declines in cognitive functioning are on par with
other age-related physiological changes. In addition, age-related
declines do not occur only for some people; Salthouse presented parallel
age-related declines at all regions of the distribution for both low and
high functioning populations. Declines in cognitive functioning also is
not limited to people but is seen in animal models---with increased age,
more difficulty is observed in terms of classical conditioning of
eyeblinks in rabbits, water maze learning in mice, and learning without
errors by dogs.

Age-related declines beginning in early adulthood are not just
cross-sectional as longitudinal changes are observed. Salthouse noted
that maturation and retest effects confound longitudinal studies;
confounding may be prevented with variable retest intervals and multiple
retests.

Different perspectives on the localization of age-related decline focus
on the neuroanatomical region, processing stages, and organizational
structure of abilities. Salthouse has been researching this latter
perspective for the past 2 years. Almost all cognitive abilities are
positively correlated with one another, so variables can be organized
into a hierarchical structure of first- and second-order abilities
(second-order latent constructs).

According to Salthouse, at least four separate types of possible causal
mechanisms should be examined to explain age-related changes: (1) the
common factor is a prefrontally mediated mechanism, perhaps related to a
decrease in synchronization of neural signals or imbalance of
neurotransmitters (e.g., dopamine-modulating signals); (2) improvement
in vocabulary performance with age could be caused by increased
experience and exposure to opportunities for new information; (3) speed
performance, which may be related to efficiency of communication between
different regions of the brain, degeneration of myelin, and/or impaired
neural connectivity; and (4) memory performance is affected by the
degradation of medial-temporal lobe and connecting circuits in the
brain. The methodology of reducing the numbers of statistically unique
influences enables researchers to be more parsimonious in developing
explanations. True explanations should address why age-related effects
happen and what the mechanisms are by which they operate. Salthouse
proposed that a true cause of age-related cognitive change should alter
the developmental trajectory of age-related cognitive change. Aging
studies should be conducted over an extended time period. Although this
is best studied through intervention, reliance on statistical mediation
is often necessary to see a pattern over time.

Almost 100 years of research has been conducted on age and cognitive
functioning; Salthouse stressed that it is important to ensure
cumulative progress in order to move forward. We can establish
cumulative progress by studying each new variable in the context of what
is already known. Age affects the target variable, but it also is
apparent that vocabulary, reasoning, and other factors have effects as
well. With reference constructs, we can determine how much of the
age-related effects are total and how much of the effect on the target
variable is unique and statistically independent. If we do not ensure
cumulative progress in the way described, Salthouse posits that we
simply are using different labels to describe the same phenomena.

In the discussion that followed, a participant asked whether the
variable components would be weighted differently when examining the
features of systems of abilities that matter in terms of economic
outcomes versus health outcomes. For example, whether some abilities are
more important for financial success remains to be studied. Another
participant commented that when engaging in a decision-making task, many
processes work separately but in parallel; however, they may share
common causes. While there are shared influences, the cause of the
influences is still ambiguous.

It was reiterated that older adults build on a large database of
experiences in which a current experience is likened to another one,
resulting in a generalized ability to draw from experience to make
decisions. This is relevant for a great many economic behaviors.
Questions for further study include whether experience can be measured
and the extent to which experience overlaps with professional expertise.

**Scott Huettel, Ph.D., Duke University**

***[Neuroimaging the Aging Brain: Methodological Insights from Cognitive
Neuroscience]{.mark} \[Link to Huettel_NIA.ppt\]***

Neuroimaging techniques have become increasingly critical for the study
of brain structure and function. Over the past few years, there has been
increasing interest in using these techniques---and in particular
fMRI---for studying the brain changes accompanying normal aging.
However, the simple translation of experimental methods from young to
elderly subjects poses challenges for researchers. Because several
neuroimaging techniques (e.g., fMRI and Positron Emission Tomography)
assess concentrations of metabolites delivered through the vascular
system, any age-related differences in vascular properties have the
potential to influence neuroimaging data. It is important to consider
the implications of this and related problems for the study of aging,
and it is especially important to distinguish age-related changes in
neuroimaging measurement from age-related changes in underlying brain
function.

[Methodological and Structural Changes]{.underline}

The fMRI Blood-Oxygenation-Level-Dependent (BOLD) hemodynamic response
originates in the neuron, where it is predicted by dendritic activity.
Under normal conditions, there is a constant extraction of oxygen from
red blood vessels, but when neurons are active, there is a surplus of
oxygenated hemoglobin to that part of the brain, resulting in a decrease
in the local concentration of deoxygenated hemoglobin. Because
deoxygenated hemoglobin suppresses some forms of MRI signal, one can use
MRI to measure changes in the concentration of deoxygenated hemoglobin
and, in turn, brain function (fMRI).

Age-related structural changes in the cerebrovascular system may have
functional consequences. These changes include thickening of vessel
walls, hypertension, venous occlusions, changes in capillary structure,
reduced blood flow, and reduced oxygen consumption. Studies have found
that these structural changes probably do not influence the fMRI BOLD
signal or BOLD refractory effects, while they do influence BOLD
signal-to-noise ratio (SNR). Two studies have reported that younger
adults have a better SNR than older adults, suggesting that age-related
differences in brain activation may reflect differences in SNR, not
cognition. It also was noted that head motion may have been a factor in
the results; older adults tend to experience more head motion during
imaging. To address problems for between-group comparisons, Huettel
suggested Group by Condition testing and the use of parametric
manipulations; if similar effects of the behavioral parameter are seen
in both groups, one can have more confidence in the results.

