An overactive mind: Investigating racing thoughts in ADHD, hypomania and comorbid ADHD and bipolar disorder via verbal fluency tasks

Latent mechanisms of language disorganization relate to specific dimensions of psychopathology

Comprehensible communication is critical for social functioning and well-being. In psychopathology, incoherent discourse is assumed to reflect disorganized thinking, which is classically linked to psychotic disorders. However, people do not express everything that comes to mind, rendering inferences from discourse to the underlying structure of thought challenging. Indeed, a range of psychopathologies are linked to self-reported disorganized thinking in the absence of language output incoherence. Here we combine natural language processing and computational modeling of free association to detail the relationship between disorganized thinking and language (in)coherence in a large sample of participants varying across different dimensions of psychopathology. Our approach allowed us to differentiate between disorganized thinking, disinhibited thought expression and deliberate creativity. We find evidence for both under-regulated and over-regulated disorganized thinking, which relate to two specific dimensions of psychopathology: self-reported eccentricity and suspiciousness. Broadly, these results underscore the theoretical progress afforded by analyzing latent dimensions underlying behavior and psychopathology.

Dynamics of spontaneous thoughts: Exploration, attentional profile and the segmentation of the stream of thoughts

For a long time, clinical knowledge and first-person reports have pointed to individual differences in the dynamics of spontaneous thoughts, in particular in the extreme case of psychiatric conditions (e.g. racing thoughts in Attention Deficit / Hyperactivity Disorder, ADHD; rumination in depression). We used a novel procedure to investigate this individual variability by combining verbal fluency tasks and introspective reports of thought content. Our goal was twofold. First, we tested the hypothesis that a greater segmentation of the stream of thoughts would be associated with trait inattention, in line with subjective reports of ADHD patients. Second, we tested whether the segmentation of the stream of thoughts increased with an increased tendency for exploratory behavior, following recent theoretical claims on the mechanisms underpinning the generation of spontaneous thoughts. Our results support both hypotheses, shedding light on the factors contributing to the individual variability in the dynamics of the stream of thought.

forager: a Python package and web interface for modeling mental search

Analyzing data from the verbal fluency task (e.g., "name all the animals you can in a minute") is of interest to both memory researchers and clinicians due to its broader implications for memory search and retrieval. Recent work has proposed several computational models to examine nuanced differences in search behavior, which can provide insights into the mechanisms underlying memory search. A prominent account of memory search within the fluency task was proposed by Hills et al. (2012), where mental search is modeled after how animals forage for food in physical space. Despite the broad potential utility of these models to scientists and clinicians, there is currently no open-source program to apply and compare existing foraging models or clustering algorithms without extensive, often redundant programming. To remove this barrier to studying search patterns in the fluency task, we created forager, a Python package ( https://github.com/thelexiconlab/forager ) and web interface ( https://forager.research.bowdoin.edu/ ). forager provides multiple automated methods to designate clusters and switches within a fluency list, implements a novel set of computational models that can examine the influence of multiple lexical sources (semantic, phonological, and frequency) on memory search using semantic embeddings, and also enables researchers to evaluate relative model performance at the individual and group level. The package and web interface cater to users with various levels of programming experience. In this work, we introduce forager's basic functionality and use cases that demonstrate its utility with pre-existing behavioral and clinical data sets of the semantic fluency task.

Automated Speech Analysis in Bipolar Disorder: The CALIBER Study Protocol and Preliminary Results

Background: Bipolar disorder (BD) involves significant mood and energy shifts reflected in speech patterns. Detecting these patterns is crucial for diagnosis and monitoring, currently assessed subjectively. Advances in natural language processing offer opportunities to objectively analyze them. Aims: To (i) correlate speech features with manic-depressive symptom severity in BD, (ii) develop predictive models for diagnostic and treatment outcomes, and (iii) determine the most relevant speech features and tasks for these analyses. Methods: This naturalistic, observational study involved longitudinal audio recordings of BD patients at euthymia, during acute manic/depressive phases, and after-response. Patients participated in clinical evaluations, cognitive tasks, standard text readings, and storytelling. After automatic diarization and transcription, speech features, including acoustics, content, formal aspects, and emotionality, will be extracted. Statistical analyses will (i) correlate speech features with clinical scales, (ii) use lasso logistic regression to develop predictive models, and (iii) identify relevant speech features. Results: Audio recordings from 76 patients (24 manic, 21 depressed, 31 euthymic) were collected. The mean age was 46.0 ± 14.4 years, with 63.2% female. The mean YMRS score for manic patients was 22.9 ± 7.1, reducing to 5.3 ± 5.3 post-response. Depressed patients had a mean HDRS-17 score of 17.1 ± 4.4, decreasing to 3.3 ± 2.8 post-response. Euthymic patients had mean YMRS and HDRS-17 scores of 0.97 ± 1.4 and 3.9 ± 2.9, respectively. Following data pre-processing, including noise reduction and feature extraction, comprehensive statistical analyses will be conducted to explore correlations and develop predictive models. Conclusions: Automated speech analysis in BD could provide objective markers for psychopathological alterations, improving diagnosis, monitoring, and response prediction. This technology could identify subtle alterations, signaling early signs of relapse. Establishing standardized protocols is crucial for creating a global speech cohort, fostering collaboration, and advancing BD understanding.

Symptoms of ADHD and Autism Spectrum Disorder Interactively Predict Children's Verbal Fluency

OBJECTIVE

Verbal fluency, the capacity to generate words from a designated category, predicts myriad cognitive and life outcomes. The study investigated verbal fluency in children with ADHD, autism spectrum disorder (ASD), and comorbid ADHD and ASD, to understand how ADHD- and ASD-related symptoms individually and jointly predict verbal fluency, and the underlying linguistic and cognitive substrates.

