Borderline personality disorder classification based on brain network measures during emotion regulation

Neuroimaging and Brain-Based Markers Identifying Neurobiological Markers Associated With Criminal Behaviour, Personality Disorders, and Mental Health: A Narrative Review

We begin the review by pointing to the common stigma associated with mental health issues, which often derives from a lack of understanding or incomplete knowledge. Neurobiological research provides us with a new lens to help challenge and dispel common assumptions and misunderstandings and gives an understanding of sexual behaviours that influence society. As such, it generates substantial evidence for the structural and functional asymmetry of the brains of individuals with mental disorders. However, this type of representation poses many challenges to traditional thinking and constantly provokes change in perspective and empathy towards those individuals. In the review, we go deeper into the effects of neurobiological findings on understanding criminal behaviours and personality disorders, looking further beyond behavioural health. These problems, which were once mainly discussed as moral ones or viewed from the perspective of character flaws, are analysed today through neurological considerations pointing to their complexity. When the root of bipolar disorder is revealed to be neurological, society will react with more information and understanding, hence reducing the stigmatisation and discrimination meted out to people with these problems. At a macro level, findings from neurobiology affect society in ways that go beyond individuals; social attitudes, laws, and policies about the services rendered are influenced. Operating as a catalyst within the community, neurobiological research helps to initiate social change through the creation of an informed, understanding public forum. Thus, it creates broader value for those dealing with behavioural and mental health challenges. The first and most important question of this narrative review is focused on identifying identifiable neurobiological markers that are closely related to criminal conduct, personality disorders, and mental health disorders. Through this review, we aim to present detailed insights into the neurological foundations that anchor these phenomena via a narrative analysis of contemporary literature. The potential implications are finding problems early to apply specific treatment and learning an advanced strategy for social attitudes. This will promote a more humanistic approach based on adequate information on the behavioural and mental health issues involved.

A Comprehensive Literature Review of Borderline Personality Disorder: Unraveling Complexity From Diagnosis to Treatment

Borderline personality disorder (BPD) is a severe mental illness marked by unpredictable feelings, behaviors, and relationships. Symptoms like emotional instability, impulsivity, and poor social connections are the basis for diagnostic criteria. A noteworthy discovery highlights the clinical overlap between BPD and several psychotic disorders by arguing that BPD and psychotic symptoms raise the risk of psychopathology. According to neuroimaging evidence, structural and functional brain changes, notably in regions controlling affective regulation and impulse control, are seen in BPD patients. Adolf Stern, a psychoanalyst, used the word "borderline" in 1938 to describe patients who exhibited increased symptoms during therapy and displayed masochistic tendencies. Modern BPD research has highlighted the complexity of symptoms like boredom, a former diagnostic criterion associated with feelings of emptiness. Though there are still unanswered problems regarding its precise, practical components, the treatment technique known as Schema therapy (ST) has shown promise in treating BPD. It's interesting to note that BPD displays complex relationships with other illnesses; for instance, some neurochemical pathways coincide with those in bulimia nervosa, pointing to a deeper level of interconnection. Concerning diagnosis, BPD's defining symptoms include, among others, the fear of abandonment, identity disruption, and recurrent suicidal conduct. The range of treatment options includes pharmacological interventions and psychotherapies like dialectical behavior therapy (DBT). Even though antidepressants like selective serotonin reuptake inhibitors (SSRIs) are routinely prescribed, research on their efficacy is ongoing, underlining the significance of thorough treatment planning. In conclusion, BPD continues to be a complex condition that calls for early detection, especially considering that it usually manifests in adolescence. While many patients report symptom relief, lingering problems still exist, emphasizing the value of comprehensive and personalized treatment strategies.

Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry

BACKGROUND

The development of machine learning models for aiding in the diagnosis of mental disorder is recognized as a significant breakthrough in the field of psychiatry. However, clinical practice of such models remains a challenge, with poor generalizability being a major limitation.

METHODS

Here, we conducted a pre-registered meta-research assessment on neuroimaging-based models in the psychiatric literature, quantitatively examining global and regional sampling issues over recent decades, from a view that has been relatively underexplored. A total of 476 studies (n = 118,137) were included in the current assessment. Based on these findings, we built a comprehensive 5-star rating system to quantitatively evaluate the quality of existing machine learning models for psychiatric diagnoses.