Different brain regions show different patterns of lifespan change in
brain volume; that is, not all regions show a decline. The frontal lobes
exhibit a consistent gradual decline, the hippocampus shows a sharp
decline after middle age, but visual cortex volume remains relatively
constant. Huettel noted that white matter can be measured using a
relatively new technique called diffusion tensor imaging (DTI). There is
a decrease in white matter integrity as people age; this is significant
because the integrity of white matter tracts often mediates performance.

Logistical issues that account for differences in experimental
procedures with the elderly include reduced tolerance for time in the
scanner (older adults generally tolerate sessions of 60 to 75 minutes in
the scanner, whereas younger adults tolerate sessions of 75 to 90
minutes); more extensive head motion; reduced sensory abilities
(difficulty attending to stimuli or processing it at a low level);
reduced performance on many cognitive tasks; a biased subject sample
(the typical elderly adult in studies discussed by Huettel is college
educated, has no significant health problems, is taking only minimal
medication, and has a college level vocabulary); and a different
motivation for participating---financial incentives are not as important
to the majority of older participants, who are motivated by the sense
that they are advancing scientific knowledge.

[Functional Changes]{.underline}

Huettel next discussed functional changes and the concept of selective
versus non-selective deficits in brain function. Some brain responses
change selectively, while others change in a more graded way. A second
theme is the idea of functional compensation, in which a lack of
behavioral changes in the elderly may be the result of changes in the
underlying process. An example of selective deficits in a memory study
shows that some areas of the brain improve with age and others do not;
the elderly showed attenuation of recollection-based activation in the
hippocampus but enhancement of familiarity-based activation in the
rhinal cortex. In contrast, in other systems where there are
non-selective deficits, there is less extensive brain activation in
older adults. Imaging studies show that in tasks involving memory and
attention, some elderly adults rely on compensatory strategies to
recruit the assistance of additional brain regions to maintain
performance; in one study (Cabeza et al., 2002), high-performing older
subjects show bilateral prefrontal brain activity, while low performers
show activity only on one side. In tasks involving executive control,
younger subjects recruit the prefrontal cortex, while older subjects
recruit other regions, such as the thalamus and basal ganglia, which may
reflect impaired functioning of the prefrontal cortex in this group. A
number of methodological caveats were raised regarding compensation
effects reported in the literature. Outcomes are dependent on the
significance thresholds used for reporting brain activity; depending on
where these thresholds are set (and there is no universal standard)
older and younger adults may look more or less similar (Cabeza, 2002).
Importantly in the context of this meeting, very little is known about
the brain correlates of selective deficits and compensation in reward
systems. The extent to which compensation may be present in reward
systems in aging is a promising area for study, especially since the
techniques and methodology are available.

During the discussion that followed, Dr. Brian Knutson observed that new
developments in imaging have changed the field considerably, with
unprecedented depth of neuroimage resolution on a second-to-second
basis. Whereas 10 years ago subcortical areas could not be seen, today
there is a coherent accumulation of knowledge about what brain areas to
observe when subjects are making decisions. Now it is time for
application with older adults. The "super elderly" is not an
unreasonable place to start as they may provide a benchmark for
comparing with other groups that may exhibit functional deficiencies.

Because of some of the technical difficulties with imaging and older
adults (e.g., tolerance for and immobilization in scanner), participants
were interested in approaches that can be applied to facilitate study of
older subjects. To obtain an adequate imaging signal, an experiment must
be repeated several times, raising questions about brain activation to
activities that cannot be repeated, such as one-shot economic exchanges.
Knutson stated the possibility of breaking research questions into
subgroups so that new knowledge can be obtained in a systematic way.
Care also should be exercised not to draw conclusions prematurely;
others emphasized the importance of reporting observed relations between
activation across different areas of the brain.

Participants discussed the problem of individual differences. In
addition to vascular differences, there are tissue composition
differences that likely have effects on individual differences.
Discussion revealed that more knowledge is needed about differences in
neurotransmitters or variation of firing rates in relation to brain
efficiency.

Other suggestions for further study included comparing people who have
done well vs. poorly economically and examining brain activity for
monetary incentive tasks. It would be helpful to know if no precise
variable is found that differentiates these groups. It also would be of
value to measure impulsivity versus conscientiousness, and the effect of
education on the brain.

**Alan M. Garber, M.D., Ph.D., Stanford University**

***[Decision Challenges in Health Care]{.mark} \[Link to Garber.ppt\]***

Older Americans face several difficult health-related decisions that
impose cognitive and emotional burdens. Among them are the selection of
high-quality health care providers, choices of specific medical
treatments, decisions regarding the aggressiveness of end-of-life care,
and selection of health plans (supplemental insurance, Medicare Part D
drug plans). Because there is no perfect treatment for any given
condition, the costs, benefits, and side effects of each must be weighed
against the others. A patient's decision whether to undergo surgery, for
example, is not driven solely by medical considerations and hence
subject primarily to expert physician judgment, but also by patient
preferences, so patient decision making cannot be entirely delegated.

In his presentation, Dr. Alan Garber briefly described projects on
health decisions being performed by the Stanford's Roybal Center, the
Center on Advancing Decision Making in Aging, which provides seed
funding for relatively junior investigators; and related NIA-supported
research at Stanford University. Current projects include efforts to
incorporate health preferences of older adults into the electronic
medical record by integrating a decision tool to guide patient choice
(Amar Das); work in affective forecasting and decision-making in older
adults (Knutson); research on age differences in the processing of
health care information (Joseph Mikels); and a study on age differences
in emotional and cognitive decision-making (Ian Gotlib and Elaine R.
Robertson). Of particular interest to this workshop is a project on
risk-taking and financial decision-making in older adults being
undertaken by Knutson, Gregory Larkin, and Camelia Kuhnen.

