Contact
Biomedical Research Center251 Bayview Boulevard
Baltimore, MD 21224
Email: vaughn.steele@nih.gov
Education
B.A. - Psychology, University of Minnesota
Ph.D. - Cognitive Psychology, University of Minnesota
Research Interests
Dr. Steele received his B.A (2004) in Psychology and Ph.D. (2011) in Cognitive Psychology from the University of Minnesota. In 2011 he accepted a post-doctoral fellowship at the non-profit Mind Research Network in Albuquerque, New Mexico. In 2014, he achieved the position of assistant professor of translational neuroscience at the Mind Research Network. He also holds assistant research professor and research scientist positions in departments of psychology at the University of New Mexico and University of Maryland, College Park, respectively. In 2015, Dr. Steele accepted a post-doctoral fellow position in Dr. Elliot Stein’s lab at the intramural research program at the National Institutes of Health, National Institute on Drug Abuse in Baltimore Maryland.
Dr. Steele focuses on bridging the gap between understanding basic cognitive functions and clinical applications with an emphasis on developing neuroprediction models of substance abuse and relapse. His research aims to elucidate the underlying neural networks related to cognitive control and response inhibition using electroencephalography (EEG), magnetic resonance imaging (MRI), and transcranial magnetic stimulation (TMS). He employs advanced analytical methods, such as time-frequency analysis, principal component analysis, independent component analysis, and pattern classifiers.
Projects
A specific, ongoing research goal is to further develop neuroprediction models of substance abuse and relapse which can then affect policy changes related to substance abuse as well as developing targeted, specialized treatment programs.
Selected Publications
2016
Anderson NE Steele VR, Claus ED
Neuroimaging measures of error-processing: Extracting reliable signals from event-related potentials and functional magnetic resonance imaging. Journal Article
In: Neuroimage, 2016.
@article{Steele2016,
title = {Neuroimaging measures of error-processing: Extracting reliable signals from event-related potentials and functional magnetic resonance imaging.},
author = {Steele VR, Anderson NE, Claus ED, Bernat EM, Rao V, Assaf M, Pearlson GD, Calhoun VD, Kiehl KA.},
url = {https://www.ncbi.nlm.nih.gov/pubmed/26908319},
doi = {doi: 10.1016/j.neuroimage.2016.02.046},
year = {2016},
date = {2016-02-22},
journal = {Neuroimage},
abstract = {Error-related brain activity has become an increasingly important focus of cognitive neuroscience research utilizing both event-related potentials (ERPs) and functional magnetic resonance imaging (fMRI). Given the significant time and resources required to collect these data, it is important for researchers to plan their experiments such that stable estimates of error-related processes can be achieved efficiently. Reliability of error-related brain measures will vary as a function of the number of error trials and the number of participants included in the averages. Unfortunately, systematic investigations of the number of events and participants required to achieve stability in error-related processing are sparse, and none have addressed variability in sample size. Our goal here is to provide data compiled from a large sample of healthy participants (n=180) performing a Go/NoGo task, resampled iteratively to demonstrate the relative stability of measures of error-related brain activity given a range of sample sizes and event numbers included in the averages. We examine ERP measures of error-related negativity (ERN/Ne) and error positivity (Pe), as well as event-related fMRI measures locked to False Alarms. We find that achieving stable estimates of ERP measures required four to six error trials and approximately 30 participants; fMRI measures required six to eight trials and approximately 40 participants. Fewer trials and participants were required for measures where additional data reduction techniques (i.e., principal component analysis and independent component analysis) were implemented. Ranges of reliability statistics for various sample sizes and numbers of trials are provided. We intend this to be a useful resource for those planning or evaluating ERP or fMRI investigations with tasks designed to measure error-processing.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Error-related brain activity has become an increasingly important focus of cognitive neuroscience research utilizing both event-related potentials (ERPs) and functional magnetic resonance imaging (fMRI). Given the significant time and resources required to collect these data, it is important for researchers to plan their experiments such that stable estimates of error-related processes can be achieved efficiently. Reliability of error-related brain measures will vary as a function of the number of error trials and the number of participants included in the averages. Unfortunately, systematic investigations of the number of events and participants required to achieve stability in error-related processing are sparse, and none have addressed variability in sample size. Our goal here is to provide data compiled from a large sample of healthy participants (n=180) performing a Go/NoGo task, resampled iteratively to demonstrate the relative stability of measures of error-related brain activity given a range of sample sizes and event numbers included in the averages. We examine ERP measures of error-related negativity (ERN/Ne) and error positivity (Pe), as well as event-related fMRI measures locked to False Alarms. We find that achieving stable estimates of ERP measures required four to six error trials and approximately 30 participants; fMRI measures required six to eight trials and approximately 40 participants. Fewer trials and participants were required for measures where additional data reduction techniques (i.e., principal component analysis and independent component analysis) were implemented. Ranges of reliability statistics for various sample sizes and numbers of trials are provided. We intend this to be a useful resource for those planning or evaluating ERP or fMRI investigations with tasks designed to measure error-processing.
