Abstract
Background U.S. nationwide estimates indicate that 50% to 80% of prisoners have a history of substance abuse or dependence. Tailoring substance abuse treatment to specific needs of incarcerated individuals could improve effectiveness of treating substance dependence and preventing drug abuse relapse. We tested whether pretreatment neural measures of a response inhibition (Go/NoGo) task would predict which individuals would or would not complete a 12-week cognitive behavioral substance abuse treatment program. Methods Adult incarcerated participants (n = 89; women n = 55) who volunteered for substance abuse treatment performed a Go/NoGo task while event-related potentials (ERPs) were recorded. Stimulus- and response-locked ERPs were compared between participants who completed (n = 68; women = 45) and discontinued (n = 21; women = 10) treatment. Results As predicted, stimulus-locked P2, response-locked error-related negativity (ERN/Ne), and response-locked error positivity (Pe), measured with windowed time-domain and principal component analysis, differed between groups. Using logistic regression and support-vector machine (i.e., pattern classifiers) models, P2 and Pe predicted treatment completion above and beyond other measures (i.e., N2, P300, ERN/Ne, age, sex, IQ, impulsivity, depression, anxiety, motivation for change, and years of drug abuse). Conclusions Participants who discontinued treatment exhibited deficiencies in sensory gating, as indexed by smaller P2; error-monitoring, as indexed by smaller ERN/Ne; and adjusting response strategy posterror, as indexed by larger Pe. The combination of P2 and Pe reliably predicted 83.33% of individuals who discontinued treatment. These results may help in the development of individualized therapies, which could lead to more favorable, long-term outcomes.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 75-83 |
| Number of pages | 9 |
| Journal | Biological Psychiatry |
| Volume | 76 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jul 1 2014 |
| Externally published | Yes |
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Keywords
- Drug treatment
- event-related potentials
- pattern classifier
- principal component analysis
- response errors
- response inhibition
- support vector machine
ASJC Scopus subject areas
- Biological Psychiatry
- Medicine(all)
Cite this
Brain potentials measured during a Go/NoGo task predict completion of substance abuse treatment. / Steele, Vaughn R.; Fink, Brandi C.; Maurer, J. Michael; Arbabshirani, Mohammad R.; Wilber, Charles H.; Jaffe, Adam J.; Sidz, Anna; Pearlson, Godfrey D.; Calhoun, Vince Daniel; Clark, Vincent P.; Kiehl, Kent A.
In: Biological Psychiatry, Vol. 76, No. 1, 01.07.2014, p. 75-83.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Brain potentials measured during a Go/NoGo task predict completion of substance abuse treatment
AU - Steele, Vaughn R.
AU - Fink, Brandi C.
AU - Maurer, J. Michael
AU - Arbabshirani, Mohammad R.
AU - Wilber, Charles H.
AU - Jaffe, Adam J.
AU - Sidz, Anna
AU - Pearlson, Godfrey D.
AU - Calhoun, Vince Daniel
AU - Clark, Vincent P.
AU - Kiehl, Kent A.
PY - 2014/7/1
Y1 - 2014/7/1
N2 - Background U.S. nationwide estimates indicate that 50% to 80% of prisoners have a history of substance abuse or dependence. Tailoring substance abuse treatment to specific needs of incarcerated individuals could improve effectiveness of treating substance dependence and preventing drug abuse relapse. We tested whether pretreatment neural measures of a response inhibition (Go/NoGo) task would predict which individuals would or would not complete a 12-week cognitive behavioral substance abuse treatment program. Methods Adult incarcerated participants (n = 89; women n = 55) who volunteered for substance abuse treatment performed a Go/NoGo task while event-related potentials (ERPs) were recorded. Stimulus- and response-locked ERPs were compared between participants who completed (n = 68; women = 45) and discontinued (n = 21; women = 10) treatment. Results As predicted, stimulus-locked P2, response-locked error-related negativity (ERN/Ne), and response-locked error positivity (Pe), measured with windowed time-domain and principal component analysis, differed between groups. Using logistic regression and support-vector machine (i.e., pattern classifiers) models, P2 and Pe predicted treatment completion above and beyond other measures (i.e., N2, P300, ERN/Ne, age, sex, IQ, impulsivity, depression, anxiety, motivation for change, and years of drug abuse). Conclusions Participants who discontinued treatment exhibited deficiencies in sensory gating, as indexed by smaller P2; error-monitoring, as indexed by smaller ERN/Ne; and adjusting response strategy posterror, as indexed by larger Pe. The combination of P2 and Pe reliably predicted 83.33% of individuals who discontinued treatment. These results may help in the development of individualized therapies, which could lead to more favorable, long-term outcomes.
AB - Background U.S. nationwide estimates indicate that 50% to 80% of prisoners have a history of substance abuse or dependence. Tailoring substance abuse treatment to specific needs of incarcerated individuals could improve effectiveness of treating substance dependence and preventing drug abuse relapse. We tested whether pretreatment neural measures of a response inhibition (Go/NoGo) task would predict which individuals would or would not complete a 12-week cognitive behavioral substance abuse treatment program. Methods Adult incarcerated participants (n = 89; women n = 55) who volunteered for substance abuse treatment performed a Go/NoGo task while event-related potentials (ERPs) were recorded. Stimulus- and response-locked ERPs were compared between participants who completed (n = 68; women = 45) and discontinued (n = 21; women = 10) treatment. Results As predicted, stimulus-locked P2, response-locked error-related negativity (ERN/Ne), and response-locked error positivity (Pe), measured with windowed time-domain and principal component analysis, differed between groups. Using logistic regression and support-vector machine (i.e., pattern classifiers) models, P2 and Pe predicted treatment completion above and beyond other measures (i.e., N2, P300, ERN/Ne, age, sex, IQ, impulsivity, depression, anxiety, motivation for change, and years of drug abuse). Conclusions Participants who discontinued treatment exhibited deficiencies in sensory gating, as indexed by smaller P2; error-monitoring, as indexed by smaller ERN/Ne; and adjusting response strategy posterror, as indexed by larger Pe. The combination of P2 and Pe reliably predicted 83.33% of individuals who discontinued treatment. These results may help in the development of individualized therapies, which could lead to more favorable, long-term outcomes.
KW - Drug treatment
KW - event-related potentials
KW - pattern classifier
KW - principal component analysis
KW - response errors
KW - response inhibition
KW - support vector machine
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UR - http://www.scopus.com/inward/citedby.url?scp=84902255918&partnerID=8YFLogxK
U2 - 10.1016/j.biopsych.2013.09.030
DO - 10.1016/j.biopsych.2013.09.030
M3 - Article
C2 - 24238783
AN - SCOPUS:84902255918
VL - 76
SP - 75
EP - 83
JO - Biological Psychiatry
JF - Biological Psychiatry
SN - 0006-3223
IS - 1
ER -