The University of Chicago

Behavioral control as a moderator for stimulant-

enhanced performance on executive functioning tasks

by Margarit Davtian

August 2010

A paper submitted in partial fulfillment of the requirements for the Master of Arts

degree in the Master of Arts Program in the Social Sciences

Faculty Advisor: Harriet de Wit

Preceptor: Christy Hoffman

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Abstract

While there is a broad literature to suggest that healthy individuals may be motivated to

use amphetamine in part because of its cognitive enhancing effects, it is also known that

individuals vary in their responses to amphetamine, perhaps because of differences in dopamine

function. The present study proposed that trait levels of behavioral control may moderate

individual variations in the effects of stimulants on cognitive performance, particularly on

executive functioning tasks. Using a double-blind, randomized, within-subjects design, the study

measured both the simple (i.e. psychomotor reaction time) and complex (i.e. executive

functioning) cognitive performance of healthy participants high and low in behavioral control,

after receiving a placebo, 5 mg, 10 mg, and 20 mg, dose of d-amphetamine. The results showed

that d-amphetamine improved psychomotor reaction time in a dose-dependent manner within the

entire sample, without improving executive functioning measures. Stimulant effects on executive

functioning performance were also not observed when individuals were split into high and low

behavioral control groups. Taken together, these results demonstrate the dissociative effects of

stimulants on various cognitive domains, suggesting a more thorough investigation of the neural

correlates underlying individual variability in stimulant abuse patterns.

Introduction

Stimulants such as amphetamine, caffeine, and nicotine are among the most widely used

substances of abuse. These drugs share the ability to sustain attention, heighten vigilance,

diminish fatigue, and increase general work output (Koelega, 1993; Lieberman et al., 1987b); as

such, the cognitive effects of stimulants may contribute to their illicit use and abuse.

Improvements in cognition have been observed with the administration of the typical stimulant

d-amphetamine and the psychostimulant drug methylphenidate (Ritalin) when used in clinical

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settings to treat impairments in attention and impulsivity characteristic of children with attention

deficit/hyperactive disorder (ADHD; Barkley, 1997). Controlled studies have revealed that the

acute administration of d-amphetamine also improves healthy participants’ performance on such

lower-order cognitive tasks as rapid information processing, short-term memory, and

psychomotor reaction time (Fillmore et al., 2005; Ward et al., 1997; Pigeau et al., 1995; de Wit

et al., 2002). In light of these findings, some researchers have proposed that healthy individuals

may be motivated to use illicit stimulants such as cocaine and amphetamines both because of the

reinforcing euphoric properties and the desire to self-medicate behavioral or cognitive deficits

similar to, but in a milder form, than those seen in ADHD children (Khantzian, 1985; Schiffer,

1988; Mattay et al., 2003). However, individuals differ in their cognitive responses to

amphetamine, perhaps due to differences in underlying neural mechanisms (Fillmore et al.,

2003). Some theorists argue that individual differences in abuse vulnerability can be partly

explained by a marked variability in acute behavioral and cognitive responses to amphetamine,

with some individuals benefiting from its cognitive enhancing effects more than others (Kimberg

et al., 1997), thereby heightening their risk for abuse. However, individual variability in

stimulant-enhanced performance effects have been difficult to predict a priori, and few

psychopharmacological explanations for individual differences have been established. The

purpose of the present study, therefore, is to explore the variability in healthy participants’

responses to d- amphetamine by investigating the relatively unexamined characteristic of

behavioral control as a potential moderator of its cognitive enhancing effects. That is, I will

investigate whether individuals high or low in behavioral control exhibit different responses to

an acute dose of d-amphetamine on measures of cognitive abilities, particularly executive

functions.

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Behavioral control is a cognitive ability, specifically within the domain of executive

functioning. The key characteristic of behavioral control, which is the ability to inhibit or

terminate a prepotent response, provides a framework for understanding many basic inhibitory

and attentional processes (Baddeley & Della Sala, 1996) that result in the “disinhibition” or

“dyscontrol” of behavior when disrupted. For example, lesion studies in rodents have

demonstrated that damage to prefrontal cortex (PFC) areas disrupts presynaptic dopaminergic

pathways and generates a wide range of behavioral disturbances manifested by impulsive,

exaggerated, or extreme behaviors (Oscar-Berman, 1978; Jentsch & Taylor, 1999). The cognitive

and behavioral dysfunctions that characterize ADHD have also been attributed to impaired

inhibitory mechanisms related to prefrontal dopaminergic pathways (Tannock, 1998; Barkley,

1997). Thus, the basic inhibitory mechanisms controlled by these dopaminergic pathways may

“set the stage” for other lower-order cognitive abilities (Barkley, 1997), as well as higher-order

executive functions (Figure 1). For this reason, deficiencies in cognitive and behavioral functions

have often been understood according to a “bottom-up” theory, such that basic behavioral control

processes impair the proper functioning of higher-order executive tasks (Barkley, 1997). For

• RIP

• Short-term memory

• Psychomotor

reaction time

Figure 1. Distinction between higher-order executive functions and lower-order cognitive

abilities.

Lower-order

Cognitive Abilities

Higher-order

Executive Functions

Behavioral Control

• Working

memory

• Cognitive

Flexibility

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example, researchers have found that stimulants generally enhance cognitive functioning in

children with ADHD and in healthy individuals initially poor at inhibiting their responses. This

enhancement of cognition may result from a facilitation of inhibitory mechanisms that control

attention regulation involved in disregarding non-relevant stimuli in order to process and respond

to relevant stimuli (Finn, 2002; Neill & Valdes, 1996). Thus, while behavioral control is a subset

of executive functioning, it serves as an important building block for the execution of other

cognitive operations. This “bottom-up” approach may be critical in understanding individual

differences in stimulant effects on more complex executive abilities because it indicates that

stimulants may improve executive functioning performance via the more basic inhibitory

processes of behavioral control (Jentsch & Taylor, 1999).