RESULTS

A global sampling inequality in these models was revealed quantitatively (sampling Gini coefficient (G) = 0.81, p < .01), varying across different countries (regions) (e.g., China, G = 0.47; the USA, G = 0.58; Germany, G = 0.78; the UK, G = 0.87). Furthermore, the severity of this sampling inequality was significantly predicted by national economic levels (β =  - 2.75, p < .001, R²_adj = 0.40; r =  - .84, 95% CI: - .41 to - .97), and was plausibly predictable for model performance, with higher sampling inequality for reporting higher classification accuracy. Further analyses showed that lack of independent testing (84.24% of models, 95% CI: 81.0-87.5%), improper cross-validation (51.68% of models, 95% CI: 47.2-56.2%), and poor technical transparency (87.8% of models, 95% CI: 84.9-90.8%)/availability (80.88% of models, 95% CI: 77.3-84.4%) are prevailing in current diagnostic classifiers despite improvements over time. Relating to these observations, model performances were found decreased in studies with independent cross-country sampling validations (all p < .001, BF₁₀ > 15). In light of this, we proposed a purpose-built quantitative assessment checklist, which demonstrated that the overall ratings of these models increased by publication year but were negatively associated with model performance.

CONCLUSIONS

Together, improving sampling economic equality and hence the quality of machine learning models may be a crucial facet to plausibly translating neuroimaging-based diagnostic classifiers into clinical practice.

Altered intrinsic functional network connectivity is associated with impulsivity and emotion dysregulation in drug-naïve young patients with borderline personality disorder

BACKGROUND

Despite impulse control and emotion regulation being altered in borderline personality disorder (BPD), the specific mechanism of these clinical features remains unclear. This study investigated the functional connectivity (FC) abnormalities within- and between- default mode network (DMN), salience network (SN), and central executive network (CEN) in BPD, and examined the association between aberrant FC and clinical features. We aimed to explore whether the abnormal large-scale networks underlie the pathophysiology of impulsivity and emotion dysregulation in BPD.

METHODS

Forty-one young, drug-naïve patients with BPD (24.98 ± 3.12 years, 20 males) and 42 healthy controls (HCs; 24.74 ± 1.29 years, 17 males) were included in resting-state functional magnetic resonance imaging analyses. Independent component analysis was performed to extract subnetworks of the DMN, CEN, and SN. Additionally, partial correlation was performed to explore the association between brain imaging variables and clinical features in BPD.

RESULTS

Compared with HCs, BPD showed significant decreased intra-network FC of right medial prefrontal cortex in the anterior DMN and of right angular gyrus in the right CEN. Intra-network FC of right angular gyrus in the anterior DMN was significantly negatively correlated with attention impulsivity in BPD. The patients also showed decreased inter-network FC between the posterior DMN and left CEN, which was significantly negatively correlated with emotion dysregulation.

CONCLUSION

These findings suggest that impaired intra-network FC may underlie the neurophysiological mechanism of impulsivity, and abnormal inter-network FC may elucidate the neurophysiological mechanism of emotion dysregulation in BPD.

Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis: A Systematic Review

IMPORTANCE

Neuroimaging-based artificial intelligence (AI) diagnostic models have proliferated in psychiatry. However, their clinical applicability and reporting quality (ie, feasibility) for clinical practice have not been systematically evaluated.

OBJECTIVE

To systematically assess the risk of bias (ROB) and reporting quality of neuroimaging-based AI models for psychiatric diagnosis.

EVIDENCE REVIEW

PubMed was searched for peer-reviewed, full-length articles published between January 1, 1990, and March 16, 2022. Studies aimed at developing or validating neuroimaging-based AI models for clinical diagnosis of psychiatric disorders were included. Reference lists were further searched for suitable original studies. Data extraction followed the CHARMS (Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines. A closed-loop cross-sequential design was used for quality control. The PROBAST (Prediction Model Risk of Bias Assessment Tool) and modified CLEAR (Checklist for Evaluation of Image-Based Artificial Intelligence Reports) benchmarks were used to systematically evaluate ROB and reporting quality.

FINDINGS

A total of 517 studies presenting 555 AI models were included and evaluated. Of these models, 461 (83.1%; 95% CI, 80.0%-86.2%) were rated as having a high overall ROB based on the PROBAST. The ROB was particular high in the analysis domain, including inadequate sample size (398 of 555 models [71.7%; 95% CI, 68.0%-75.6%]), poor model performance examination (with 100% of models lacking calibration examination), and lack of handling data complexity (550 of 555 models [99.1%; 95% CI, 98.3%-99.9%]). None of the AI models was perceived to be applicable to clinical practices. Overall reporting completeness (ie, number of reported items/number of total items) for the AI models was 61.2% (95% CI, 60.6%-61.8%), and the completeness was poorest for the technical assessment domain with 39.9% (95% CI, 38.8%-41.1%).