One of Garber's projects concerns both the personal and policy tradeoffs
in Medicare coverage of different forms of care for serious illness,
ranging from aggressive intensive care to "comfort" or palliative care.
As part of this project, the Stanford group conducted a pilot study
about cancer treatments, which are often expensive and toxic. The
greatest expense of Medicare is in aggressive care. The researchers were
interested in whether patients would want very aggressive care for
terminal cancer, and whether they thought Medicare should pay for it.
The goal of the study was to provide pilot data on individuals' basic
preferences for medical treatments at the end of life under a common
scenario, and their opinions on whether Medicare coverage ought to be
available for these services, regardless of their own preferences.
Subjects were Stanford alumni ranging in age from 20 to 87 years. They
were given the following scenario: "Imagine that you have just received
a diagnosis of pancreatic cancer, a serious life-threatening disease
that can cause considerable discomfort and is difficult to treat. Your
doctor tells you that without treatment it is unlikely that you will
survive for more than a year." They were then asked to answer questions
about four possible treatment options. Option 1 was a relatively new and
untested treatment that would take 1 year to administer, is relatively
painless, but has unknown side effects. Option 2 involved a traditional
combination of chemotherapy and radiation therapy that would take 1 year
to administer and has very uncomfortable side effects. Option 3 focused
on comfort, including treatment of pain and discomfort, hospice care,
and support for patients and their loved ones in managing their
households and helping them stay in their homes as long as possible.
Option 4 was hospital intensive care with life support at the end of
life.

Subjects were asked how likely they were to want each option, and how
strongly they felt that Medicare should cover each option. Different
versions of the questionnaire were framed in terms of short versus long
time perspective (number of additional years treatment might give the
subject \[1 or 10 years\]), the life-or-death frame ("prolong your life"
or "delay your death"), and the chance that the treatment would work
("relatively low" or "good").

Participants questioned whether framing in the context of other people
versus the self would result in a different answer, and whether people
are fully aware of what they are receiving for the cost of treatment.
The meaningfulness of data depends on giving subjects benefit
information about outcomes and efficacy in the framing of the questions.
The outcome in all cases is death from pancreatic cancer, and the
questions were designed to assess basic preferences for how one
preferred to approach that ending, from a medical care perspective, as
well as whether one felt that Medicare ought to make the other options
available for those who preferred them.

In terms of study outcomes, Garber reported that middle-aged respondents
were more likely to want the new treatment particularly when chances of
success were good, whereas older adults did not show this change in
preference. Age and framing of questions did not influence whether
respondents wanted Medicare to pay for the new treatment. Middle aged
respondents were also more likely to want the traditional treatment than
other age groups, while this option was less preferred overall. Of
interest was that more people wanted this option available through
Medicare even when they did not want the treatment for themselves. The
majority of subjects in each age group wanted comfort care, with this
preference strongest among those for whom treatment options were
presented as having a low chance of success. An even larger proportion
in each age group wanted comfort care services covered under Medicare.
Younger respondents were more likely to want intensive care services
than older age groups, with a significant decline in this preference
across cohorts. A similar age-related decline was evident in opinions
about whether intensive care services should be covered by Medicare,
with only 39 percent of the oldest group endorsing this view, compared
to 51 percent and 61 percent in the middle- and younger aged groups,
respectively. If the individual questionnaire framed treatments as
"delaying death," rather than "prolonging life," intensive care services
were preferred, a sort of inverse negative framing effect. It was
pointed out that this would be an example of a reduction of a loss, in
which case the preference does not agree with earlier theories of risk
aversion in the elderly, however, the possible negative connotation of
the term "prolonging" may have biased the results against the life
frame.

Subjects also indicated their preference for type of Medicare plan;
Garber described this process as a crude way of determining what people
think the plan design should look like. The majority in all groups
wanted a plan focusing on comfort and quality of life, while the
percentage of those wanting a focus on hospital and treatment services
regardless of life expectancy and quality-of -life concerns was much
less, especially in the older adult group (only 11 percent). The second
plan was meant to be similar to a traditional Medicare plan, where
patients could receive unlimited aggressive care but with no guarantee
that it would work. According to a *Wall Street Journal* poll,
more-educated respondents would consider costs more in health care
treatment decisions than would less-educated respondents.

In the final part of his presentation, Garber gave a "tour" of the
Medicare Web site (<http://www.medicare.gov/>) to demonstrate the
complex, cognitively burdensome decision tasks involved in the selection
of Medicare Part D drug plans. While people can compare numerous drug
plans (48 for the area near Stanford) on the Web site, the prescription
search function, which calculates how much out-of-pocket one would pay
in a year under different plans, only recognizes brand names of drugs,
not their chemical or generic names. When four common prescription drugs
were entered for a hypothetical patient, the total costs under plans
presented as options were high, ranging from \$1,500 to \$5,000 per
year. The goal of the comparison is to help patients make a choice based
on risk, yet the Web site does not provide any modeling of scenarios,
such as the need to change drugs or the development of a new illness.