Executive functions refer to a set of higher order cognitive abilities that enable an

individual to inhibit, shift, plan, and organize information in order to achieve a desired goal

(Baddeley, 1986). Important executive functions include working memory (e.g. rapid monitoring

and manipulation of stimuli), cognitive flexibility (e.g. shifting and reconstructing information),

and behavioral control (e.g. inhibiting a prepotent response). These functions are subserved by

frontal and prefrontal cortex (PFC) regions that receive extensive input from subcortical

dopamine (DA) systems (Kane & Engle, 2002; Berger, Gaspar, & Verney, 1991). Amphetamine

and methylphenidate enhance general cognitive performance by mimicking and blocking the

reuptake of the catecholamine dopamine (DA) and increasing its levels by stimulating release

from the presynaptic terminal (Solanto, 1998). Because DA signaling is critical for cognitive

functions subserved by cortical and subcortical areas (Floresco & Magyar, 2006), it is generally

hypothesized that stimulants enhance performance by increasing DA neurotransmission to these

regions (Mehta & Riedel, 2006). Consistent with this idea, stimulants are particularly effective in

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improving the cognitive performance in individuals who are believed to be low in baseline

stimulation of DA receptors (e.g. ADHD children; Tannock, 1998). These findings suggest that

d-amphetamine exerts its effects on executive functions via DA receptor mechanisms similar to

those underlying executive functioning. Because basic inhibitory processes “set the stage” for

other cognitive functions by directly increasing dopaminergic activity in prefrontal brain regions,

executive functions relevant to behavioral control may also depend on cortical DA activities

(Jentsch & Taylor, 1999). Therefore, I hypothesize that individual differences in behavioral

control may moderate stimulant-enhanced performance effects on executive functioning, perhaps

as a result of neural variations in DA activity.

There is evidence that amphetamine and methylphenidate improve such lower-order

cognitive abilities as rapid information processing (RIP; Fillmore et al., 2005; Ward et al., 1997),

short-term memory (Pigeau et al., 1995), and psychomotor reaction time (Ward et al., 1997;

Makris et al., 2007; de Wit et al., 2002) in healthy volunteers. However, reports of stimulant

effects on higher-order executive functions have been inconsistent. For example, while Fillmore

et al. (2005) found that d-amphetamine enhanced performance on the RIP task in healthy

volunteers, it did not concurrently enhance behavioral control (as measured by the stop-signal

task). Similarly, studies that have used the N-back and Wisconsin Card Sorting tasks (WCST) to

measure stimulant effects on the working memory and cognitive flexibility of healthy volunteers

have reported mixed results. For example, Makris et al. (2007) found that d-amphetamine

improved working memory, but Elliott et al. (1997) found that the drug only enhanced working

memory performance during the first session (when the task and situation was novel to the

participants), and Mintzer and Griffith (2003) found no improvements. In addition, Elliot et al.

(1997), like Mattay et al. (1996), found that amphetamine did not improve cognitive flexibility in

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healthy individuals, as indicated by the number of perseverative (i.e. repetition of a particular,

incorrect response) and total errors. These inconsistencies have led researchers to conclude that

stimulants have dissociable effects on various components of cognitive processing, producing

different effects on executive functioning than on speed of information processing, short-term

recall, or psychomotor reaction time.

Recent neuroimaging studies have assessed DA activity in healthy volunteers’ brains

while they performed on the N-back and WCST after the administration of d-amphetamine. The

findings have indicated that amphetamine improved the working memory performance of

individuals who were initially poor at the task and had low levels of DA activity (Mattay, 2003).

Similarly, those who had low levels of DA activity also made more perseverative errors on the

WCST under placebo conditions, and made fewer errors after the acute administration of d-

amphetamine. Interestingly, individuals who had high levels of DA activity and, consequently,

higher baseline performance, did not show d-amphetamine effects on low to moderate working

memory loads, but showed decreased performance on high working memory loads (3 N-backs).

These results suggest an inverted U-shape relationship between DA levels and executive

functioning performance, such that performance is optimal at moderate levels of DA and worse

at lower and higher levels (Figure 2; Mattay, 2003), paralleling other findings that have found

stimulant-enhanced cognitive and behavioral performance of ADHD children in a similar

inverted U-shape and dose dependent manner (Perry et al., 2008). Analogous results have also

been obtained by de Wit et al. (2000) when examining d-amphetamine effects on the behavioral

control of healthy volunteers; although individuals initially high in behavioral control did not

fluctuate from baseline levels after receiving d-amphetamine, the behavioral control of

individuals with low baseline levels was improved after its acute administration. Thus, executive

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functioning seems to be enhanced after d-amphetamine administration in individuals with lower

baseline behavioral control (and low DA levels), and unchanged or decreased in individuals with

higher baseline behavioral control (and high DA levels).

Figure 2. Inverted U-shape relationship between DA levels and executive functioning performance, as

proposed by Mattay (2003).

Taken together, these results indicate that the variation in stimulant effects on cognitive

and behavioral task performance seems to be related to individual differences in DA function

(Mattay et al., 2003). Based on the knowledge that ADHD is characterized by low behavioral

control (Barkley, 1997), and children with ADHD have low DA receptors (Volkow et al., 2007),

it can be inferred that healthy individuals with low baseline levels of behavioral control may also

have low DA receptors. Although past studies have not directly investigated DA activities of

healthy volunteers with low baseline levels of behavioral control during working memory and

cognitive flexibility tasks, some genetic studies have reported evidence suggesting that DA

activities relate to performance on behavioral control measures. For example, some studies have

observed a significant interaction between the DRD4 and DAT dopaminergic genotypes in

healthy volunteers with poor behavioral control capacity, as indicated by long stop reaction times

(SRTs) on the stop-signal task (Congdon et al., 2008); other studies have found that children

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with ADHD who carry similar alleles of the DRD4 and DAT genotypes are more impulsive than

their healthy counterparts (Roman et al., 2001). These findings imply that low behavioral control

in healthy adults may stem from similar mechanisms as the impairments seen in children with

ADHD. Because behavioral control serves as an important prerequisite for other executive

functioning skills (i.e. the ability to process relevant stimuli and disregard non-relevant stimuli;

Barkley, 1997), reduced control may be the primary disturbance that interferes with executive

functioning capacities of ADHD children. Thus, behavioral control may be a key marker that can

be used to predict who will show improved executive functioning with stimulant administration.

