Energy Landscape Analysis of Age-related Changes in Human Brain Activity

Complex functions of the human brain rely on dynamic coordination of functionally different neural systems. To understand such brain activity at a network level, here we applied the so-called energy landscape analysis (Fig. 1; [1, 2]) to resting-state fMRI data obtained from healthy younger and older adults. This analysis characterizes large-scale brain dynamics within an energy landscape (Fig. 1(e)) by inferring the maximum entropy model from empirical data (Fig. 1(d)). We used this method to measure the correlation between the efficiency of the neural dynamics and a behavioral index [2]. The efficiency of the neural dynamics was defined as the tendency of transitions between two frequently visited activity patterns. We found that in younger adults, a behavioral score quantifying cognitive functions was predicted by the efficiency of neural dynamics in the so-called cingulo-opercular network (CON), whereas that of older adults was correlated with the efficiency in the so-called default-mode network (DMN). These results demonstrate age-related changes in brain dynamics and suggest the importance of investigating large-scale neural dynamics for better understanding human complex cognitive functions.

Takahiro Ezaki, Michiko Sakaki, Takamitsu Watanabe and Naoki Masuda
Tuesday, September 25, 2018 - 17:15 to 17:30


The official Hotel of the Conference is
Makedonia Palace.

Conference Organiser: NBEvents

The official travel agency of the Conference is: Air Maritime

Photo of Thessaloniki seafront courtesy of Juli Bellou
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