P3 components and adolescent binge drinking in Southwest California Indians

Neurotoxicology and Teratology 29 (2007) 153 – 163 www.elsevier.com/locate/neutera

P3 components and adolescent binge drinking in Southwest California Indians Cindy L. Ehlers a,b,⁎, Evelyn Phillips a , Gina Finnerman a , David Gilder a , Philip Lau a , Jose Criado c a

Department of Molecular and Integrative Neurosciences, The Scripps Research Institute, 10550 N. Torrey Pines Rd., La Jolla, CA 92037, USA b Molecular and Experimental Medicine, The Scripps Research Institute, 10550 N. Torrey Pines Rd., La Jolla, CA 92037, USA c Scripps Clinic, Division of Neurology, Brain Research and Treatment Center, 10666 N. Torrey Pines Rd., La Jolla, CA, 92037, USA Received 24 August 2006; received in revised form 29 November 2006; accepted 29 November 2006 Available online 8 December 2006

Abstract In adolescence, consuming a large number of drinks over a short interval of time (e.g. binging) is not an uncommon occurrence. Since adolescence is an important neurodevelopmental period, the effect of binge drinking on brain and behavior has become a significant health concern. The present study evaluated event-related potentials (ERPs) in young adult Southwest California Indians who had a history of binge drinking during their adolescence. One hundred twenty five participants who were currently 18–25 yrs of age who were free of Axis I psychiatric diagnoses were categorized as: 1) reporting no binge drinking during adolescence (N 5 drinks per occasion before age 18) or drug dependence diagnoses 2) reporting binge drinking during adolescence with no drug dependence diagnoses 3) reporting binge drinking during adolescence and drug dependence diagnoses. ERPs were collected using a facial discrimination task. Adolescent alcohol and drug exposure was found to be associated with decreases in the latency of an early P3 component (P350). Decreases in a later component amplitude (P450) were also found in young adults exposed to alcohol, and those exposed to alcohol and drugs. However, that finding appears to be a combined result of predisposing factors such as family history of alcoholism and presence of other externalizing diagnoses. Taken together these preliminary studies suggests that adolescent binge drinking may result in a decreases in P3 component latencies and amplitudes perhaps reflecting a loss or delay in the development of inhibitory brain systems. © 2006 Elsevier Inc. All rights reserved. Keywords: Native Americans; Alcohol dependence; Drug dependence; Adolescents; ERPs; P300

1. Introduction Although tribes differ with regard to the use of alcohol and drugs several Native American communities have alcohol dependence rates that are 2–5 times higher than the general US population [54,83,90,96,118]. Few studies have investigated risk factors that may contribute to the variance in these high rates of the disorder. Within the Native American population adolescents are a particularly high risk group [see 27,99,116,117]. Native American adolescents show the highest prevalence rates of alcohol use compared to other ethnic groups [2,14,24,35,38,48, 89,102,110,121]. ⁎ Corresponding author. The Scripps Research Institute, 10550 North Torrey Pines Road, SP30-1501, La Jolla, CA 92037, USA. Tel.: +1 858 784 7058; fax: +1 858 784 7409. E-mail address: [email protected] (C.L. Ehlers). 0892-0362/$ - see front matter © 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.ntt.2006.11.013

Indian adolescent drinking practices are hypothesized to result from an interaction of risk behaviors (e.g. antisocial behavior, peer pressure, stressful life events) and protective behaviors (school success, cultural activities, family support) [see 5,35,92,95]. Environmental factors such as living on a reservation and/or attending a boarding school have also been suggested to impact drug abuse [89,94,98,101]. There have been few studies evaluating biologically based risk factors, or the neurobehavioral consequences of adolescent use/abuse of alcohol in Native Americans. The relationship between early onset of drinking and subsequent development of alcohol-related problems has been well documented in a number of large local and national surveys [4,59,74,91]. Grant and Dawson [55] have estimated, based on the NLAES data, that the odds of alcohol dependence decreased by 14% with each increasing year drinking was forestalled. In the twin sample studied by Prescott and Kendler [111] the risk