Despite the close association between behavioral control and other forms of executive

functioning, no study has explored how individual differences in behavioral control may relate to

stimulant effects on executive functions. Therefore, the present study used the stop-signal task to

assess between-subject differences in trait (baseline) levels of behavioral control in executive

function. I hypothesized that behavioral control would moderate the acute enhancing effects of d-

amphetamine on lower-order (i.e. psychomotor reaction time) and higher-order (i.e. working

memory and cognitive flexibility) cognitive functions. A secondary goal was to examine whether

self-report measures and behavioral measures of behavioral control provide equally good

prediction of amphetamine effects (Reynolds et al., 2005).

To accomplish the main goal of the study, I examined the effects of d-amphetamine

(placebo, 5 mg, 10 mg, 20 mg) on performance on the Wisconsin Card Sorting, N-Back and

Digit Symbol Substitution tasks in healthy volunteers high and low in behavioral control, as

measured by the stop-signal task. This led to three primary hypotheses: 1a. I predicted that there

would be a main effect of baseline levels of behavioral control on executive functioning, with

participants low in behavioral control performing more poorly than participants high in

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behavioral control on executive functioning tasks under placebo conditions. 1b. I predicted that

task-measured behavioral control would be a significant moderator, with those low in task

behavioral control (i.e. longer SRTs) showing improved performance on the two executive

functioning measures (i.e. the N-back and Wisconsin Card Sorting tasks) after receiving d-

amphetamine, while those high in baseline levels of behavioral control showing changes in

executive functioning in an inverted U-shaped and dose-dependent manner (i.e. low doses of

amphetamine improve performance, and higher doses impair performance) and 1c. I predicted a

main effect of dose on the subjects’ performance on the Digit Symbol Substitution task (DSST),

an RIP task; based on previous findings (Makris et al., 2007), I did not expect moderation of the

effects on RIP by behavioral control, but rather dose-dependent improvements in psychomotor

reaction time in both high and low behavioral control groups, thus demonstrating disassociation

of the effects of amphetamine on different cognitive domains.

To accomplish the secondary aim of this study, which was to compare the predictive

ability of multiple methods of measuring behavioral control, I first examined the correlation

between the self-report and task measures of behavioral control, and second, I examined the

relationship between self-reported behavioral control and amphetamine-produced changes in

executive functioning. This led to two secondary hypotheses: 2a. I predicted that the task

measure and self-report of behavioral control would be moderately, but not highly, correlated,

and 2b. I predicted that self-report measured behavioral control would not as strongly predict the

effects of amphetamine as task-measured behavioral control. Taken together, these findings

provided a broader understanding of the way in which amphetamines may affect complex

cognitive functions, what traits might increase individual proclivities for use and abuse of

amphetamines, and the best way to measure those traits.

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Method

Participants

Data from 150 healthy male (N = 80) and female (N =70) adult volunteers between the ages of

18-35 were taken from the subject pool of an ongoing, larger study. The participants were

recruited by posters, advertisements, and word-of-mouth referrals, and eligibility for

participation was initially ascertained by a telephone interview. Eligible candidates were

scheduled for a face-to-face interview and screened for past or present psychiatric disorders

(DSM IV; APA, 1994), medical conditions, and current or lifetime recreational drug use and

history via a clinical psychiatric interview, the Michigan Alcoholism Screening Test (MAST;

Selzer, 1971), an electrocardiogram, and a physical examination by a physician. Volunteers with

a current Axis I psychiatric disorder (APA, 1994), any serious medical condition requiring

medication, past or present medical problems considered to be a contraindication for

amphetamine (e.g. hypertension, abnormal EKG) and a history with drug abuse, treatment, or

dependence were excluded from participating. In order to minimize variability in stimulant

intake, the criteria for participating in the study was limited to volunteers who smoked less than

10 cigarettes per week and consumed less than 3 cups of coffee per day. Other exclusion criteria

included less than a high school education, night shift work, lack of fluency in English, pregnant

or lactating women, women planning pregnancy during the study, or a history of any recreational

drug abuse (including alcohol) according to the DSM-IV (APA, 1994) criteria for Substance

Abuse.

Design

The study used a double-blind, placebo-controlled, within-subjects design. Each subject

participated in four experimental sessions in which they received placebo or one of three doses

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(5, 10 mg, or 20 mg) of d-amphetamine in randomized order, allowing 72 hours between

sessions for drug clearance. Prior to their first session, the participants attended an orientation

session in which they were informed of the rules and conditions of the study, asked to read and

sign the consent form, and administered practice psychomotor tests and self-report

questionnaires. For blinding purposes, the consent form listed other drugs in addition to what

was administered in the study. The subjects agreed to abstain from drugs throughout the course

of the study and were paid for their participation.

Measures

The Digit Symbol Substitution Task (DSST; Wechsler, 1997). This task was used as a

manipulation check to confirm the effect of the chosen drug doses on a domain known to be

strongly affected by stimulants, and to examine the specificity of any observed effects to

executive functioning. The DSST is a paper-and-pencil task that measures lower-order cognitive

abilities in attention, motor performance, response speed, and visuomotor coordination. The task

consists of nine random symbols (e.g. asterisks and dashes) that are individually paired with

numbers one through nine. Participants have 90 seconds to reproduce the pattern of symbols

corresponding to numbers presented in an array of twenty rows as quickly as possible. The

measure of performance is the total number of correctly substituted symbols within the given

time frame.

