Traditional neuropsychological assessments have long served as the foundation for evaluating cognitive functioning. However, these tools face critical limitations: they often rely on outdated measures, are prone to retest effects, lack population-specific norms, and require trained clinicians. Furthermore, they typically yield broad total scores, masking the complexity of underlying processes and dynamic interactions. In parallel, mental health assessments frequently depend on subjective self-report, which may be biased or insensitive to subtle psychological changes.

In our lab, we are developing innovative, technology-based tools to address these gaps and advance objective, fine-grained assessments of mental and cognitive states. Our projects span several domains:

Auditory Markers of Depression: We are leveraging data from neurocognitive speech tasks to identify linguistic and acoustic features associated with depression. By analyzing elements such as speech rate, pitch variability, and prosody—and how they interact with cognitive factors like rumination and executive functioning—we aim to create scalable, non-invasive tools for early detection and monitoring of depression, especially in aging populations.

Affective Flexibility Assessment via Task Switching: We have developed a novel affective voluntary task-switching paradigm that captures emotional flexibility in real time. This task enables us to assess how individuals choose to switch between emotional tasks, providing a dynamic, ecologically valid measure of affective flexibility that can inform our understanding of psychopathology and resilience.

Together, these efforts reflect our lab's commitment to building objective, personalized, and clinically relevant tools that overcome the constraints of traditional assessments and self-report measures.