Electrophysiological Biomarkers of Chemotherapy-related Cognitive Impairment and Recovery
Conditions: Myelodysplastic Syndrome, Effects of Chemotherapy, Mild Cognitive Impairment, Multiple Myeloma, Non-hodgkin Lymphoma, Chronic Lymphocytic Leukemia, Acute Lymphoid Leukemia, Chronic Myeloid Leukemia, Acute Myeloid Leukemia
Sponsor: University of Nebraska

FRED & PAMELA BUFFETT CANCER CENTER SRC PROTOCOL 
 
 
Title Page ............................................................................................................................ 2 
Abstract .............................................................................................................................. 3 
Schema ............................................................................................................................... 4 
Section 1.0 
Objectives .................................................................................................. 4 
Section 2.0 
Introduction, which includes background data and future aims.................. 6 
Section 3.0 
Eligibility criteria ......................................................................................... 8 
Section 4.0 
Randomization/registration procedures ..................................................... 9 
Section 5.0 
Treatment plan or research design ............................................................ 9 
Section 6.0 
Measurement of effect ............................................................................... 15 
Section 7.0 
Study parameters ...................................................................................... 16 
Section 8.0 
Drug formulation and procurement ............................................................ 16 
Section 9.0 
Toxicity and adverse event reporting guidelines ........................................ 16 
Section 10.0 
Biostatistical considerations including stopping criteria ............................. 17 
Section 11.0 
Records to be kept .................................................................................... 19 
Section 12.0 
Patient consent form statement ................................................................. 20 
Section 13.0 
References ................................................................................................ 20 
Section 14.0 
Data collection forms ................................................................................. 27 
Section 15.0 
SRC Approval Letter .................................................................................. 28 
Section 16.0 
IRB Approval Letter ................................................................................... 29 
Section 17.0 
CCTR Grant Application ............................................................................ 30 
Section 18.0 
CCTR Funding Approval Letter ................................................................. 33 
Section 19.0 
CPCP Grant Application ............................................................................ 35 
Section 20.0 
CPCP Funding Approval Letter ................................................................. 36 

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PROTOCOL TITLE 
Electrophysiological biomarkers of chemotherapy-related cognitive impairment 
 
Principle Investigator: 
Vijaya Bhatt, MD 
E: vijaya.bhatt@unmc.edu 
P: 402-559-5163 
 
Secondary Investigators: 
Matthew Rizzo, MD 
E: matthew.rizzo@unmc.edu 
P: 402-559-4849 
Sachin Kedar, MD 
E: sachin.kedar@unmc.edu 
P: 402-559-8553 
David Anderson, MS 
E: david.anderson@unmc.edu 
P: 402-559-6870 
Statistician: 
Kendra Schmid, PhD 
E: kkschmid@unmc.edu 
P: 402-559-8117 
Participating Personnel: 
Lori Maness, MD 
Krishna Gundabolu, MD 
Matthew Lunning, MD 
Sarah Holstein, MD, PhD 
James Armitage, MD 
Muhamed Baljevic, MD 
Philip Bierman, MD 
Robert Bociek, MD 
Julie Vose, MD, MBA 
Sushil Kumar, PhD 
Jennifer Merickel, PhD 
Matthew Garlinghouse, PhD 
Emily Frankel, BS 
Kaitlin Smits, BS 
Vikas Mudgapalli, BA 
Chris Thomas 
Gaurav Kumar, MBBS 

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Abstract: 
The goal of this study is to better understand the influence of chemotherapy treatment on the neural 
mechanisms of attention and cognition. Extant literature lacks diversity in studied cancer populations and 
treatment protocols, and provides limited understanding of the cognitive abilities that are impaired by 
chemotherapy. To overcome these limitations, this study will employ a sophisticated battery of tests in 
understudied cancer populations with hematological malignancies (HM). Eligible participants will either be 
patients diagnosed with Myelodysplasic Syndrome (MDS), Acute Myelogenous Leukemia (AML), Acute 
Lymphocytic Leukemia (ALL), Multiple Myeloma (MM), Non-Hodgkin Lymphoma (NHL), Chronic 
Lymphocytic Leukemia (CLL), and Chronic Myelogenous Leukemia (CML). Demographically-matched 
healthy control participants will be included for comparison. 
After diagnosis and treatment protocols have been established, patients will be inducted into the 
longitudinal study comprised of three visits: 1) after diagnosis but prior to chemotherapy treatment (baseline), 
2) one-month post-baseline or after one treatment cycle (whichever comes first), and 3) three-months 
post-baseline or after three treatment cycles (whichever comes first). Patients will undergo a test battery 
designed to measure specific behavioral and neural mechanisms of attention; tests will either be computer-
based cognitive tasks or simulated driving tests that immerse patients into virtual driving scenarios. During 
each test, EEG will be concurrently measured through non-invasive scalp electrophysiology recordings; EEG 
recordings will reveal underlying neural mechanisms affected by chemotherapy. Additionally, 
neuropsychological tests of vision, attention, and memory will be administered, as well as questionnaires to 
evaluate health, mobility, and life space. Finally, blood samples will be collected to examine levels of 
circulating inflammatory markers present in some cancer patients. This study will allow us to better 
understand the mechanisms through which chemotherapy influences cognitive performance. Results from 
this study may allow informed treatment decision-making and therapy selection based on patients’ goal of 
care and value to preserve cognitive and functional capacity. 
 
 
 

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Schema: 
 
 
Section 1.0 Objectives: 
The broad goal of this research project is to develop a core set of biomarkers for detecting 
chemotherapy related cognitive impairment (or ‘chemobrain’). Multiple clinical studies have documented 
cognitive impairment in chemotherapy patients, demonstrating impairments most frequently in attention and 
memory abilities, among other cognitive functions. Neuroimaging studies in these patients have shown 
structural and functional changes across cortical networks often linked with neural mechanisms of attention, 
including fronto-parietal cortical regions. Together, behavioral and neuroimaging studies converge on the 
hypothesis that attention networks are most impacted by chemotherapy. 
Explanatory mechanisms for chemotherapy-related cognitive impairment require further research 
and clarification for several reasons: 1) current research has focused on breast cancer populations and 