The N-back working memory task (Callicott et al., 1999). This task measures the executive

functioning component of working memory by requiring participants to continually update and

recall a sequence of digits, with “N-back” referring to the number of digits they have to recall.

Each digit (1-4) is briefly flashed in the corners of a diamond-shaped boxed and presented in

random order. The task consists of eight cycles, or “memory loads” with 16 1-back, 2-back, and

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3-back combinations, alternating with a 0-back sensorimotor task. During the 0-back condition,

the participant is instructed to respond with the number presented on the screen; during the N-

back condition, the participant must respond with the number corresponding to the digit

presented N digits previously (i.e. 1-back, 2-back, or 3-back). The subjects’ accuracy (number of

correct responses relative to the number of trials presented) is recorded to indicate performance

on each working memory load.

Wisconsin Card Sorting Task (WCST; Heaton et al., 1993). This task measures the executive

functioning components of cognitive flexibility and abstract reasoning by testing the ability to

shift problem-solving strategies as needed. Participants view a computer screen that displays a

set of four key cards with markings that differ in color, shape, and number. The participant must

match each card from a “deck” (presented sequentially on the screen) with one of the four key

cards on the basis of either color, shape, or number. After a series of correct responses (e.g.

matching correctly on “color” 6 times in a row) indicating that the participant has deduced the

rule, the rule is changed (for example to “shape”) and the participant must again use trial and

error to determine a new rule for matching. The participant is not informed what the possible

rules are, and is not told when the rule is changed. The procedure is repeated until the participant

has cycled through all 3 rules twice, or until the card count has reached 128, whichever occurs

first. The participants’ performance is indicated by the proportion of perseverative errors (the

total number of errors that occur when a participant is required to switch to another rule but

persists in responding by the previous rule, relative to the number of trials administered), and the

total number of errors.

Stop-signal task (Logan and Cowan, 1984). The stop task is used to measure the executive

functioning component of behavioral control as indexed by subjects’ stop reaction time (SRT) to

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stimuli initiating stop and go responses. Subjects are asked to respond to “go” signals (e.g., a

circle or a cross) presented on the computer screen as rapidly as possible, but to inhibit their

response when a “stop” signal (e.g,. a tone) occurs. The tone (stop) is presented on 25% of the

trials at varying delays following each symbol (go). The delay is varied systematically and

adjusted to the subjects’ performance until they successfully inhibit their responses on

approximately 50% of the trials. The subjects’ SRT (measured in milliseconds) is calculated by

subtracting their delay from their go reaction times on each trial, indicating the time it takes to

successfully overcome the prepotent tendency to respond to go signals, with longer SRTs

indicating a weaker inhibitory process.

The Multidimensional Personality Questionnaire-Brief Form (MPQ-BF; Patrick et al., 2002).

The MPQ is a comprehensive personality questionnaire that consists of three super factors

labeled Positive Emotionality, Negative Emotionality, and Constraint, each with its own

personality trait correlates. Because the present study focuses on behavioral control, only scores

from the Control subscale of the Constraint factor will be considered. The 5 items comprising the

Control subscale assess the degree to which an individual plans ahead, tries to anticipate events,

and is cautious, reflective, sensible, rational, and organized. The alpha coefficient for the 5-item

Control subfactor is 0.74 (Patrick et al., 2002), with higher scores indicating higher subjective

levels of control.

Procedure

The subjects participated in four 4-hr sessions conducted in the Human Behavioral

Pharmacology Lab (HBPL). Each session was conducted from 9:00 A.M. to 1:00 P.M. in standard

comfortably furnished testing rooms replicating a living-room environment. Upon their arrival,

the subjects provided urine samples that were tested for recent drug use and pregnancy, and

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breath samples for breath alcohol level (BAL) and carbon monoxide (CO) level. Pre-drug

subjective effects, psychomotor performance and vital signs were also recorded. At 9:30 A.M.,

participants ingested a capsule containing placebo or d-amphetamine (5, 10 mg or 20 mg), and

dependent measures were obtained every half hour. During times when dependent measures

were not being collected, subjects were given the choice of whether to relax, watch a movie, or

read. At the end of each session, subjects completed an end of session questionnaire reporting

their subjective experience with the drug they received.

Analyses

Hypothesis 1a. To test the main effect of baseline levels of behavioral control on

executive functioning, I conducted a between-subjects ANOVA examining N-back and WCST

scores of individuals high and low in task-measured behavioral control at placebo.

Hypothesis 1b. To test whether d-amphetamine differentially affected performances on

the N-back and WCST in individuals high and low in task-measured behavioral control, a

median split on the participants’ stop-signal task performance initially separated them into high

and low task-measured behavioral control groups. I then performed two 2 x 4 x 2 ANOVAs with

behavioral control (high vs. low) as a between subjects variable, dose of amphetamine (5 mg, 10

mg, and 20 mg vs. placebo) as a within subjects variable, and gender entered as an additional

between-subjects independent, potentially confounding variable. I chose to examine the effects

of each dose relative to placebo, as the effects of behavioral control at the placebo dose alone had

already been examined in Hypothesis 1a; moreover, including the placebo scores in a 4-level

(placebo, 5 mg, 10 mg, 20 mg) repeated measures ANOVA with behavioral control as an

independent variable would have involved analyzing that same variance twice. These analyses

primarily examined the hypothesized interactions between behavioral control and amphetamine

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on N-back and WCST scores, and any moderation by gender. Any potential main effects of

amphetamine in the entire sample were examined in separate repeated measures ANOVA with

dose (placebo, 5 mg, 10 mg and 20 mg) as the independent variable and the measures of

executive functioning as the dependent variable.

