The aim of this master's thesis was to determine whether the improved performance in the n-back task and associated neural changes result from learning and training in the task or the actual effect of therapeutic interventions. We compared a group of healthy individuals and individuals with depression, combining objective measurements (n-back task) and subjective self-assessment scales of clinical symptoms.
The research findings indicate that individuals with depression are more sensitive to cognitive load, suggesting an impaired ability to maintain and update information in working memory. Observed deficits in reaction time and accuracy support the hypothesis of reduced cognitive flexibility and greater susceptibility to disturbances in information processing. These findings highlight the need for multidimensional diagnostic and therapeutic approaches that will consider cognitive impairments as a key aspect of depressive disorders.
One of the main findings of this study is the confirmation of the learning effect, as both groups—healthy individuals and individuals with depression—showed improvements in accuracy and reaction time during the second measurement. However, the improvement was less pronounced in individuals with depression compared to healthy participants, which may indicate difficulties in adapting to repetitive tasks.
ndividuals with depression may have a reduced ability to update cognitive strategies and adapt to new information, potentially leading to slower learning or decreased efficiency in tasks that require cognitive flexibility. These results emphasize the need for further research into the impact of depression on cognitive flexibility and learning ability, as well as an exploration of how these factors manifest in daily functioning and cognitive rehabilitation.
Advancements in understanding and measuring depression require the integration of various theoretical approaches, the use of advanced measurement tools, and interdisciplinary collaboration. Theories that conceptualize depression as a complex system, along with dynamic measurement approaches, offer promising pathways for a deeper understanding of depressive disorder.
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