Grounding cognitive-level processes in behavior: the view from dynamic systems theory

Exploring Interrelationships between Mental Health Symptoms and Cognitive Impairment in Aging People Living with HIV in China

INTRODUCTION

Mental health symptoms and cognitive impairment are highly prevalent and intertwined among aging people living with HIV (PLWH). This study aimed to assess the interrelationships and strength of connections between individual mental health symptoms and cognitive impairment. We sought to identify specific symptoms linking mental health and cognitive impairment in aging PLWH.

METHODS

Participants in the Sichuan Older People with HIV Infections Cohort Study (SOHICS) were recruited between November 2018 and April 2021 in China. Mental health symptoms, including depression and anxiety, were assessed by the Patient Health Questionnaire (PHQ-9) and General Anxiety Disorder-7 (GAD-7), respectively. Cognitive impairment was assessed by the Montreal Cognitive Assessment-Basic (MoCA-B). Partial correlation networks were used to depict the interrelationships between mental health symptoms and cognitive impairment, and bridge strength was used to identify specific symptoms linking mental health and cognitive impairment.

RESULTS

Of the 1,587 recruited participants with a mean age of 63.0 years old, 47.0% had mild or severe cognitive impairment. Network analysis revealed that cognitive function, visual perception, and problem-solving task of the MoCA-B were negatively correlated with appetite, energy, and motor of the PHQ-9, respectively. Based on their interrelationships, problem-solving task and motor acted as bridge symptoms.

CONCLUSION

Problem-solving task and motor may be potential intervention targets to reduce the overall risk of mental health symptoms and cognitive impairment. Future research could assess the feasibility and effectiveness of specific interventions designed for the two symptoms of aging PLWH.

Learning words in space and time: Contrasting models of the suspicious coincidence effect

In their 2007b Psychological Review paper, Xu and Tenenbaum found that early word learning follows the classic logic of the "suspicious coincidence effect:" when presented with a novel name ('fep') and three identical exemplars (three Labradors), word learners generalized novel names more narrowly than when presented with a single exemplar (one Labrador). Xu and Tenenbaum predicted the suspicious coincidence effect based on a Bayesian model of word learning and demonstrated that no other theory captured this effect. Recent empirical studies have revealed, however, that the effect is influenced by factors seemingly outside the purview of the Bayesian account. A process-based perspective correctly predicted that when exemplars are shown sequentially, the effect is eliminated or reversed (Spencer, Perone, Smith, & Samuelson, 2011). Here, we present a new, formal account of the suspicious coincidence effect using a generalization of a Dynamic Neural Field (DNF) model of word learning. The DNF model captures both the original finding and its reversal with sequential presentation. We compare the DNF model's performance with that of a more flexible version of the Bayesian model that allows both strong and weak sampling assumptions. Model comparison results show that the dynamic field account provides a better fit to the empirical data. We discuss the implications of the DNF model with respect to broader contrasts between Bayesian and process-level models.

Escala de desarrollo armónico (EDA): Una propuesta para la evaluación clínica del desarrollo infantil desde la Teoría de Sistemas

Los profesionales de las ciencias de la salud y de la educación necesitan herramientas adecuadas para llevar a cabo la prevención de los trastornos del desarrollo infantil. La Escala de Desarrollo Armónico –EDA–, se presenta como una propuesta que permite la coordinación interdisciplinaria y la colaboración de los educadores. La escala se ha construido para observar el ascenso del paisaje epigenético individual desde el paradigma de los sistemas dinámicos. Para lograrlo, se han estudiado parámetros que pueden explicar la evolución del sistema –índice de armonía y cociente de desarrollo estable–, un mecanismo del cambio –tirón cognitivo– y fuerzas moldeadoras –velocidad y cristalización–, siguiendo el principio de «armonía» para alcanzar el máximo desarrollo potencial. La estructura de la escala es adecuada para funcionar como un test adaptativo informatizado, por lo que resulta accesible, fácil de usar y puede validarse siguiendo la metodología de respuesta al ítem –TRI–. Las cualidades «orgánicas» de la EDA permiten un funcionamiento interactivo a través de Internet –www.maternal.eu–, donde ya presta servicio a educadores, profesionales e investigadores.

