Interpersonal dysfunction in borderline personality: a decision neuroscience perspective

Abstract

Borderline personality disorder (BPD) is characterized by disadvantageous decisions that are often expressed in close relationships and associated with intense negative emotions. Although functional neuroimaging studies of BPD have described regions associated with altered social cognition and emotion processing, these correlates do not inform an understanding of how brain activity leads to maladaptive choices. Drawing on recent research, we argue that formal models of decision-making are crucial to elaborating theories of BPD that bridge psychological constructs, behavior, and neural systems. We propose that maladaptive interactions between Pavlovian and instrumental influences play a crucial role in the expression of interpersonal problems. Finally, we articulate specific hypotheses about how clinical features of BPD may map onto neural systems that implement separable decision processes.

From Description to Explanation: Integrating Across Multiple Levels of Analysis to Inform Neuroscientific Accounts of Dimensional Personality Pathology

“…He articulated three levels of analysis that are involved in the study of any information-processing system: (1) the computational level, which describes the purpose of the system; (2) the algorithmic level, which specifies the processes or rules the system uses to achieve its purpose; and (3) the implementational level, which describes how these processes or rules are physically realized in the nervous system. Studies that attempt to link traits directly to neurobiology jump from the computational to the implementational level of Marr's framework, paying little attention to the algorithmic mechanisms that are vital to understanding how the brain generates stable individual differences in personality (Hallquist, Hall, Schreiber, & Dombrovski, 2018). As a result, these studies tend to promote a naïve reductionism within personality neuroscience, as though simply mapping every trait to its corresponding synapse, cell, region, or network will somehow yield an explanatory account of the consistencies in human experience.…”

“…At this point, formal models of behavior and decision making are relatively novel within the literature on personality and personality pathology. Nonetheless, these models provide promising avenues for future research, as they can serve as vital tools in the effort to identify the latent algorithmic processes that contribute to personality function and dysfunction (Hallquist et al, 2018;Patzelt et al, 2018). By integrating computational modeling techniques with the vast array of neuroscientific tools at researchers' disposal, personality neuroscientists may be able to uncover more mechanistic theories of personality pathology that provide clear predictions for the cognitive processes that bridge between the brain and trait-relevant behavior.…”

Interfacing neural constructs with the Hierarchical Taxonomy of Psychopathology: ‘Why' and ‘how'

“…Processes of interest are often drawn from the literature on associative learning and decision making. For example, Hallquist et al described a mechanistic model of borderline personality disorder that linked behavioural manifestations of latent decision‐making processes to neural‐system activity (quantified using electrocortical and functional neuroimaging responses) and phenotypic aspects of the disorder. These authors argued that simple correlations between psychological variables (e.g.…”

“…trait neuroticism) and neural responses have been small and inconsistent because of the substantial theoretical gap between what is measured via these modalities. They advocated for computational modelling as a promising technique for bridging these units of analysis through modelling of latent intermediate processes and testing theories of how and why separable processes lead to measurable behaviours, symptoms, and neural responses . Computational modelling has also been used to elucidate the mechanisms of cognitive control deficits in schizophrenia .…”

“…Despite these myriad advantages and the natural coupling of computational modelling with the HiTOP framework, some limitations and cautionary points warrant mention. First, computational models are specific to the tasks by which data are collected; moreover, it can be difficult to parse competing mechanisms within a single task . Additionally, test–retest reliability and construct validity have been less systematically investigated in computational phenotyping than in, for example, personality psychology .…”