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for developing alcohol dependence decreased by 21% for each year delayed. There is also substantial evidence that links an early history of antisocial behaviors to the development of alcohol use disorders in general population samples [28,81, 115,138]. Early patterns of alcohol use may also lead to other problem behaviors and conversely early antisocial orientations can contribute to the onset of drinking [113,114]. We have demonstrated that early onset of intoxication in Southwest California Indians is a highly significant variable in predicting both the time to onset of alcohol dependence as well as its prevalence in the population [45]. Consistent with the literature, several other risk factors have also been found to be associated with alcohol dependence in SWC Indians including: being male, unmarried, dropping out of high school, having a first degree family history of alcohol dependence, and having an externalizing diagnosis (conduct disorder or antisocial personality disorder) [45]. Interestingly, having an internalizing diagnosis (any affective or anxiety disorder) has not been found to be associated with an alcohol dependence diagnosis nor did it influence the time from first intoxication to the development of alcohol dependence [45,54]. Studying bio-behavioral risk factors for and the consequences of underage alcohol use in Native Americans is crucial for a number of reasons. The fact that underage drinking is more likely to lead to the rapid development of alcohol dependence suggests that alcohol may be “more addicting” to underage drinkers, a finding also partly confirmed by controlled studies in animal models of the disorder [126]. Also from a developmental point of view, alcohol and other substance exposure during adolescence may have long lasting consequences. Rapid changes in neural organization occur during this time period [75,120] including a reduction in the number of synapses in cortical and subcortical structures, and changes in neurotransmitter and receptor levels [92,131,135]. It has been suggested that these changes in CNS organization may make the brain uniquely vulnerable to insult by drug use/abuse. In fact some investigators have suggested, based on animal studies, that there may be a “drug-induced developmental neurotoxicity of adolescence” [33,124]. Thus, during adolescence, drugs may be both more addicting and more neurotoxic, a combination that makes drug abuse particularly malignant for adolescents. Electrophysiology has been successfully used to assess the chronic effects of long-term alcohol usage [15] although it has not been employed specifically to assay the effects of adolescent alcohol exposure. It has distinct advantages in indexing cognitive changes associated with alcohol exposure since cognition and behavior can be indexed simultaneously and subtle dysfunctions in specific stages in information processing can be detected. One electrophysiological measure that has been commonly been used to assay alcohol effects and alcohol related risks is the P300 component of the ERP. Although not all studies agree, changes in both the amplitude and latency of the P300 component of the ERP have been reported in alcoholics and in subjects with a family history of alcoholism (for reviews see [64,66,107,108,109]). There is also a literature suggesting that P300 amplitude deficits are associated with conduct disorder/antisocial personality disorder [6–12,26,29,

