Why some brains switch gears more efficiently than others
Peer-Reviewed Publication
Updates every hour. Last Updated: 3-Jan-2026 20:11 ET (4-Jan-2026 01:11 GMT/UTC)
The human brain is constantly processing information that unfolds at different speeds – from split-second reactions to sudden environmental changes to slower, more reflective processes such as understanding context or meaning.
A new study from Rutgers Health, published in Nature Communications, sheds light on how the brain integrates these fast and slow signals across its complex web of white matter connectivity pathways to support cognition and behavior.
Why does cancer sometimes recur after chemotherapy? Why do some bacteria survive antibiotic treatment? In many cases, the answer appears to lie not in genetic differences, but in biological noise — random fluctuations in molecular activity that occur even among genetically identical cells.
Biological systems are inherently noisy, as molecules inside living cells are produced, degraded, and interact through fundamentally random processes. Understanding how biological systems cope with such fluctuations — and how they might be controlled — has been a long-standing challenge in systems and synthetic biology.
Although modern biology can regulate the average behavior of a cell population, controlling the unpredictable fluctuations of individual cells has remained a major challenge. These rare “outlier” cells, driven by stochastic variation, can behave differently from the majority and influence system-level outcomes.
This longstanding problem has been answered by a joint research team led by Professor KIM Jae Kyoung (KAIST, IBS Biomedical Mathematics Group), KIM Jinsu (POSTECH), and Professor CHO Byung-Kwan (KAIST), which has developed a novel mathematical framework called the “Noise Controller” (NC). This achievement establishes a level of single-cell precision control previously thought impossible, and it is expected to provide a key breakthrough for longstanding challenges in cancer therapy and synthetic biology.