Hypothesis 1c. In order to analyze how d-amphetamine affected performances on the

DSST, I first examined the main effects of dose on DSST performance by performing a repeated

measures ANOVA with dose (placebo, 5 mg, 10 mg, and 20 mg) as the independent variable and

DSST scores as the dependent variable. In order to examine the specificity of the moderation

effects of behavioral control on executive versus simple cognitive functions, a median split on

the participants’ stop-signal task performance separated them into high and low task-measured

behavioral control groups. I then performed a 2 x 4 x 2 ANOVA with behavioral control (high

vs. low) as a between subjects variable, dose of amphetamine (5 mg, 10 mg, and 20 mg vs.

placebo) as a within subjects variable, and gender entered as an additional between-subjects

independent, potentially confounding variable; these dose effects were examined relative to

placebo.

Hypothesis 2a. In order to examine the association between task-measured and self-

reported behavioral control, a within-subjects correlation between the two measures was

conducted.

Hypothesis 2b. In order to examine whether task-measured or self-reported behavioral

control was the stronger predictor of d-amphetamine enhanced performance on the WCST and

N-back tasks, the above analyses were replicated using the median split obtained by the Control

submeasure of the MPQ.

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Results

Correlations

Correlations between the dependent measures under placebo conditions were examined in

the full sample. Poor performance on the stop signal task correlated with poor performance on

the WCST, indicating that longer stop reaction times (SRT) were associated with more

perseverative and total errors (Table 1). Additionally, more perseverative errors on the WCST

correlated with more total errors, as well as lower 2-back and 3-back accuracy on the N-back

task. Higher 1-back accuracy correlated with higher 2-back and 3-back accuracy, while higher 2-

back accuracy correlated with higher 3-back accuracy. Lastly, higher self-reported behavioral

control on the MPQ correlated with higher 2-back accuracy on the N-back task. The results did

not indicate a significant correlation between the Control subfactor on the MPQ and SRTs on the

stop-signal task. These patterns of associations provide support for the validity of the tasks

selected to measure executive functioning.

Table 1

Intercorrelations Between Dependent Measures

____________________________________________________________________________

Task component Mean Incorrect 2-back 3-back SRT

____________________________________________________________________________

Perseverative Errors .86** -.20* -.17* .29**

Mean Incorrect ---- ---- ---- .28**

1-back ---- .45** .39** ----

2-back ---- ---- .60** ----

MPQ-Control ---- .17* .60** ----

** Correlation is significant at the .01 level (2-tailed)

* Correlation is significant at the .05 level (2-tailed).

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Dose x Median Split Interactions: Task-measured Behavioral Control

Wisconsin Card Sorting Task. Two 3 (dose minus placebo) x 2 (median split) x 2

(gender) ANOVAs were conducted with the proportion of perseverative errors and the mean

number of total errors entered as dependent variables and median split on the task measure of

behavioral control and gender as independent variables. Additionally, a one-way repeated

measures ANOVA with dose as the independent variable was conducted on the entire sample to

examine any main effects of amphetamine on WCST perseverative or mean errors. No

significant main effects of dose were observed on either perseverative or total errors on the

WCST performance within the entire sample. Additionally, no significant dose x median split

interactions were obtained, indicating that the high and low task-measured behavioral control

groups did not differ significantly on the cognitive flexibility component of executive

functioning after the administration of d-amphetamine.

N-back. A 3 (dose minus placebo) x 3 (N-back memory load) x 2 (median split) x 2

(gender) ANOVA was performed, with mean accuracy on the memory loads as dependent

variables and median split on the task-measure of behavioral control and gender as independent

variables. Additionally, a two-way repeated measures ANOVA with dose (placebo, 5 mg, 10 mg

and 20 mg) and N-back memory load (1, 2, 3) as the independent variables was conducted on the

entire sample to examine any main effects of amphetamine on N-Back accuracy. No significant

main effects of dose were observed on the N-back scores within the entire sample. Additionally,

no significant dose x median split x memory load interactions were obtained, indicating that the

high and low task-measured behavioral control groups did not differ significantly on the working

memory component of executive functioning after the administration of d-amphetamine.

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DSST. A 3 (dose minus placebo) x 2 (median split) x 2 (gender) ANOVA was conducted

with mean area under the curve at each dose as dependent variables and median split on the task

measure of behavioral control and gender as independent variables. Additionally, a one-way

repeated measures ANOVA with dose (placebo, 5 mg, 10 mg and 20 mg) as the independent

variable was conducted on the entire sample to examine any main effects of amphetamine on

DSST speed. A significant main effect of dose was observed on the DSST scores within the

entire sample F(3, 435)=3.1, p <.05. These results confirm the efficacy of the chosen doses of d-

amphetamine on RIP performance and indicate that psychomotor performance on the DSST was

significantly improved in a dose-dependent manner (Figure 3). No significant dose x median

split interactions were obtained, indicating that high and low task-measured behavioral control

groups did not differ significantly on psychomotor speed after the administration of d-

amphetamine.

Figure 3. Main effects of dose on the Digit Symbol Substitution Task (DSST) across the entire sample,

measured by the mean area under the curve performance at each dose. The results indicate dose-

dependent improvements after the acute administration of d-amphetamine.

Dose x Median Split Interactions: Self-reported Behavioral Control

Wisconsin Card Sorting Task. Similar to analyses conducted using task-measured

behavioral control, two 3(dose minus placebo) x 2(median split) x 2 (gender) ANOVAs were

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conducted, with the proportion of perseverative and the mean number of total errors entered as

dependent variables and median split on the self-reported measure of behavioral control and

gender as independent variables. The results indicated a significant dose x median split

interaction on the mean number of total errors F(2, 208)= 3.1, p<.05, though this interaction was

not observed on the proportion of perseverative errors. Relative to placebo, individuals high in

self-reported behavioral control produced a higher mean of total errors at the lowest dose, while

the performance of individuals low in self-reported behavioral control did not fluctuate

significantly from baseline across any dose. These results indicate that d-amphetamine produced

significant decrements in the performance of individuals high in self-reported behavioral control

at the lowest dose, while improving their performance at the moderate dose and returning it to

baseline at the highest dose. In contrast, the performance of individuals low in self-reported

behavioral control was unchanged at the lowest and highest doses, and slightly worse at the

moderate dose (Figure 4).