76,100] as well as other psychiatric disorders related to and/or comorbid with alcoholism [13,72,73]. It has also been suggested that lowered P300 amplitude may be a general measure of CNS disinhibition [16] or frontal executive dysfunction [52,82]. The present report is part of a larger study exploring risk factors for alcoholism among Southwest California Indians (collectively called Mission Indians) [42–44,50,51,54,133]. In this study, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) was employed to evaluate a sample of 525 reservation dwelling Southwest California Indians from eight contiguous reservations. The specific goal of this report was to examine the association between reported levels of adolescent drinking, with and without other drug dependence, and the P3 component of the ERP in a subset of young adult (18–25 yrs) Southwest California Indians. 2. Methods 2.1. Participants Participants were recruited from eight geographically contiguous reservations with a total population of about 3000 individuals, using a combination of a venue-based method for sampling hard-to-reach populations [80,97] as well as a respondent-driven procedure [60] as previously described [44,54]. Transportation from home to The Scripps Research Institute was provided by the study. To be included in the larger study, participants had to be Mission Indian, at least 1/16th Native American Heritage (NAH), between the age of 18 and 70 yrs, and be mobile enough to be transported from his or her home to the General Clinical Research Center (GCRC) of The Scripps Research Institute (TSRI). The protocol for the study was approved by the Institutional Review Board (IRB) of TSRI, the Scientific Advisory Committee of the GCRC, and the Indian Health Council, a tribal review group overseeing health issues for the reservations where recruitment was undertaken. 2.2. Measures Potential participants first met individually with research staff to have the study explained and give written informed consent. During a screening period, participants had blood pressure and pulse taken, took an alcohol breathalyzer test to assess blood alcohol concentration, and completed a questionnaire that was used to gather information on demographics, personal medical history, ethnicity, and drinking history [119]. No individuals with detectable breath alcohol levels were included in the study dataset (n = 3). During the screening period, the study coordinator also noted whether the participant was agitated, tremulous, or diaphoretic. Each participant also completed an interview with the SSAGA [25] which was used to make substance use disorder and psychiatric disorder diagnoses according to DSM-III-R criteria [1]. The SSAGA is a fully structured, poly-diagnostic psychiatric interview that has undergone both reliability and validity testing [25,62]. It has

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been used in another Native American sample [65,63]. Interviewers were trained by personnel from the COGA. The SSAGA interview retrospectively asks about the use and abuse of and dependence on alcohol. Drinking history was obtained using a timeline follow back procedure. Each participant was asked when they first began drinking regularly (drank at least 1 drink a month for a six month period). They were then asked to document their quantity and frequency of drinking from that time to the present indicating when any change in their pattern of drinking occurred. The SSAGA was used to collect information on the age at first intoxication, demographic variables and was also used to make a lifetime diagnosis of alcohol abuse or dependence, drug abuse and dependence, conduct disorder, antisocial personality disorder (ASPD), and Axis I disorders according to DSM-III-R criteria [1]. All best final diagnoses were made by a research psychiatrist/ addiction specialist. Information on family history of alcohol dependence was collected using the Family History Assessment Module (FHAM) developed by COGA [112]. 2.3. ERP collection and analyses Seven channels of ERP data (FZ, CZ, PZ, F3, F4, F7, and F8, referenced to linked ear lobes with a forehead ground, international 10–20 system) were obtained using gold-plated electrodes with impedance held below 5 kΩ. Frontal electrodes were emphasized in the montage as previous data had suggested that P3 decrements in frontal areas distinguished subjects with a family history of alcohol dependence [see 6]. An electrode placed left lateral infraorbitally and reference to the left earlobe was used to monitor both horizontal and vertical eye movements. ERP recording signals were amplified (high pass 0.5 Hz, 35 Hz low pass) using a Nihon Kohden EEG machine and were transferred on-line to a PC for digitation. The combined gain of the EEG amplifiers and the analog-to-digital multiplexer amplifier was 50 K. The present study used a facial discrimination task [46,56,61] that was adapted for use in an ERP paradigm [103]. The stimuli were digital photographs of happy, neutral and sad faces presented on a computer screen for 1000 ms with an inter-trial interval of 1000–1500 ms. The pre-stimulus interval was 150 ms. Participants were instructed to depress a counter whenever a happy or sad face was displayed (36 trials each) and not to respond to neutral faces (144 trials). There were 36 total faces (12 each of happy, neutral, and sad) presented in random order for a total of 216 trials. The number of male and female faces presented was also equally distributed among neutral, sad and happy stimuli. The ERP trials were digitized at a rate of 256 Hz. Individual trials containing excessive eye movement artifact as well as trials where the EEG exceeded ± 250 mV (b 5% of the trials) were eliminated before averaging. Trials in which subjects responded below the 300 ms and above the 1000 ms latency window were excluded. The occurrence of eye movements was noted on individual trials and eliminated prior to averaging. For target stimuli, only trials with correct identification were included in the averaging. The P350 and P450 components of the