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ignored other prevalent tumor types; 2) few studies have examined dose-response effects of specific 
chemotherapy treatments on cognitive impairment; 3) neuropsychological tests used to characterize 
chemotherapy-related cognitive impairment provide limited resolution for understanding impairments of 
specific neural mechanisms; 4) neural factors associated with cognitive impairment have not been 
sufficiently distinguished from non-neural (e.g. psychosocial) factors. Despite these limitations of current 
research, chemotherapy-related cognitive impairment affects everyday function and quality of life in cancer 
survivors. This is a problem that merits further investigation and cannot be ignored. 
To overcome these critical limitations of current research on chemotherapy-related cognitive 
impairment, we propose a two-year pilot study that aims to systematically examine the influence of cancer 
stage and treatment toxicity on attention abilities in patients diagnosed with a hematological malignancy 
(HM). We will establish and measure a core battery of behavioral and electrophysiological measures of 
attention to assess the impact of chemotherapy on this central cognitive ability. 
Our specific aims are to: 
SA1. 
Quantify chemotherapy-related attention impairments in HM patients 
H1a. HM groups will not differ from comparison subjects in attention abilities prior to chemotherapy 
and will perform worse than comparison subjects without cancer or chemotherapy after 
treatment. 
H1b. Degree of chemotherapy exposure will predict magnitude of attention impairments. 
SA2.  Quantify the link between chemotherapy-related attention impairments and 
electrophysiological measures of attention in HM patients and comparison subjects 
H2a. HM groups will not differ from comparison subjects in electrophysiological measures of 
attention prior to treatment but will differ from comparison subjects without cancer or 
chemotherapy after treatment. 
H2b. Degree of chemotherapy exposure will predict magnitude of changes in electrophysiological 
measures of attention. 
H2c. Electrophysiological measures of attention decline will be predicted by concurrent impairments 
in behavioral measures of attention (as in H1b). 
SA3.  Quantify the effects of chemotherapy-related attention impairment on complex real-world 
behavior measured in controlled-simulations of on-road driving scenarios designed to 
challenge driver attention abilities 
H3a. HM groups will not differ in driving performance prior to treatment, and will perform worse than 
comparison subjects without cancer or chemotherapy. 
H3b. Degree of chemotherapy exposure will predict magnitude of changes in simulated driving 
performance. 
H3c. Declines in simulated on-road driving performance will be predicted by concurrent impairments 
in behavioral (as in H1a) and electrophysiological measures (as in H2a) of attention. 
Impact 
Our approach will allow us to more rigorously study the underlying mechanisms of chemotherapy-related 
cognitive impairment. The forthcoming pilot project promises to extend knowledge on chemobrain by 
longitudinally investigating chemotherapy treatments for hematological malignancies, an understudied 
cancer population. Results from this study will have implications for several collaborative efforts across basic 
and clinical research silos on campus, with a broad potential for impacting our knowledge, treatment, control, 
and prevention of chemotherapy-related cognitive impairment. Furthermore, this line of work promises to 
benefit the Cancer Prevention and Control Program (CPCP) – a research arm of the Fred & Pamela Buffet 
Cancer Center. Our goal is that this line of research will advance the study and understanding of risk factors 
associated with chemotherapy, allowing clinicians to make informed treatment 

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recommendations to mitigate cognitive impairment and preserve cognitive function, independence, and 
quality of life in our ever-increasing cancer survivor population. 
Section 2.0 Introduction: 
Multiple behavioral studies have documented chemotherapy-related cognitive impairment across a 
broad range of cognitive abilities, with deficits most frequently observed in processing speed1-11, 
attention7,9,10,12-20, and memory1,2,4,5,7,12-15,17,21-24,49. Although the mechanism through which chemotherapy 
influences cognitive impairment is poorly understood, chemotherapy-related cognitive decline remains an 
important public health concern, given the impact of cognitive health on quality of life. 
While behavioral measures tell us what cognitive abilities are impaired by chemotherapy, they do 
not tell us how cognitive abilities are impaired. Our hypothesis is that chemotherapy negatively affects 
neural structures underlying attention mechanisms, which in turn would impair information processing and 
memory abilities. According to current research, attention mechanisms are largely supported by the so- 
called fronto-parietal attention network52-56, a largescale cortical network comprised of frontal and parietal 
cortical regions interconnected by long-range white-matter tracks. Specifically, parietal cortex has been 
implicated in the deployment of attention mechanisms towards relevant information in the environment57-60 
and frontal cortex has been implicated in modulating goal-directed behaviors that govern mechanisms of 
attentional control61-63. Thus, impairments within fronto-parietal cortical regions would likely translate to 
concurrent impairments in attention mechanisms. 
Neuroimaging studies have revealed changes in both the structure and function of neural tissue 
after treatment, suggesting chemotherapy may have an impact on the integrity of neural architectures 
essential to impaired attention mechanisms. While some structural magnetic resonance imaging (MRI) 
studies have reported global reductions in total gray and white matter volume5,25-29, more informative 
studies have demonstrated chemotherapy-related reductions in gray and white matter volumes primarily in 
frontal30-33,50,51 and parietal30,31,34,35 cortical regions. In addition, diffusor tensor imaging (DTI) studies31,35 
have demonstrated reduced white matter track integrity between frontal and parietal cortical regions. Thus, 
MRI studies have revealed chemotherapy-related impairments in both the structure and connectivity of the 
fronto-parietal attention network. 
Extending findings provided by structural MRI studies, functional MRI studies have documented 
distributed modulations of neural activity within the fronto-parietal attention network following chemotherapy 
treatment. During performance in working memory and executive functioning tasks, chemotherapy-related 
suppression of neural activity has been shown in parietal cortex26,33,36,37,41, whereas chemotherapy-related 
enhancement of neural activity has been shown in frontal cortex26,36-41. One possible interpretation of this 
empirical pattern is that chemotherapy damages parietal networks responsible for the selection of task- 
relevant information in the environment, leading to a reduction in neural resources available in parietal 
cortex, and a subsequent hyperactivation of frontal cortex in the enforcement of top-down goals to 
compensate for impairments in parietal cortex. These functional imaging studies complement structural 
imaging studies by demonstrating concurrent abnormalities in the fronto-parietal attention network. 
Despite the growing body of literature on chemotherapy-related cognitive and neural impairment, 
research is absent for understanding the impact of chemotherapy on real-world behavior. This lacking body 
of literature is problematic because computer-based tasks and paper-and-pencil tests provide poor 
experimental fidelity for understanding the link between cognitive performance and behavior in the wild. 
Given that motor vehicle driving is a nearly ubiquitous real-world behavior that recruits multiple cognitive 
domains101, 102, and that impairments in driving performance and safety have been documented in 
individuals with low cognitive functioning103,104 and neurological disease105-109, chemotherapy-related 
cognitive impairment may be associated with poor driving performance and safety. Thus, future studies 
examining the link between chemotherapy-related cognitive impairment and real-world behaviors, such as 