2015
Steele, Vaughn R; Rao, Vikram; Calhoun, Vince D; Kiehl, Kent A
Machine learning of structural magnetic resonance imaging predicts psychopathic traits in adolescent offenders. Journal Article
In: Neuroimage, vol. 145, no. Pt B, pp. 265–273, 2015, ISSN: 1095-9572 (Electronic); 1053-8119 (Linking).
@article{Steele2015c,
title = {Machine learning of structural magnetic resonance imaging predicts psychopathic traits in adolescent offenders.},
author = {Steele, Vaughn R and Rao, Vikram and Calhoun, Vince D and Kiehl, Kent A},
url = {https://www.ncbi.nlm.nih.gov/pubmed/26690808},
doi = {10.1016/j.neuroimage.2015.12.013},
issn = {1095-9572 (Electronic); 1053-8119 (Linking)},
year = {2015},
date = {2015-12-12},
journal = {Neuroimage},
volume = {145},
number = {Pt B},
pages = {265--273},
abstract = {Classification models are becoming useful tools for finding patterns in neuroimaging data sets that are not observable to the naked eye. Many of these models are applied to discriminating clinical groups such as schizophrenic patients from healthy controls or from patients with bipolar disorder. A more nuanced model might be to discriminate between levels of personality traits. Here, as a proof of concept, we take an initial step toward developing prediction models to differentiate individuals based on a personality disorder: psychopathy. We included three groups of adolescent participants: incarcerated youth with elevated psychopathic traits (i.e., callous and unemotional traits and conduct disordered traits; n=71), incarcerated youth with low psychopathic traits (n=72), and non-incarcerated youth as healthy controls (n=21). Support vector machine (SVM) learning models were developed to separate these groups using an out-of-sample cross-validation method on voxel-based morphometry (VBM) data. Regions of interest from the paralimbic system, identified in an independent forensic sample, were successful in differentiating youth groups. Models seeking to classify incarcerated individuals to have high or low psychopathic traits achieved 69.23% overall accuracy. As expected, accuracy increased in models differentiating healthy controls from individuals with high psychopathic traits (82.61%) and low psychopathic traits (80.65%). Here we have laid the foundation for using neural correlates of personality traits to identify group membership within and beyond psychopathy. This is only the first step, of many, toward prediction models using neural measures as a proxy for personality traits. As these methods are improved, prediction models with neural measures of personality traits could have far-reaching impact on diagnosis, treatment, and prediction of future behavior.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Classification models are becoming useful tools for finding patterns in neuroimaging data sets that are not observable to the naked eye. Many of these models are applied to discriminating clinical groups such as schizophrenic patients from healthy controls or from patients with bipolar disorder. A more nuanced model might be to discriminate between levels of personality traits. Here, as a proof of concept, we take an initial step toward developing prediction models to differentiate individuals based on a personality disorder: psychopathy. We included three groups of adolescent participants: incarcerated youth with elevated psychopathic traits (i.e., callous and unemotional traits and conduct disordered traits; n=71), incarcerated youth with low psychopathic traits (n=72), and non-incarcerated youth as healthy controls (n=21). Support vector machine (SVM) learning models were developed to separate these groups using an out-of-sample cross-validation method on voxel-based morphometry (VBM) data. Regions of interest from the paralimbic system, identified in an independent forensic sample, were successful in differentiating youth groups. Models seeking to classify incarcerated individuals to have high or low psychopathic traits achieved 69.23% overall accuracy. As expected, accuracy increased in models differentiating healthy controls from individuals with high psychopathic traits (82.61%) and low psychopathic traits (80.65%). Here we have laid the foundation for using neural correlates of personality traits to identify group membership within and beyond psychopathy. This is only the first step, of many, toward prediction models using neural measures as a proxy for personality traits. As these methods are improved, prediction models with neural measures of personality traits could have far-reaching impact on diagnosis, treatment, and prediction of future behavior.