CONCLUSIONS AND RELEVANCE

This systematic review found that the clinical applicability and feasibility of neuroimaging-based AI models for psychiatric diagnosis were challenged by a high ROB and poor reporting quality. Particularly in the analysis domain, ROB in AI diagnostic models should be addressed before clinical application.

Borderline Personality Disorder: Updates in a Postpandemic World

Progress in understanding borderline personality disorder has unfolded in the last decade, landing in a new COVID-19-influenced world. Borderline personality disorder is now firmly established as a valid diagnosis, distinct from its co-occurring mood, anxiety, trauma-related, and behavioral disorders. Further, it is also understood as a reflection of general personality dysfunction, capturing essential features shared among all personality disorders. Neuroimaging research, representing the vast neurobiological advances made in the last decade, illustrates that the disorder shares frontolimbic dysfunction with many psychiatric diagnoses but has a distinct signature of interpersonal and emotional hypersensitivity. This signature is the conceptual basis of the psychotherapies and clinical management approaches proven effective for the disorder. Medications remain adjunctive and are contraindicated by some guidelines internationally. Less invasive brain-based therapeutics show promise. The most significant change in the treatment landscape is a focus on briefer, less intensive formats of generalist management. Shorter variants of therapies, such as dialectical behavior therapy and mentalization-based treatment, are in the process of being shown to be adequately effective. Earlier intervention and greater emphasis on functional improvement are needed to more effectively curb the disabilities and risks of borderline personality disorder for patients and their families. Remote interventions show promise in broadening access to care.

Dificultades en la regulación emocional de pacientes con trastorno límite de personalidad atendidos en un centro de terapia dialéctico conductual de Medellín, Colombia

La desregulación emocional puede expresarse de distinta manera en el trastorno límite de personalidad (TLP), posiblemente por la influencia del contexto cultural. El objetivo de este estudio fue caracterizar las dificultades en la regulación emocional en pacientes con TLP que consultan a un centro especializado en Terapia Dialéctico Conductual (DBT) en la ciudad de Medellín, Colombia. Se realizó un estudio de corte transversal con 54 pacientes, principalmente mujeres jóvenes, solteras y de estrato socioeconómico alto con TLP que ingresaron a tratamiento y se les aplicó la “Escala de Dificultades en la Regulación Emocional” (DERS). Se calcularon la mediana (M) y rango intercuartílico (RIQ) y valor de p con la U de Mann-Whitney y el tamaño del efecto (valor r). El puntaje total en la DERS fue alto (M=134; RIQ=117-142). Se encontraron diferencias entre hombres y mujeres, con un tamaño de efecto intermedio (Mmujer=135,5 versus Mhombre=119; p=0,047; r=-0,26). No se encontraron diferencias entre grupos etarios, pero las dificultades en la regulación emocional sí fueron diferentes en los pacientes que cursaban además con TDAH, ansiedad, depresión y ansiedad combinados, y trastorno bipolar. Esto indicaría que en pacientes de una ciudad de Colombia en tratamiento con DBT, las dificultades en la regulación emocional son altas y parecen ser mayores en las mujeres. La presencia de ansiedad, depresión, TDAH y trastorno bipolar podría influir en la intensidad de la desregulación emocional y en las facetas en la que se manifiesta, lo que sugiere alta variabilidad dentro del diagnóstico.

Functional MRI findings in personality disorders: A review

Personality disorders (PDs) have a prevalence of approximately 10% in the United States, translating to over 30 million people affected in just one country. The true prevalence of these disorders may be even higher, as the paucity of objective diagnostic criteria could be leading to underdiagnosis. Because little is known about the underlying neuropathologies of these disorders, patients are diagnosed using subjective criteria and treated nonspecifically. To better understand the neural aberrancies responsible for these patients' symptoms, a review of functional MRI literature was performed. The findings reveal that each PD is characterized by a unique set of activation changes corresponding to individual structures or specific neural networks. While unique patterns of neural activity are distinguishable within each PD, aberrations of the limbic/paralimbic structures and default mode network are noted across several of them. In addition to identifying valuable activation patterns, this review reveals a void in research pertaining to paranoid, schizoid, histrionic, narcissistic, and dependent PDs. By delineating patterns in PD neuropathology, we can more effectively direct future research efforts toward enhancing objective diagnostic techniques and developing targeted treatment modalities. Furthermore, understanding why patients are manifesting certain symptoms can advance clinical awareness and improve patient outcomes.