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driving, will provide novel insight into the impact of chemotherapy treatment on public health and safety. 
While MRI offers high spatial resolution of cortical structures, it is limited by its low temporal 
resolution of an indirect measure of neural activity (i.e. oxygenated blood flow associated with metabolic 
demands of neurons). In contrast, scalp electroencephalogram (EEG) offers high temporal resolution of 
population-level neuro-electrical activity occurring at synapses, thus providing millisecond-by-millisecond 
resolution of direct recordings of neural activity; this level of temporal resolution is necessary for measuring 
rapid cognitive processes, such as shifts of attention or information processing. In a handful of EEG 
studies, chemotherapy-related impairments have been documented in the so-called P300 EEG 
component43-46, an electrophysiological correlate of information processing in working memory64-66, 
suggesting that chemotherapy negatively affects the amount of attention resources available for stimulus 
processing. Together, MRI and EEG studies converge on the hypothesis that chemotherapy negatively 
affects neural structure and function within the fronto-parietal attention network. 
In summary, chemotherapy negatively affects performance on behavioral measures of processing 
speed, attention, and memory, and has a profound impact on the structural and functional integrity of 
cortical regions within the fronto-parietal attention network. In the current proposal, our goal is to take a top- 
down approach to understanding how chemotherapy leads to impaired attention mechanisms. To this end, 
we will be employing a battery of cognitive (SA1) and simulated real world (SA3) tasks that target specific 
attention mechanisms; these tasks are able to measure subtle differences in attention processes within and 
between subjects on the order of milliseconds. To track task-related neural activity on the same timescale, 
we will incorporate EEG recordings into our cognitive battery (SA2) to link neural impairments of attention 
with cognitive impairments of attention in chemotherapy patients. Results from this line of research will 
provide motivation for further top-down research and new lines of bottom-up research to better understand 
how chemotherapy negatively affects the biological pathways underlying the fronto-parietal attention 
network. 
 
Motivation 
Despite numerous investigations on the impact of chemotherapy on cognitive performance, current 
research is limited in four major ways: 
First, most research has studied breast cancer patients, making it difficult to dissociate the impact 
of chemotherapy on neurocognitive dysfunction from other factors specific to the breast cancer population. 
In particular, breast cancer almost exclusively affects female populations and impacts organs integral to 
female identity. Additionally, the lack of studies examining interactions between hormone treatment and 
chemotherapy treatment on cognitive health leaves hormonal factors as an alternative explanation for 
cognitive impairment observed in this population. In order to fully demonstrate the direct impact of 
chemotherapy on cognitive function, it is necessary to study chemotherapy-related cognitive decline in a 
broader cancer population that controls for gender, psychosocial, and hormonal confounds. 
Second, the neural mechanisms of chemotherapy-related cognitive impairment remain largely 
unknown. Neuroimaging studies of chemobrain have examined blood-oxygenated level dependent activity 
associated with neural metabolic demands, and have converged on the hypothesis that chemotherapy 
affects the structural and functional integrity of frontal and parietal cortical regions. While these studies 
appear to provide some insight into the mechanisms of chemobrain, neuroimaging methods are limited 
both by their poor temporal resolution and reliance on blood-related correlates of neural activity. Given that 
chemotherapy introduces cardiotoxic effects and impairs the integrity of the blood brain barrier67-69, current 
evidence is confounded by neuroimaging methods because they measure blood-related activity. Thus, 
neuroimaging studies remain inconclusive in determining whether chemotherapy affects the function of 
frontal and parietal cortical areas or the vasculature providing metabolic demands to frontal and parietal 
regions. To rule out vasculature-related impairments associated with chemotherapy, alternative methods 

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that more directly measure neural activity, such as scalp EEG, should be incorporated into studies of 
chemobrain. Currently, only a handful of electrophysiological studies have examined the impact of 
chemotherapy treatment on a single electrophysiological component (i.e. P300), which was evoked by a 
non-demanding cognitive task. Further electrophysiological studies must incorporate more demanding 
tasks that challenge specific attention mechanisms. Given the limitations of current research on the neural 
mechanisms of chemobrain, it is still unclear how chemotherapy affects the functional integrity of the fronto- 
parietal attention network. Together, cognitive and electrophysiological measures of attention provide a 
powerful tool for isolating neural mechanisms influenced by chemotherapy treatment. Thus, more work 
should be devoted to more rigorous and targeted electrophysiological studies of attention, which will be 
integral to separating neural from non-neural factors associated with chemobrain. 
Third, neuropsychological tests typically recruit multiple cognitive domains, limiting specificity of 
impaired cognitive functions. For example, most paper-and-pencil tests recruit additional speed of 
processing and motor control abilities during task performance. Furthermore, methods for measuring task- 
related neural activity during neuropsychological testing are yet to be established. In contrast, computer- 
based cognitive tests allow researchers to selectively measure specific cognitive processes by 
manipulating display timing and stimulus characteristics, thus providing insight into how different cognitive 
systems interact during task performance. Furthermore, numerous studies have linked performance in 
computer-based cognitive tasks with neural function through MRI and EEG methods. In particular, the high 
temporal resolution of EEG methods demands cognitive testing instruments that provide concurrent 
temporal resolution through precisely timed stimulus presentation. Thus, studies of chemotherapy-related 
cognitive impairment would benefit from the incorporation of more sophisticated cognitive batteries. 
Finally, previous studies have used measures with high experimental control and low external 
validity, providing limited insight into how chemotherapy-related cognitive impairment translates to real- 
world behavior. It is essential to understand how chemotherapy affects real-world behaviors that could have 
a profound impact on public health, as impairments in these activities could lead to incursions with the 
general population. Importantly, identifying which aspects of real-world behaviors are affected by 
chemotherapy could lead to the development of targeted rehabilitation strategies, ultimately leading to 
improved cognitive health and quality of life. Thus, combining basic and translational research into future 
studies will provide better insights into how the lives of chemotherapy patients – and the lives of those in 
their surroundings – are affected on a daily basis. 
 
Section 3.0 Eligibility Criteria: 
Inclusion criteria for HM patients include: 1) HM diagnosis, 2) scheduled to receive treatment 
based on risk classification, 3) between 19 to 80 years of age, and 4) normal or corrected-to-normal vision. 
Inclusion criteria for healthy controls will be that they are matched to patient demographics. 
Exclusion criteria for HM patients include the presence of: 1) second cancer diagnosis in addition to recent 
HM diagnosis (however, patients with localized skin cancer may not be excluded), 2) prior radiation or chemotherapy 
treatment, 3) cognitive impairment (MMSE score <25) prior to baseline assessment, 4) patients who are critically ill or 
require urgent initiation of chemotherapy will be excluded from this study, 5) patients with any other condition that 
may not allow safe participation in the study based on the clinical judgment of the treating oncologist will be excluded. 
Exclusion criteria for healthy controls include HM cancer diagnosis in addition to all exclusion criteria for HM patients. 
There is the potential to detect cognitive impairment in research participants during cognitive assessment. After 
consent, if a participant receives an MMSE score of 20 or less, they will be discontinued from the study. 

