Associations of Alzheimer Disease and Related Dementia Neuropathologies With Timely Diagnosis of Dementia in Healthcare Settings.

Alexithymia is defined by difficulties in identifying and describing feelings, a restricted imagination, and a pronounced externally oriented thinking style (; ). Although it is not formally recognized as a clinical diagnosis, thresholds for clinically significant levels have been established. Rather than a categorical condition, alexithymia is conceptualized as a continuous trait present throughout the general population, including among healthy individuals. Alexithymia severity is relatively stable and is associated with increased symptom severity across diverse mental health conditions (; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ). Due to the strong association between alexithymic traits and various forms of psychopathology, the transdiagnostic clinical relevance of addressing alexithymia is widely acknowledged. However, the effectiveness of current therapeutic interventions for alexithymia remains limited (; ; ; ; ). Identifying the neural mechanisms underlying alexithymia may clarify the limitations of existing interventions and inform the development of more effective, targeted treatments. Despite efforts in the literature to address these issues, two primary concerns persist. First, although studies in clinical populations have yielded valuable insights into the neural correlates of alexithymia, their interpretation is frequently confounded by co-occurring mental health or substance use disorders, making it difficult to isolate the neural patterns specific to alexithymia. Additionally, much of this research relies on task-based paradigms, which measure brain activity only in response to specific task demands. For instance, during tasks involving the identification or observation of emotionally valenced stimuli, individuals with alexithymia show reduced activity in the anterior cingulate cortex (ACC) (; ), insula, amygdala (), left dorsolateral prefrontal cortex (dlPFC), dorsal pons, cerebellum (), and posterior cingulate cortex () compared to healthy controls. Task-based studies in healthy adults implicate similar brain regions. For example, the Difficulty Identifying Feelings (DIF) subscale of the Toronto Alexithymia Scale (TAS-20; ) has been associated with decreased right amygdala activity when observing emotionally salient stimuli (; ). Additionally, an a priori analysis of speech intonation processing regions found that the Difficulty Describing Feelings (DDF) TAS-20 subscale was associated with decreased activity in the left superior temporal gyrus (STG) and bilateral amygdala (). Collectively, these findings indicate that alexithymia is associated with reduced reactivity in regions involved in affective stimulus processing and sensory integration in both clinical and healthy populations, particularly during introspection and mentalizing. However, the focus on a priori-defined regions related to specific tasks limits the generalizability of these findings. Because these effects are context-dependent, such studies highlight an interaction between alexithymia and task performance, leaving the intrinsic neural features of alexithymia unresolved and emphasizing the need for nontask-based functional magnetic resonance imaging (fMRI) approaches to assess alexithymia variance. Resting-state functional connectivity (rsFC) provides a powerful framework for examining intrinsic brain organization independent of task demands. Nevertheless, most rsFC studies of alexithymia have relied on hypothesis-driven analyses restricted to a priori regions of interest derived from task-based paradigms. While this approach has yielded valuable insights, it inherently limits discovery and may fail to capture the distributed nature of alexithymia-related neural alterations. Across both clinical and non-clinical populations, elevated alexithymia has been linked to widespread disruptions involving limbic, executive control, and self-referential networks, including altered amygdala–prefrontal and insula–prefrontal connectivity, as well as disruptions of default mode network connectivity (; ; ; ; ). The heterogeneity and breadth of these findings suggest that alexithymia cannot be adequately characterized by isolated regional abnormalities. Instead, they point to a need for unbiased connectivity analyses capable of identifying network-level organization that may be overlooked by regionally constrained approaches. The present study directly addresses this gap by adopting a comprehensive, data-driven rsFC framework to define connectivity patterns predictive of alexithymia.