When self comes to a wandering mind: Brain representations and dynamics of self-generated concepts in spontaneous thought

Spontaneous thought separates into clusters of negative, positive, and flexible thinking

The nature and frequency of spontaneous thoughts play a critical role in cognitive processes like perception, decision-making, attention, and memory. Deficits in these processes are also greatly associated with the development and maintenance of psychopathology. However, the underlying cognitive dynamics of free and stuck spontaneous thought remain unclear, as these often occur in the absence of measurable behaviors. Here, we analyze free word-association data using attractor-state dynamic modeling, which conceptualizes stuck spontaneous thought as navigating a multidimensional semantic space while in the presence of strong attractor locations. Word-association data was collected from an exploratory sample (N1 = 65), a first replication sample (N2 = 79), and, following pre-registration, a second replication sample (N3 = 222). After the data was embedded into a 3-dimensional semantic space and fit by our dynamic model, unsupervised learning consistently grouped data into four clusters across all independent samples. These clusters were characterized by two distinct patterns of stuck negative thinking, a pattern of protective positive thinking, and a pattern of flexible mind-wandering. Our results support a method for modeling spontaneous thought and isolate distinct sub-types that may not be accessible using retrospective self-report methods. We discuss implications for clinical and cognitive science.

A free association semantic task for fNIRS-based perinatal depression assessment

Perinatal depression (PD) is a highly prevalent psychological disorder that has a detrimental effect on infant and maternal physical and mental health, but effective and objective assessment of PD is still insufficient. In recent years, the functional near-infrared spectroscopy (fNIRS) has been acknowledged as an effective non-invasive tool for clinical assessment of depression. This study proposed a free association semantic task (FAST) paradigm for fNIRS-based assessment of PD. To better address the emotion characteristics of PD, the participants are required to generate a dynamic concept chain based on positive, negative or neutral seed words, while 48-channel fNIRS recordings over frontal and bilateral temporal regions. Results from twenty-two late-pregnant women revealed that, the oxyhemoglobin (oxy-Hb) changes during the FAST with the positive and negative seed words over the frontal region were correlated with PD severity, which was different from the correlation patterns in the FAST with neutral seed word and the classical verbal fluency test (VFT). Furthermore, distinct correlation patterns were also observed in the FAST with the positive and negative seed words, manifested in fNIRS channels corresponding to the right dorsolateral prefrontal cortex (DLPFC) and right inferior frontal gyrus (IFG), respectively. Moreover, regression analyses showed that the FAST with positive and negative seed words can well explain the severity of PD. Our findings suggest the proposed FAST paradigm as a promising approach for PD assessment.

Individual variability in neural representations of mind-wandering

Mind-wandering is a frequent, daily mental activity, experienced in unique ways in each person. Yet neuroimaging evidence relating mind-wandering to brain activity, for example in the default mode network (DMN), has relied on population- rather than individual-based inferences owing to limited within-person sampling. Here, three densely sampled individuals each reported hundreds of mind-wandering episodes while undergoing multi-session functional magnetic resonance imaging. We found reliable associations between mind-wandering and DMN activation when estimating brain networks within individuals using precision functional mapping. However, the timing of spontaneous DMN activity relative to subjective reports, and the networks beyond DMN that were activated and deactivated during mind-wandering, were distinct across individuals. Connectome-based predictive modeling further revealed idiosyncratic, whole-brain functional connectivity patterns that consistently predicted mind-wandering within individuals but did not fully generalize across individuals. Predictive models of mind-wandering and attention that were derived from larger-scale neuroimaging datasets largely failed when applied to densely sampled individuals, further highlighting the need for personalized models. Our work offers novel evidence for both conserved and variable neural representations of self-reported mind-wandering in different individuals. The previously unrecognized interindividual variations reported here underscore the broader scientific value and potential clinical utility of idiographic approaches to brain-experience associations.

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.

Digital assessment of cognitive-affective biases related to mental health

With an increasing societal need for digital therapy solutions for poor mental health, we face a corresponding rise in demand for scientifically validated digital contents. In this study we aimed to lay a sound scientific foundation for the development of brain-based digital therapeutics to assess and monitor cognitive effects of social and emotional bias across diverse populations and age-ranges. First, we developed three computerized cognitive tasks using animated graphics: 1) an emotional flanker task designed to test attentional bias, 2) an emotional go-no-go task to measure bias in memory and executive function, and 3) an emotional social evaluation task to measure sensitivity to social judgments. Then, we confirmed the generalizability of our results in a wide range of samples (children (N = 50), young adults (N = 172), older adults (N = 39), online young adults (N=93), and depression patients (N = 41)) using touchscreen and online computer-based tasks, and devised a spontaneous thought generation task that was strongly associated with, and therefore could potentially serve as an alternative to, self-report scales. Using PCA, we extracted five components that represented different aspects of cognitive-affective function (emotional bias, emotional sensitivity, general accuracy, and general/social attention). Next, a gamified version of the above tasks was developed to test the feasibility of digital cognitive training over a 2-week period. A pilot training study utilizing this application showed decreases in emotional bias in the training group (that were not observed in the control group), which was correlated with a reduction in anxiety symptoms. Using a 2-channel wearable EEG system, we found that frontal alpha and gamma power were associated with both emotional bias and its reduction across the 2-week training period.