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Section 4.0 Registration Procedure: 
Patients will be recruited through the Department of Internal Medicine, Division of Hematology- 
Oncology with the assistance of Drs. Vijaya Bhatt, Lori Maness, Krishna Gundabolu, Sarah Holstein, Matthew 
Lunning, James Armitage, Muhamed Baljevic, Philip Bierman, Robert Bociek, and Julie Vose. Recently 
diagnosed HM patients will contact – or be contacted by – new patient coordinators to schedule a clinical visit 
at UNMC. During initial scheduling with new patient coordinators, patient contact information will be recorded 
in a Patient Tracker, and they will be informed that research is being conducted to study cognitive abilities in 
HM patients. A brief description of the study will be included in their new patient packet. At the time of their 
clinical visit, Drs. Bhatt, Maness, Gundabolu, Holstein, Lunning, James Armitage, Muhamed Baljevic, Philip 
Bierman, Robert Bociek, and Julie Voss will provide further information about the study, and ask patients if 
they are interested in participating. Interested patients will be screened for inclusion/exclusion criteria, 
provided with informed consent during their clinical visit, and their demographic information will be collected 
after consenting to participating in the study. After their clinical visit, a member of the Mind & Brain Health 
Laboratory (MBHL) will contact consented patients to schedule their initial pre- treatment research study visit. 
MBHL lab personnel will coordinate with patient case managers to determine their next treatment date so 
that subsequent study visits can be scheduled accordingly. 
Demographically matched healthy controls will be recruited from the MBHL registry and RedCap 
(#564-10-EP: Building UNMC-based research programs focused on wellness, frailty, and aging) registry 
based on demographic information collected from HM patients who have already been inducted into the 
study. Specifically, healthy controls will be matched to HM patients along the dimensions of age (5 years), 
gender (same gender), race (same race), and education (2 years). These registries provide query options 
for search for specific demographic factors, and are comprised of individuals who have expressed interest 
in participating in research studies. In addition, spouses or caregivers of chemotherapy patients may be 
recruited as healthy controls to examine the psychosocial effects of caring for chemotherapy patients on 
cognitive abilities. 
Given the limited availability for enrollment of HM patients into this study, potential research 
patients will not be selected based on demographic factors of gender and race. Nevertheless, equal 
preference will be given to individuals across all gender and race categories. 
Research participants that have been recruited into the study will be undergo study induction either 
in the Division of Hematology/Oncology (HM patients) or in the Mind and Brain Health Labs (healthy 
controls). After study induction, all research participants will undergo the same testing battery within the 
Department of Neurological Sciences at each study visit. HM patients will complete each testing battery 
prior to undergoing their chemotherapy treatment scheduled on the same day. 
Research participants will receive monetary compensation ($20/hour) for their participation. In the event that 
adequate funding is not secured for compensation, research participants will be recruited as volunteers. 
Section 5.0 Treatment Plan of Research Design: 
Experimental Design 
Patients will be recruited from one of two targeted treatment groups, based on their risk 
stratification: 1) high risk group for examining the influence of chemotherapy on cognitive impairment; and 
2) low risk supportive care treatment schedules, which represents the chemotherapy control group. 
Additionally, we will recruit a demographically matched (matched at age, gender, and educational status) 
healthy control group, which will serve as the cancer and chemotherapy control group. 
Participants will complete a three-month longitudinal study that will examine the parametric effects 
of HM-specific chemotherapy treatments on cognitive and electrophysiological measures of attention 

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mechanisms. We will sample during intervals corresponding to the onset of treatment cycles, thus giving us 
the opportunity to examine additive dose-response effects of chemotherapy treatment. Sampling intervals 
for chemotherapy patients (or control patients) will occur according to the following schedule: 1) after HM 
diagnosis but prior to receiving chemotherapy treatment, providing a baseline assessment, 2) one month 
after baseline assessment or after one treatment cycle (whichever comes first), 3) three months after 
baseline assessment after three treatment cycles (whichever comes first). 
Experimental Control Measures. There are several health factors that may be affected by HM 
disease and treatment that could potentially impact cognitive performance independent of chemotherapy 
treatment per se. To mitigate these potential confounds, we will measure these factors across patients and 
controls to include as cofactors during the modeling procedure of our analysis. If there is a link between 
factors unrelated to chemotherapy and variability in cognitive performance across groups, we will include 
these additional cofactors in the final model to control for these confounds; if there is no link between 
factors unrelated to chemotherapy and variability in cognitive performance, we will not include these factors 
in the final model. 
Experimental control measures will include: 
฀ Disease Comorbidity. Patients may have other diseases in addition to the HM diagnosis critical 
to the current proposal. Hematopoietic cell transplantation-comorbidity index (HCT-CI) is a tool 
commonly utilized in the transplant setting that measures multiple organ impairments across 
17 different categories of organ dysfunction. Results from the HCT-CI are summated into a 
single total score, which will serve as a baseline measurement of disease comorbidity. Patients 
without any known or suspected cardiac or pulmonary diseases will be considered to have 
normal echocardiogram and pulmonary function test during calculation of HCT-CI. 
฀ Anemia. HM patients will likely suffer from anemia that could result in fatigue. To control for 
anemia-related fatigue on cognitive ability, we will measure blood cell counts in patients and 
control participants. Blood cell counts will be collected from HM patients’ most recent clinical 
visits. For healthy controls, we will obtain blood cell counts from their most recent clinical visit 
as well, though this measure may not be as recent as that of an HM patient; given that we do 
not anticipate these levels changing significantly in the healthy population, larger variability in 
the difference between blood and cognitive testing will not impose any limitation on our 
experimental design. 
฀ Health and Mobility Questionnaires. Several questionnaires will be used to determine health, 
mobility, psychosocial status, and medication usage; these measures will be used to control for 
non-neural factors that may contribute to cognitive health. Questionnaires to be administered 
include: Beck Depression Inventory (depression screen), medication usage form (list of current 
medications), health survey questionnaire (inventory of health status and activity level), and life 
space questionnaire (mobility inventory). 
Attention Battery 
The goal of Specific Aim 1 is to construct a cognitive battery that decomposes the general 
construct of attention into its underlying mechanisms, enabling the examination of chemotherapy-related 
impairments across multiple processes of attention. To this end, we selected tasks that isolate four 
mechanisms of attention: 1) processing speed – time required to attend and recognize an item, 2) inhibitory 
control – ability to ignore irrelevant items, 3) disengagement speed – time required to release attention from 
an item, and 4) storage capacity – number of items that can be simultaneously attended. 
Attention mechanisms measured by our battery are relevant to daily activities in the real world, 
such as holding a conversation in a noisy diner. For example, while listening to a friend speaking (i.e. target 
stimulus), the sounds of other patrons speaking (i.e. irrelevant stimulus) or dishes crashing to the floor (i.e. 