Figure 4. Dose x median split interactions on the mean number of total errors made at each dose, relative

to placebo, on the WCST performance of individuals high versus low in self-reported behavioral control.

N-back. Similar to analyses conducted using task-measured behavioral control, a 3 (dose

minus placebo) x 3 (N-back memory load) x 2 (median split) x 2 (gender) ANOVA was

performed, with mean accuracy on the memory loads as dependent variables and median split on

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the self-reported measure of behavioral control and gender as independent variables. No

significant dose x median split x memory load interactions were obtained, indicating that the

high and low task-measured behavioral control groups did not differ significantly on the working

memory component of executive functioning after the administration of d-amphetamine.

DSST. Similar to analyses conducted using task-measured behavioral control, a 3 (dose

minus placebo) x 2 (median split) x 2 (gender) ANOVA was conducted with the mean area under

the curve at each dose as dependent variables and median split on the task measure of behavioral

control and gender as independent variables. No significant dose x median split interactions were

obtained, indicating that the high and low task-measured behavioral control groups did not differ

significantly on psychomotor task performance.

Discussion

The overarching goal of the study was to investigate the relatively unexplored component

of behavioral control as potentially critical in understanding individual variations in stimulant

response patterns and risk for stimulant abuse. The rationale of the study was that healthy

individuals might be motivated to use amphetamine in part because of its cognitive enhancing

effects (Khantzian, 1985). While individual differences in stimulant-enhanced performance

effects are difficult to predict, psychopharmacological explanations have proposed that

individuals low in baseline DA activation benefit more from the cognitive enhancing effects of

stimulants, as seen in studies with ADHD children (Tannock, 1998). Because the primary

disturbance in ADHD is characterized by reduced behavioral control, and inhibitory functions

subserved by dopaminergic pathways set the occasion for other executive functions, this study

hypothesized that healthy participants low in behavioral control (and presumably low in DA

activity) will improve in executive functioning performance after d-amphetamine, while those

22

high in behavioral control (and presumably high in DA activity) will either show no response or

get worse. The study additionally examined correlations between self-reported and task-

measured behavioral control in order to observe which measures provided a better prediction of

amphetamine effects.

The main finding of the study was that d-amphetamine did not differentially improve the

executive functioning performance of healthy individuals high versus low in behavioral control,

though some differences were observed when the groups were split according to the self-reported

measure. However, the significant results obtained on the total number of errors on the WCST

contradicted the main hypothesis of the study, showing that the performance of individuals high

in self-reported behavioral control fluctuated more from baseline than that of individuals low in

self-reported behavioral control, after the administration of d-amphetamine. These results

indicate that d-amphetamine may have affected the groups differently, but because a significant

effect was not obtained on any other measure of the executive functioning tasks, the explanation

for this pattern remains unclear. Furthermore, it is unclear whether the self-report or task

measure is a better prediction of the behavioral control construct because the results obtained

from the median split conducted on either measure were not significant. However, the two

measures of the behavioral control construct were not correlated, supporting previous literature

(Reynolds et al., 2006) and suggesting that behavioral tendencies reported by self-report scales

may not detect similar traits when measured with behavioral tasks. A possible explanation for

this discrepancy may be attributed to the subjective nature of self-reported measures, while

behavioral tasks are more objective and less susceptible to the possible biases in self-perceptions.

The findings are in line with previous literature in showing that stimulant effects on the

23

working memory and cognitive flexibility of healthy volunteers are not large or unmixed

(Fillmore et al., 2005; Makris et al., 2002; Elliot et al., 1997). As hypothesized, however,

d-amphetamine was effective in creating changes in RIP task performance, producing dose-

dependent improvements on psychomotor reaction time within the entire sample. These results

were not altered by splitting the sample into high and low task-measured and self-reported

behavioral control groups. Taken together, past findings (Ward et al., 1997; Koelega, 1993) and

the results of the current study indicate that stimulants can enhance aspects of lower-order

cognitive processes such as attention, psychomotor speed, and visuomotor coordination, without

producing concomitant improvements in higher-order executive tasks involved in complex

cognitive functions. Because of the inconsistencies of these results, the cognitive effects of

amphetamine and its dissociable influence on performance must be delineated.

One hypothesis that may account for this pattern of results is compatible with the

rejection by Broadbent (1984) of a unitary mechanism of action on cognitive performance.

According to his theory, performance is organized into two levels of action: the lower-level

mechanisms (e.g. the striate nuclei) include processes that respond directly to incoming stimuli,

while the higher level mechanisms (e.g. the prefrontal cortex) monitor the successful completion

of performance and compensate for any inefficiency that might develop during task execution.

Based on this approach, Robbins and Everitt (1987) proposed a dual, potentially conflicting

effect of amphetamine on performance, such that lower mechanisms may be modulated by DA

activation, while upper mechanisms rely on both DA and noradrenergic receptors important in

prefrontal cortex functions (Thomas et al., 1992), especially the dorsal noradrenergic bundle

(DNAB). The enhancement of cognitive performance by d-amphetamine may therefore depend

on either dopaminergic or noradrenergic influences, or a combination of both. These dual

24

patterns of processing may therefore help explain the dissociable effect of d-amphetamine on

executive functioning and psychomotor performance observed in the present sample. The

complex modulatory influence of prefrontal dopaminergic and striatal noradrenergic mechanisms

were beyond the scope of observation in the current study, and may not have been adequately

tapped by the behavioral phenotype chosen (i.e. stop-signal task performance).