During the discussion period, the point was made that the insurance
component is relatively low and that what is really at risk is the
patient's cost for the current year. A patient can always re-enroll in a
different plan the following year. Other research suggests that once
patients are enrolled in a plan, it takes a major event to change plans.
It also was noted that if health care consumers were perfect at
estimating costs, the insurance industry would not be viable since
insurance models are based on probabilities of covered events.

One participant observed that the cost information on the Medicare Web
site is presented in a way that requires some side calculations and that
the estimated annual cost is actually more than it initially appears.
Several participants observed that as they had not noticed this, it is
likely that people who are cognitively impaired would be even less
likely to notice this. Some felt that there are too many options, with
many drug plans without name recognition in comparison to more
well-known entities like the American Association of Retired Persons and
recognized insurers. People often are not aware that many of the plans
are offered by the same insurer.

Willis suggested that it might be beneficial to study a health care plan
scenario where drugs for temporary illnesses were priced with subsidies
and long-term use drugs for chronic conditions are offered at market
prices, which could attract consumers who would use the drugs briefly
and drive away others with chronic illnesses.

In conclusion, Garber stated that choices facing older Americans are
likely to become more complex and more consequential, and it is
increasingly important to improve the way that choices are framed to
enable older people to make better decisions. When dealing with
uncertainty, it is difficult to determine whether a choice is optimal or
even successful. The Medicare Part D plan will steer people toward a
default option because the preference of older adults often is to stay
put and avoid making active choices in the face of complex decisions.
Because the entity that controls the presentation of information has
such a strong influence on the decisions, it is important to consider as
well who should be allowed to play that role.

**Retirement Economics and Aging**

**David Laibson, Ph.D., Harvard University**

***[Neuroeconomics and Savings]{.mark} \[Link to Laibson.ppt\]***

Laibson discussed intertemporal decisions which play a central role in
lifecycle planning. Such decision-making is affected by a preference for
instant gratification. Recent research in neuroeconomics has identified
the neural foundations of taste for instant gratification. Intertemporal
choice models that incorporate this preference explain a wide range of
behaviors, including procrastination, passivity, and undersaving.
Results from a number of experiments suggest that people typically
choose instant gratification in the present moment, but when choosing
for the future, they show patience and select the healthier,
normatively-recommended choice (Read & van Leeuwen, 1998; Read,
Loewenstein, & Kalyanaraman, 1999).

The discounted utility function, which weights current utility flows
more than future utility flows, reflects what economists call dynamic
inconsistency. When a consumption opportunity is far away in time,
consumers make patient choices, but these patient preferences reverse
when the time for consumption actually arrives (i.e., preferences held
at date *t* do not agree with preferences held at date *t*+1). For
example, Akerlof's model of procrastination (1991) suggests that a plan
to exercise tomorrow is a very attractive option because the effort cost
of exercise is postponed into the future. Of course, perpetually
planning to exercise tomorrow will not produce the desired outcome.
Similar self-defeating behaviors are common, such as failing to make a
401(k) contribution or failing to stick to a plan of healthy eating.

A 2004 study (Choi, et al.) studied an active-decision enrollment system
for 401(k) participation. Upon employment, employees were required to
indicate whether they wanted or did not want to participate in the
savings plan; being passive was not an option. This resulted in a marked
increase in the participation rate, raising participation rates to 70
percent (from 40 percent). Madrian and Shea (2001) showed that automatic
enrollment -- with an opt-out option -- also generates high levels of
401(k) participation. However, typical automatic enrollment systems have
a low default savings rate of 2-3 percent of income. Participants
overwhelmingly stay at the automatic enrollment default, even though the
rate is not optimal. These findings argue for the imposition of
deadlines to eliminate passivity or the adoption of automatic enrollment
defaults with high savings rate.

Unsuccessful "solutions" to savings problems have included (1) paying
employees to save in the form of employer matches and (2) financial
education, which does not appear to be effective on its own. Choi,
Laibson, and Madrian (2004) found that in a sample of seven companies,
an average of half of employees over 59.5 years old were not fully
exploiting their employer match, indicating an average loss of 1.6
percent of their salaries per year.

The effects of financial education are also disappointing, Employees who
attend financial education seminar have good intentions to change their
401(k) savings behavior, but most do not follow through. Consistent with
this finding, the effect of scandals such as those at Enron and Worldcom
do not induce net sales of employer stock at other companies.

Laibson discussed the underlying mechanisms that drive these phenomena.
Why are preferences inconsistent? Is the mechanism adaptive, and how
should it be modeled? Does it arise from a single time-preference
mechanism, or is it the result of the interaction of multiple systems?
Examinations of the analytic and emotional brain in an fMRI study
indicate that time-discounting reflects the combined influence of two
neural systems: The limbic and the fronto-parietal systems. These two
systems are implicated separately in "emotional" and "analytic" brain
processes, respectively. The limbic (emotional) brain does not value
delayed rewards but creates a drive for instant gratification.

The agenda for future research should include age variation and how it
can affect factors such as limbic drive, cortical control, learning and
memory, and analytic cognition. Laibson presented a final example from a
study of credit card "teaser" rates, showing how quickly different age
groups learn how to exploit a complicated teaser rate offer. "Naïves"
never seemed to learn how to avoid paying too much, while
"sophisticates" learned immediately how to exploit the offer. People in
midlife were the most successful in exploiting the credit card offer. It
took longer for young adults to figure out what to do, Older adults were
particularly vulnerable to making mistakes. One of the real challenges
that lies ahead, Laibson contended, is to build a world that offers more
protection against the bad financial offers that older adults receive.