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distractor stimulus) compete for our limited attentional resources, thus providing opportunities for our 
attention to be distracted away from our friend speaking and towards an irrelevant stimulus. This 
hypothetical scenario provides examples of the four attention mechanisms measured in Specific Aim 1: 
speed at which speech of friend can be processed to understanding (processing speed), ability to ignore 
other patrons speaking and dishes crashing (inhibitory control), speed at which attention can be released 
from a distracting stimulus and re-engaged with the conversation (disengagement speed), and how much 
information from the conversation can be held in memory (storage capacity). 
Collectively, our cognitive battery will offer millisecond-by-millisecond resolution of attention 
processes engaged by participants during task performance. 
Capture task. Capture tasks70-74 are an ideal candidate for studying attention because they offer 
experimenters a tool to precisely measure the cost of processing an irrelevant stimulus within a capturing 
display (inhibitory control mechanism) and the timecourse of releasing attention when it is captured by an 
irrelevant stimulus (disengagement speed mechanism). 
In this task (Figure 2), participants are instructed to identify a target item (e.g. a green square with 
a notch on one side) presented among multiple distractor items within a search display; prior to the search 
display, a brief capture display is presented that contains a colored distractor item similar (contingent 
condition) or dissimilar (singleton condition) to the target color. Performance is measured as response time 
to correctly identify and respond with the location of the notch in target items. Previous studies have 
demonstrated: 1) longer reaction times in the contingent condition relative to the singleton condition, 
because attention is more likely to be distracted by a contingent stimulus that matches the target stimulus 
color, and 2) shorter reaction times in both conditions at longer inter-stimulus intervals (ISI; time difference 
between capture display and search display), because attention is more likely to disengage from the 
capturing stimulus prior to the onset of the search display when ISIs are longer. 
In the current proposal, we will be able to directly measure the effects of chemotherapy treatment 
on inhibitory control mechanisms as they apply to the suppression of an irrelevant stimulus and 
disengagement mechanisms as they apply to the release of captured attention from an irrelevant stimulus. 
 
Filtering task. Filtering tasks75,76 are an ideal candidate for studying attention because they offer 
experimenters a tool to precisely measure the amount of information that can be simultaneously attended 
(storage capacity mechanism) and the efficiency to filter out irrelevant information embedded among 
relevant information (inhibitory control mechanism). 
In this task (Figure 3), participants are instructed to remember the value (e.g. orientation) of target 
items (e.g. blue lines) during a blank delay period (storage condition); on some trials, participants are 
instructed to ignore distractor items (e.g. red lines) presented simultaneously among target items (filtering 
condition). Performance is measured as response accuracy of correctly reporting the presence or absence 
of a target value change in a memory probe following the blank delay period. Previous studies have 

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demonstrated: 1) lower response accuracy as the number of relevant items to be remembered increases, 
2) lower response accuracy in filtering conditions relative to storage conditions when the number of relevant 
items is held constant across conditions, and 3) individuals with larger storage capacities show smaller 
costs in response accuracy in the filtering condition. 
In the current proposal, we will be able to directly measure the effects of chemotherapy treatment 
on storage capacity mechanisms as they apply to the amount of information that can remembered and 
inhibitory control mechanisms as they apply to the suppression of irrelevant information. 
 
 
Mobile cognitive testing. To track the timecourse of cognitive impairment between 
chemotherapy treatment cycles, patients will be given the option to complete customized attention tasks at 
home using BrainBaseline (Digital Artefacts), a mobile cognitive testing platform for use on a personal iPad 
or iPhone. De-identified data will be wirelessly transferred to HIPAA compliant servers maintained by 
Digital Artefacts. 
Electrophysiology 
The goal of Specific Aim 2 is to measure scalp electrophysiology to examine chemotherapy-related 
impairments in the neural mechanisms of attention on the timescale of milliseconds. To this end, we 
selected electrophysiological components that isolate four specific attention mechanisms: 1) deployment 
speed – time required to rapidly shift attention from one location to another, 2) target enhancement – 
amount of neural resources allocated towards selection of target item, 3) distractor suppression – amount 
of neural resources allocated towards inhibition of distractor item, and 4) online storage – amount of 
resources allocated toward storing target items in mind. 
N2pc. The N2pc component77-80 has been used in multiple empirical studies to examine neural 
mechanisms of attention because it reveals both when and where attention is being deployed early during 
visual processing. The N2pc is a relative negative amplitude deflection in posterior parietal electrodes with 
latency of 175-250 milliseconds, with more negative amplitudes occurring in electrodes contralateral to the 
attended visual field (Figure 4 left panel). For example, when attention must be deployed towards a target 
stimulus (e.g. a blue square outline with a notch on one side) presented in the left visual field, 
electrophysiological amplitudes observed in posterior parietal electrodes are more negative in contralateral 
(i.e. right hemisphere) electrodes relative to ipsilateral (i.e. left hemisphere) electrodes during the N2pc time 
window. 
N2pc latency tracks deployment speed, where longer latencies suggest slower deployment speed; 
N2pc amplitude tracks target enhancement, where larger amplitudes suggest more resources were 
allocated towards target selection. Here, the N2pc component will be used to measure chemotherapy- 
related differences in target selection during capture and filtering tasks. 
Pd. The Pd component81-83 was more recently discovered and has been used to study inhibitory 
control mechanisms of attention due to its sensitivity to ignoring irrelevant information. The Pd is a relative 

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positive amplitude deflection in posterior electrodes with latency of 200-300 milliseconds, with more positive 
amplitudes occurring in electrodes contralateral to an ignored visual field (Figure 4 middle panel). 
Pd latency tracks deployment speed, where longer latencies suggest slower deployment speed; Pd 
amplitude tracks distractor suppression, where larger amplitudes suggest more resources were allocated 
towards inhibiting distractor items. Here, the Pd component will be used to measure chemotherapy-related 
differences in distractor suppression during the capture task. 
Contralateral Delay Activity (CDA). The CDA component has been used in multiple empirical 
studies to examine neural mechanisms of attention specific to storage capacity because it tracks both 
which information is being stored in mind and how much information is being stored in mind 75,76,84. The 
CDA component is a sustained relative negative amplitude modulation in posterior electrodes that onsets at 
approximately 300-400 milliseconds, with more negative amplitudes occurring in electrodes contralateral to 
the remembered visual field (Figure 4 right panel). CDA amplitude tracks online storage, where larger 
amplitudes suggest that more items are stored in mind75,76. Here, the CDA will be used to measure 
chemotherapy-related differences in storage capacity during the filtering task. 
 
