JCJanna M. Colaizzi

Janna M. Colaizzi

*This is an algorithmically generated author record based on publicly available information.

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Janna M. Colaizzi has a total of 27 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    The propensity to sign-track is associated with externalizing behavior and distinct patterns of reward-related brain activation in youth

    by Janna M. Colaizzi, Shelly B. Flagel, Ashley N. Gearhardt, Michelle A. Borowitz, Rayus Kuplicki, Vadim Zotev, Grace Clark, Jennifer Coronado, Talia Abbott, Martin P. Paulus

    Externalizing behaviors in childhood often predict impulse control disorders in adulthood; however, the underlying bio-behavioral risk factors are incompletely understood. In animals, the propensity to sign-track, or the degree to which incentive motivational value is attributed to reward cues, is associated with externalizing-type behaviors and deficits in executive control. Using a Pavlovian conditioned approach paradigm, we quantified sign-tracking in 40 healthy 9–12-year-olds. We also measured parent-reported externalizing behaviors and anticipatory neural activations to outcome-predicting cues using the monetary incentive delay fMRI task. Sign-tracking was associated with attentional and inhibitory control deficits and the degree of amygdala, but not cortical, activation during reward anticipation. These findings support the hypothesis that youth with a propensity to sign-track are prone to externalizing tendencies, with an over-reliance on subcortical cue-reactive brain systems. This research highlights sign-tracking as a promising experimental approach delineating the behavioral and neural circuitry of individuals at risk for externalizing disorders.


  • Open Access

    The propensity to sign-track is associated with externalizing behaviour and distinct patterns of reward-related brain activation in youth

    by Janna M. Colaizzi, Shelly B. Flagel, Ashley N. Gearhardt, Michelle A. Borowitz, Rayus Kuplicki, Vadim Zotev, Grace Clark, Jennifer Coronado, Talia Abbott, Martin P. Paulus

    Externalizing behaviours in childhood often predict impulse control disorders in adulthood; however, the underlying biobehavioural risk factors are incompletely understood. In animals, the propensity to signtrack, or the degree to which incentive motivational value is attributed to reward cues, is associated with externalizing-type behaviours and deficits in executive control. Using a Pavlovian conditioned approach paradigm, we quantified sign-tracking in healthy 9-12-year-olds. We also measured parent-reported externalizing behaviours and anticipatory neural activations to outcome-predicting cues using the monetary incentive delay fMRI task. Sign-tracking was associated with attentional and inhibitory control deficits and the degree of amygdala, but not cortical, activation during reward anticipation. These findings support the hypothesis that youth with a propensity to sign-track are prone to externalizing tendencies, with an over-reliance on subcortical cue-reactive brain systems. This research highlights sign-tracking as a promising experimental approach delineating the behavioural and neural circuitry of individuals at risk for externalizing disorders.

  • Open Access

    Latent Variables Quantifying Neighborhood Characteristics and Their Associations with Poor Mental Health

    by Katherine L. Forthman, Janna M. Colaizzi, Hung-Wen Yeh, Rayus Kuplicki, Martin P. Paulus

    Neighborhood characteristics can have profound impacts on resident mental health, but the wide variability in methodologies used across studies makes it difficult to reach a consensus as to the implications of these impacts. The aim of this study was to simplify the assessment of neighborhood influence on mental health. We used a factor analysis approach to reduce the multi-dimensional assessment of a neighborhood using census tracts and demographic data available from the American Community Survey (ACS). Multivariate quantitative characterization of the neighborhood was derived by performing a factor analysis on the 2011–2015 ACS data. The utility of the latent variables was examined by determining the association of these factors with poor mental health measures from the 500 Cities Project 2014–2015 data (2017 release). A five-factor model provided the best fit for the data. Each factor represents a complex multi-dimensional construct. However, based on heuristics and for simplicity we refer to them as (1) Affluence, (2) Singletons in Tract, (3) African Americans in Tract, (4) Seniors in Tract, and (5) Hispanics or Latinos in Tract. African Americans in Tract (with loadings showing larger numbers of people who are black, single moms, and unemployed along with fewer people who are white) and Affluence (with loadings showing higher income, education, and home value) were strongly associated with poor mental health (R2=0.67, R2=0.83). These findings demonstrate the utility of this factor model for future research focused on the relationship between neighborhood characteristics and resident mental health.


  • Open Access

    Extracurricular activities, screen media activity, and sleep may be modifiable factors influencing children’s cognitive functioning: Evidence from the ABCD study

    by Namik Kirlic, Janna Colaizzi, Kelly Theresa Cosgrove, Zsofia Cohen, Henry Yeh, Florence Breslin, Amanda Sheffield Morris, Robin Aupperle, Martin P Paulus

    PurposeFluid cognitive functioning (FCF), or the capacity to learn, solve problems, and adapt to novel situations, is instrumental for academic success, psychological well-being, and adoption of healthy behaviors. Our knowledge concerning factors associated with FCF, including those that may be targeted with interventions to improve outcomes, remains limited. MethodsWe used a machine learning (ML) framework in conjunction with a large battery of measures from 9,718 youth from the Adolescent Brain Cognitive Development (ABCD) study to identify factors associated with the observed variability in FCF performance. Youth age-corrected composite FCF score was derived from the National Institutes for Health Toolbox Neurocognitive Battery. A ML pipeline using a stack ensemble of multiple ML algorithms and nested cross-validation to avoid overfitting was conducted to examine factors associated with FCF. Results The identified ML algorithm explained 14.74% of variance (95%CI: 14.53-14.88%) in FCF. Among the most important factors were those that replicated previous research (e.g., socioeconomic factors), as well as novel, potentially modifiable factors, including extracurricular involvement, screen media activity, and sleepConclusionsPragmatic and scalable interventions targeting these behaviors may not only enhance cognitive performance but may also protect against the negative impact of socioeconomic and mental health factors on cognitive performance in at-risk youth. The longitudinal data from ABCD will be able to begin to assess causality by examining how changes in these factors affect subsequent cognitive performance.


  • Mapping sign-tracking and goal-tracking onto human behaviors

    by Janna M. Colaizzi, Shelly B. Flagel, Michelle A. Joyner, Ashley N. Gearhardt, Jennifer L. Stewart, Martin P. Paulus