Journal of Counseling Psychology 2014, Vol. 61, No. 4, 534-540

© 2014 American Psychological Association 0022-0167/14/$ 12.00 http://dx.doi.org/10.1037/cou0000024

Neuroscience Research on Aging and Implications for Counseling Psychology Stephen L. Wright

Fernando Diaz

University of Northern Colorado

University of Santiago de Compostela (USC)

The advances in neuroscience have led to an increase in scientific understanding of the aging process, and counseling psychologists can benefit from familiarity with the research on the neuroscience of aging. In this article, we have focused on the cognitive neuroscience of aging, and we describe the progression of healthy aging to Alzheimer’s disease, given its high prevalence rate among older adults (Alzheimer’s Association, 2013). Common techniques used to study the cognitive neuroscience of aging are explained in regards to measuring age-related changes in the brain and the role of biomarkers in identifying cognitive decline related to Alzheimer’s disease. Using this information and in collaboration with cognitive neuroscientists, it is our hope that counseling psychologists may further pursue research areas on aging as well as design appropriate interventions for older individuals who may be experiencing cognitive impairment. Keywords: cognitive neuroscience, aging, Alzheimer’s disease, biomarkers

The growing interest in the study of aging derives largely from the increasing percentage of the population in most world regions that consists of adults over the age of 65. Older adults currently make up 20% of the population, and it is expected that in 2050 the rate will exceed 30% in many countries. This accelerated aging of the population has serious economic, health, and social concerns that must be faced (Arai et al., 2012). One area of growing concern is the increasing prevalence of Alzheimer’s disease (AD) and other dementias among older adults, which occurs in about 5.2 million people in the United States, represents a prevalence rate of about 6% for those age 60 and older (Alzheimer’s Association, 2013), and occurs globally in approximately 35.6 million people, 58% living in countries with low or middle incomes, and with numbers expected to almost double every 20 years (Prince et al., 2013). AD is a progressive neurodegenerative disease characterized clinically by a progressive and gradual decline in cognitive func­ tion (American Psychiatric Association, 2013), and neuropathologically by the presence of abnormal neuritis (neuropil threads), specific neuron loss, and synapse loss in addition to the hallmark findings of neurofibrillary tangles and senile (amyloid) plaques (Murphy & LeVine, 2010). There are approximately 11% of people age 65 and older, and 32% of people age 85 and older who

have AD (Alzheimer’s Association, 2013). The estimated annual incidence of AD appears to increase dramatically with age, from approximately 53 new cases per 1,000 people age 65-74, to 170 new cases per 1,000 people age 75-84, to 231 new cases per 1,000 people age 85 and older—the “oldest-old” (Hebert, Scherr, Bienias, Bennett, & Evans, 2003). Consequently, one of the main challenges of the 21st century is to achieve the best possible physical and mental health for the entire population, and particu­ larly for older adults. This requires reaching a deeper understand­ ing of the healthy neurocognitive aging process and the factors that influence this process. Although many areas of aging are being studied, we have focused on the cognitive neuroscience of aging to provide a framework for counseling psychologists. Specifically, the tech­ niques and the biomarkers used to study the continuum of healthy aging to AD are described in this article. Using this information, counseling psychologists may further pursue research areas on aging to understand how to optimize cognitive performance in older individuals as well as design appropriate interventions for older people who may be experiencing cognitive impairment to help promote functional independence and improve quality of life.