Brain decoding of spontaneous thought: Predictive modeling of self-relevance and valence using personal narratives

The contents and dynamics of spontaneous thought are important factors for personality traits and mental health. However, assessing spontaneous thoughts is challenging due to their unconstrained nature, and directing participants' attention to report their thoughts may fundamentally alter them. Here, we aimed to decode two key content dimensions of spontaneous thought-self-relevance and valence-directly from brain activity. To train functional MRI-based predictive models, we used individually generated personal stories as stimuli in a story-reading task to mimic narrative-like spontaneous thoughts (n = 49). We then tested these models on multiple test datasets (total n = 199). The default mode, ventral attention, and frontoparietal networks played key roles in the predictions, with the anterior insula and midcingulate cortex contributing to self-relevance prediction and the left temporoparietal junction and dorsomedial prefrontal cortex contributing to valence prediction. Overall, this study presents brain models of internal thoughts and emotions, highlighting the potential for the brain decoding of spontaneous thought.

Environmental and dietary exposure to 24 polycyclic aromatic hydrocarbons in a typical Chinese coking plant

Polycyclic aromatic hydrocarbons (PAHs), known for their health risks, are prevalent in the environment, with the coking industry being a major source of their emissions. To bridge the knowledge gap concerning the relationship between environmental and dietary PAH exposure, we explore this complex interplay by investigating the dietary exposure characteristics of 24 PAHs within a typical Chinese coking plant and their association with environmental pollution. Our research revealed Nap and Fle as primary dietary contaminants, emphasizing the significant influence of soil and atmospheric pollution on PAH exposure. We subjected our data to non-metric multidimensional scaling (NMDS), Spearman correlation analysis, Lasso regression, and Weighted Quantile Sum (WQS) regression to delve into this multifaceted phenomenon. NMDS reveals that dietary PAH exposure, especially within the high molecular weight (HMW) group, is common both within and around the coking plant. This suggests that meals prepared within the plant may be contaminated, posing health risks to coking plant workers. Furthermore, our assessment of dietary exposure risk highlights Nap and Fle as the primary dietary contaminants, with BaP and DahA raising concerns due to their higher carcinogenic potential. Our findings indicate that dietary exposure often exceeds acceptable limits, particularly for coking plant workers. Correlation analyses uncover the dominant roles of soil and atmospheric pollution in shaping dietary PAH exposure. Soil contamination significantly impacts specific PAHs, while atmospheric pollution contributes to others. Additionally, WQS regression emphasizes the substantial influence of soil and drinking water on dietary PAHs. In summary, our study sheds light on the dietary exposure characteristics of PAHs in a typical Chinese coking plant and their intricate interplay with environmental factors. These findings underscore the need for comprehensive strategies to mitigate PAH exposure so as to safeguard both human health and the environment in affected regions.

Individual variability in neural representations of mind-wandering

Mind-wandering is a frequent, daily mental activity, experienced in unique ways in each person. Yet neuroimaging evidence relating mind-wandering to brain activity, for example in the default mode network (DMN), has relied on population-rather than individual-based inferences due to limited within-individual sampling. Here, three densely-sampled individuals each reported hundreds of mind-wandering episodes while undergoing multi-session functional magnetic resonance imaging. We found reliable associations between mind-wandering and DMN activation when estimating brain networks within individuals using precision functional mapping. However, the timing of spontaneous DMN activity relative to subjective reports, and the networks beyond DMN that were activated and deactivated during mind-wandering, were distinct across individuals. Connectome-based predictive modeling further revealed idiosyncratic, whole-brain functional connectivity patterns that consistently predicted mind-wandering within individuals but did not fully generalize across individuals. Predictive models of mind-wandering and attention that were derived from larger-scale neuroimaging datasets largely failed when applied to densely-sampled individuals, further highlighting the need for personalized models. Our work offers novel evidence for both conserved and variable neural representations of self-reported mind-wandering in different individuals. The previously-unrecognized inter-individual variations reported here underscore the broader scientific value and potential clinical utility of idiographic approaches to brain-experience associations.

Neural patterns differentiate traumatic from sad autobiographical memories in PTSD

For people with post-traumatic stress disorder (PTSD), recall of traumatic memories often displays as intrusions that differ profoundly from processing of 'regular' negative memories. These mnemonic features fueled theories speculating a unique cognitive state linked with traumatic memories. Yet, to date, little empirical evidence supports this view. Here we examined neural activity of patients with PTSD who were listening to narratives depicting their own memories. An intersubject representational similarity analysis of cross-subject semantic content and neural patterns revealed a differentiation in hippocampal representation by narrative type: semantically similar, sad autobiographical memories elicited similar neural representations across participants. By contrast, within the same individuals, semantically similar trauma memories were not represented similarly. Furthermore, we were able to decode memory type from hippocampal multivoxel patterns. Finally, individual symptom severity modulated semantic representation of the traumatic narratives in the posterior cingulate cortex. Taken together, these findings suggest that traumatic memories are an alternative cognitive entity that deviates from memory per se.

Recent advances in the neuroscience of spontaneous and off-task thought: implications for mental health

People spend a remarkable 30-50% of awake life thinking about something other than what they are currently doing. These experiences of being "off-task" can be described as spontaneous thought when mental dynamics are relatively flexible. Here we review recent neuroscience developments in this area and consider implications for mental wellbeing and illness. We provide updated overviews of the roles of the default mode network and large-scale network dynamics, and we discuss emerging candidate mechanisms involving hippocampal memory (sharp-wave ripples, replay) and neuromodulatory (noradrenergic and serotonergic) systems. We explore how distinct brain states can be associated with or give rise to adaptive and maladaptive forms of thought linked to distinguishable mental health outcomes. We conclude by outlining new directions in the neuroscience of spontaneous and off-task thought that may clarify mechanisms, lead to personalized biomarkers, and facilitate therapy developments toward the goals of better understanding and improving mental health.