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ERP were quantified using a computerized peak detection routine that identifies baseline-to-peak amplitudes (in μV). The baseline was determined by averaging the 100 ms of prestimulus activity obtained for each trial. The routine is userdriven and each peak detection must be verified by the user to occur within specified latency windows (P350: 250–400 ms: P450: 400–600 ms). All peaks were quantified by one investigator (E.P., R EEG Tech), and verified by a second investigator (C.L.E.), both of whom were blind to participants characteristics. 2.4. Data analyses The data analyses were based on the specific aim that was to determine if any associations existed between adolescent drinking and drug usage, and P3 ERP components. The hypotheses that were generated were based on previous ERP research in populations at varying degrees of risk for the development of alcohol dependence (see 7,8) as well as ERP studies from this SWC Indian population [39,40]. The focus was on two components: the P350 and P450 components of the ERP; a principal component analysis (PCA) was performed over the seven electrode locations for the P350 and P450 amplitudes to the three faces (neutral, sad, happy) in the facial recognition task. For each of the stimuli, varimax rotation yielded two components (eigenvalues N 1, range 1.18–5.70). The electrode sites loading on the first factor were the frontal leads (FZ, F3, F4, F7, F8) (loadings ranged from 0.81 to 0.94). The electrode sites loading on the second factor were the two more posterior leads (CZ, PZ). The two orthogonal factors each explained between 81 and 89% of the variance for the ERP task. P350 and P450 amplitudes and latencies were each averaged across the electrode sites within each of the two identified components: 1 = (FZ, F3, F4, F7, F8), 2 = (CZ, PZ), generating a mean latency and a mean amplitude for each of the two regions. These regionally averaged scores were generated for each stimulus condition (neutral, sad, happy) generating mean amplitude and latency for each of the two component regions, for each stimulus category for each individual. The regionally averaged P350 and P450 amplitudes and latencies generated by the facial discrimination task were used as dependent variables. The aim of the study was to test for association between P350 and P450 component amplitude and latencies and a participant's adolescent drinking and drug use history. For these analyses, P350 and P450 amplitudes and latencies for the two components identified in the PCA (frontal leads, centro-parietal leads) generated to the stimuli obtained from the stimuli in the facial discrimination task (happy, sad, neutral), were evaluated between the three groups of participants (controls, alcohol exposure, alcohol and drug exposure) using multivariate ANCOVAs where family history of alcoholism and presence of ASPD/CD were covariates. Fisher's exact test for dichotomous variables and ANOVA for continuous variables were used to evaluate potential differences in demographic variables between groups (low alcohol use in adolescence, high alcohol use in adolescence, high alcohol and drug use during adolescence). Statistical significance was set at the 0.05 probability level.

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3. Results Five hundred seventy one participants' records were available for these analyses. Individual records were excluded if the participant was older than 25 yrs of age or they had an Axis I psychiatric diagnosis. Inclusion criteria were that the participant must fit within one of the three following categories: 1) reporting no regular binge drinking during adolescence (mean intake per occasion before age 18 was b 5 drinks per occasion) and no drug dependence diagnoses, 2) reporting regular binge drinking (mean intake before age 18 was N 5 drinks per occasion) during adolescence with no lifetime drug dependence diagnoses, 3) reporting binge drinking during adolescence and drug dependence diagnoses. A lifetime DSM-III-R drug dependence diagnoses was defined as meeting dependence criteria for one or more of the following substance categories: marijuana, cocaine, stimulants, sedatives, opiates, hallucinogens, PCP and solvents. Table 1 presents the demographic characteristics of the three groups. The three groups of participants (control, alcohol exposed, alcohol and drug exposed, n = 125) were not significantly different in age, in the numbers of males and female participants, in the number of years of education or in their percentage of Native American Heritage. An overall significant difference between the three groups was found on: family history of alcohol dependence, lifetime history of alcohol dependence, age at first intoxication, adolescent drinking quantities and frequencies, the maximum number of drinks they had ever consumed in a 24 h period and in the presence of an ASPD or CD diagnosis. A post-hoc analysis revealed that the alcohol exposed and alcohol and drug exposed groups did not significantly differ on any of these variables. However, the