Cognitive Neuroscience of Aging The cognitive neuroscience of aging (see Cabeza, 2004; Cabeza, Nyberg, & Park, 2005; Grady, 2008, 2012) recently emerged as a scientific discipline thanks to the increasing convergence in recent decades between the psychology of aging and the neuroscience of aging. These two fields brought unique perspectives that allowed for the merging of theoretical and research approaches to the study of aging. This convergence was also aided by technical and meth­ odological developments that allow researchers to use noninvasive recording techniques of human brain activity while participants are performing cognitive tasks. Therefore, the goal of the cognitive neuroscience of aging is to determine the relationships between the

Stephen L. Wright, Department of Applied Psychology and Counselor Education, University of Northern Colorado; Fernando Dfaz, Department of Clinical Psychology and Psychobiology, Faculty of Psychology, Uni­ versity of Santiago de Compostela (USC). This work was partially financially supported by Spanish Ministerio de Economi'a y Competitividad Grant PSI2010-22224-C03-03 and Galician Gov­ ernment Grants PGIDIT07PXIB211018PR, 10 PXIB 211070 PR, and Ref: CN 2012/033. They were awarded to Fernando Diaz. Correspondence concerning this article should be addressed to Stephen L. Wright, Department of Applied Psychology and Counselor Education, University of Northern Colorado, 501 20th Street, 200 McKee Hall - Box 131, Greeley, CO 80639. E-mail: [email protected]

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effects of aging on behavioral measures and on the brain assessed through neuroimaging (Cabeza et al., 2005).

Research Techniques A number of tools have been developed to study human brain activity during the performance of cognitive tasks. These tools include neuroimaging techniques, such as positron emission to­ mography (PET) and functional magnetic resonance imaging (fMRI), as well as electromagnetic recording techniques, which include electroencephalography (EEG), event-related potentials (ERPs), and magnetoencephalography (MEG). In each of these in vivo techniques, the signal and the information that are gathered on brain function covary with the mental process of interest. Each of these techniques records human brain activity in a different man­ ner and are noninvasive or moderately invasive (PET), as well as low (EEG/ERP) or moderate in cost. Some of them directly record changes in electrical potentials (EEG/ERP) or magnetic fields (MEG) generated in the membranes of neurons, whereas others record changes in the level of blood oxygenation of the regional cerebral blood flow (fMRI), or metabolic changes (PET), indi­ rectly derived from neural activity. Each technique uses specific procedures and recording devices, as well as methods of analysis of the obtained signal. These differences determine the varying degree of precision or the level of spatial and temporal resolution of each technique. Of these techniques, the most commonly used in cognitive neuroscience of aging studies are the fMRI and the ERP. The fMRI allows us to map with a high-spatial resolution (between 1 and 3 mm) different brain areas and neural networks associated with specific cognitive functions, thus providing infor­ mation about the brain areas that are activated while performing a cognitive process. Because the ERP technique measures taskrelated electrical changes occurring directly in neuron populations associated with cognitive events (e.g., attention, working memory, response preparation), it is especially useful for studying the speed and the timing of cognitive processes, because of its high temporal resolution (in the order of a millisecond).

Theoretical Models Recently, functional neuroimaging studies of aging have re­ vealed different activation patterns between older adults and younger adults for different cognitive processes (for reviews, see Eyler, Sherzai, Kaup, & Jeste, 2011; Fabiani, 2012; Grady, 2008, 2012; Park & Reuter-Lorenz, 2009; Spreng, Wojtowicz, & Grady, 2010). For instance, research has revealed that older adults use more areas of the brain than younger adults performing similarly on the same task. Different theoretical postulates have been used to describe these age differences, which have included a compensa­ tory role (e.g., hemispheric asymmetry reduction in older adults; Cabeza, Anderson, Locantore, & McIntosh, 2002; or a posterioranterior shift in aging; Davis, Dennis, Fleck, Daselaar, & Cabeza, 2008; a compensation-related utilization of neural circuit hypoth­ esis; Park & Reuter-Lorenz, 2009; Reuter-Lorenz & Cappell, 2008) or dedifferentiation, which is the inefficient use of neural resources or reduction in the selectivity of responses (Li, Lindenberger, & Sikstrom, 2001). Furthermore, there are two well-known models that are fre­ quently used to describe the compensatory role of aging, and both

