Tension shapes memory: Computational insights into neural plasticity
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Mechanical forces have recently emerged as critical modulators of neural communication, yet their role in high-level cognitive functions remains poorly understood. Here, we present a biologically inspired spiking neural network model that integrates mechanical tension, vesicle dynamics, and spike-timing-dependent plasticity to examine how tension influences learning, memory, and cognitive operations such as pattern completion, projection, and association. We find that increased tension enhances synaptic efficiency by accelerating vesicle clustering and recovery, resulting in a 67% improvement in memory recall speed and a 17% increase in inter-regional synchrony during projection relative to relaxed states. Conversely, a 20% reduction in tension leads to a 31% decline in memory association performance, highlighting the tension-sensitive accessibility of stored information. The model further reveals that networks with 20% inhibitory neurons achieve optimal spatial precision in memory encoding and recall. Together, these in silico findings position mechanical tension as a functional neuromodulator and suggest new directions for neuromorphic design and energy-efficient, living computing platforms.
Author summary
Our brains are not only electrical and chemical systems but also mechanical ones. Neurons and their connections are constantly under tension, yet the role of these physical forces in shaping memory and thought remains poorly understood. In this work, we built a computer model of a brain-like network that allowed us to test how mechanical tension influences learning and memory. We found that higher tension improved the speed and accuracy of memory recall, strengthened communication between groups of neurons, and supported more reliable association of memories. In contrast, reducing tension made memories harder to access, though they could be recovered once tension was restored. We also discovered that having the right balance between excitatory and inhibitory neurons was crucial for both storing and recalling information. Our results suggest that tension is not just a background property of brain tissue but an active player in cognition, with potential implications for understanding memory disorders and designing new brain-inspired technologies.