control group differed from the other two groups on: lifetime history of alcohol dependence diagnoses, age at first intoxication, adolescent drinking quantities and frequencies, the maximum number of drinks they had ever consumed in a 24 h period and in the presence of an ASPD or CD diagnosis, and the control group and the alcohol plus drugs group differed on a family history of alcohol dependence (but not the control and alcohol only group). In Fig. 1 examples are presented of ERP waveforms from individual participants to indicate the presence of the P350 and P450 components that were identified. The stimuli for this task were 36 realistic digital photographs of male and female, white non-Hispanic faces, with happy, neutral and sad expressions. While this paradigm clearly differs from those used to classically generate P3a and P3b components, the facial expressions did generate 2 components, one with a latency around 350 ms and one with a latency centering on 450 ms. The P350 component is more distinct in the frontal leads, in that the waveform returns to baseline prior to the P450 component, in approximately two/thirds of the participants. In the central and parietal leads the waveform may be distinct or it may appear as a “hump” and not return completely to baseline. One interpretation of the finding that this paradigm generated of two separate P300 components is that the facial stimuli may have been perceived as somewhat “novel” by these Native American young adults. Alternatively, in a recent report by Dien and colleagues [36] it was concluded that P3a's can be elicited by target stimuli, in general, that are not necessarily novel or confined to an oddball paradigm. Multivariate ANCOVA (where family history of alcohol dependence and presence of ASPD/CD were covariates) that

Table 1 Demographic characteristics of Native American young adults (n = 125) Demographic variable Gender (n) Male Female Age (yrs) Years of education Native American heritage (n) b50% ≥ 50% Alcohol dependence diagnosis (n) ⁎, ⁎⁎ No Yes Family history of alcohol dependence (n) ⁎⁎ Family history negative Family history positive Age of first intoxication (in years)⁎, ⁎⁎ Adolescent drinking quantity (drinks per occasion)⁎, ⁎⁎ Adolescent drinking frequency (days per month)⁎, ⁎⁎ Largest number of drinks ever consumed over a 24-hour period⁎, ⁎⁎ Diagnosis of CD or ASPD (n)⁎, ⁎⁎ No Yes Values are x¯ ± SEM unless indicated. ⁎ Control vs. alcohol exposed group (p b .05). ⁎⁎ Control vs. alcohol and drug exposed group (p b .05).

Control (n = 36)

Alcohol exposure (n = 30)

Alcohol and drug exposure (n = 59)

p-value

15 21 19.639 ± 2.193 11.472 ± 1.682

15 15 19.767 ± 2.079 11.233 ± 1.501

22 37 20.322 ± 2.232 11.610 ± 1.300

0.516

22 14

13 17

25 34

0.175

36 0

11 19

11 48

0.000

21 15 16.952 ± 1.627 (n = 21) 0.306 ± 0.786 0.250 ± 0.770 7.229 ± 7.021 (n = 35)

11 19 14.179 ± 2.405 (n = 28) 13.433 ± 9.145 12.500 ± 8.807 28.933 ± 21.504

15 42 13.932 ± 2.157 10.712 ± 5.392 10.780 ± 6.724 28.390 ± 17.959

0.008

35 1

22 8

42 17

0.276 0.520

0.000 0.000 0.000 0.000 0.007

C.L. Ehlers et al. / Neurotoxicology and Teratology 29 (2007) 153–163 Fig. 1. Individual averages of event-related potentials (ERPs) elicited by a facial discrimination task in 6 SWC Indian young adults. Averages are presented for midline frontal (Fz) central (Cz) and parietal (Pz) leads. The location of the P350 and P450 components are indicated in the Fz electrode location.

