Beyond deliberate thought and structured cognitive processes flows spontaneous, undirected thinking, such as MW (Fox et al., 2015). MW is a shift from task-related and stimulus-driven thoughts to internal thoughts (Smallwood and Schooler, 2015). It also occurs in the absence of a task and can involve trains of thought, when attention shifts toward the internal world, such as during daydreaming, recalling memories, or visualizing mental images, rather than focusing on the external world and stimuli (Christoff et al., 2016). This phenomenon accounts for approximately 30 to 50 % of waking time and can be both beneficial and detrimental. Although MW may be linked to performance deficits due to spontaneous, uncontrolled thoughts, occurring during reading, working-memory tasks, intelligence tests, and other cognitive activities (Mooneyham and Schooler, 2013), it also plays an important role in creative thinking, strategic reasoning, and planning, all of which support problem-solving (Bozhilova et al., 2018).

Additionally, ADHD is another condition in which MW is notably altered (Bozhilova et al., 2018). ADHD is a neurodevelopmental disorder that affects approximately 5.3 % of children worldwide (Polanczyk et al., 2015). Children diagnosed with ADHD exhibit a persistent pattern of inattention, impulsivity, and/or hyperactivity that is developmentally inappropriate and interferes with daily functioning (Koutsoklenis and Honkasilta, 2023). Not only can ADHD lead to adverse outcomes, such as academic and occupational difficulties as well as cognitive deficits (Christakou et al., 2013), but it may also increase the risk (by up to 300 %) of developing secondary mental health disorders, including depression, anxiety disorders, and substance abuse (Kessler et al., 2014). Therefore, since ADHD plays a major role in the early-life onset of functional impairments, understanding its underlying mechanisms remains a crucial area of study (Nigg et al., 2020).

Although spontaneous thought is a widespread experience, it can be altered in various clinical populations, manifesting as excessive worry in anxiety disorders, rumination in depression, and obsessions in obsessive-compulsive disorder (OCD) (Christoff et al., 2016; Spinhoven et al., 2015). One potential contributor to various ADHD symptoms and impairments is MW (Mowlem et al., 2019). Research further supports this by showing that both ADHD and MW are linked to similar cognitive and functional deficits (Bozhilova et al., 2018). For instance, while difficulty in sustaining attention on tasks is a core characteristic of ADHD, MW has also been shown to interfere with sustained attention in response-based tasks (Christoff et al., 2016; Stawarczyk et al., 2011). Although MW may share some underlying mechanisms with executive functions such as attention (Christoff et al., 2016), the relationship between MW and sustained attention remains controversial, with conflicting findings in the literature. For instance, contrary to previous beliefs, Martínez-Pérez et al. (2023) found that vigilance, a key component of attention, operates independently of MW.

Since more accurate diagnosis and targeted interventions during childhood can improve long-term outcomes of ADHD, identifying objective markers such as MW during this developmental stage is crucial for effective intervention (Coghill and Seth, 2015). The ages of 7 to 15 represent a critical period for both the emergence of ADHD symptoms and impairments and the maturation of functional brain networks (Asherson et al., 2016). Additionally, it has been proposed that MW is likely to become more frequent during this period (Bozhilova et al., 2018). Given the significance of this developmental stage, the present study specifically focuses on this period to explore how MW manifests in ADHD. The key question is whether MW can serve as a measurable marker of ADHD psychopathology. One way to address this is by investigating its relationship with ADHD’s primary symptoms and cognitive dysfunctions, particularly sustained attention deficits.

Understanding this connection depends on how MW is assessed. It can be evaluated through direct and indirect measures, including self-reports and physiological markers. Among these, neuroimaging techniques such as fMRI have provided crucial insights into the neural correlates of MW (Bozhilova et al., 2018). Studies consistently link MW to increased activity in the default mode network (DMN) (Fox et al., 2015). The DMN is known as a set of brain regions (including Medial Prefrontal Cortex, Inferior Parietal Lobule, and Posterior Cingulate Cortex) that are consistently less active during experimental tasks and more active under baseline conditions (Raichle et al., 2001). Although this network has been identified as a key source of task-unrelated and internally directed thoughts, other brain areas also contribute to MW and other forms of spontaneous thoughts (Buckner and Vincent, 2007; Fox et al., 2015). In fact, several non-DMN regions, including dorsal anterior cingulate cortex, rostrolateral prefrontal cortex, insula, and lingual gyrus have been reported to be equally central to MW as DMN regions (Bozhilova et al., 2018; Fox et al., 2015). Increased DMN activity, along with reduced functional connectivity between the DMN and task-positive networks such as the Fronto-Parietal Network (FPN) and Executive Control Network (ECN), has been consistently linked to MW (Fox et al., 2015; Golchert et al., 2017).

EEG research has also revealed heightened activity in delta, theta, and alpha frequency bands during MW, while beta activity consistently decreases (Kam et al., 2022; Soltanzadeh et al., 2024). However, conventional EEG analysis primarily captures surface-level electrical activity and does not effectively localize cortical sources and assess connectivity patterns (Yokoyama et al., 2024). To address this limitation, the adoption of functional connectivity (FC) and current source density (CSD) analyses to EEG-based investigation would enhance the localization, identification, and interpretation of neural activity involved in MW (Krukow and Jonak, 2022). Therefore, in the current study, the researcher employs these advanced analyses to better characterize the neural dynamics of MW.

The present study is designed to assess the relationship between MW and sustained attention to clarify MW’s role in ADHD and determine whether MW can serve as an objective and measurable marker of ADHD-related cognitive dysfunction, potentially informing novel diagnostic and intervention strategies.