Driving Simulation 
The goal of Specific Aim 3 is to implement simulations of driving scenarios that integrate 
laboratory-based attention mechanisms into a naturalistic environment that requires the coordination of 
multiple cognitive domains, including attention. By selectively challenging distinct attention mechanisms 
under different driving conditions and loads (e.g. traffic, pedestrians, road signs), we will be able to evaluate 
how impairments in attention affects driving outcomes. Broadly speaking, the goal of testing patients in 
simulated driving scenarios is to determine how computer-based cognitive tasks (SA1) translate into real- 
world driving behavior. 
Car following task. The car following task requires drivers to follow a lead vehicle at a constant 
distance of two car lengths85,86. During this task, the lead vehicle pseudo-randomly changes its velocity, 
requiring drivers to vigilantly attend the lead vehicle to avoid an incursion while maintaining the instructed 
two-car length distance. Critically, the lead vehicle will occasionally brake during the drive, requiring drivers 
to rapidly brake in order to avoid collision. If attention is not fixed on the lead vehicle, an accident will likely 
occur. Outcome measures for the car following task include: 1) mean distance between lead vehicle and 
driver, 2) brake delay, measured as the delay between lead vehicle and driver braking time, and 3) crash, a 
binary variable that indicates if a collision occurred. 

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The car following task requires the recruitment of the following attention mechanisms: 1) 
processing speed, used to process and update working memory with task-specific cues (e.g. braking, 
change of speed) provided by the lead vehicle, 2) target enhancement, required to enhance task-specific 
lead vehicle cues, and 3) inhibitory control, required to inhibit the processing of irrelevant environmental 
information (e.g. other vehicles, pedestrians, etc.). 
Visual search task. The visual search task87-91 requires participants to search for a target item 
among multiple distractor items while driving; this task uses displays similar to the search display of the 
capture task. Search item configurations can be manipulated to evoke either the N2pc or the Pd to 
measure attentional shifts related to target enhancement or distractor suppression, respectively, during 
driving performance. This line of research will be the first to examine rapid shifts of attention during driving 
behavior. 
The visual search task requires the recruitment of the following attention mechanisms: 1) 
processing speed, used to process each search item in turn in order to find the target item, 2) deployment 
speed, used to rapidly shift attention towards candidate search items, and 3) target enhancement, used to 
resolve target items from distractor items. 
 
 
Specific Aim 1 
Specific Aim 2 
Specific Aim 3 
Attention 
Mechanism 
Capture Task Filtering Task N2pc Pd CDA Car Following Visual Search 
Processing Speed 
X 
 
X 
X 
Deployment Speed 
X 
X 
X 
Target Enhancement 
X 
X 
X 
Distractor 
Suppression 
 
X 
Inhibitory Control 
X 
X 
 
X 
X 
Disengagement 
Speed 
X 
 
Storage Capacity 
X 
 
X 
Table 2: Summary of attention mechanisms probed in 
each specific aim Auxiliary Measurements 
In addition to the proposed battery, we will administer several neuropsychological exams to 
determine whether the range of cognitive impairments predominately observed in the breast cancer 
population are reflected in the HM population. These exams will give us the opportunity to link patterns of 
cognitive impairment between cancer populations. Additionally, we have selected novel measures 
(circulating inflammatory proteins, retinal anatomy) within the domain of the chemobrain literature to further 
explore the impact of chemotherapy on the brain and body. 
Cognitive assessment. Clinical neuropsychological exams to be used in the current proposal 
include: Mini-Mental State Examination5,14,20 (MMSE; mental status, dementia screening tool), Trails A and 
B1-4,6-11,15,18,20,22-24,35 (processing speed), Useful Field of View (UFOV; processing speed, divided attention, 
inhibitory control), Paced Auditory Serial Attention Task18,23 (PASAT; working memory, arithmetic), 
Stroop2,3,5-9,12,17,23,24 (executive function). 
Vision assessment. Clinical measures of visual deficits to be used include: visual acuity, contrast 
sensitivity (discrimination threshold for light and dark boundaries), frequency doubler task (visual field 
deficits), visual function questionnaire (self-reported impairment of visual function), and neuro- 
ophthalmology supplement (NAS)-10 (self-reported impairment of visual function). 

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Retinal anatomy. Retinal anatomy is an underutilized tool for studying the link between brain 
disease and cognitive impairment, particularly in cancer populations. Optical coherence tomography (OCT) 
provides an easy, non-invasive and reliable method of studying retinal anatomy in healthy and diseased 
populations. With an axial resolution of 4-6 micrometer, the new generation spectral domain OCT can 
reliably identify the various neuronal layers of the retina. 
Previous work has demonstrated a link between retinal anatomy integrity and 
neurodegeneration110, particularly in Alzheimer’s Disease111, Parkinson’s Disease112, and Multiple 
Sclerosis113. In the current proposal, OCT measurements will allow us to determine the presence of 
neurodegeneration of the retina in cancer patients receiving chemotherapy, and link declines in retinal 
anatomy integrity with concurrent declines in cognitive performance. Thus, this method has potential to 
further develop non-invasive and rapid imaging biomarkers for chemotherapy-related cognitive impairment. 
Cirrus HD-OCT (Carl Zeiss Meditec Inc.) will be used to obtain scans of the retina and optic nerve. 
Specifically, the Macular Cube and the Optic disc cube scans will be performed at each visit. These scans 
can be performed without the need for pupillary dilation and takes about 2 minutes per eye. The relevant 
parameters obtained with the optic nerve scan includes the retinal nerve fiber layer thickness (global 
average, quadrant average and clock hour average). The macular cube scans will provide the ganglion 
cell/inner plexiform layer thickness (global average and sector average) and macular thickness. 
Given the link between retinal anatomy and neurodegeneration, which has direct implications for 
cognitive impairment, OCT will be measured for all three groups across the three study visits in the 
following manner: HM groups will undergo OCT measurement at all three study visits; given that we 
anticipate minimal variability in healthy participants across a three-month time period, a randomly sampled 
subset of healthy controls (n=10) will undergo OCT across all three study visits. This measurement protocol 
will allow us to control for any within-subject variability in retinal anatomy that may be observed across 
groups so that we can account for concurrent variability in cognitive performance. 
Circulatory Inflammatory Proteins. Circulatory levels of cytokine interleukin (IL) proteins and C- 
Reactive Proteins (CRPs) have been found to negatively affect brain function. Specifically, increased levels 
of IL proteins92-97 and CRPs116-118 have both been associated with impairments of memory and executive 
function, and has been implicated as a potential mechanism for chemotherapy-related cognitive 
impairment114,115. Given tumor presence and chemotherapy treatment associated with increased levels of 
these proteins in the blood98-100, measurement of inflammatory protein levels is essential to further 
understand the link between cancer, chemotherapy, and cognitive impairment. 
Given the link between inflammatory protein concentration levels and cognitive impairment, CRP 
concentrations will be measured for all three groups at all three study visits; this measurement protocol will 
allow us to control for any within-subject variability in CRP concentration levels that may be observed 
across groups so that we can account for concurrent variability in cognitive performance. 
 