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compared the P350 and P450 ERP components between the three groups (control, alcohol exposed, alcohol and drug exposed) revealed that the control group differed from the alcohol and drug exposed groups on the latency of the P350 component. As seen in Fig. 2, a significant increase in P350 latency was found in the control group as compared to the alcohol exposed in response to the happy (frontal: F = 9.84, df = 1,62, p b 0.003; centro-parietal: F = 14.8, df = 1,62, p b 0.0001) neutral (frontal: F = 4.6, df = 1,62, p b 0.035; centro-parietal: F = 4.7, df = 1,62, p b 0.034) and sad (frontal: F = 4.16, df = 1,62, p b 0.046; centro-parietal: F = 5.8, df = 1,62,

Fig. 3. Grand averages of event-related potentials (ERPs) elicited from SWC Indian adults in response to the target (happy, sad) stimuli in SWC Indians. Averages are presented for midline frontal (Fz) central (Cz) and parietal (Pz) leads. Data are presented for controls with no binge drinking during adolescence or drug dependence in the solid lines, those participants who experienced binge drinking during adolescence but no drug dependence in the long dashed lines and those who experienced binge drinking during adolescence and also had drug dependence in the short dashed lines. A significantly lower P450 amplitude was found in the alcohol, and alcohol and drug dependence groups.

Fig. 2. P350 latency elicited from SWC Indian young adults in response to different facial stimuli (happy, neutral and sad) in frontal and centro-parietal leads. Data are presented for controls with no binge drinking during adolescence or drug dependence in the solid bars, those participants who experienced binge drinking during adolescence but no drug dependence in the open bars and those who experienced binge drinking during adolescence and also had drug dependence in the dotted bars. A significantly shorter P350 latency was observed in the alcohol and alcohol and drug dependence groups when compared to controls (⁎p b 0.05, ⁎⁎p b 0.01).

p b 0.019) facial expressions. A significant increase in the P350 latency was also found in the control group as compared to the drug and alcohol exposed groups in response to the happy (frontal: F = 6.3, df = 1,89, p b 0.014; centro-parietal: F = 7.88, df = 1,89, p b 0.006) and neutral (frontal: F = 4.2, df = 1,89, p b 0.042; centro-parietal: F = 5.5, df = 1,89, p b 0.021) facial expressions. No significant differences were found between the alcohol exposed and alcohol and drug exposed groups on P350 latency. No significant effects on P350 amplitude were found between the groups. Family history and presence of ASPD/CD were not found to be significant co-variates in any of these analyses. Additionally, there were no significant differences in the behavioral reaction time to indicate a correct target stimulus between the three groups. Fig. 3 displays grand averages of the event related potentials for the three groups of participants for the target stimuli (happy and sad facial expressions). P450 amplitude was found to be lower between the three substance exposure groups in response to the happy target stimuli. A significantly smaller P450 amplitude was seen in the alcohol exposed group when compared to the no exposure controls in the centro-posterior leads (F = 10.8, df = 1,62, p b 0.002), and family history of alcohol dependence, but not personal history of CD/ASPD, was found to be a significant