In reaction to Laibson's presentation, workshop participants commented
that many important financial incentives such as 401(k) and health care
savings accounts are surprisingly underutilized by people who are not
unsophisticated and who range in age. This may have to do with the way
in which the information about these incentives is presented.

**Robert Willis, Ph.D., University of Michigan**

***[The Health and Retirement Study]{.mark} \[Link to Willis.ppt\]***

Dr. Robert Willis sought to introduce psychologists and neuroscientists
to the Health and Retirement Study (HRS) and to discuss features of the
survey and findings from it that would be of particular interest to
these scientific communities. After providing some background on the
history, general purposes, overall design, and scientific productivity
of the HRS, he reviewed the core content areas of the HRS, its
evolution, and its steady-state design. The original HRS cohort was
interviewed first in 1992 and included persons ages 51 to 61 at the time
(born between 1931 and 1941), as well as spouses of age-eligible
persons, with a longitudinal followup every 2 years. In 1998, a redesign
merged the HRS with an older cohort of persons age 70+ in 1993 into a
single study and added new cohorts to effect a steady state design. In
2004, the HRS was awarded additional funds from the Social Security
Administration to conduct most interviews in person, which made the
inclusion of performance measures possible. Today, cognitive issues and
cognitive measures are playing an increasingly larger role in the study.
Comparable studies inspired by the HRS have been developed in 17
countries in Europe and Asia. These include the English Longitudinal
Study of Ageing (ELSA); the Survey of Health, Ageing, and Retirement in
Europe (SHARE); the Mexican Health and Aging Study (MHAS); and the
Korean Longitudinal Study of Aging (KLoSA). Japan and China may be next
to develop similar studies.

One important supplement of the HRS, which began in 2001, is an in-home
substudy of dementia. The Aging, Demographics, and Memory Study (ADAMS)
uses a stratified random sample based on survey measures of the risk of
dementia involving three groups: (1) Those with high probability; (2)
those for whom dementia is less certain; and (3) those who are
apparently normal. The dementia assessment is conducted through case
conference by an expert research group at Duke University that is
familiar with these types of assessments. The sample population in ADAMS
is very different than a typical clinic population, being usually 8 or
10 years younger.

New directions for the HRS include the addition of biomarkers that are
major and multi-dimensional predictors of disease, death, and
dysfunction; performance measures such as grip strength, timed walk,
lung capacity, and blood pressure; a new psychosocial module; and new
cognitive measures beginning in the HRS 2006 core survey, such as a
repeat of the adaptive number series test given in 2004 with the
addition of vocabulary and prospective memory measures.

International data on retirement trends and the influence of policy on
these trends were discussed, and new data on retirement expectations
from the HRS were presented. The long-term trend in the United States
from 1850 to 1990 has been toward earlier retirement, but the trend
toward lower labor-force participation at older ages is much sharper in
a number of European countries than in the United States. International
trends toward earlier retirement are related to incentives, as
retirement policy shapes retirement behavior. The HRS has pioneered
surveys about expectations on a wide variety of topics including
survival to a given age, bequests, stock market returns, and work and
retirement expectations. Researchers have used the work expectation
questions in earlier waves and have found them to be useful predictors
of actual work and retirement in later waves. There are signs of
reversal of the long-term trend toward early retirement seen from the
1850s through the mid-1980s; labor-force participation at older ages has
been flat since then, and the "early boomer" cohort in the HRS (born
1948 through 1953) expects to work more than earlier cohorts.

Willis also presented research findings based on HRS data that show a
strong correlation between health and wealth. A study on the economic
consequences of a husband's death shows that widows are most subject to
poverty, especially if they are widowed early. A study on predicted
wealth based on the dynamic optimization model (adapting savings
optimally throughout time) versus actual wealth shows that most people
have more net worth than is "optimal" and that retirement savings are in
fact adequate.

Finally, Willis described how the HRS is monitoring the new Medicare
Prescription Drug program using a 2005 mail survey, the 2006 core
survey, and planned future surveys. One mail survey conducted in the
fall of 2005 asked respondents about their knowledge of Medicare Part D,
how they were obtaining their information, and so on. An Internet panel
in November 2006 during open enrollment will help design questions for
people over age 65 who have experience with Medicare Part D and those
under age 65 who have helped their parents or others make decisions
about Part D. Findings from the 2005 survey suggest that the cognitive
burden required to take advantage of Medicare Part D is related
inversely to the cognitive capacity of eligible beneficiaries.

**General Discussion**

The issue of incentives for subject participation in neuroeconomics
research was discussed. It was noted that incentives and rewards are
forms of economic institutions, so perhaps it would be valuable for
exploring the relationship between behavior and incentive structures in
behavioral economic tasks. Some felt that equal payments to all subjects
would not be as effective as offering different incentives based on
performance.

The idea that older adults learn to master emotions by avoiding negative
experiences generated further discussion. Levenson and Mather speculated
that someone who avoids negative situations also will avoid risky
choices or decisions altogether in cases where there is potential for a
negative outcome. One participant described this behavior as quite
rational, since avoidance in such cases may represent the best
regulatory strategy for emotion. With non-confrontation the problem does
not completely disappear, but many things do improve with avoidance,
especially social situations. Another reason why the elderly often avoid
making decisions on financial offers altogether is perhaps that they
understand that they are not able to distinguish a good offer from a bad
one, and avoidance may be the process by which older adults control for
deficits in comprehension.