Steele, Vaughn R; Maurer, Michael J; Bernat, Edward M; Calhoun, Vince D; Kiehl, Kent A
Error-related processing in adult males with elevated psychopathic traits. Journal Article
In: Personal Disord, vol. 7, no. 1, pp. 80–90, 2015, ISSN: 1949-2723 (Electronic); 1949-2723 (Linking).
@article{Steele2015b,
title = {Error-related processing in adult males with elevated psychopathic traits.},
author = {Vaughn R Steele and Michael J Maurer and Edward M Bernat and Vince D Calhoun and Kent A Kiehl},
url = {https://www.ncbi.nlm.nih.gov/pubmed/26479259},
doi = {10.1037/per0000143},
issn = {1949-2723 (Electronic); 1949-2723 (Linking)},
year = {2015},
date = {2015-10-19},
journal = {Personal Disord},
volume = {7},
number = {1},
pages = {80--90},
address = {The Mind Research Network & Lovelace Biomedical and Environmental Research Institute.},
abstract = {Psychopathy is a serious personality disorder characterized by dysfunctional affective and behavioral symptoms. In incarcerated populations, elevated psychopathic traits have been linked to increased rates of violent recidivism. Cognitive processes related to error processing have been shown to differentiate individuals with high and low psychopathic traits and may contribute to poor decision making that increases the risk of recidivism. Error processing abnormalities related to psychopathy may be attributable to error-monitoring (error detection) or posterror processing (error evaluation). A recent 'bottleneck' theory predicts deficiencies in posterror processing in individuals with high psychopathic traits. In the current study, incarcerated males (n = 93) performed a Go/NoGo response inhibition task while event-related potentials (ERPs) were recorded. Classic time-domain windowed component and principal component analyses were used to measure error-monitoring (as measured with the error-related negativity [ERN/Ne]) and posterror processing (as measured with the error positivity [Pe]). Psychopathic traits were assessed using Hare's Psychopathy Checklist-Revised (PCL-R). PCL-R Total score, Factor 1 (interpersonal-affective traits), and Facet 3 (lifestyle traits) scores were positively related to posterror processes (i.e., increased Pe amplitude) but unrelated to error-monitoring processes (i.e., ERN/Ne). These results support the attentional bottleneck theory and further describe deficiencies related to elevated psychopathic traits that could be beneficial for new treatment strategies for psychopathy.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Psychopathy is a serious personality disorder characterized by dysfunctional affective and behavioral symptoms. In incarcerated populations, elevated psychopathic traits have been linked to increased rates of violent recidivism. Cognitive processes related to error processing have been shown to differentiate individuals with high and low psychopathic traits and may contribute to poor decision making that increases the risk of recidivism. Error processing abnormalities related to psychopathy may be attributable to error-monitoring (error detection) or posterror processing (error evaluation). A recent 'bottleneck' theory predicts deficiencies in posterror processing in individuals with high psychopathic traits. In the current study, incarcerated males (n = 93) performed a Go/NoGo response inhibition task while event-related potentials (ERPs) were recorded. Classic time-domain windowed component and principal component analyses were used to measure error-monitoring (as measured with the error-related negativity [ERN/Ne]) and posterror processing (as measured with the error positivity [Pe]). Psychopathic traits were assessed using Hare's Psychopathy Checklist-Revised (PCL-R). PCL-R Total score, Factor 1 (interpersonal-affective traits), and Facet 3 (lifestyle traits) scores were positively related to posterror processes (i.e., increased Pe amplitude) but unrelated to error-monitoring processes (i.e., ERN/Ne). These results support the attentional bottleneck theory and further describe deficiencies related to elevated psychopathic traits that could be beneficial for new treatment strategies for psychopathy.