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models relate to hemispheric asymmetry. The hemispheric asym­ metry reduction in older adults, known as the HAROLD model, posits that “prefrontal cortex activity during cognitive perfor­ mances tends to be less lateralized in older adults than younger adults” (Cabeza, 2002, p. 85). Functional neuroimaging and be­ havioral evidence (e.g., episodic memory retrieval, episodic mem­ ory encoding/sematic memory retrieval, working memory, percep­ tion, and inhibitory control) provides support for the HAROLD model, and the decrease in lateralization during aging may be attributed to changes in global neurocognitive networks and/or regional neural changes (Cabeza, 2002). Whereas, the HAROLD model is applied to the prefrontal cortex brain regions, the second well-known model, called the right hemi-aging model, accounts for changes throughout the other brain regions (Dolcos, Rice, & Cabeza, 2002). The right hemi-aging model postulates that the right hemisphere experiences a greater degree of age-related cog­ nitive decline than the left hemisphere (e.g., spatial processing vs. verbal processing, respectively), but the research is inconclusive, and further research is warranted (Dolcos et al., 2002). Another differential age-related pattern of activation identified through neuroimaging techniques (e.g., fMRI) is the default mode network (DMN). The DMN is a specific anatomically defined brain system preferentially active when individuals are not focused on the external environment (Buckner, Andrews-Hanna, & Schacter, 2008) but is suppressed during task performance. However, the DMN appears to be less suppressed in older adults than in younger adults during task performance (Raichle & Snyder, 2007) and can be interpreted as an index of the increased behavioral distractibility in aging (Daselaar, Prince, & Cabeza, 2004). Understanding these models will provide guidance for counseling psychologists, as they conduct future research on aging, secure grants for funding of research, and implement interventions targeted to the areas of the brain affected by the aging process. In addition to the models, research studies using the ERP tech­ nique have shown support for differential age-related patterns (see Friedman, 2011). Specifically, as adults age, the differential pat­ terns found have included a decline in processing speed (Amenedo & Diaz, 1998); a lower top-down attentional control, with conse­ quential distractibility (Amenedo & Diaz, 1998); a posterioranterior shift with aging (Adrover-Roig & Barcelo, 2010; Ame­ nedo & Diaz, 1998); inhibitory deficits (Diaz & Amenedo, 1998; Dustman, Emmerson, & Shearer, 1996); and a decline in episodic memory (McDaniel, Jacoby, & Einstein, 2008). Despite these age differences, cognitive research has also re­ vealed that adults maintain some cognitive functions with age, such as vocabulary and other crystallized abilities, and emotional regulation. In addition, stereotypes may also influence cognitive performance in older adults. Specifically, Levy (1996) discovered that when positive stereotypes related to aging were primed in older adults, they experienced improved cognitive performance in memory, increased memory self-efficacy, and improved views of aging; as opposed to when negative stereotypes were primed, older adults experienced decreases in the aforementioned areas (Levy, 1996). These negative age stereotypes are powerful over time. Specifically, individuals over the age of 60 with more negative age stereotypes have shown a greater decline in memory performance over a 38-year period, compared with those who hold less negative age stereotypes (Levy, Zonderman, Slade, & Ferrucci, 2012). Accordingly, it may be helpful for counseling psychologists to

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apply social justice principles to help combat negative stereotypes related to aging, as well as focusing on the positive strengths like word sophistication and improved decision making. For instance, Rabaglia and Salthouse (2001) found that older adults used a greater number of diverse and sophisticated words, but used less grammatical complexity across two studies (n = 399, n = 459) with participants ranging in age from 18 to 90. Research also supports the notion that crystallized intelligence remains more stable during aging than fluid intelligence (Li et al., 2004), which may be related to improved decision-making performance among older adults (Li, Baldassi, Johnson, & Weber, 2013). Nevertheless, other cognitive functions continue to show age-related differences that are important for counseling psychologists to consider when working with clients (e.g., processing speed, the susceptibility to the effects of interference on cognitive tasks, episodic memory, working memory, attention, and task switching; see reviews in Fabiani, 2012; Grady, 2012; Park & Reuter-Lorenz, 2009). Fur­ thermore, there is a growing interest in health psychology among counseling psychologists and training programs (Raque-Bogdan, Torrey, Lewis, & Borges, 2013), as well as a movement toward integrative care (American Psychological Association, 2008), in­ creasing the need for further understanding of the cognitive changes associated with the aging process.