It is equally important to consider that, although “executive functions” encompass higher

order cognitive abilities, the underlying dopaminergic mechanisms that control and guide

behavior and cognitive performance are also not unitary and may have differential responses to

stimulants (Floresco & Magyar, 2006). For example, some studies have shown that D1 subtypes

of DA receptors are primarily responsible for facilitating influence over working memory

functions in laboratory rats (Seamans & Yang, 2004); others have demonstrated that the

blockade of D2 but not D1 receptors in the prefrontal cortex of rats caused impairments in

attentional set-shifting and a considerable increase in perseverative errors (Floresco & Magyar,

2006), while preserving working-memory functions. These findings indicate that stimulant

effects on executive functioning performance may not only vary as a function of individual

levels of baseline DA transmission, but also as a result of specific executive functioning

components that correspond with individual D1 or D2 activation.

Given the complex nature of DA receptor activity in mediating distinct prefrontal cortex

functions, it can be concluded that no d-amphetamine effects on either working memory or

cognitive flexibility components of executive functioning were observed in this study because

the measures of behavioral control utilized were not sensitive in detecting individual baseline

locations on the hypothetical inverted U. The nonsignificant results may also be attributed to the

homogeneity of the sample; it is likely that even the low behavioral control group of healthy

25

participants was performing at their optimal level of DA stimulation required for adequate

behavioral control performance. The median split may thus have not adequately assessed

inhibitory mechanisms due to the specific characteristics of the sample, thereby separating the

healthy participants into corresponding levels of behavioral control. For example, it is likely that

the young healthy volunteers were high functioning and made few errors on the executive

functioning tasks, introducing the possibility that a ceiling effect reduced the sensitivity of the

tasks to the effects of d-amphetamine. The findings of the study may thus be limited in external

validity due to controlled laboratory settings of a homogenous sample. Future investigations

should examine behavioral control in more heterogeneous populations using a variety of

measures that will ascertain both the behavioral and physiological correlates of the effects of

d-amphetamine, in addition to direct examination of related genotypes. Doing so will allow

researchers in behavioral pharmacology to recognize vulnerable phenotypes and develop

prevention and intervention strategies for those at heightened risk for drug abuse.

26

References

American Psychiatric Association. (2000). Substance abuse. Diagnostic and statistical manual

of mental disorders (4th ed): Washington, D.C.

Baddeley, A. D. (1986). Working memory. Oxford, England: Clarendon Press.

Baddeley, A.D., Della Sala, S. (1996). Working memory and executive control. Philosophical

Transactions of the Royal Society of London, 351: 1397-1404.

Barkley, R. A. (1997). Behavioral inhibition, sustained attention, and executive functions:

Constructing a unifying theory of ADHD. Psychological Bulletin, 121(1): 65-94.

Berger B., Gaspar P., Verney C. (1991)Dopaminergic innervation of the cerebral cortex:

unexpected differences between rodents and primates. Trends in Neuroscience, 14: 21-27.

Broadbent, D.E. (1984). Performance and its measurements. British Journal of Clinical

Pharmacology, 18: S5-S9.

Callicott, J. H., Mattay, V. S., Bertolino, A., Finn, K., Coppola, R., Frank, J. A., et al. (1999).

Physiological characteristics of capacity constraints in working memory as revealed by

functional MRI. Cerebral Cortex (New York, N.Y.: 1991), 9(1): 20-26.

Congdon, E., Lesch, K. P., & Canli, T. (2008). Analysis of DRD4 and DAT polymorphisms and

behavioral inhibition in healthy adults: Implications for impulsivity. American Journal of

Medical Genetics, Part B, Neuropsychiatric Genetics : The Official Publication of the

International Society of Psychiatric Genetics, 147B(1): 27-32.

de Wit, H., Crean, J., & Richards, J. B. (2000). Effects of d-amphetamine and ethanol on a

measure of behavioral inhibition in humans. Behavioral Neuroscience, 114(4): 830-837.

27

de Wit, H., Enggasser, J. L., & Richards, J. B. (2002). Acute administration of d-amphetamine

decreases impulsivity in healthy volunteers. Neuropsychopharmacology 27(5): 813-825.

Elliott, R., Sahakian, B. J., Matthews, K., Bannerjea, A., Rimmer, J., & Robbins, T. W. (1997).

Effects of methylphenidate on spatial working memory and planning in healthy young

adults. Psychopharmacology, 131(2): 196-206.

Fillmore, M.T., Rush, C.R., Marczinski, C.A. (2003). Effects of d-amphetamine on

behavioral control in stimulant abusers: the role of prepotent response tendencies. Drug

and Alcohol Dependence, 71(2): 143-152.

Fillmore, M. T., Kelly, T. H., Martin, C. A. (2005). Effects of d-amphetamine in human models

of information processing and inhibitory control. Drug and Alcohol Dependence, 77(2):

151-159.

Finn, P. R. (2002). Motivation, working memory, and decision making: A cognitive-motivational

theory of personality vulnerability to alcoholism. Behavioral and Cognitive

Neuroscience Reviews, 1(3): 183-205.

Floresco, S.B., Magyar, O. (2006). Mesocortical dopamine modulation of executive functions:

beyond working memory. Psychopharmacology, 188(4): 567-585.

Heaton, R.K., Chelune, G.J., Talley, J.L., Kay, G.G., & Curtiss, G. (1993). Wisconsin Card

Sorting Test Manual (Psychological Assessment Resources, Odessa, FL).

Kane, M.J., Engle, R.W. (2002). The role of prefrontal cortex in working-memory capacity,

executive attention, and general fluid intelligence: An individual differences perspective.

Psychonomic Bulletin & Review, 9(4): 637-671.

Jentsch, J.D., Taylor, J.R. (1999). Impulsivity resulting from frontostriatal dysfunction in drug

28

abuse: Implications for the control of behavior by reward-related stimuli.

Psychopharmacology,146:373–390.

Khantzian, E.J. (1985). The self-medication hypothesis of addictive disorders-focus on heroin

and cocaine dependence. American Journal of Psychiatry, 142(11): 1259-1264.

Kimberg, D.Y., D’Esposito, M., Farah, M.J. (1997). Effects of bromocriptine on human subjects

depend on working memory capacity. Neuroreport, 8(16): 3581-3585.

