INVESTIGATING CORRELATIONS OF RESTING-STATE FRACTAL BRAIN CONNECTIVITY AND COGNITIVE PERFORMANCE IN HEALTHY AGING
Czoch Ákos
Molecular Medicine Division
Dr. Várnai Péter
SE Élettani Intézet könyvtára
2026-02-12 16:00:00
Cellular and Molecular Physiology
Dr. Hunyady László
Dr. Rácz Frigyes Sámuel
Dr. Négyessy László
Dr. Herényi Levente
Dr. Benyó Zoltán
Dr. Decmann Ábel
Dr. Hricisák László
I investigated the relationship between fractal connectivity and cognitive functions within the context of healthy aging. My primary objective was to uncover how age-related alterations in brain connectivity patterns influenced cognitive abilities. Firstly, I delved into fractal connectivity (FrC), which represents the self-similar patterns of brain activity crucial for cognitive performance. To estimate and analyze FrC our lab developed a method termed Multiple-Resampling Cross-Spectral Analysis (MRCSA), the bivariate extension of Irregular-Resampling Auto-Spectral Analysis (IRASA). This technique allowed for an unbiased estimation of the spectral slope, which characterizes fractal connectivity. Secondly, to test cognitive performance I utilized tasks from the Cambridge Neuropsychological Test Automated Battery (CANTAB) to assess various cognitive domains. These tests provided comprehensive insights into visual memory, attention, reaction time, and problem-solving abilities. The impact of aging on fractal connectivity and cognitive performance formed the third focal area of my study. I investigated age-related differences in connectivity patterns and their correlations with cognitive test outcomes. The results revealed that healthy aging was associated with distinct changes in fractal connectivity, which might be the underlying cause for the observed decline in specific cognitive capabilities. To ensure statistical robustness, the False Discovery Rate (FDR) method was employed to adjust the number of comparisons in the case of CANTAB and Bonferroni’s method of multiple comparisons with the connectivity metrics. The results of my study indicated that increased cognitive load affected FrC differently in younger and older adults. Healthy elderly individuals displayed distinct connectivity patterns compared to younger participants, and these patterns correlated with their cognitive performance. I identified significant age-related differences in fractal connectivity linked to specific cognitive domains, highlighting the potential of FrC as a biomarker for cognitive aging. It must be stressed that further research is needed to explore potential therapeutic interventions that could mitigate age-related cognitive decline. In conclusion, my dissertation established that FrC plays a crucial role in cognitive functioning, and its alteration with age might contribute to cognitive decline. By understanding the neural mechanisms underlying age-related cognitive changes, we could develop more effective strategies to support cognitive longevity.