Cognitive Neuroscience of AD In addition to understanding the typical aging process, counsel­ ing psychologists must be prepared to work with older adults facing cognitive declines like dementia and AD. Through the use of neuroimaging techniques (e.g., ERP, fMRI) to study relation­ ships between the age effects on behavioral measures and age effects on the brain, researchers have been able to test hypotheses derived from theoretical models of cognitive and of neurocognitive aging to better understand the process of dementia and AD. This has led to the emergence of new explanatory theories of cognitive brain function in healthy aging (e.g., the scaffolding theory of aging and cognition; Park & Reuter-Lorenz, 2009) and the effects of age-related diseases on brain function, especially for AD and other types of dementia. More specifically, neuroimaging tech­ niques have been used to study promising biomarkers of pro­ dromic and preclinical stages of AD, which is an increased area of research given the high prevalence rate among older adults (Alz­ heimer’s Association, 2013). Accordingly, biomarkers are param­ eters (anatomic, biochemical, physiological) that can be measured in vivo and that reflect specific features of disease-related patho­ physiological processes. It is vital for counseling psychologists to understand the biomarkers related to cognitive decline given that cognitive decline in late life has been associated with loss of independence, functional decline in activities of daily living, nurs­ ing home placement, and mortality (Smith, Nielson, Woodard, Seidenberg, & Rao, 2013; Yaffe et al., 2002). Thus, efforts are underway to identify preclinical biomarkers in order to better predict future cognitive decline and AD (Woodard et al., 2012).

AD and the Biomarker Model The neuropathological changes associated with AD may occur from 10 to 20 years before there are noticeable clinical symptoms (Jack et al., 2010; Sperling et al., 2011). At the same time, the

biomarker model of the preclinical stage of AD parallels the hypo­ thetical pathophysiological sequence of AD and is relevant to tracking the preclinical stages of AD (see Sperling et al., 2011). The biomarker model includes a set of biomarkers (i.e., measureable features of the disease-related process) that would be present in the preclinical stages of AD and that likely follow an ordered temporal pattern. Before the prodromal stage, a subtle change from baseline level of cognition and poor performance on more challenging cognitive tests can be de­ tected. From this stage, cognitive functioning is likely to progress to mild cognitive impairment (MCI) and then to AD dementia. The preclinical stage of AD may be divided into two periods: (a) a latent phase with no observable symptoms and (b) a prodromal phase of mild symptoms that do not meet diagnostic criteria for probable or possible AD (Smith et al., 2013). The prodromal phase of AD is a heterogeneous clinical entity characterized by objective evidence of cognitive decline and is without any notable impairment in the per­ formance of daily activities. This is a condition termed MCI (Petersen, 2004; Petersen et al., 1999). In the preclinical phase, biomarkers are used to establish the presence of pathophysiological AD in people with no or very subtle overt symptoms. In both the MCI and AD dementia criteria, clinical diagnoses are paramount, and biomarkers are complimentary (Jack et al., 2011). MCI is considered as an intermediate stage between the cogni­ tive changes associated with healthy aging and the early clinical features of dementia (Petersen, 2004; Petersen et al., 1999). Among the different subtypes of MCI, there is amnestic MCI (aMCI), and it is the most likely to progress to AD (Albert et al., 2011; Petersen, 2004; Petersen et al., 2001). AMCI criteria include subjective and objective demonstration of episodic memory im­ pairment without generalized dementia and with intact activities of daily living (Petersen et al., 2001). The annual conversion rate from MCI to AD ranges between 8% and 16% in the literature (Busse, Hensel, Guhne, Angermeyer, & Riedel-Heller, 2006; Petersen et al., 1999). Furthermore, the long preclinical phase of AD and the MCI stage provide a critical opportunity for potential intervention with disease-modifying ther­ apy, if we are able to elucidate the link between the pathophysi­ ological process of AD and the emergence of the clinical syndrome (see Sperling et al., 2011). On the basis of counseling psychology’s emphasis on strengths and on prevention (Chwalisz & Obasi, 2008), counseling psychologists may be able to assess the symp­ toms related to MCI developing during the preclinical phase and then refer the person to the appropriate individual for treat­ ment. Thus, early identification of vulnerable individuals may permit targeted early intervention and prevention trials that delay the onset of cognitive decline or help maintain cognitive function in older adults, which may slow the development of AD and will have a major public health impact (see Smith et al., 2013).