Section 6.0 Measurement of Effect: 
Cognitive Battery 
฀ 
Response time (Capture Task) and response accuracy (Filtering Task) 
Electrophysiology 
฀ 
Amplitude and latency of N2pc, Pd, and CDA electrophysiological components 
Driving Simulation 
฀ 
Response time (Visual Search Task) 
฀ 
Brake time, mean following distance, and number of incursions (Car Following Task) 
CRP 
฀ 
Concentration levels of circulating inflammatory proteins 

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OCT 
฀ 
Surface area and volume of retinal ganglion cell layer and optic nerve fiber 
Given that we are not proposing an intervention trial our primary outcome measures will not be related to 
the progression of HM. 
Section 7.0 Study Parameters: 
Summary of Study Events and Durations. Each study visit is anticipated to take approximately 2.5 
hours to complete. Table 1 contains a summary for the schedule of study events to occur at each research 
component. Study induction takes place at the beginning of Visit 1. Time requirements for research 
participants at each study event are as follows: 
฀ Study Induction (~.5 total hours): 
o Informed consent (20 minutes) 
o Demographic Information (10 minutes) 
o Comorbidity Index (conducted offline) 
o Anemia Evaluation (conducted offline 
฀ Each Study Visit (~2.5 total hours): 
o Cognitive Battery (40 minutes) 
o Electrophysiology (15 minutes) 
o Driving Simulation (20 minutes) 
o Neuropsychological Exams (45 minutes) 
o Health & Mobility Questionnaires (10 minutes) 
o OCT (10 minutes) 
o Blood Collection (10 minutes) 
 
Pre- 
Induction 
Study 
Induction 
Visit 1 
(Month 
0) 
Visit 2 
(After Month 1 or 
1 treatment 
cycle) 
Visit 3 
(After Month 3 or 
3 treatment 
cycles) 
HM Diagnosis 
X 
Control Group ID 
X 
Informed Consent 
X 
Demographic 
Information 
X 
Comorbidity Index 
X 
Anemia Evaluation 
X 
Chemotherapy 
Treatment 
 
X 
X 
X 
Cognitive Battery 
X 
X 
X 
Electrophysiology 
X 
X 
X 
Driving Simulation 
X 
X 
X 
Neuropsychological 
Exams 
X 
X 
X 
Health & Mobility 
Questionnaires 
X 
X 
X 

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OCT 
X 
X 
X 
Blood Collection/ 
Protein Assay 
X 
X 
X 
 
Section 8.0 Drug Formulation and Procurement: 
This pilot study is not a pharmaceutical trial. 
Section 9.0 Toxicity and Adverse Event Reporting Guidelines: 
 
 
There is the potential to detect cognitive impairment in research participants during cognitive 
assessment. After consent, if a participant receives an MMSE score of 20 or less, they will be discontinued 
from the study. If cognitive impairment is identified, research personnel will proceed in the following way. 
First, the participant will be informed that an unexpected finding was encountered that may have clinical 
significance, and that the clinical significance is best determined in conjunction with his or her primary care 
physician. Next, research personnel will ask the participant for their permission to contact their primary care 
physician to help facilitate follow-up to determine clinical significance. The primary care physician will then 
be contacted and provided clinical context and concerns sufficient to allow for subsequent evaluation, 
workup, and treatment of any unexpected finding. If the participant refuses to have the research personnel 
directly contact their physician, the research personnel will offer the participant a written explanation that an 
abnormal neurological finding was encountered and the written material will include encouragement to have 
an evaluation, as well as a phone number of the Mind and Brain Health Labs to contact with questions or in 
case they change their mind. 
nsiderations: 
Our primary goal is to examine the effects of chemotherapy on behavioral and electrophysiological 
measures of cognitive ability in an understudied cancer population. To this end, analyses for the proposed 
pilot project will be performed on three groups: healthy controls (no cancer, no chemotherapy), very-low to 
intermediate risk HM patients receiving supportive care treatment (no chemotherapy), and intermediate to 
very-high risk HM patients receiving chemotherapy treatment. 
Statistical Power. Although many of the statistical analyses will involve complex modeling 
procedures, the main emphasis of our aims and hypotheses is to determine differences between groups 
and pre-post treatment. Hence, the issue of statistical power can be addressed via consideration of the 
magnitude of standardized effect sizes that can be detected with reasonable probability. The current study 
aims to collect pilot data and demonstrate protocol feasibility for future studies and funding opportunities. 
As such, we plan to obtain 15 samples per group for a total sample size of 45. 
While we realize we will not have sufficient power to declare smaller effects statistically significant, 
as this is a pilot study, it will allow us to estimate effect sizes for a number of outcomes to conduct fully 
powered studies. In future large-scale confirmatory studies, with a sample size of 32 per group, we will 
have 80% power to detect a standardized effect size of 0.65 (a medium to large effect) for within group 
changes, and an effect size of .9 for between group differences. These power calculations assume a two- 
tailed alpha of 0.01 to informally adjust for multiple comparisons and multiple testing. A standardized effect 
size of 0.65 corresponds to a 10% difference in response time from healthy controls (mean=1394.75, 
standard deviation = 213.23). This sample size will allow adequate power to detect medium to large effects 
within group, and large effects between groups. 
Statistical Analysis. To assess the data collected, for each group, we will first produce frequency 
tables, calculate descriptive statistics, and create univariate graphs (e.g. box-plots, histograms) on the 
This research has been classified as Minimal Risk. 

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predictor and response variables to investigate distributional properties and check for outliers in the data. 
Although the specific statistical models that we will use to test our formal hypotheses and to calculate 
confidence intervals will depend on the outcome distributions that we observe in our data, we anticipate 
using linear mixed models and generalized linear mixed models, as appropriate. This modeling approach 
allows us to properly account for the distribution of the outcome measure while also properly modeling 
repeated effects and adjusting for potentially confounding variables. Confidence intervals of all effects will 
be calculated in order to assess clinical significance of statistical results. 
We will employ linear mixed models and general linear models to assess within-subject, between- 
subject, and mixed effects of: 
฀ Behavior: 
o Capture condition, stimulus ISI, and treatment group on response time measures in the 
Capture Task 
o Filtering condition, storage load, and treatment group on response accuracy measures in the 
Filtering Task 
฀ Driving simulation: 
o Treatment group on response time measures in the Visual Search Task 
o Treatment group on lead car distance variability, brake time, and number of incursions during 
the Car Following Task 
฀ Electrophysiology: 
o Capture condition, stimulus ISI, and treatment group on Pd (amplitude, latency) and N2pc 
(amplitude, latency) measures during the Capture Task of the Attention Battery 
o Filtering condition, storage load, and treatment group on N2pc (amplitude, latency) and CDA 
(amplitude) measures during the Filtering Task of the Attention Battery 
o Treatment group on N2pc (amplitude, latency) and Pd (amplitude, latency) measures during 
the Visual Search Task of the Driving Simulation 
Our primary hypothesis is that chemotherapy treatment negatively affects core neural mechanisms 
of attention. Here, we present predictions for how chemotherapy would affect outcome measures from each 
task and electrophysiological measure, where specific predictions are given based on how impairments in 
different attention mechanisms would affect the pattern of data observed in each task. 
Attention Measures 
Capture task. Two dissociable mechanisms of attention are measured in this task. First, inhibitory 
control is required to suppress the processing of the capture display; inhibitory control mechanisms will be 
tracked by the Pd component. Second, disengagement speed is required to rapidly release attention from 
capture displays to prepare for the subsequent search display; disengagement mechanisms will be tracked 
by the N2pc component. There are three possible predictions for impairments in each attention measured 
in the capture task. 
฀ Hypothesis 1: Inhibition effect/No disengagement effect. Relative to comparison subjects, this 
hypothesis predicts a chemotherapy-related: 1) increase in response time differences between 
contingent and singleton capture conditions, 2) increase in Pd amplitude, and 3) decrease in N2pc 
amplitude. 
฀ Hypothesis 2: No inhibition effect, disengagement effect. Relative to comparison subjects, this 
hypothesis predicts a chemotherapy-related: 1) increase in response times in both capture conditions, 
2) decrease in N2pc amplitude, and 3) no difference in Pd amplitude. 