Caldwell, Brendan M; Harenski, Carla L; Harenski, Keith A; Fede, Samantha J; Steele, Vaughn R; Koenigs, Michael R; Kiehl, Kent A
Abnormal frontostriatal activity in recently abstinent cocaine users during implicit moral processing. Journal Article
In: Front Hum Neurosci, vol. 9, pp. 565, 2015, ISSN: 1662-5161 (Print); 1662-5161 (Linking).
@article{Caldwell2015,
title = {Abnormal frontostriatal activity in recently abstinent cocaine users during implicit moral processing.},
author = {Brendan M Caldwell and Carla L Harenski and Keith A Harenski and Samantha J Fede and Vaughn R Steele and Michael R Koenigs and Kent A Kiehl},
url = {https://www.ncbi.nlm.nih.gov/pubmed/26528169},
doi = {10.3389/fnhum.2015.00565},
issn = {1662-5161 (Print); 1662-5161 (Linking)},
year = {2015},
date = {2015-10-16},
journal = {Front Hum Neurosci},
volume = {9},
pages = {565},
address = {The Mind Research Network and Lovelace Biomedical and Environmental Research Institute Albuquerque, NM, USA.},
abstract = {Investigations into the neurobiology of moral cognition are often done by examining clinical populations characterized by diminished moral emotions and a proclivity toward immoral behavior. Psychopathy is the most common disorder studied for this purpose. Although cocaine abuse is highly co-morbid with psychopathy and cocaine-dependent individuals exhibit many of the same abnormalities in socio-affective processing as psychopaths, this population has received relatively little attention in moral psychology. To address this issue, the authors used functional magnetic resonance imaging (fMRI) to record hemodynamic activity in 306 incarcerated male adults, stratified into regular cocaine users (n = 87) and a matched sample of non-cocaine users (n = 87), while viewing pictures that did or did not depict immoral actions and determining whether each depicted scenario occurred indoors or outdoors. Consistent with expectations, cocaine users showed abnormal neural activity in several frontostriatial regions during implicit moral picture processing compared to their non-cocaine using peers. This included reduced moral/non-moral picture discrimination in the vACC, vmPFC, lOFC, and left vSTR. Additionally, psychopathy was negatively correlated with activity in an overlapping region of the ACC and right lateralized vSTR. These results suggest that regular cocaine abuse may be associated with affective deficits which can impact relatively high-level processes like moral cognition.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Investigations into the neurobiology of moral cognition are often done by examining clinical populations characterized by diminished moral emotions and a proclivity toward immoral behavior. Psychopathy is the most common disorder studied for this purpose. Although cocaine abuse is highly co-morbid with psychopathy and cocaine-dependent individuals exhibit many of the same abnormalities in socio-affective processing as psychopaths, this population has received relatively little attention in moral psychology. To address this issue, the authors used functional magnetic resonance imaging (fMRI) to record hemodynamic activity in 306 incarcerated male adults, stratified into regular cocaine users (n = 87) and a matched sample of non-cocaine users (n = 87), while viewing pictures that did or did not depict immoral actions and determining whether each depicted scenario occurred indoors or outdoors. Consistent with expectations, cocaine users showed abnormal neural activity in several frontostriatial regions during implicit moral picture processing compared to their non-cocaine using peers. This included reduced moral/non-moral picture discrimination in the vACC, vmPFC, lOFC, and left vSTR. Additionally, psychopathy was negatively correlated with activity in an overlapping region of the ACC and right lateralized vSTR. These results suggest that regular cocaine abuse may be associated with affective deficits which can impact relatively high-level processes like moral cognition.
Steele, Vaughn R; Claus, Eric D; Aharoni, Eyal; Vincent, Gina M; Calhoun, Vince D; Kiehl, Kent A
Multimodal imaging measures predict rearrest. Journal Article
In: Front Hum Neurosci, vol. 9, pp. 425, 2015, ISSN: 1662-5161 (Print); 1662-5161 (Linking).