Additional discussion focused on the notion that as people age, there is
both a reduction of processing speed and an increase in wisdom and
knowledge. It may be worthwhile to think about decision tasks that study
the processing of new information versus drawing on existing
information. One idea that has not yet been addressed is the theory that
people will make a better decision if they "sleep on it" rather than
deciding in the moment; this may be studied in the lab.

It also was observed that given the many bad financial offers the
elderly are given through the mail or on the telephone, and the fact
that those most motivated to give them financial assistance are those
who are profiting from them, the elderly do need to be activists. Older
adults may also benefit from learning how to delegate decisions and who
they can entrust with decisions. Policy prescriptions, specifically in
terms of interventions to stem the flood of exploitative credit card
offers made to older adults, also were discussed, although it is not
clear that Government intervention is going to benefit the elderly. Just
as is the case for policy makers, researchers must be careful not to
inject value judgments on people's choices. For example, a person's
wellbeing and happiness are not necessarily linked with their amount of
savings.

Related to the measurement of wellbeing, it was observed that rather
than studying emotions simply as "positive" or "negative," it may be
worthwhile to differentiate them; for example, calm and exhilaration
both can be classified as positive emotions. However the experience of
these emotions may be differentially valued at different life stages.
Researchers might also wish to take into account self-relevant emotions
(e.g., shame, pride, embarrassment) that may have different impact on
decision making at different times of life, for greater precision or
predictability. These more complex and self-relevant emotions may
account for occupational choice, selection of a mate, and so on. It was
also emphasized that people often experience multiple emotions
concurrently; even positive and negative emotions can be experienced
together. It might be helpful to look at how these kinds of emotions and
emotional blends could be measured better in decision making contexts.

**Concluding Remarks**

[Rangel]{.mark} \[Link to Rangel.ppt\] concluded the workshop with
wrap-up remarks in which he presented goals and applications of
neuroeconomics as topics for discussion. One of the main goals of
neuroeconomics, he stated, is to decipher how the brain computes the
solutions to different types of decision-making problems. Specifically,
neuroeconomists want to know which variables are computed, how they
interact, how they lead to choices, their neural basis, and whether the
brain can solve the same decision-making problem in different modes.
Another goal of neuroeconomists is to study how the brain computes its
subjective experience of well-being, how these processes differ from the
decision-making process, and how they affect decision-making processes.
Lastly, neuroeconomists seek to understand the implications of this
knowledge for all of the behavioral sciences and their applications.
Development of a common language, he contended, can be achieved only by
understanding how decision-making is coded and processed and after
computational models have been thoroughly tested. He noted the need for
common definitions of terms such as "emotion," which was used in several
different ways throughout the workshop.

In terms of cross-disciplinary fertilization, what can neuroeconomics
contribute to aging studies? Rangel emphasized the characterization of
processes required for good decision-making in different situations, and
the need to develop tools to study how these processes change over the
life cycle. Likewise, what can aging studies contribute to
neuroeconomics? We have developed a menu of life-cycle behavioral
changes that need explanation. A second identified topic involved
typology of processes and choice situations. In order to make sound
choices, the brain needs to deploy multiple processes; therefore, we
need to identify the minimal set of separate processes required to
understand decision-making. Different choices are likely to be solved
using a different composition of these processes, so we also should
identify a useful taxonomy of decision-making situations that will
require study.

Rangel's third topic for discussion addressed which tasks should be
selected and studied. Identifying a battery of benchmark tasks is
crucial to understanding how decision-making processes change over the
life cycle and how this affects decision-making performance. Finally,
Rangel identified two types of external validity tests that are of
concern: population validity and task validity. He asked whether there
are any "golden standards" we should follow at the intersection of
neuroeconomics and aging. For example, if there is no cash incentive,
there is a good chance that the cognitive process will not be the same
as it would be in a real economic transaction. The panel agreed that the
degree to which decision contexts are realistic in the laboratory will
be critical to the justification of the research and credibility of
results.

In general discussion, the need for a taxonomy of decision processes was
underscored. An important component of an effective model is a set of
established tasks that control for such factors as framing effects. Key
decision types---essential critical tasks that would impact the
well-being of older adults---should be identified as well as how
performance on these tasks changes over the age range.

Two kinds of influence on age-related changes in decision making were
discussed: (1) That of institutions and (2) that of individual
differences, such as IQ and processing speed. It was noted that
institutions have been shown to trump individual differences and that "a
world can be built" around people with lower cognitive abilities that
will make them seem like better decision-makers. Thus, it may be
worthwhile to concentrate on institutional change. Others emphasized
that individual differences matter. The longitudinal data from the HRS
are valuable for studying this. Evidence exists to show that inequality
of cognitive abilities can have real economic costs, such as
vulnerability to scams, which leads to those individuals having less
money for health care plans and other necessities.

The issue of heterogeneity is an important one. There is tremendous
variation in how most complex decisions, such as those about life
savings, are made. Outcome data suggest that over half the population
are good decision-makers. It was suggested that researchers obtain
validation on a community-based population. It was noted that as the HRS
already is established, a relatively inexpensive first step might be to
give neuroeconomists access to the sample for imaging. It also was
suggested to embed a smaller study into a larger survey, to obtain more
precise measurements of covariates.