Neuroimaging and Biomarkers The fMRI technique has been used in researching MCI biomark­ ers. Research has pointed to changes in the hippocampus as one of these biomarkers, such as a higher activation of the hippocampus in adults with MCI when compared with both healthy controls and patients with probable AD (Dickerson & Sperling, 2008). This may represent a compensatory hyperactivation necessary to achieve successful memory encoding (Kircher et al., 2007) that has been associated with a subsequent decrease in activation and with

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progression to AD (O’Brien et al., 2010). However, when engaged in episodic memory encoding and recall tasks, other studies have observed decreased activation of the hippocampus in MCI partic­ ipants relative to healthy controls (Celone et al., 2006; Trivedi et al., 2008), which may be related to more advanced atrophy of the hippocampus (Celone et al., 2006; O’Brien et al., 2010). The ERP technique has shown promising results when searching for MCI biomarkers. For instance, using a total sample of 580 people age 50 or older who reported subjective complaints of memory loss to their family physician, a group of cognitive neuroscientists conducted three pivotal ERP research studies over a 5-year period with a selected sample of 63 healthy individuals and 30 individuals with aMCI to identify potential cognitive and neurocognitive markers of MCI, as well as impairment in presymptomatic stages of AD (Cespon, GaldoAlvarez, & Diaz, 2013; Cid-Femandez, Lindln, & Diaz, 2014; Lindln, Correa, Zurron, & Diaz, 2013). These three studies demonstrated that recording ERPs while participants performed cognitive tasks was a suitable method for obtaining neurocognitive MCI biomarkers. The identification of these MCI biomarkers may aid counseling psychol­ ogists in their work with older adults and as they pursue research with neuroscientists.

Implications for Counseling Psychologists The area of neuropsychology has been relevant for counseling psychologists over the years (Ryan, Lopez, & Lichtenberg, 1999), and there is a growing interest in health psychology among coun­ seling psychologists (Raque-Bogdan et al., 2013) and the need for integrative care (American Psychological Association, 2008). Thus, it is important for counseling psychologists working with older adults to be aware of the advances in neuroscience related to aging, and specifically the progression of healthy aging to AD based on the high prevalence rate of AD among older adults (i.e., 11%), and being the sixth leading cause of death in the United States (Alzheimer’s Association, 2013). The emergence of cognitive neuroscience of aging has led to new theories of brain functioning to guide research on the contin­ uum of healthy aging to AD. Understanding cognitive impairments related to aging can aid counseling psychologists in their work with clients. For instance, it is common for individuals with MCI, who have subsequently been diagnosed with AD, to have impair­ ments in episodic memory (Albert et al., 2011). In accordance with the guidelines for evaluating dementia (American Psychological Association, 2012), counseling psychologists can use assessments that screen for possible impairments in episodic memory, such as tests that assess both immediate and delayed recall like the Rey Auditory Verbal Learning Test or the Wechsler Memory Scale (Albert et al., 2011), or even brief screening tools (Ortega, Alvarez de Sotomayor, Gonzalez, & Fernandez, 2013). Additionally, other forms of memory impairments (i.e., working memory) have been found among individuals that have progressed to AD (Gagnon & Belleville, 2011), and using multiple assessments targeting addi­ tional cognitive functions (e.g., attentional processing, short-term memory, working memory, episodic memory) may aid clinicians in the identification of AD dementia (Summers & Saunders, 2012). Counseling psychologists should also consider the biomarkers re­ lated to AD (Alzheimer’s Association, 2013) when pursuing research and working with older adults, as well as the associated identification techniques (e.g., ERP). Subsequently, we may be able to assess the