@article{Steele2015,
title = {Multimodal imaging measures predict rearrest.},
author = {Vaughn R Steele and Eric D Claus and Eyal Aharoni and Gina M Vincent and Vince D Calhoun and Kent A Kiehl},
url = {https://www.ncbi.nlm.nih.gov/pubmed/26283947},
doi = {10.3389/fnhum.2015.00425},
issn = {1662-5161 (Print); 1662-5161 (Linking)},
year = {2015},
date = {2015-08-03},
journal = {Front Hum Neurosci},
volume = {9},
pages = {425},
address = {Mind Research Network and Lovelace Biomedical and Environmental Research Institute, Albuquerque NM, USA.},
abstract = {Rearrest has been predicted by hemodynamic activity in the anterior cingulate cortex (ACC) during error-processing (Aharoni et al., 2013). Here, we evaluate the predictive power after adding an additional imaging modality in a subsample of 45 incarcerated males from Aharoni et al. (2013). Event-related potentials (ERPs) and hemodynamic activity were collected during a Go/NoGo response inhibition task. Neural measures of error-processing were obtained from the ACC and two ERP components, the error-related negativity (ERN/Ne) and the error positivity (Pe). Measures from the Pe and ACC differentiated individuals who were and were not subsequently rearrested. Cox regression, logistic regression, and support vector machine (SVM) neuroprediction models were calculated. Each of these models proved successful in predicting rearrest and SVM provided the strongest results. Multimodal neuroprediction SVM models with out of sample cross-validating accurately predicted rearrest (83.33%). Offenders with increased Pe amplitude and decreased ACC activation, suggesting abnormal error-processing, were at greatest risk of rearrest.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Rearrest has been predicted by hemodynamic activity in the anterior cingulate cortex (ACC) during error-processing (Aharoni et al., 2013). Here, we evaluate the predictive power after adding an additional imaging modality in a subsample of 45 incarcerated males from Aharoni et al. (2013). Event-related potentials (ERPs) and hemodynamic activity were collected during a Go/NoGo response inhibition task. Neural measures of error-processing were obtained from the ACC and two ERP components, the error-related negativity (ERN/Ne) and the error positivity (Pe). Measures from the Pe and ACC differentiated individuals who were and were not subsequently rearrested. Cox regression, logistic regression, and support vector machine (SVM) neuroprediction models were calculated. Each of these models proved successful in predicting rearrest and SVM provided the strongest results. Multimodal neuroprediction SVM models with out of sample cross-validating accurately predicted rearrest (83.33%). Offenders with increased Pe amplitude and decreased ACC activation, suggesting abnormal error-processing, were at greatest risk of rearrest.
Maurer, Michael J; Steele, Vaughn R; Edwards, Bethany G; Bernat, Edward M; Calhoun, Vince D; Kiehl, Kent A
Dysfunctional error-related processing in female psychopathy. Journal Article
In: Soc Cogn Affect Neurosci, vol. 11, no. 7, pp. 1059–1068, 2015, ISSN: 1749-5024 (Electronic); 1749-5016 (Linking).
