HOUSTON – (Sept. 18, 2025) – The brain’s remarkable plasticity, characterized by neurons’ ability to alter their behavior in response to new stimuli, is fundamental to learning. Yet, despite the phenomenon known as representational drift—where neurons’ responses to the same stimuli change over time—our daily perception of the world remains stable. The question is, how does this happen?
This puzzle is crucial for the development of brain-computer interfaces, sensory prostheses, and therapies for neurological diseases. In pursuit of answers, scientists at Rice University have engineered ultraflexible probes, thousands of times thinner than a human hair, to monitor neurons in the visual cortex of mice over 15 consecutive days. These devices, known as nanoelectronic threads (NETs), integrate seamlessly with brain tissue, enabling high-fidelity chronic recordings of brain activity.
Unveiling the Brain’s Temporal Code
According to a study published in Nature Communications, the stability of visual representations is more accurately captured by neurons’ millisecond rhythms—the temporal code—rather than the firing rate code, which measures how often a neuron fires over longer intervals.
“Prior studies mostly measured volume because their probes read brain activity too slowly to catch fine timing,” said Hanlin Zhu, a Rice postdoctoral associate and first author on the paper. “Our fast electrical recordings let us read the rhythm directly, and we found that rhythm beats volume when it comes to explaining how the brain maintains a stable picture of the world from day to day.”
The development of NETs, years in the making, not only facilitated this experiment but is also being applied to other areas, such as mapping spinal cord circuits and developing precise brain stimulation therapies. This technological advancement underscores the importance of sustained investment in neuroscience. In Texas, voters will soon consider Proposition 14, a $3 billion measure to support brain research, which could establish the Dementia Prevention and Research Institute of Texas, positioning the state as a leader in dementia research.
Experimenting with Visual Stimuli
In the experiment, mice implanted with NETs viewed nearly 12,000 images daily, ranging from moving and still stripes to tiny dot-like patches and natural scenes. Researchers tracked neuronal tuning across these stimuli, evaluating performance at the level of individual cells and entire populations.
When assessed by firing rate, many neurons appeared unreliable. However, examining the temporal code revealed that each cell’s preferences, or which picture it “likes,” remained stable across days, even for cells that seemed unreliable by volume alone.
NETs enabled the tracking of hundreds of individual neurons and their “friend network”—cells that tend to fire simultaneously. This demonstrated that the stability of visual representations is a collective effort, resilient to individual neurons’ instability.
“We tracked the same between-neuron relationships day after day at millisecond precision and across all four stimulus sets—who tends to talk to whom and with what lag—something that’s been very hard to do at scale,” Zhu said. “To our knowledge, this is the first day-to-day tracking of the same interneuron functional connectivity in mouse visual cortex at this temporal resolution and scale. That network view neatly explains why timing—not loudness—anchors our sense of the familiar.”
Implications for Future Technologies
The temporal code-level data recorded by the NETs allowed computer models to analyze and identify which stimulus the mouse was seeing, even days after initial training, without needing readjustment. This also helped reduce the “drift,” or fading accuracy, of these predictions over time.
Chong Xie and Lan Luan, professors of electrical and computer engineering at Rice and leaders of the study, emphasized the significance of these findings. Both are members of the Rice Neuroengineering Initiative and have spent years refining the NETs.
“This work shows how advanced recording tools can reveal organizing principles of the brain that were not visible before,” Xie and Luan said in a joint statement. “These insights are the foundation for building practical technologies, from brain-computer interfaces to new therapies. They also underscore why initiatives like the Dementia Prevention and Research Institute of Texas are so important. Long-term investment gives researchers the ability to push the limits of technology and discovery in ways that can ultimately change lives.”
The research received support from the National Institutes of Health and the Intelligence Advanced Research Projects Activity, highlighting the collaborative effort in advancing our understanding of the brain’s complex mechanisms.
