Previous research suggests that NP function varies with the length of abstinence or withdrawal severity in CUD. For example, set shifting, a core executive function, is impaired when tested 2-4 weeks after last drug use in CUD (Ardila et al, 1991; Berry et al, 1993); this impairment is not evident at shorter abstinence periods (within 72 h of last drug use) (Berry et al, 1993). Since screening urine for drugs of abuse is common in clinical practice (eg, to assess adherence to treatment goals), we examined whether NP performance in CUD differs as a function of this objectively measured index of abstinence. In addition, we examined the extent to which dysphoric symptoms affect NP function, since depression/dysphoria is a common psychostimulant withdrawal symptom (Association, 2000). Depression/dysphoria is also associated with more severe dependence (Schuckit et al, 1999; Sofuoglu et al, 2003), exacerbating NP deficits in drug-abusing (Di Sclafani et al, 2002) and non-drug abusing (Fossati et al, 2002) populations.

The NP battery (see Table 2) was composed of well-validated NP measures of attention and executive function, memory, facial and emotion recognition, and motor function (Lezak, 1995). Also included in the battery were measures of verbal and non-verbal intelligence estimated with age-corrected scores from the reading subscale of the Wide Range Achievement Test 3 (WRAT 3) (Wilkinson, 1993) and matrix reasoning subscale of the Wechsler Abbreviated Scale of Intelligence III, respectively. Although the WRAT 3 reading subtest is considered an achievement test, it is also used as an estimate of verbal IQ and premorbid intelligence and is highly related to other word-based IQ indices such as the National Adult Reading Test (r = 0.8) and verbal IQ indices from the Wechsler intelligence scales for children and adults (r = 0.7). It is also a better verbal IQ estimate in lower SES and minority populations (Strauss et al. 2006). Tasks measuring attention/executive function were the (1) Controlled Oral Word Association Task (Benton, 1968) assessing flexibility of verbal thought processes and the ability to update working memory (number of correct words produced for phonemic (2 categories-letters `F' and `S') and semantic categories (2 categories-`animals' and `fruits and vegetables'), 1 min per category); sensitivity and specificity for both indices are reliable in discriminating controls from those with impaired frontal function (sensitivity of 88 and 100% has been reported for phonemic and semantic categories, respectively) (Lezak, 1995); (2) digit span (standardized scores based on the sum of raw scores for both forward and backward tests) and letter-number sequencing subtests from the Wechsler Adult Intelligence Scale III; Wechsler, 1997) assessing attentional capacity and verbal working memory; both subtests have adequate sensitivity and specificity (Lezak, 1995); (3) Symbol Digit Modalities Test (Smith, 1982) assessing attentional capacity (written; number of correct responses in 90 s; possessing ample sensitivity (approximately 80%) in detecting brain injury and learning disorders) (Lezak, 1995); (4) Trail Making Test (Reitan, 1955) assessing visual motor tracking, cognitive flexibility, and planning (trails A and B are very sensitive to cognitive decline and differentiate controls from both mild and severe head trauma patients; sensitivity of 77 and 79% has been reported for trails A and B, respectively) (O'Donnell et al, 1984; Lezak, 1995); (5) Mazes subtest from the Wechsler Intelligence Scale for Children III (Wechsler, 1987) assessing planning and sustained attention (this subtest is a `satisfactory substitute for longer adult tests such as the Porteus mazes' in assessing executive functioning for most clinical purposes; (we used scaled scores based on norms for the highest (16 years) age) (Lezak, 1995); (6) Wisconsin Card Sort Test 3 (Berg, 1948) computerized version (Heaton, 1999) assessing set shifting and planning (specificity for the Wisconsin Card Sort Test is reported to be low, however it is very sensitive to the effects of frontal damage); and the (7) Color-Word Stroop Task (Golden, 1978), an index of directed attention and cognitive flexibility (the Color-Word Stroop is sensitive to both mild and severe frontal lobe impairment, differentiating those with learning disabilities or Attention Deficit Hyperactivity disorder from controls (eg, sensitivity, 89%)) (Homack and Riccio, 2004; Lezak, 1995). Two newly developed tasks of executive function were also included in this NP battery, and although more studies are needed to test their validity, recent reports have provided evidence for their utility in distinguishing specific executive domains: (8) the Attention Network Test (Fan et al, 2002) using reaction time to measure alerting (response readiness), orientating (scanning/selection), and executive control (conflict resolution); and the (2) Iowa Gambling Task (Bechara et al, 1994) measuring advantageous decision making. Verbal learning and memory was assessed by the (10) California Verbal Learning Task II (CVLT) (Delis et al, 2000) involving list learning, recall, recognition, semantic and serial learning strategies, and the degree of vulnerability to cognitive interference (performance on the CVLT effectively discriminates patients with left vs right temporal lobe dysfunction from control subjects) (Lezak, 1995). Emotion and facial recognition was measured with the (11) Ekman Faces test (Ekman, 1993) measuring recognition of six different emotions (sensitivity and specificity for the Ekman tests are good (eg, 94% sensitivity and 100% specificity in discriminating patients with frontotemporal dysfunction from healthy controls)) (Diehl-Schmid et al, 2007) and (12) Benton Facial Recognition Test (corrected long form scores) (Benton, 1990) that measured the ability to match faces. Motor function was measured by the (13) Timed Gait test (Robertson et al, 2006) (average time to walk a 12-foot floor-length back and forth for a total of three trials), with fine motor coordination assessed by the (14) Finger Tapping Test (the mean of the closest three out of five trials for each hand) (Reitan, 1985), a simple test of motor speed and motor control (tests of its sensitivity/specificity indicates that this test is a poor screening instrument but is useful as a diagnostic supplement) (Lezak, 1995), and (15) Grooved Pegboard Test (Ruff and Parker, 1993), a motor task including complex coordination (there is adequate sensitivity for this test in classifying brain damaged patients) (Lezak, 1995). All tests were presented in the same fixed order for all subjects. The complete battery was administered in a quiet room with all but three subjects completing the NP battery in one sitting. To minimize fatigue, subjects were encouraged to take a short break toward the middle of the battery. Cigarette smokers were asked to refrain from smoking throughout the NP session and the short break; nevertheless, two subjects smoked a partial cigarette during the short break. In addition, nine smokers reported smoking a cigarette just prior to the NP assessment.