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[]{.mark}

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# APPENDIX A

**National Institute on Aging**

**Workshop on Neuroeconomics and Aging**

**March 31--April 1, 2006**

**Workshop Participants**

Carrie Armel, Ph.D., Department of Economics, Stanford University

Paul Brest, The William and Flora Hewlett Foundation

Laura L. Carstensen, Ph.D., Department of Psychology, Stanford
University

Cindy Cryder, Ph.D., Department of Social and Decision Sciences and
Department of

Psychology, Carnegie Mellon University

Mauricio Delgado, Ph.D., Department of Psychology, Rutgers University

John Dickhaut, Ph.D., Carlson School of Management, University of
Minnesota

Melissa L. Finucane, Ph.D., Center for Health Research, Kaiser
Permanente Hawai'i

Alan M. Garber, M.D., Ph.D., Departments of Medicine, Economics, and
Health Research and

Policy, Stanford University

David Grether, Ph.D., Department of Economics, California Institute of
Technology

Scott Huettel, Ph.D., Department of Psychiatry and Behavioral Science,
Duke University

Michael D. Hurd, Ph.D., Center for the Study on Aging, RAND

Cendri Hutcherson, Department of Psychology, Stanford University

Julian Jamison, Ph.D., Institute of Business and Economic Research,
University of California at

Berkeley

Marisa Knight, Department of Psychology, University of California at
Santa Cruz

Brian Knutson, Ph.D., Department of Psychology, Stanford University

Camelia (Cami) M. Kuhnen, Graduate School of Business, Stanford
University

David Laibson, Ph.D., Department of Economics, Harvard University

Gregory R. Larkin, Department of Psychology, Stanford University

Robert W. Levenson, Ph.D., Department of Psychology, University of
California at Berkeley

Mara Mather, Ph.D., Department of Psychology, University of California
at Santa Cruz

Samuel M. McClure, Ph.D., Department of Psychology, Princeton University

Daniel L. McFadden, Ph.D., Department of Economics, University of
California at Berkeley

Deanna Novak, Department of Psychology, University of California at
Santa Cruz

Ellen Peters, Ph.D., Department of Psychology, University of Oregon

Hilke Plassmann, Ph.D., Department of Economics, Stanford University

Antonio Rangel, Ph.D., Department of Economics, Stanford University

Mary Rigdon, Ph.D., Institute for Social Research, University of
Michigan

Susann Rohwedder, Ph.D., RAND

Timothy A. Salthouse, Ph.D., Department of Psychology, University of
Virginia

Alan G. Sanfey, Ph.D., Department of Psychology, University of Arizona

Paul Slovic, Ph.D., Department of Psychology, University of Oregon

Robert Willis, Ph.D., Department of Economics, University of Michigan

Paul J. Zak, Ph.D., Department of Economics, Claremont Graduate
University

### National Institute on Aging (NIA) Participants

Jeffrey W. Elias, Ph.D., Behavioral and Social Research (BSR), NIA

Lis Nielsen, Ph.D., BSR, NIA

John W. R. Phillips, Ph.D., BSR, NIA

Richard Suzman, Ph.D., BSR, NIA

Dominique Channell, Rose Li and Associates, Inc. (contractor)

Rose Maria Li, Rose Li and Associates, Inc. (contractor)

# APPENDIX B

# National Institute on Aging

# Workshop on Neuroeconomics and Aging

**Recommended Readings**

**Scott Huettel recommends:**

Cabeza, R., Nyberg, L., & Park, D. (2005). *Cognitive Neuroscience of
Aging: Linking Cognitive and Cerebral Aging.* New York: Oxford
University Press

Hedden, T. & Gabrieli, J.D.E. (2004). Insights into the ageing mind: A
view from cognitive neuroscience. *Nature Reviews Neuroscience* 5
(February): 89-96.

D'Esposito, M., Deouell, L.Y., & Gazzaley, A. (2003). Alterations in the
BOLD fMRI signal with ageing and disease: a challenge for neuroimaging.
*Nature Reviews Neuroscience* 4 (11, November): 863-72.