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symptoms related to MCI and to develop appropriate disease­ modifying interventions that could assist in slowing the progression of the disease and the associated impairments. For instance, a growing body of literature continues to show that physical activity reduces the risk of developing dementia (Alzheimer’s Association, 2013), as well as being beneficial for those who do have dementia based on metaanalytic findings (Heyn, Abreu, & Ottenbacher, 2004), and behavioral based programs have been designed to increase physical actively for older individuals with dementia (Logsdon, McCurry, Pike, & Teri, 2009). Social and cognitive engagement also helps prevent AD (Alz­ heimer’s Association, 2013). For example, a longitudinal study with 75-year-olds revealed that mental and social engagement were in­ versely related to dementia in aging individuals, and they suggest these areas may help protect against dementia (Wang, Karp, Winblad, & Fratiglioni, 2002). By working together, counseling psychologists and cognitive neuroscientists may be able to determine through re­ search which interventions (e.g., physical activity, Alzheimer’s As­ sociation, 2013; social or mental engagement, Wang et al., 2002) are most effective for a specific biomarker based on the phases of AD. Specifically, biomarkers that have been identified in the early stages of AD could be tracked over a longitudinal period while counseling psychologists are working from therapeutic approaches designed to increase social engagement (i.e., interpersonal psychotherapy [IPT]) or physical activity to examine the effectiveness of the interventions based on the changes in biomarkers. AD is the most common type of dementia and occurs in 60%-80% of the cases (see Alzheimer’s Association, 2013, Table 1). However, it is essential for counseling psychologists to keep in mind that other conditions may resemble dementia, but in fact may be reversible forms of dementia. For instance, in a meta-analysis of 39 studies (N = 5,620) examining dementia etiology, Clarfield (2003) found that 9% of cases were classified as a potentially reversible cause of dementia, such as depression, trauma, alcohol abuse, medications, and other medical conditions (e.g., metabolic conditions). In regards to depres­ sion, more nonspecific patterns of cognitive deficits are more com­ mon with major depression, but consistent deficits of cognitive func­ tioning and memory are more likely in AD (American Psychological Association, 2013). To aid counseling psychologists’ ability to accu­ rately identify and treat individuals, it may be helpful to use a model that works through differential diagnoses (e.g., Spengler, Strohmer, Dixon, & Shivy, 1995) and incorporates statistical methods UFgisdottir et al., 2006). Additionally, working from a biopsychosocial model (Suls & Rothman, 2004) and consulting with primary care providers may also assist in differential diagnoses. For instance, using a depression-screening instrument and conducting a brief mini-mental status exam with clients may help identify feelings of depression and determine whether there is an acute change in cognitive functioning that would require immediate medical attention or if their cognitive functioning is progressing as expected with AD or dementia (Brown, Raue, Halpert, Adams, & Titler, 2009). Accordingly, there are multiple treatment methods shown to be effective for depression in older adults with cognitive declines, such as monthly maintenance of IPT (Carreira et al., 2008) and modified cognitive behavior therapy (CBT; Regan & Varanelli, 2013). When working with older adults who are experiencing feelings of depression, counseling psychologists should also em­ phasize the importance of physical activity and social engagement, given that both are related to decreasing feelings of depression (Bridle, Spanjers, Patel, Atherton, & Lamb, 2012; Glass, Mendes

