Complex cognitive functions such as working memory and decision-making require information maintenance over seconds to years, from transient sensory stimuli to long-term contextual cues. While theoretical accounts predict the emergence of a corresponding hierarchy of neuronal timescales, direct electrophysiological evidence across the human cortex is lacking. Here, we infer neuronal timescales from invasive intracranial recordings. Timescales increase along the principal sensorimotor-to-association axis across the entire human cortex, and scale with single-unit timescales within macaques. Cortex-wide transcriptomic analysis shows direct alignment between timescales and expression of excitation- and inhibition-related genes, as well as genes specific to voltage-gated transmembrane ion transporters. Finally, neuronal timescales are functionally dynamic: prefrontal cortex timescales expand during working memory maintenance and predict individual performance, while cortex-wide timescales compress with aging. Thus, neuronal timescales follow cytoarchitectonic gradients across the human cortex, and are relevant for cognition in both short- and long-terms, bridging microcircuit physiology with macroscale dynamics and behavior.

In patients with severe aortic stenosis who are at increased surgical risk, the higher rate of survival with a self-expanding TAVR compared with surgery was sustained at 2 years. (Safety and Efficacy Study of the Medtronic CoreValve System in the Treatment of Symptomatic Severe Aortic Stenosis in High Risk and Very High Risk Subjects Who Need Aortic Valve Replacement; NCT01240902).

Patients with severe aortic stenosis at increased risk for surgery had improved 3-year clinical outcomes after TAVR compared with surgery. Aortic valve hemodynamics were more favorable in TAVR patients without differences in structural valve deterioration. (Safety and Efficacy Study of the Medtronic CoreValve(®) System in the Treatment of Symptomatic Severe Aortic Stenosis in High Risk and Very High Risk Subjects Who Need Aortic Valve Replacement; NCT01240902).

17Complex cognitive functions such as working memory and decision-making require information 18 maintenance over many timescales, from transient sensory stimuli to long-term contextual cues. 19While theoretical accounts predict the emergence of a corresponding hierarchy of neuronal 20 timescales, direct evidence in the human cortex is lacking. Here, we use a novel computational 21 approach to infer neuronal timescales from human intracranial recordings and find that 22 timescales gradually increase along the principal sensorimotor-to-association axis. Cortex-wide 23 transcriptomic analysis further shows a direct alignment between timescales and expression of 24 excitation-and inhibition-related genes, as well as genes specific to voltage-gated 25 transmembrane ion transporters. Finally, neuronal timescales are functionally dynamic: 26 prefrontal cortex timescales expand during working memory maintenance and predict individual 27 performance, while cortex-wide timescales compress with aging. Thus, neuronal timescales 28 follow cytoarchitectonic gradients across the human cortex, and are relevant for cognition in 29both short-and long-terms, bridging microcircuit physiology with macroscale dynamics and 30 behavior. 31 32One-sentence summary 33Human cortical timescales is associated with synaptic and ion channel genes, lengthens with 34 working memory maintenance, and shortens in aging. 35

A key computation underlying perceptual decisions is the temporal integration of "evidence" in favor of different states of the world. Studies from psychology and neuroscience have shown that observers integrate multiple samples of noisy perceptual evidence over time toward a decision. An influential model posits perfect evidence integration (i.e., without forgetting), enabling optimal decisions based on stationary evidence. However, in real-life environments, the perceptual evidence typically changes continuously. We used a computational model to show that, under such conditions, performance can be improved by means of leaky (forgetful) integration, if the integration timescale is adapted toward the predominant signal duration. We then tested whether human observers employ such an adaptive integration process. Observers had to detect visual luminance "signals" of variable strength, duration, and onset latency, embedded within longer streams of noise. Different sessions entailed predominantly short or long signals. The rate of performance improvement as a function of signal duration indicated that observers indeed changed their integration timescale with the predominant signal duration, in accordance with the adaptive integration account. Our findings establish that leaky integration of perceptual evidence is flexible and that cognitive control mechanisms can exploit this flexibility for optimizing the decision process.