METHOD

Thirty-three school-aged children with ADHD, 27 with ASD, 25 with comorbid ADHD and ASD, and 39 with typical development, were assessed for ADHD and ASD symptoms and completed a semantic verbal fluency task.

RESULTS

Findings indicated that ADHD and ASD symptoms, especially ADHD hyperactivity-impulsivity symptoms and language-related ASD symptoms, interactively predicted verbal fluency across diagnostic groups.

CONCLUSION

The study implicated the potential cognitive and linguistic mechanisms underlying verbal fluency differences in ADHD and/or ASD, and clinical practices on enhancing verbal fluency in these clinical groups.

Identifying different patterns of emotion dysregulation in adult ADHD

BACKGROUND

Emotion dysregulation (ED) is a core intrinsic feature of adult presenting Attention Deficit Hyperactivity Disorder (ADHD). However, the clinical expressions of ED are diverse and several questionnaires have been used to measure ED in adults with ADHD. Thus, to date, the characteristics of ED in adult ADHD remain poorly defined. The objective of this study is to identify the different patterns of ED in adults with ADHD.

METHODS

A large sample of 460 newly diagnosed adults with ADHD were recruited. Patients completed a total of 20 self-reported questionnaires. Measures consisted in the several facets of ED, but also other clinical features of adult ADHD such as racing thoughts. A factor analysis with the principal component extraction method was performed to define the symptomatic clusters. A mono-dimensional clustering was then conducted to assess whether participants presented or not with each symptomatic cluster.

RESULTS

The factor analysis yielded a 5 factor-solution, including "emotional instability", "impulsivity", "overactivation", "inattention/disorganization" and "sleep problems". ED was part of two out of five clusters and concerned 67.52% of our sample. Among those patients, the combined ADHD presentation was the most prevalent. Emotional instability and impulsivity were significantly predicted by childhood maltreatment. The ED and the "sleep problems" factors contributed significantly to the patients' functional impairment.

CONCLUSIONS

ED in ADHD is characterized along emotional instability and emotional impulsivity, and significantly contributes to functional impairment. However, beyond impairing symptoms, adult ADHD may also be characterized by functional strengths such as creativity.

Disentangling racing thoughts from mind wandering in adult attention deficit hyperactivity disorder

Introduction

Mental restlessness reported by adult with Attention Deficit Hyperactivity Disorder (ADHD) has been mainly explained by excessive mind wandering. However, the description of a mind constantly on the go is also akin to racing thoughts, predominantly described in bipolar disorder. This paper aimed at disentangling mind wandering from racing thoughts in adult with ADHD. Associations between those mental phenomena and the ADHD symptomatology were also investigated.

Methods

To this aim, 84 adults with ADHD completed self-reported questionnaires, including the Mind Wandering-Deliberate and Mind Wandering-Spontaneous questionnaires, the Racing and Crowded Thoughts Questionnaire and the Daydreaming Frequency Scale. Factorial analysis and multiple linear regressions were performed.

Results

The factor analysis yielded a two-factor solution. The first factor encompassed the three facets of racing thoughts and was predicted by emotional lability. The second comprised deliberated-MW, spontaneous-MW and daydreaming, but was neither related to the ADHD symptoms, nor functional impairment.

Discussion

These findings suggest that MW and racing thoughts are two distinguishable mental phenomena. Racing thoughts appear to be a relevant hypothesis to explain the mental restlessness in adult ADHD.

Psychopathological Dissection of Bipolar Disorder and ADHD: Focussing on Racing Thoughts and Verbal Fluency

In the present study, we propose a review and a synthesis of the work of our group about the phenomenology and the cognitive mechanisms of racing thoughts in bipolar disorder (BD) and ADHD. Contrary to the mainstream idea according to which racing thoughts are pathognomonic of BD, our work suggests that racing thoughts are enhanced in ADHD compared to hypomanic episodes of BD, whereas in euthymic episodes of BD self-reported racing thoughts are similar to the rates reported by healthy controls. Using verbal fluency tasks, we found many similarities between bipolar and ADHD subjects with one clear difference: lexical search strategy in hypomania is based on phonemic similarities rather than semantic-relatedness. However, this distinction observed in this cognitive task is certainly difficult to grasp during a clinical interview aiming to differentiate mild hypomania from combined ADHD presentation. The main landmark to distinguish them remains the episodic nature of bipolar disorders as opposed to the lifelong presentation of ADHD symptoms, a dichotomous view that is not so clear-cut in clinical practice.

Tackling emotional processing in adults with attention deficit hyperactivity disorder and attention deficit hyperactivity disorder + autism spectrum disorder using emotional and action verbal fluency tasks

Introduction

Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) are two neurodevelopmental conditions with neuropsychological, social, emotional, and psychopathological similarities. Both are characterized by executive dysfunction, emotion dysregulation (ED), and psychiatric comorbidities. By focusing on emotions and embodied cognition, this study aims to improve the understanding of overlapping symptoms between ADHD and ASD through the use of verbal fluency tasks.

Methods

Fifty-two adults with ADHD, 13 adults with ADHD + ASD and 24 neurotypical (NT) participants were recruited in this study. A neuropsychological evaluation, including different verbal fluency conditions (e.g. emotional and action), was proposed. Subjects also completed several self-report questionnaires, such as scales measuring symptoms of ED.

Results

Compared to NT controls, adults with ADHD + ASD produced fewer anger-related emotions. Symptoms of emotion dysregulation were associated with an increased number of actions verbs and emotions produced in ADHD.

Discussion

The association between affective language of adults with ADHD and symptoms of emotion dysregulation may reflect their social maladjustment. Moreover, the addition of ADHD + ASD conditions may reflect more severe affective dysfunction.