Individual differences in the production of disfluency: A latent variable analysis of memory ability and verbal intelligence

Recent work has begun to focus on the role that individual differences in executive function and intelligence have on the production of fluent speech. However, isolating the underlying causes of different types of disfluency has been difficult given the speed and complexity of language production. In this study, we focused on the role of memory abilities and verbal intelligence, and we chose a task that relied heavily on memory for successful performance. Given the task demands, we hypothesised that a substantial proportion of disfluencies would be due to memory retrieval problems. We contrasted memory abilities with individual differences in verbal intelligence as previous work highlighted verbal intelligence as an important factor in disfluency production. A total of 78 participants memorised and repeated 40 syntactically complex sentences, which were recorded and coded for disfluencies. Model comparisons were carried out using hierarchical structural equation modelling. Results showed that repetitions were significantly related to verbal intelligence. Unfilled pauses and repairs, in contrast, were marginally ( p < .09) related to memory abilities. The relationship in all cases was negative. Conclusions explore the link between different types of disfluency and particular problems arising in the course of production, and how individual differences inform theoretical debates in language production.

Model-based functional neuroimaging using dynamic neural fields: An integrative cognitive neuroscience approach

A fundamental challenge in cognitive neuroscience is to develop theoretical frameworks that effectively span the gap between brain and behavior, between neuroscience and psychology. Here, we attempt to bridge this divide by formalizing an integrative cognitive neuroscience approach using dynamic field theory (DFT). We begin by providing an overview of how DFT seeks to understand the neural population dynamics that underlie cognitive processes through previous applications and comparisons to other modeling approaches. We then use previously published behavioral and neural data from a response selection Go/Nogo task as a case study for model simulations. Results from this study served as the 'standard' for comparisons with a model-based fMRI approach using dynamic neural fields (DNF). The tutorial explains the rationale and hypotheses involved in the process of creating the DNF architecture and fitting model parameters. Two DNF models, with similar structure and parameter sets, are then compared. Both models effectively simulated reaction times from the task as we varied the number of stimulus-response mappings and the proportion of Go trials. Next, we directly simulated hemodynamic predictions from the neural activation patterns from each model. These predictions were tested using general linear models (GLMs). Results showed that the DNF model that was created by tuning parameters to capture simultaneously trends in neural activation and behavioral data quantitatively outperformed a Standard GLM analysis of the same dataset. Further, by using the GLM results to assign functional roles to particular clusters in the brain, we illustrate how DNF models shed new light on the neural populations' dynamics within particular brain regions. Thus, the present study illustrates how an interactive cognitive neuroscience model can be used in practice to bridge the gap between brain and behavior.

Causality in Psychiatry: A Hybrid Symptom Network Construct Model

Causality or etiology in psychiatry is marked by standard biomedical, reductionistic models (symptoms reflect the construct involved) that inform approaches to nosology, or classification, such as in the DSM-5 [Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; (1)]. However, network approaches to symptom interaction [i.e., symptoms are formative of the construct; e.g., (2), for posttraumatic stress disorder (PTSD)] are being developed that speak to bottom-up processes in mental disorder, in contrast to the typical top-down psychological construct approach. The present article presents a hybrid top-down, bottom-up model of the relationship between symptoms and mental disorder, viewing symptom expression and their causal complex as a reciprocally dynamic system with multiple levels, from lower-order symptoms in interaction to higher-order constructs affecting them. The hybrid model hinges on good understanding of systems theory in which it is embedded, so that the article reviews in depth non-linear dynamical systems theory (NLDST). The article applies the concept of emergent circular causality (3) to symptom development, as well. Conclusions consider that symptoms vary over several dimensions, including: subjectivity; objectivity; conscious motivation effort; and unconscious influences, and the degree to which individual (e.g., meaning) and universal (e.g., causal) processes are involved. The opposition between science and skepticism is a complex one that the article addresses in final comments.