@article{Maurer2015,
title = {Dysfunctional error-related processing in female psychopathy.},
author = {Michael J Maurer and Vaughn R Steele and Bethany G Edwards and Edward M Bernat and Vince D Calhoun and Kent A Kiehl},
url = {https://www.ncbi.nlm.nih.gov/pubmed/26060326},
doi = {10.1093/scan/nsv070},
issn = {1749-5024 (Electronic); 1749-5016 (Linking)},
year = {2015},
date = {2015-06-08},
journal = {Soc Cogn Affect Neurosci},
volume = {11},
number = {7},
pages = {1059--1068},
address = {The Nonprofit Mind Research Network (MRN), an Affiliate of the Lovelace Biomedical and Environmental Research Institute (LBERI), Department of Psychology, University of New Mexico, Albuquerque, NM 87131, mmaurer@mrn.org kkiehl@unm.edu.},
abstract = {Neurocognitive studies of psychopathy have predominantly focused on male samples. Studies have shown that female psychopaths exhibit similar affective deficits as their male counterparts, but results are less consistent across cognitive domains including response modulation. As such, there may be potential gender differences in error-related processing in psychopathic personality. Here we investigate response-locked event-related potential (ERP) components [the error-related negativity (ERN/Ne) related to early error-detection processes and the error-related positivity (Pe) involved in later post-error processing] in a sample of incarcerated adult female offenders (n = 121) who performed a response inhibition Go/NoGo task. Psychopathy was assessed using the Hare Psychopathy Checklist-Revised (PCL-R). The ERN/Ne and Pe were analyzed with classic windowed ERP components and principal component analysis (PCA). Consistent with previous research performed in psychopathic males, female psychopaths exhibited specific deficiencies in the neural correlates of post-error processing (as indexed by reduced Pe amplitude) but not in error monitoring (as indexed by intact ERN/Ne amplitude). Specifically, psychopathic traits reflecting interpersonal and affective dysfunction remained significant predictors of both time-domain and PCA measures reflecting reduced Pe mean amplitude. This is the first evidence to suggest that incarcerated female psychopaths exhibit similar dysfunctional post-error processing as male psychopaths.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Neurocognitive studies of psychopathy have predominantly focused on male samples. Studies have shown that female psychopaths exhibit similar affective deficits as their male counterparts, but results are less consistent across cognitive domains including response modulation. As such, there may be potential gender differences in error-related processing in psychopathic personality. Here we investigate response-locked event-related potential (ERP) components [the error-related negativity (ERN/Ne) related to early error-detection processes and the error-related positivity (Pe) involved in later post-error processing] in a sample of incarcerated adult female offenders (n = 121) who performed a response inhibition Go/NoGo task. Psychopathy was assessed using the Hare Psychopathy Checklist-Revised (PCL-R). The ERN/Ne and Pe were analyzed with classic windowed ERP components and principal component analysis (PCA). Consistent with previous research performed in psychopathic males, female psychopaths exhibited specific deficiencies in the neural correlates of post-error processing (as indexed by reduced Pe amplitude) but not in error monitoring (as indexed by intact ERN/Ne amplitude). Specifically, psychopathic traits reflecting interpersonal and affective dysfunction remained significant predictors of both time-domain and PCA measures reflecting reduced Pe mean amplitude. This is the first evidence to suggest that incarcerated female psychopaths exhibit similar dysfunctional post-error processing as male psychopaths.
2014
Steele, Vaughn R; Claus, Eric D; Aharoni, Eyal; Harenski, Carla; Calhoun, Vince D; Pearlson, Godfrey; Kiehl, Kent A
A large scale (N=102) functional neuroimaging study of error processing in a Go/NoGo task. Journal Article
In: Behav Brain Res, vol. 268, pp. 127–138, 2014, ISSN: 1872-7549 (Electronic); 0166-4328 (Linking).
@article{Steele2014,
title = {A large scale (N=102) functional neuroimaging study of error processing in a Go/NoGo task.},
author = {Vaughn R Steele and Eric D Claus and Eyal Aharoni and Carla Harenski and Vince D Calhoun and Godfrey Pearlson and Kent A Kiehl},
url = {https://www.ncbi.nlm.nih.gov/pubmed/24726752},
doi = {10.1016/j.bbr.2014.04.001},
issn = {1872-7549 (Electronic); 0166-4328 (Linking)},
year = {2014},
date = {2014-04-12},
journal = {Behav Brain Res},
volume = {268},
pages = {127--138},
address = {The Nonprofit Mind Research Network (MRN) & Lovelace Biomedical and Environmental Research Institute (LBERI), Albuquerque, NM 87106, USA; University of New Mexico, Albuquerque, USA. Electronic address: vsteele@mrn.org.},
abstract = {We report a functional magnetic resonance imaging (fMRI) study of 102 healthy participants who completed a demanding Go/NoGo task. The primary purpose of this study was to delineate the neural systems underlying responses to errors in a large sample. We identified a number of regions engaged during error processing including the anterior cingulate, left lateral prefrontal areas and bilateral inferior frontal gyrus, and the subthalamic nucleus. The power afforded by the large cohort enabled identification of regions not consistently measured during Go/NoGo tasks thus helping to incrementally refine our understanding of the neural correlates of error processing. With the present fMRI results, in combination with our previous exploration of response inhibition (Steele et al.), we outline a comprehensive set of regions associated with both response inhibition and error processing.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We report a functional magnetic resonance imaging (fMRI) study of 102 healthy participants who completed a demanding Go/NoGo task. The primary purpose of this study was to delineate the neural systems underlying responses to errors in a large sample. We identified a number of regions engaged during error processing including the anterior cingulate, left lateral prefrontal areas and bilateral inferior frontal gyrus, and the subthalamic nucleus. The power afforded by the large cohort enabled identification of regions not consistently measured during Go/NoGo tasks thus helping to incrementally refine our understanding of the neural correlates of error processing. With the present fMRI results, in combination with our previous exploration of response inhibition (Steele et al.), we outline a comprehensive set of regions associated with both response inhibition and error processing.