Koelega, H. S. (1993). Stimulant drugs and vigilance performance: A review.

Psychopharmacology, 111(1): 1-16.

Kramer, U. M., Rojo, N., Schule, R., Cunillera, T., Schols, L., Marco-Pallares, J., et al. (2009).

ADHD candidate gene (DRD4 exon III) affects inhibitory control in a healthy sample. BMC

Neuroscience, 10: 150.

Lieberman, H.R., Wurtman, R.J., Emde, G.G., Roberts, C., Coviella I.L.G. (1987b). The effects

of low doses of caffeine on human performance and mood. Psychopharmacology, 92: 308–

312.

Logan, G.D., & Cowan, W.B. (1984). On the ability to inhibit thought and action: A theory of an

act of control. Psychological Review, 91, 295-327.

Makris, A.P., Rush, C.R., Frederich, R.C. (2007). Behavioral and subjective effects of d-

amphetamine and modafinil in healthy adults. Experimental and Clinical

Psychopharmacology, 15(2): 123-133.

Mattay, V. S., Berman, K. F., Ostrem, J. L., Esposito, G., Van Horn, J. D., Bigelow, L. B., et al.

(1996). Dextroamphetamine enhances "neural network-specific" physiological signals: A

29

positron-emission tomography rCBF study. The Journal of Neuroscience : The Official

Journal of the Society for Neuroscience, 16(15), 4816-4822.

Mattay, V. S., Goldberg, T. E., Fera, F., Hariri, A. R., Tessitore, A., Egan, M. F., et al. (2003).

Catechol O-methyltransferase val158-met genotype and individual variation in the brain

response to amphetamine. Proceedings of the National Academy of Sciences of the United

States of America, 100(10), 6186-6191.

Mehta, M.A., Riedel, W.J. (2006). Dopaminergic enhancement of cognitive function.

Current Pharmaceutical Design, 12(20): 2487-2500.

Mintzer, M. Z., & Griffiths, R. R. (2003). Triazolam-amphetamine interaction: Dissociation of

effects on memory versus arousal. Journal of Psychopharmacology (Oxford, England),

17(1), 17-29.

Neill, W.T., Valdes, L.A. (1996). Facilitatory and inhibitory aspects of attention. In Kramer,

A.F., Coles, M.G.H., Logan, G.D. (Eds), Converging operations in the study of visual

selective attention, 77-106. Washington, D.C.: American Psychological Association.

Oscar-Berman, M. (1978). The effects of dorsolateral-frontal and ventrolateral orbitofrontal

lesions on non-spatial test performance, Neuropsychologia, 16: 259–267.

Patrick, C.J., Curtin, J.J. & Tellegen, A. (2002). Development and validation of a brief form of

the Multidimensional Personality Questionnaire. Psychological Assess, 14, 150-163.

Perry, J. L., Stairs, D. J., & Bardo, M. T. (2008). Impulsive choice and environmental

enrichment: Effects of d-amphetamine and methylphenidate. Behavioural Brain Research,

193(1), 48-54.

30

Pigeau, R., Naitoh, P., Buguet, A., McCann, C., Baranski, J., Taylor, M. (1995). Modafinil, d-

amphetamine and placebo during 64 hours of sustained mental work. I. effects on mood,

fatigue, cognitive performance and body temperature. Journal of Sleep Research, 4(4), 212-

228.

Rapoport, J. L., Buchsbaum, M. S., Weingartner, H., Zahn, T. P., Ludlow, C., & Mikkelsen, E. J.

(1980). Dextroamphetamine. its cognitive and behavioral effects in normal and hyperactive

boys and normal men. Archives of General Psychiatry, 37(8), 933-943.

Reynolds, B., Ortengren, A., Richards, J., de Wit, H. (2006). Dimensions of impulsive behavior:

personality and behavioral measures. Personality and Individual Differences, 40: 305-315.

Robbins, T.W., Everitt, B.J. (1987). Comparative functions of the central noradrenergic,

dopaminergic and cholinergic systems. Neuropharmacology, 26(7B): 893-901.

Roman, T., Schmitz, M., Polanczyk, G. (2001). Attention-deficit hyperactivity disorder: A study

of association with both the dopamine transporter gene and the dopamine D4 receptor gene.

American Journal of Medical Genetics, 105(5): 471-478.

Schiffer, F. (1988). Psychotherapy of nine successfully treated cocaine abusers: techniques and

dynamics. Journal of Substance Abuse Treatment, 5: 131–137.

Seamans, J.K., Yang, C.R. (2006). The principal features of mechanisms of dopamine

modulation in the prefrontal cortex. Progress in Neurobiology, 74(1): 1-57.

Selzer, M.L. (1971). The Michigan alcoholism screening test: the quest for a new diagnostic

instrument. American Psychiatry, 127, 1653-1658.

31

Solanto, M. V. (1998). Neuropsychopharmacological mechanisms of stimulant drug action in

attention-deficit hyperactivity disorder: A review and integration. Behavioural Brain

Research, 94(1), 127-152.

Tannock, R. (1998). Attention deficit hyperactivity disorder: Advances in cognitive,

neurobiological, and genetic research. Journal of Child Psychology and Psychiatry, and

Allied Disciplines, 39(1), 65-99.

Volkow, N. D., Wang, G. J., Newcorn, J., Telang, F., Solanto, M. V., Fowler, J. S., et al. (2007).

Depressed dopamine activity in caudate and preliminary evidence of limbic involvement in

adults with attention-deficit/hyperactivity disorder. Archives of General Psychiatry, 64(8),

932-940.

Ward, A. S., Kelly, T. H., Foltin, R. W., & Fischman, M. W. (1997). Effects of d-amphetamine

on task performance and social behavior of humans in a residential laboratory. Experimental

and Clinical Psychopharmacology, 5(2), 130-136.

Wechsler, D. (1997). Administration and scoring manual for the WAIS-III. San Antonio, TX:

Psychological Corporation.