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covariate in that analysis. A significantly smaller P450 amplitude was also seen between the no exposure controls and the alcohol plus drug dependence group in the centro-posterior leads (F = 5.5, df = 1,92; p b 0.025), however, neither family history or CD/ ASPD was found to be a significant covariate in that analysis. No significant difference in P450 amplitude was seen between alcohol exposed and drug and alcohol exposed participants. 4. Discussion In this study, decreases in the latency of the P350 component and the amplitude of the P450 component in response to a facial expression task were found in association with a history of adolescent substance exposure in SWC Indian young adults. One major theoretical interpretation of the P300 is that it indexes the mental representation of “cognitive updating” when a change occurs in the stimulus environment [37]. Many authors have contributed to the literature that suggests that the P300 may have two components, a P3a and P3b, or early and late P300 [see 106]. Early positive components (in the 300 ms range in visual tasks) have been suggested to be associated with the “novelty” of a stimulus, and with the redirection of attention monitoring [3,31,58,85,86,127]. This early positivity has also been interpreted as indexing the operation of an automatic attention network that is responsive to stimulus deviance [see 106]. The early P300 has also been associated with changes in frontal lobe activation [49,87] and is clearly diminished in patients with frontal lobe lesions [52,84]. In contrast, the late positive component (400 ms in a visual task) is elicited when a stimulus is processed and evaluated in the context of the previous stimuli and may index memory updating {for a review, see [106]}. The origin of the later P300 or stimulus “target” positivity is thought to be more posterior in origin than the earlier potentials perhaps involving temporal-parietal junction [88,137]. The findings of the present study, a decrease in P3 latency in alcohol and drug exposed young adults, is somewhat counterintuitive as some previous studies have reported increases in P3 latency as a function of alcohol dependence, particularly in older adults (see [23,104,105]). The visual P300 decreases in amplitude and latency over the course of adolescence but stabilizes in young adults [19,30,68,77,128]. It is possible that the alcohol and drug exposed young adults may be experiencing a more rapid maturing of their age-related changes in P3 latency. The mechanisms underlying the adolescent changes seen in P300 are not fully understood. There are several important brain processes that are occurring during adolescence including the attrition of synapses and neurons as well as the completion of frontal myelination (see [18,32,53,78,93,125,130,136]) that could contribute to changes in P300 morphology. It is possible that alcohol and/or drug exposure during adolescence enhances the attrition of synapses and neurons seen during this time period leading to a more rapid decrease in latency and amplitudes changes in P300 morphology. Falkenstein and colleagues [47] have suggested that a P3alike component called the “P-SR” (positivity-simple response) exists, the latency of which reflects only the detection of a stimulus as opposed to a later “P-CR” (positivity-choice

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response) or P3b that is associated with stimulus evaluation and complexity, and the need for “context updating” [36,47]. Within this theoretical construct the present findings of a shorter P350 latency in the alcohol and drug exposed group could be interpreted as a more rapid activation of the simple detection system. However, since the latency of the P450 component was equivalent was in both groups, this meant a longer time elapsed between the detection of the stimulus and the actual evaluation/ choice response. Further studies will be necessary to confirm that these findings are not spurious or simply unique to this SWC Indian population. The presence of impaired inhibitory regulation, also termed “disinhibition” [132] has been forwarded as an explanation for the decrease seen in P300 amplitude in youths who are at high risk for substance use disorder (see [7–10,16,17,20– 22,57,67,69,70,76,79,129,134]). In the present study, lower P450 amplitude was associated with adolescent alcohol exposure, and family history of alcohol dependence was a significant covariate in the analyses. This investigation extends our previous studies, in SWC Indian youth (age 8–13 yrs, prior to alcohol and drug exposure), where a significant relationship between P450 amplitude and family history for alcohol dependence as well as the presence of externalizing traits was found [39–41]. However, decreases in P300 amplitude were not found in older adult SWC Indians as a function of family history of alcohol dependence, only as a function of a personal history of alcohol dependence [34]. Hill and colleagues have suggested that the reduction in P300 amplitude seen in children at high risk for developing alcohol dependence, but not always in adults, is due to a developmental delay that can be seen in adolescents and children but is not present by adulthood [71,68]. It may be that alcohol exposure enhances this developmental delay and/or leads to a permanent deficit in P300 amplitude. This notion is partially supported by studies in animals where exposure to alcohol vapor during adolescence was found to be associated with long lasting decreases in P300 amplitudes in adult rats [123]. Thus, it is likely that P300 amplitude may index both predisposing factors as well as exposure to alcohol. It is also possible that predisposing factors may have contributed to the finding of a decreased P350 latency that was associated with adolescent alcohol exposure in this SWC Indian young adult population. However, we did not find that a family history of alcohol dependence or a personal history of an externalizing disorder (ASPD/CD) was a significant covariate in our analyses. Additionally, studies in rodents also confirm that early positive ERP components are impacted by a significant history of peri adolescent and/or adult alcohol exposure [122,123]. The results of this study should be interpreted in the context of several limitations. First, the findings may not generalize to other Native Americans or represent all SWC Indians. Second, only retrospective and cross-sectional data on alcohol use and use disorders were assessed. The ERP paradigm used was not designed to clearly delineate between P3a and P3b components, and the high pass filter (0.5 Hz) may have eliminated or reduced slow wave contributions to the overall P3 amplitude. Despite

