» Articles » PMID: 37479846

Distinct Neurocognitive Fingerprints Reflect Differential Associations with Risky and Impulsive Behavior in a Neurotypical Sample

Overview
Journal Sci Rep
Specialty Science
Date 2023 Jul 21
PMID 37479846
Authors
Affiliations
Soon will be listed here.
Abstract

Engagement in risky and impulsive behavior has long been associated with deficits in neurocognition. However, we have a limited understanding of how multiple subfunctions of neurocognition co-occur within individuals and which combinations of neurocognitive subfunctions are most relevant for risky and impulsive behavior. Using the neurotypical Nathan Kline Institute Rockland Sample (N = 673), we applied a Bayesian latent feature learning model-the Indian Buffet Process-to identify nuanced, individual-specific profiles of multiple neurocognitive subfunctions and examine their relationship to risky and impulsive behavior. All features were within a relatively normative range of neurocognition; however, there was subtle variability related to risky and impulsive behaviors. The relatively overall poorer neurocognition feature correlated with greater affective impulsivity and substance use patterns/problems. The poorer episodic memory and emotion feature correlated with greater trait externalizing and sensation-seeking. The poorer attention feature correlated with increased trait externalizing and negative urgency but decreased positive urgency and substance use. Finally, the average or mixed features negatively correlated with various risky and impulsive behaviors. Estimating nuanced patterns of co-occurring neurocognitive functions can inform our understanding of a continuum of risky and impulsive behaviors.

Citing Articles

Person-centered analyses reveal that developmental adversity at moderate levels and neural threat/safety discrimination are associated with lower anxiety in early adulthood.

Sisk L, Keding T, Ruiz S, Odriozola P, Kribakaran S, Cohodes E Commun Psychol. 2025; 3(1):31.

PMID: 40044923 PMC: 11882445. DOI: 10.1038/s44271-025-00193-x.


Enhancing Within-Person Estimation of Neurocognition and the Prediction of Externalizing Behaviors in Adolescents.

Paskewitz S, Brazil I, Yildirim I, Ruiz S, Baskin-Sommers A Comput Psychiatr. 2024; 8(1):119-141.

PMID: 39070965 PMC: 11276473. DOI: 10.5334/cpsy.112.

References
1.
Gur R, Ragland J, Moberg P, Turner T, Bilker W, Kohler C . Computerized neurocognitive scanning: I. Methodology and validation in healthy people. Neuropsychopharmacology. 2001; 25(5):766-76. DOI: 10.1016/S0893-133X(01)00278-0. View

2.
Ahn W, Ramesh D, Moeller F, Vassileva J . Utility of Machine-Learning Approaches to Identify Behavioral Markers for Substance Use Disorders: Impulsivity Dimensions as Predictors of Current Cocaine Dependence. Front Psychiatry. 2016; 7:34. PMC: 4785183. DOI: 10.3389/fpsyt.2016.00034. View

3.
Cyders M, Smith G . Emotion-based dispositions to rash action: positive and negative urgency. Psychol Bull. 2008; 134(6):807-28. PMC: 2705930. DOI: 10.1037/a0013341. View

4.
Fuster J . The prefrontal cortex--an update: time is of the essence. Neuron. 2001; 30(2):319-33. DOI: 10.1016/s0896-6273(01)00285-9. View

5.
Brazil I, van Dongen J, Maes J, Mars R, Baskin-Sommers A . Classification and treatment of antisocial individuals: From behavior to biocognition. Neurosci Biobehav Rev. 2016; 91:259-277. DOI: 10.1016/j.neubiorev.2016.10.010. View