Consistent with other reports (Pace-Schott et al, 2005), and with a previously suggested `learning lag' in drug abusers (Verdejo-Garcia et al, 2007), our results revealed immediate verbal learning (CVLT total recall) and delayed verbal memory (CVLT delay-free recall) deficits that were most pronounced in the CUD- subgroup. These findings are noteworthy in light of recent evidence from animal research that points to modulation of memory function based on the cocaine withdrawal period; synaptic activity (long-term potentiation) was significantly compromised in the CA 1 region of the hippocampus in rats which had undergone a longer withdrawal period from cocaine (100 days) vs those with shorter periods of withdrawal (3 days) (Thompson et al, 2004). The notion that memory deficits are more pronounced with longer abstinence, an effect that until now was not reliably observed in humans, is clinically relevant. Indeed, it may explain why drug abusers in treatment often fail to use newly `learned' strategies aimed to prevent relapse. However, we cannot rule out the possibility that CVLT total recall reflects attention/executive dysfunction rather than a primary learning/memory deficit. Therefore, this finding remains to be replicated using additional memory tasks (including non-verbal tasks).

Using Ekman task, no differences were found between the CUD and controls in recognition of facial emotional expression in the current study. This negative result contrasts with evidence of impaired fear recognition in recreational cocaine users (average use = once per month) (Kemmis et al, 2007) and of similar difficulties as documented using additional emotional recognition tasks in current and abstinent abusers of other drugs (eg, 3,4-methylenedioxy-N-methylamphetamine, opiates, alcohol) (Hoshi et al, 2004); (Kornreich et al, 2003; Townshend and Duka, 2003). A possible explanation for this difference may pertain to the inclusion criteria. For example, in the study by Kemmis, history of other drug dependence (eg, ecstasy, heroin, cannabis) was not exclusionary, whereas in our study it was; drugs other than cocaine may, therefore, drive impairments in emotion recognition. Therefore, it remains to be determined whether deficits in emotion recognition, particularly fear recognition, are associated with cocaine use.

The current results suggest intact simple and complex motor function in cocaine abusers. These results contrast with findings in methamphetamine-addicted individuals in whom motor function was compromised (as measured with the grooved pegboard) compared with healthy control subjects and attributed to reductions in striatal dopamine transporter levels (Volkow et al, 2001). These differential results for cocaine vs methamphetamine abusers may reflect the unique impact of these psychostimulants on dopaminergic, serotonergic or noradrenergic motor-output systems (Muller et al, 2003, 2007; Jones et al, 2007), possibly revealing more methamphetamine-induced neurotoxicity.