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de Leon, Bassuk, & Berkman, 2006) and reducing the risk of cognitive decline (Alzheimer’s Association, 2013). Likewise, one way to increase social support could be through physical activity with others, which has significantly predicted life satisfaction in older adults based on 8-year longitudinal data (Gana et al„ 2013). Due to multiple factors, diagnosing and treating depression in people with AD can be complex (Lyketsos et ah, 2011), but it is critical to treat the depression given the possible causal factor that depression and decreased hippocampal volume can lead to subse­ quent cognitive decline in older individuals (Sawyer, Corsentino, Sachs-Ericsson, & Steffens, 2012; Steffens, McQuoid, Payne, & Potter, 2011). This is another area in which counseling psycholo­ gists and cognitive neuroscientists can collaborate together on grant-funded research projects. Particularly, the National Institute of Mental Health (2008) provides support for research studies identifying biomarkers and behavioral indicators related to mental disorders. Working together, neuroscientists could search for bio­ markers that may identify which therapeutic treatments (e.g., CBT, IPT) are more effective for counseling psychologists to use when working with older adults suffering from dementia and depression. In addition to depression, there are also other neuropsychiatric symptoms that are common in the early phases (e.g., MCI) of AD, which may include sleep disorders, agitation, psychoses, and apathy (Lyketsos et al., 2011). To help counseling psychologists treat some of these symptoms, research has identified psychosocial methods for depression, agitation, and apathy in older adults with dementia that have included behavioral therapy focused on pleasant events and problem solving, psychomotor therapy groups, and multisensory stimulation, respectively (Verkaik, van Weert, & Francke, 2005). This may be another area of research for counseling psychologists and neuroscientists to collaborate in searching for which biomarkers help with a specific treatment of the aforementioned symptoms as well as offering assistance in differential diagnosis. With the rate of AD significantly increasing in low- or middleincome countries (Prince et al., 2013), counseling psychologists can be social justice agents by advocating for ways to increase resources focusing on treatment for those in underserved areas and countries as well as expanding research pursuits in similar areas. Furthermore, addressing social justice and multicultural issues are at the core of counseling psychologists’ identity (Fouad & Prince, 2012) and are relevant to neuroscience (Ivey & Zalaquett, 2011). Accordingly, counseling psychologists should advocate for system changes to help individuals who are oppressed or may not have access to resources that may help identify the early signs of dementia, based on the importance of early identification (Alzhei­ mer’s Association, 2013) and counseling psychologists’ emphasis on health and prevention (Chwalisz & Obasi, 2008). Helping address educational barriers for individuals is another way coun­ seling psychologists can act as social justice agents, given that individuals with fewer years of education are at an increased risk for AD (Alzheimer’s Association, 2013).

Conclusion The advances in neuroscience have led to an increase in scien­ tific understanding of the aging process, specifically related to AD. However, cognitive changes are not the only concern present in AD, and there are a variety of other neuropsychiatric symptoms that are associated with AD, such as depression (Lyketsos et al.,

2011), that must also be considered by counseling psychologists when working with the older adults. Further advances in neuro­ science, like the identification of biomarkers related to cognitive decline, also continue to advance our understanding of the aging process. It is our hope that counseling psychologists will use this information in collaboration with cognitive neuroscientists to fur­ ther pursue research areas on aging. Through this collaboration, we hope to be able to identify which treatment will be most appro­ priate for specific biomarkers, thus improving the quality of life of those who have AD and other dementias.

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Neuroscience research on aging and implications for counseling psychology.

The advances in neuroscience have led to an increase in scientific understanding of the aging process, and counseling psychologists can benefit from f...
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