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these limitations, this report represents an important step in an ongoing investigation to determine genetic and environmental factors associated with substance use and use disorders in this high risk and understudied ethnic group. 5. Summary Our preliminary evidence suggests that adolescent alcohol exposure is associated with decreases in P350 latencies. Decreases in P450 amplitude are also noted in alcohol exposed young adults however that finding may be a combined result of predisposing factors as well as adolescent alcohol exposure. Interestingly, these findings appear to be associated with exposure to alcohol and were not enhanced by exposure to other drug dependencies. Acknowledgements Supported in part by AA10201, DA019333 the Center for Minority Health/Health Disparities, the Stein Endowment fund and a General Clinical Research Center Grant 00833. JRC is recipient of the Dallas and Mary Clark Fellowship in Human Neurophysiology at the Brain Research and Treatment Center, Scripps Clinic, La Jolla, CA. The authors thank Michelle Dixon, Linda Corey, Lilach Harris, Susan Lopez, and Vincent Wong for assistance in data collection and analyses, and Shirley Sanchez for editing the manuscript. References [1] American Psychiatric Association, Diagnosis and statistical manual of mental disorders (DSM-III-R); American Psychiatric Association; Task Force, American Psychiatric Association, Washington, D.C. 1987. [2] J.G. Bachman, J.M. Wallace Jr., P.M. O'Malley, L.D. Johnston, C.L. Kurth, H.W. Neighbors, Racial/ethnic differences in smoking, drinking, and illicit drug use among American high school seniors, 1976–89, Am. J. Public Health 81 (1991) 372–377. [3] F. Barcelo, S. Suwazono, R.T. Knight, Prefrontal modulation of visual processing in humans, Nat. Neurosci. 3 (2000) 399–403. [4] G.M. Barnes, J.W. Welte, Patterns and predictors of alcohol use among 7–12th grade students in New York State, J. Stud. Alcohol 47 (1986) 53–62. [5] S.C. Bates, F. Beauvais, J. Trimble, American Indian adolescent alcohol involvement and ethnic identification, Subst. Use Misuse 32 (1997) 2013–2031. [6] L.O. Bauer, Frontal P300 decrements, childhood conduct disorder, family history, and the prediction of relapse among abstinent cocaine abusers, Drug Alcohol Depend. 44 (1997) 1–10. [7] L.O. Bauer, V.M. Hesselbrock, Subtypes of family history and conduct disorder: effects on P300 during the stroop test, Neuropsychopharmacology 21 (1999) 51–62. [8] L.O. Bauer, V.M. Hesselbrock, P300 decrements in teenagers with conduct problems: implications for substance abuse risk and brain development, Biol. Psychiatry 46 (1999) 263–272. [9] L.O. Bauer, V.M. Hesselbrock, CSD/BEM localization of P300 sources in adolescents “at-risk": evidence of frontal cortex dysfunction in conduct disorder, Biol. Psychiatry 50 (2001) 600–608. [10] L.O. Bauer, V.M. Hesselbrock, Brain maturation and subtypes of conduct disorder: interactive effects on P300 amplitude and topography in male adolescents, J. Am. Acad. Child Adolesc. Psychiatry 42 (2003) 106–115.

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