**David Laibson recommends:**

James Choi, David Laibson, Brigitte Madrian, and Andrew Metrick "
[Saving for Retirement on the Path of Least
Resistance](http://www.som.yale.edu/faculty/jjc83/plr_bpf.pdf),"
forthcoming in Ed McCaffrey and Joel Slemrod, eds., *Behavioral Public
Finance*.\
\
James Choi, David Laibson, and Brigitte C. Madrian " [Are Education and
Empowerment Enough? Under-Diversification in 401(k)
Plans](http://post.economics.harvard.edu/faculty/laibson/papers/BPEA.pdf)"
*[Brookings Papers on Economic
Activity](http://www.brookings.edu/es/commentary/journals/bpea_macro/bpea_macro.htm)*
2:2005.\
 \
James Choi, David Laibson, Brigitte Madrian, and Andrew Metrick
["Passive Decisions and Potent
Defaults."](http://www.nber.org/papers/w9917) In David Wise, ed.,
[Analyses in the Economics of Aging.]{.underline} Chicago, IL:
University of Chicago Press, 2005, pp. 59-78\
 \
Samuel M. McClure, David Laibson, George Loewenstein and Jonathan D.
Cohen, "[Separate Neural Systems Value Immediate and Delayed Monetary
Rewards](http://post.economics.harvard.edu/faculty/laibson/papers/laibson_science.pdf)"
[*Science*](http://www.sciencemag.org/cgi/content/abstract/306/5695/503?maxtoshow=&HITS=10&hits=10&RESULTFORMAT=&fulltext=laibson&searchid=1132181659013_19931&stored_search=&FIRSTINDEX=0)
306, October 15, 2004.\
 \
James Choi, David Laibson, and Brigitte C. Madrian "[Plan Design and
401(k) Savings
Outcomes](http://post.economics.harvard.edu/faculty/laibson/papers/plandesign.pdf),"
[National Tax
Journal](http://ntj.tax.org/wwtax/ntjrec.nsf/175d710dffc186a385256a31007cb40f/224cbf3a03b5dff585256eb30051fdaf?OpenDocument),
57(2), June 2004 pp. 275-98.\
 \
James Choi, David Laibson, Brigitte Madrian, and Andrew Metrick "[For
Better or For Worse: Default Effects and 401(k) Savings
Behavior](http://post.economics.harvard.edu/faculty/laibson/papers/forbetter.pdf)"
in David Wise editor *Perspectives in the Economics of Aging*. Chicago,
IL: University of Chicago Press, 2004, pp. 81-121.\
 \
James Choi, David Laibson, Brigitte Madrian, and Andrew Metrick
"[Optimal
Defaults](http://www.ingentaconnect.com/content/aea/aer/2003/00000093/00000002/art00029)"
*American Economic Review Papers and Proceedings*, May 2003, pp.
180-185.\
 \
David Laibson, Andrea Repetto and Jeremy Tobacman. "[A Debt
Puzzle](http://post.economics.harvard.edu/faculty/laibson/papers/sept17.pdf)"
in eds. Philippe Aghion, Roman Frydman, Joseph Stiglitz, Michael
Woodford, *Knowledge, Information, and Expectations in Modern Economics:
In Honor of Edmund S. Phelps*, Princeton: Princeton University Press,
2003, 228-266.\
\
James J. Choi, David Laibson, Brigitte Madrian, and Andrew Metrick.
"Defined Contribution Pensions: Plan Rules, Participant Decisions, and
the Path of Least Resistance" in ed. James Poterba, *Tax Policy and the
Economy*, 16, 2002, pp. 67-113.\
 \
George-Marios Angeletos, David Laibson, Andrea Repetto, Jeremy
Tobacman,and Stephen Weinberg),"[The Hyperbolic Consumption Model:
Calibration, Simulation, and Empirical
Evaluation](http://links.jstor.org/sici?sici=0895-3309(200122)15:3<47:THCMCS>2.0.CO;2-5)"
*Journal of Economic Perspectives*, August 2001, pp. 47-68. \[Reprinted
in G. Loewenstein ed. volume on Intertemporal Choice, Russell Sage
Foundation.\]\
 \
David Laibson, Andrea Repetto and Jeremy Tobacman. ["Self-Control and
Saving for
Retirement"](http://www.brookings.edu/press/books/bpea198.htm)
*Brookings Papers on Economic Activity*, No. 1, 1998, 91-196. 
\[Reprinted in *Social Security Reform: Financial and Political Issues
in International Perspective,* edited by Robin Brooks and Assaf Razin,
Cambridge University Press, 2005.\]\
 \
David Laibson, "[Golden Eggs and Hyperbolic
Discounting](http://mitpress.mit.edu/catalog/item/default.asp?ttype=6&tid=407),"
*Quarterly Journal of Economics*, 62, May 1997, 443-77.

**Robert Levenson recommends:**

Levenson, R.W. (2000). Expressive, physiological, and subjective changes
in emotion across adulthood. In S.H. Qualls & N. Abeles (Eds.),
*Psychology and the Aging Revolution: How We Adapt to Longer Life*. (pp.
123-140). Washington, DC, US: American Psychological Association.

Levenson, R.W., Carstensen, L.L., & Gottman, J.M. (1994). Influence of
age and gender on affect, physiology, and their interrelations: A study
of long-term marriages. *Journal of Personality & Social Psychology*,
67(1), 56-68.

Carstensen, L.L., Graff, J., Levenson, R.W., & Gottman, J.M. (1996).
Affect in intimate relationships: The developmental course of marriage.
In C. Magai & S.H. McFadden (Eds.), *Handbook of Emotion, Adult
Development, and Aging*. (pp. 227-247). San Diego, CA: Academic Press,
Inc.

**Mara Mather recommends:**

Mather, M. (2006). A review of decision making processes: Weighing the
risks and benefits of

aging. In L. L. Carstensen & C. R. Hartel (Eds.), *When I\'m 64.*
Committee on Aging Frontiers in

Social Psychology, Personality, and Adult Developmental Psychology.
Washington, DC: The

National Academies Press, 145-173.

Mather, M., & Carstensen, L. L. (2005). Aging and motivated cognition:
The positivity effect in

attention and memory. *Trends in Cognitive Sciences*, 9, 496-502.

**Paul Slovic recommends:**

Peters, E., & Västfjäll, D. (2005, November). *Affective processes in
decision making by older adults.* Paper presented at the National
Research Council Workshop on Decision Making by Older Adults,
Washington, DC.

Slovic, P., Finucane, M. L., Peters, E., & MacGregor, D. G. (2002). The
affect heuristic. In T. Gilovich, D. Griffin, & D. Kahneman (Eds.),
*Heuristics and Biases: The Psychology of Intuitive Judgment* (pp.
397-420). New York: Cambridge University Press.

[^1]: This meeting summary was prepared by Rose Li and Associates, Inc.
    (<rose@roseliassociates.com>). This version has benefited from
    helpful comments by Jeff Elias and Lis Nielsen. The findings and
    views reported in this document reflect both individual and
    collective opinions of the workshop participants and not necessarily
    those of the National Institute on Aging, National Institutes of
    Health, or the U.S. Department of Health and Human Services.