2013
Steele, Vaughn R; Fink, Brandi C; Maurer, Michael J; Arbabshirani, Mohammad R; Wilber, Charles H; Jaffe, Adam J; Sidz, Anna; Pearlson, Godfrey D; Calhoun, Vince D; Clark, Vincent P; Kiehl, Kent A
Brain potentials measured during a Go/NoGo task predict completion of substance abuse treatment. Journal Article
In: Biol Psychiatry, vol. 76, no. 1, pp. 75–83, 2013, ISSN: 1873-2402 (Electronic); 0006-3223 (Linking).
@article{Steele2013b,
title = {Brain potentials measured during a Go/NoGo task predict completion of substance abuse treatment.},
author = {Vaughn R Steele and Brandi C Fink and Michael J Maurer and Mohammad R Arbabshirani and Charles H Wilber and Adam J Jaffe and Anna Sidz and Godfrey D Pearlson and Vince D Calhoun and Vincent P Clark and Kent A Kiehl},
url = {https://www.ncbi.nlm.nih.gov/pubmed/24238783},
doi = {10.1016/j.biopsych.2013.09.030},
issn = {1873-2402 (Electronic); 0006-3223 (Linking)},
year = {2013},
date = {2013-10-11},
journal = {Biol Psychiatry},
volume = {76},
number = {1},
pages = {75--83},
address = {Mind Research Network and Lovelace Biomedical and Environmental Research Institute, University of New Mexico, Albuquerque, New Mexico; Department of Psychology, University of New Mexico, Albuquerque, New Mexico. Electronic address: vrsteele@mrn.org.},
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.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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.
Steele, Vaughn R; Aharoni, Eyal; Munro, Gillian E; Calhoun, Vince D; Nyalakanti, Prashanth; Stevens, Michael C; Pearlson, Godfrey; Kiehl, Kent A
A large scale (N=102) functional neuroimaging study of response inhibition in a Go/NoGo task. Journal Article
In: Behav Brain Res, vol. 256, pp. 529–536, 2013, ISSN: 1872-7549 (Electronic); 0166-4328 (Linking).
