Borderline personality disorder and learning: The influences of emotional state and social versus nonsocial feedback.

BACKGROUND: Borderline personality disorder (BPD) has been associated with decision-making deficits, yet such deficits may be context dependent, particularly emotional state and social context. Reinforcement learning models offer an avenue to pinpoint decision-making impairments. The current study used reinforcement learning models to examine whether feedback type (social vs. nonsocial) or emotional state (neutral vs. negative) influence the association between BPD and decision making. METHOD: Adults (N = 131) with a range of BPD symptoms completed a diagnostic interview and a computerized learning task after neutral and negative emotion inductions. We examined accuracy, learning rate, and exploration. RESULTS: We conducted linear models to examine the association between BPD criteria, feedback type, and emotional state on learning parameters and learning accuracy. We found that the negative emotion condition was associated with greater exploration, particularly for those with elevated BPD features. Furthermore, elevated BPD features were associated with impaired accuracy when aiming to avoid loss. A 3-way interaction between BPD, emotion, and feedback indicated that, for people with higher BPD features, learning performance was further impaired when receiving social feedback in the negative emotion condition. LIMITATIONS: Several limitations warrant mention, including a relatively homogenous sample, possible co-occurring diagnoses, and methodological consideration with the learning task. CONCLUSIONS: The present study underscored the link between BPD and learning impairments. Amplified learning alterations under negative social contexts have important implications for identifying optimal venues to teach new skills (of relevance to treatment) for those with BPD.

"Leap before you look": Conditions that suppress explicit, knowledge-based learning during visuomotor adaptation.

When learning a novel visuomotor mapping (e.g., mirror writing), accuracy can improve quickly through explicit, knowledge-based learning (e.g., aim left to go right), but after practice, implicit or procedural learning takes over, producing fast, natural movements. This procedural learning occurs automatically, whereas it has recently been found that knowledge-based learning can be suppressed by the gradual introduction of the novel mapping when participants must make fast movements and visuomotor perturbations are small (e.g., 30° rotations). We explored the range of task instructions, perturbation parameters, and feedback that preclude or encourage this suppression. Using a reaching task with a rotation between screen position and movement direction, we found that knowledge-based learning could be suppressed even for an extreme 90° rotation, but only if it was introduced gradually and only under instructions to move quickly. If the rotation was introduced abruptly or if instructions emphasized accuracy over speed, knowledge-based learning occurred. A second experiment indicated that knowledge-based learning always occurred in the absence of continuous motion feedback, evidenced by the time course of learning, the aftereffects of learning when the rotation was abruptly removed, and the outcome of formal model comparison between a dual-state (procedural and knowledge-based) versus a single-state (procedural only) learning model of the data. A third experiment replicated the findings and verified that the knowledge-based component of the dual-state model corresponded to explicit aiming, whereas the procedural component was slow to unlearn. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A Unified Theoretical Framework for Cognitive Sequencing.

The capacity to sequence information is central to human performance. Sequencing ability forms the foundation stone for higher order cognition related to language and goal-directed planning. Information related to the order of items, their timing, chunking and hierarchical organization are important aspects in sequencing. Past research on sequencing has emphasized two distinct and independent dichotomies: implicit vs. explicit and goal-directed vs. habits. We propose a theoretical framework unifying these two streams. Our proposal relies on brain's ability to implicitly extract statistical regularities from the stream of stimuli and with attentional engagement organizing sequences explicitly and hierarchically. Similarly, sequences that need to be assembled purposively to accomplish a goal require engagement of attentional processes. With repetition, these goal-directed plans become habits with concomitant disengagement of attention. Thus, attention and awareness play a crucial role in the implicit-to-explicit transition as well as in how goal-directed plans become automatic habits. Cortico-subcortical loops basal ganglia-frontal cortex and hippocampus-frontal cortex loops mediate the transition process. We show how the computational principles of model-free and model-based learning paradigms, along with a pivotal role for attention and awareness, offer a unifying framework for these two dichotomies. Based on this framework, we make testable predictions related to the potential influence of response-to-stimulus interval (RSI) on developing awareness in implicit learning tasks.