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฀ Hypothesis 3: Inhibition effect, disengagement effect. Relative to comparison subjects, this hypothesis 
predicts a chemotherapy-related: 1) increase in response times in both capture conditions, 2) increase 
in response time differences between contingent and singleton capture conditions, 3) increase in Pd 
amplitude, and 4) decrease in N2pc amplitude. 
Filtering task. Two dissociable mechanisms of attention are measured in this task. First, inhibitory 
control is required to suppress the encoding of distractor items; inhibitory control mechanisms will be 
tracked by both the N2pc and CDA electrophysiological components. Second, sufficient storage capacity is 
required to maintain multiple items in working memory during the delay period; storage capacity will be 
tracked by the CDA electrophysiological component. There are three possible predictions for impairments 
in each attention mechanism measured in the filtering task. 
฀ Hypothesis 1: Capacity effect, no inhibitory control effect. Relative to comparison subjects, this 
hypothesis predicts a chemotherapy-related: 1) decrease in response accuracy in both storage and 
filtering conditions, 2) decrease in CDA amplitude, and 3) no difference in N2pc amplitude. 
฀ Hypothesis 2: No capacity effect, inhibitory control effect. Relative to comparison subjects, this 
hypothesis predicts a chemotherapy-related: 1) decrease in response accuracy only in the filter 
condition, 2) increase in N2pc amplitude, and 3) increase in CDA amplitude. 
฀ Hypothesis 3: Capacity effect, inhibitory control effect. Relative to comparison subjects, this hypothesis 
predicts a chemotherapy-related: 1) increase in response accuracy differences between filtering and 
storage conditions, 2) increase in N2pc amplitude, and 3) increase in CDA amplitude. 
Car following task. According to the hypothesis that chemotherapy treatment impairs processing 
speed, a chemotherapy-related decline should be observed in car-following performance because fewer 
resources would be available for processing lead vehicle events. Specifically, delayed processing would 
lead to delayed updating of lead vehicle driving information, which would lead to greater variability in car- 
driver distance and longer delay in driver brake onset, where longer brake delays would lead to more 
crashes. 
Visual search task. According to the hypothesis that chemotherapy treatment impairs deployment 
speed, a chemotherapy-related increase in response time should be observed because attentional 
resources will be slower to deploy; furthermore, changes in the complexity of the driving environment (e.g. 
road hazards, high visual load) would lead to longer response times as a function of complexity because 
attentional resources would be more engaged with more complex environments, leading to poorer inhibitory 
control. For electrophysiology, this hypothesis predicts chemotherapy-related reductions in N2pc amplitude 
and increases in N2pc latency – because lower inhibitory control would lead to a lower probability of being 
prepared to deploy attention towards the task-relevant search display. 
Auxiliary Measures 
Cognitive assessment. According to the hypothesis that chemotherapy impairs attention 
mechanisms, we predict impairments in performance across neuropsychological exams within the cognitive 
assessment, because these tests measure cognitive abilities directly related to attention. For example, 
memory tests (e.g. CVLT, BVRT) require attention to successfully encode information into memory storage; 
failures of attention would lead to failures of encoding into memory, and thus impairments in memory 
retrieval. 
Vision assessment and retinal anatomy. Our hypothesis is that chemotherapy negatively affects 
higher-level attention mechanisms, such that attention impairments cannot be explained by impairments in 
low-level visual processes. Therefore, we predict no changes across vision assessment exams and 
questionnaires. Conversely, given the hypothesis that chemotherapy leads to morphological changes in 

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neural structures, and the fact that the retina is a neural structure, we do predict reductions in retinal and 
optic nerve thickness. 
C-Reactive Proteins. According to previous work, circulatory levels of C-Reactive Proteins (CRPs) 
increase in response to inflammation, including tumor genesis and growth. We therefore predict an 
increase in CRP levels in HM patients relative to healthy controls; furthermore, we predict further increase 
in CRP levels in HM patients receiving chemotherapy relative to HM patients receive best supportive care 
treatment. Finally, we hypothesis that increases in CRP levels will predict concurrent increases in attention 
impairment both within and between research participants. 
Section 11.0 Records to be Kept: 
The following forms will be collected during each study visit, and stored in locked filing cabinets within keycard 
restricted lab space in the Mind and Brain Health Labs (first floor of Clarkson Doctor Building North). Data 
collection forms will be entered electronically into a study database on a password-protected, encrypted, 
dedicated research network. 
฀ Phone Screen Script 
฀ Patient Tracker 
฀ Demographic Form 
฀ MMSE Data Collection Form 
฀ HM Data Collection Form 
฀ Hematopoietic Cell Transplant Co-Morbidity Index (HCT-CI) 
฀ Beck Depression Index 
฀ Life Space Questionnaire 
฀ Medication Form 
฀ Health Survey 
฀ Visual Function Questionnaire 
฀ Far Visual Acuity Form 
฀ Contrast Sensitivity Form 
฀ Frequency Doubler Task (FDT) Record Sheet 
฀ Trails A Data Collection Form 
฀ Trails B Data Collection Form 
฀ Stroop Test – Participant Form 
฀ Stroop Test – Scoring Form 
฀ PASAT Scoring Sheet 
฀ UFOV Scoring Sheet 
In addition to the forms indicated above, electronic records of performance during the cognitive, 
electrophysiological, and simulation batteries will be maintained in their raw form on password protected 
computers. After completing each testing battery, raw data will be stored on a password-protected, encrypted, 
dedicated research network. 
Section 12.0 Patient Consent: The consent form must adhere to the guidelines established by the 
Institutional Review Board of the University of Nebraska Medical Center. 
 
Section 13.0 References 

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