@article{Steele2013,
title = {A large scale (N=102) functional neuroimaging study of response inhibition in a Go/NoGo task.},
author = {Vaughn R Steele and Eyal Aharoni and Gillian E Munro and Vince D Calhoun and Prashanth Nyalakanti and Michael C Stevens and Godfrey Pearlson and Kent A Kiehl},
url = {https://www.ncbi.nlm.nih.gov/pubmed/23756137},
doi = {10.1016/j.bbr.2013.06.001},
issn = {1872-7549 (Electronic); 0166-4328 (Linking)},
year = {2013},
date = {2013-06-10},
journal = {Behav Brain Res},
volume = {256},
pages = {529--536},
address = {The Mind Research Network, United States; University of New Mexico, United States. Electronic address: vsteele@unm.edu.},
abstract = {We report a functional magnetic resonance imaging (fMRI) study of healthy adult participants who completed a demanding Go/NoGo task. The primary purpose of this study was to delineate the neural systems underlying successful and unsuccessful response inhibition using a large sample (N=102). We identified a number of regions uniquely engaged during successful response inhibition, including a fronto-parietal network involving the anterior cingulate, supplementary motor areas, lateral and inferior prefrontal regions, and the inferior parietal lobule. Unique hemodynamic activity was also noted in the amygdala and in frontostriatal regions including the inferior frontal gyrus and portions of the basal ganglia. Also, contrasts were defined to explore three variants of hemodynamic response allowing for more specificity in identifying the underlying cognitive mechanisms of response inhibition. Addressing issues raised by prior small sample studies, we identified a stable set of regions involved in successful response inhibition. The present results help to incrementally refine the specificity of the neural correlates of response inhibition.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We report a functional magnetic resonance imaging (fMRI) study of healthy adult participants who completed a demanding Go/NoGo task. The primary purpose of this study was to delineate the neural systems underlying successful and unsuccessful response inhibition using a large sample (N=102). We identified a number of regions uniquely engaged during successful response inhibition, including a fronto-parietal network involving the anterior cingulate, supplementary motor areas, lateral and inferior prefrontal regions, and the inferior parietal lobule. Unique hemodynamic activity was also noted in the amygdala and in frontostriatal regions including the inferior frontal gyrus and portions of the basal ganglia. Also, contrasts were defined to explore three variants of hemodynamic response allowing for more specificity in identifying the underlying cognitive mechanisms of response inhibition. Addressing issues raised by prior small sample studies, we identified a stable set of regions involved in successful response inhibition. The present results help to incrementally refine the specificity of the neural correlates of response inhibition.
2012
Steele, Vaughn R; Bernat, Edward M; van den Broek, Paul; Collins, Paul F; Patrick, Christopher J; Marsolek, Chad J
In: Brain Res, vol. 1492, pp. 92–107, 2012, ISSN: 1872-6240 (Electronic); 0006-8993 (Linking).
@article{Steele2012,
title = {Separable processes before, during, and after the N400 elicited by previously inferred and new information: evidence from time-frequency decompositions.},
author = {Vaughn R Steele and Edward M Bernat and Paul van den Broek and Paul F Collins and Christopher J Patrick and Chad J Marsolek},
url = {https://www.ncbi.nlm.nih.gov/pubmed/23165117},
doi = {10.1016/j.brainres.2012.11.016},
issn = {1872-6240 (Electronic); 0006-8993 (Linking)},
year = {2012},
date = {2012-11-16},
journal = {Brain Res},
volume = {1492},
pages = {92--107},
address = {The Mind Research Network, Albuquerque, NM 87106, United States; Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM 87108, United States. vsteele@mrn.org},
abstract = {Successful comprehension during reading often requires inferring information not explicitly presented. This information is readily accessible when subsequently encountered, and a neural correlate of this is an attenuation of the N400 event-related potential (ERP). We used ERPs and time-frequency (TF) analysis to investigate neural correlates of processing inferred information after a causal coherence inference had been generated during text comprehension. Participants read short texts, some of which promoted inference generation. After each text, they performed lexical decisions to target words that were unrelated or inference-related to the preceding text. Consistent with previous findings, inference-related words elicited an attenuated N400 relative to unrelated words. TF analyses revealed unique contributions to the N400 from activity occurring at 1-6 Hz (theta) and 0-2 Hz (delta), supporting the view that multiple, sequential processes underlie the N400.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Successful comprehension during reading often requires inferring information not explicitly presented. This information is readily accessible when subsequently encountered, and a neural correlate of this is an attenuation of the N400 event-related potential (ERP). We used ERPs and time-frequency (TF) analysis to investigate neural correlates of processing inferred information after a causal coherence inference had been generated during text comprehension. Participants read short texts, some of which promoted inference generation. After each text, they performed lexical decisions to target words that were unrelated or inference-related to the preceding text. Consistent with previous findings, inference-related words elicited an attenuated N400 relative to unrelated words. TF analyses revealed unique contributions to the N400 from activity occurring at 1-6 Hz (theta) and 0-2 Hz (delta), supporting the view that multiple, sequential processes underlie the N400.
